how to improve tsa problem solving

How to Approach the TSA Test in 2024: An Oxford Graduate’s Preparation Advice

This guide is written by Rhiannon (Experimental Psychology, University of Oxford graduate). Rhiannon leads you through her top tips for preparation, including how to approach the test, how best to structure your preparation, key aspects of critical thinking and problem solving and examination technique.

What is the Thinking Skills Assessment (TSA)?

The TSA is a test designed to assess your ability to critically analyse and make use of information. It requires both a logical approach to analysis, and creativity in being able to flexibly make hypotheses about the material given. It is currently required for entrance applications to a number of courses at Oxford, Cambridge and UCL universities: Experimental Psychology, Geography, Human Sciences, Philosophy, Politics and Economics, and Psychology, Philosophy and Linguistics . The TSA is specifically designed to assess the skills that are integral to success in these subjects.

The test is comprised of two main question types: critical thinking, and problem solving. The specific question types and skills assessed in these sections are discussed below. Importantly, there is very little specific knowledge that is required for this test. It is based around your ability to engage with and critically analyse information that is provided. However, you can and will improve your score with thorough preparation and a good understanding of what the questions are asking you.

What is it assessing, and why?

Critical thinking is a key part of university study. Rather than simply reading and absorbing large volumes of information, it is important to be able to assess them for their true meaning. If you read an opinion piece, even from an expert in the field, it is important not just to take it at face value. Upon analysing the structure of an argument, you may find it to be flawed. You may identify that an argument rests upon some hidden assumptions, and that the argument itself is only true if these hidden assumptions are.

Being able to carry out such an analysis is a key part of university essay writing. In your own essays you will also be forming a series of arguments, often through an evaluation and assimilation of the views of others. It is helpful to be aware of the structure of your own reasoning, whether there are any assumptions your argument is relying upon, and if so whether these assumptions will hold. This will make your own arguments more compelling.

Critical Thinking for the TSA

The critical thinking section is based around the appraisal of arguments: examining the components of an argument to see if there are any flaws to it, and that undermine its conclusion.

A premise is something that must be true for an argument to hold. For example, in the argument ‘eating meat is morally wrong because animals are sentient beings’, the premise is that animals really are sentient beings. If they are not, or if their sentience is unknown, then the argument does not hold. When you are reading an argument, think about whether it relies on any particular premises for the conclusions to be true.

Alternatively, an argument may not stand because there is a flaw in its logic. There are a number of reasons for this. For example; sometimes an argument will mistake an association, or correlation, with causation. In the statement ‘people who go running regularly live longer on average, therefore if I go running I will live longer’ it is assumed that because two things (running, and living for longer) are associated, one must cause the other. However, this is not necessarily true, as there may be other reasons for people who run regularly to live longer: for example, they may have had more money, more free time, or have been less likely to have a health condition that could interfere with running.

In the TSA, it is important to base your judgement only on what is given to you in the text. In the above example, you may be aware of evidence showing the running does in fact have a causal association with life expectancy, or you may suspect that it would do. However, this is different to a piece of information that is directly proven by the text.

When an argument is very long or wordy, it can be difficult to work out exactly what the structure of the argument is. It can be helpful to split an argument up into a particular form that you are familiar with, perhaps using arrows, or replacing elements of the argument with ‘A’ or ‘B’. In general, statements that follow words such as ‘so’, ‘thus’, or ‘consequently’ are likely to be the conclusion of the argument.

Problem Solving for the TSA

The problem solving component tests your ability to use information in a creative way. It requires logical and numerical skills applied to a novel situation. For example, you may be asked a question on how to organise multiple timings when cooking a meal, or how to transfer a certain volume of liquid given only a limited number and size of containers.

These questions are based around numerical concepts, so you may find it helpful to brush up on some simple mathematical concepts such as percentages and ratios . You may also find it helpful to practise mental arithmetic so that you can answer questions more quickly. However, remember the test is assessing your ability to problem solve rather than any complex mathematical knowledge.

If in doubt, go back to basics and remind yourself what the question is asking you to do. It may help to underline key words from the question stem if you are sitting a paper exam. It can also be very helpful to write down your thought process as you are working out an answer, so that you can go back and correct any mistakes or points of confusion that you come across.

You may find that there are several different ways of answering the question, and you are unsure which method is best. It is perfectly fine to try a number of different ways of coming to an answer by a process of trial and error : after all, this process of logical reasoning is a key part of what the test is assessing! However, be sure to keep an eye on the time and do not spend too long on the most difficult questions at the expense of the other ones. Remember, you can flag and go back to a question later on.

How should I prepare for the TSA?

Practise! Familiarise yourself with the different examples and past questions available online on the TSA website. Remember, although the skills assessed are abstract, you will improve through practice

Try to pick out examples of arguments in everyday life, and focus on attempting to analyse their arguments. What are they really saying (their conclusions)? Does the argument rely on any premises for the conclusion to be true?

Devise a strategy for managing your time. Depending on the type of question that you find the most challenging, you may not wish to split your time equally between the two sections. Make sure you are familiar with the way that you are going to manage your time, so that you aren’t caught out by the end

Make sure you are happy with the logistics of taking the test. Ensure you know the location of the test centre, and leave yourself plenty of time to get there. It is also important to check the identification documents that you need, and make sure you have these ready in plenty of time

Top Tips on the day

There is no negative marking, so make sure you always put an answer down, even if it is a complete guess

Pay attention to timings! Don’t be tempted to spend too much time on a particularly difficult question

Try to stay calm, and don’t panic if you are unsure of the answers. Remember, the test is supposed to challenge you, and there is no need to get every question right! Even the very best candidates will make errors and feel uncertain at times

How Can U2 Help Prepare You For the TSA & Wider Oxbridge Application (e.g. Personal Statement, Interview Preparation, Summer School, Research Projects)?

U2 offers TSA admissions test preparation either as part of our wider Oxbridge Mentoring programmes or as pay-as-you-go sessions ( book a free consultation to discuss options).

The Process:

1) We suggest an Oxbridge graduate/ TSA tutor in the student’s course of application as a mentor and send their full CV for review. Our tutors are deeply familiar with the admissions process and experienced in supporting students’ TSA preparation.

2) We typically suggest beginning with a 1.5 hour informal assessment/ taster session , where the mentor will informally assess the student’s current performance level for the TSA (and interview if interested in wider application mentoring). Following this, we issue a report with feedback, and structure a plan to best prepare.

3) U2’s approach for regular TSA sessions: We have linked an example TSA course structure curated for a student looking for a TSA to Interview preparation course ( link ). This is typically customised by the tutor chosen and individualised to the student and their particular requirements.

Frequency of sessions can be decided between student and mentor. Honing the skills necessary to succeed in the TSA test ideally requires long-term preparation.

Wider Application Support

U2's Oxbridge programmes aim to advance students to the level required for success through regular tutorial sessions and specific admissions preparation (for personal statement, admissions test & interview). In sessions, students are expected to orally communicate, defend, analyse & critique ideas or solve problems, in conversation with the tutor, as in an Oxbridge tutorial. This readies students for the challenging entry process and provides them with the tools needed to stand out amongst other strong candidates.

We offer some of the most comprehensive support available at present, with an entire interactive online platform, Minds Underground™ , built to take care of all students' co-curricular needs in preparation for university application and future careers, including research projects, masterclasses and summer schools. U2 has a remarkable track record of success supporting students in entry to Oxbridge and currently work with over 20 schools in the UK and internationally to enhance their Oxbridge provision.

We would be delighted to support you through what can be a challenging, but incredibly rewarding process.

Sessions from £70/h, or we customise wider application programmes (quote on enquiry).

How to Approach the Cambridge MML Admissions Test: Our Updated 2024 Guide

How to approach history ib revision to achieve a 7: our updated 2024 study guide.

10 Tips for TSA Section 1

What is TSA Section 1?

Section 1 of the TSA is a 90-minute, 50-question paper that assesses your ability to reason verbally and mathematically. These skills are a generic indicator of the ability to study at an undergraduate level, particularly in essay-based courses. Section 1 will be the only part of the TSA they must do for some people. For others, there will be a 30-minute essay task afterwards. To find out whether you need to sit the TSA and which parts, read our article, including the Cambridge and Oxford TSA test date . In this article, we will cover some helpful TSA section 1 tips to help you ace the exam.

What are the Questions like?

Each question is worth one mark and is multiple choice, and you have five answers. Oxford TSA Section 1 questions fall into one of two categories: Critical Thinking, which tests your ability to understand arguments, and Problem Solving, which tests your numerical reasoning ability. There are 25 questions of each type mixed throughout the exam, and they are roughly in order of difficulty.

Problem Solving

There are three types of Problem Solving questions, which test different aspects of your numerical reasoning ability.

• Relevant Selection: This assesses your ability to pick out relevant information from the question material and ignore irrelevant and distracting information, and use only the relevant information to come to your answer
• Finding Procedures: Usually you will have less information to work with, but will have to find and carry out appropriate mathematical operations to get to your answer. The method you need to use may not always be immediately apparent. 
• Identifying Similarities: You will have to interpret data presented in different ways. These could be graphs, tables, charts etc. and you will have to compare them with other representations to find similarities and make inferences to get to your answer.

Critical Thinking

This tests your ability to understand and identify the features of logical arguments. You will read a passage and have to answer a question on some aspect of it. There are seven types of Critical Thinking questions in Oxford TSA Section 1. 

Identifying the Main Conclusion

You will have to identify which statement from the list of possible answer choices best expresses the argument’s main conclusion. The conclusion will be in the text, perhaps phrased differently, so you must pick it out and match it up with the right answer. These questions follow a similar phrasing: ‘Which of the following best expresses the main conclusion of the above argument?’

Drawing a Conclusion

You’ll need to choose which of the possible answers is a conclusion that you can reasonably draw from the arguments presented in the passage. The conclusion itself won’t be in the passage. These questions follow a similar phrasing: ‘Which one of the following conclusions is best supported by the passage above?’

Identifying an Assumption

Assumptions are not stated in the argument, but you can take for granted in order to reach the conclusion. You’ll first have to identify the conclusion in the passage, then think about what important point needed to reach that conclusion has not been stated in the passage. These questions follow a similar phrasing: ‘Which of the following is an underlying assumption of the argument above?’

Assessing the Impact of Additional Evidence

You’ll have to choose which of the answers would most weaken/strengthen the argument in the passage. These questions are phrased: ‘ Which of the following, if true, would most weaken (or strengthen, depending on the question) the above argument?’

Detecting Reasoning Errors

You must identify the flaw in the argument. Work out why the conclusion does not follow from the reasons given in the argument. These questions are phrased: ‘Which of the following is the best statement of the flaw in the argument above?’

Matching Arguments

You will need to pick out which answer choice is structured most similarly to the argument in the passage. These questions follow a similar format: ‘Which of the following most closely parallels the reasoning used in the above argument?’

Applying Principles

You will have to work out what principle, or general recommendation, the argument in the passage rests upon, and match it to one of the answers that uses the same principle. These questions follow a similar format: ‘Which one of the following best illustrates the principle underlying the argument above?’

How is it marked?

The Oxford TSA Section 1 is automatically marked by a computer, and 1 mark is awarded for each answer that is correct. It is not negatively marked, so you don’t lose any points for a wrong answer. Your marks are then statistically converted into a score that takes into account the question and paper difficulty. For more information on TSA scores, you can check out our article What is a Good TSA Score ?

TSA Section 1 Tips

1. prepare.

TSA preparation is tip number one because it is the single most important thing you must do to succeed in TSA Section 1. Don’t think you’ll do fine if you leave it all to the night before. Because TSA is an aptitude test to a certain extent, it’s more of a skill to learn, and that takes plenty of time and practice.

2. Brush up on your maths skills

The maths required doesn’t go above GCSE level, and it’s fairly simple even then. However, you won’t get a calculator, so if you’ve not done maths for a while or got used to always having a calculator within reach for A-level maths, you’ll want to practice working things out by hand. Speed is of the essence as you don’t get very long to answer the questions. 

3. Learn the question types

In Critical Thinking, most of the time you’ll be able to figure out the question type easily from the phrasing of the question. This will help you identify exactly what you have to do to find the answer. It’s not always clear what type of question a Problem Solving question is, but if you’re able to spot that something is Relevant Selection it’ll hopefully stop you falling into the traps the distracting information might lead you towards, for example.

4. Read the TSA question very carefully

There will often be nuances in the wording or small pieces of information that are key to understanding how to find the answer. Make sure you fully understand the question before starting to answer. It might help to get a basic overview first, to help eliminate irrelevant bits, but make sure you fully understand the relevant information so the question does not catch you out. 

5. Develop a timing strategy and stick to it

You only get 1.8 minutes per question, which is not very long at all. Some questions might be fairly straight-forward and answerable quickly, and others may take longer than 1.8 minutes. Doing practice papers will help you identify what sorts of questions are quick to answer and which you may need more time on, so use that to plan your question timings. Set a limit after which you have to move on, even if you haven’t found the answer – it’s not worth spending several minutes of your precious time on one question when there’s 49 others that need answering. Set a target of how many questions you want to have answered by certain time points in the exam to keep track of your progress. Our TSA Online Course provides more TSA section 1 tips and timing strategies to help you stick to the time.

6. Use process of elimination

Remember – you will always have the answer in front of you, as one of your five options. Use this to your advantage and start eliminating wrong answers if you can’t immediately see a method to the right one. Even if you can’t get to an answer, if you manage to eliminate three that are obviously wrong your odds of a correct guess just increased from ⅕ to ½!

7. Move straight on once you’ve answered a question

It can be tempting to deliberate over your answer and check it again and again, but you don’t have time. Move on to the next question as soon as you’ve got to an answer you’re pretty happy with. If you somehow have spare time at the end, use it to check things, but chances are you won’t have much time to spare.

8. Use the resources that are available in the TSA exam

You will be able to take rough notes in the exam, which is a good idea. Some calculations will be too long to do in your head without risking mistakes. It also might help if you struggle with spatial reasoning to sketch things out. If a question feels really confusing, writing down your working out can make it clearer, and being able to look over your working out will make it easier to spot errors. You won’t need to do this for all questions – some are very easy mental maths – but don’t be afraid to write stuff down if you feel it will help. 

9. Use everything you can find to prepare

There’s plenty of TSA past papers online for free that you can use to practice. Section 1 of the BMAT has the same types of questions as the TSA, there’s just fewer of them , so use BMAT Section 1 past papers too. You can also apply your developing Critical Thinking skills in everyday life – consider the logical structure of arguments you come across in your studies, or in newspapers, for example. 

10. Read through the explained answers on the Specimen Paper

This is an excellent way to get an idea of what is expected of you when answering questions. The people who set the test produce the papers, so it’s your best insight into the rationale behind the questions and the kind of reasoning they expect you to be able to do. Take your time to understand the answers and apply any new ways of thinking you might come across to your own practice attempts and see how you get on. 

With some hard work and preparation, you can maximise your score in TSA Section 1. If you’re looking for some extra guidance, Our expert tutors can give you 1-1 support to help you ace TSA Section 1!

→What is TSA Section 1?

TSA Section 1 is the first part of the Thinking Skills Assessment, an admissions test used by some universities in the UK to assess a student’s potential to study a particular subject.

→What does TSA Section 1 assess?

TSA Section 1 assesses a student’s critical thinking, problem-solving, and reasoning skills through a series of multiple-choice questions.

→How can I prepare for TSA Section 1?

To prepare for TSA Section 1, you should familiarize yourself with the format of the test, practice your critical thinking and problem-solving skills, and review past papers and sample questions.

→What are some tips for taking TSA Section 1?

Some tips for taking TSA Section 1 include managing your time effectively, reading the questions carefully, eliminating obviously incorrect answers, and practicing good test-taking strategies such as educated guessing.

→Can I retake TSA Section 1?

It depends on the university’s policies. Some universities allow students to retake TSA Section 1, while others do not. You should check with the specific university you are applying to for their retake policies.

→How important is TSA Section 1 for university admissions?

The importance of TSA Section 1 varies depending on the university and the course you are applying for. However, it is generally considered an important factor in the admissions process and can have a significant impact on your chances of being accepted.

Save my name, email, and website in this browser for the next time I comment.

Personalised 1-1 tuition, tailored to your TSA needs by our expert tutors

A comprehensive online course to boost your TSA preparation! Written by our TSA experts

Prepare for your interview with the help of our expert Oxbridge tutors, who will personalise your sessions according to university and college

• FREE Applying to Oxbridge Course
• FREE TSA Past Papers

Oxford Thinking Skills Assessment (TSA): A Complete Guide

Dr Rahil Sachak-Patwa

The Oxford Thinking Skills Assessment (TSA) is a critical part of the application process for several courses at the University of Oxford. It's a unique test designed to assess your problem-solving and critical thinking skills, both of which are essential for success in higher education. The TSA is divided into two parts: a 90-minute, multiple-choice assessment, and a 30-minute writing task. In 2024, the TSA will be a paper-based test.

The multiple-choice section is designed to evaluate your problem-solving skills, including numerical reasoning, as well as your critical thinking skills, such as understanding argument and reasoning using everyday language. The writing task, on the other hand, seeks to evaluate your ability to organise ideas in a clear and concise manner, and communicate them effectively in writing.

The TSA is used as an additional tool to differentiate between candidates who, on paper, may appear equally qualified. With most applicants predicted top grades and boasting excellent personal statements and references, the TSA provides an extra piece of information that helps identify the very best candidates.

The Importance of the TSA in Oxford Admissions

The TSA plays a significant role in the Oxford admissions process . With the majority of applicants achieving top grades and presenting impressive personal statements, the TSA serves as an additional differentiator for admissions tutors.

The Oxford admissions process is holistic, considering a wide range of academic performances, including exam scores, interview performance, and, of course, the TSA score. It's not uncommon for the TSA to be referred to in your interview. You may be asked how you think the test went, or they may disclose your score to you.

Interestingly, different subjects weigh the TSA exam differently. For instance, successful Philosophy, Politics, and Economics (PPE) candidates often score around 70, which is a high TSA score. This is due to a combination of the TSA’s weighting as well as a reflection of the subject’s competitiveness.

In essence, the TSA is used because applicants to these prestigious universities tend to be very closely matched on paper. It provides an extra layer of information that helps identify the very best candidates.

Get expert help with the TSA

The world's leading online TSA tutoring provider trusted by students, parents, and schools globally.

4.92 /5 based on 480 reviews

Who Needs to Take the TSA?

The TSA, or Thinking Skills Assessment, is a pre-interview written test that is required for applicants to certain courses at the University of Oxford. The test is not subject-specific but instead assesses a range of general skills that are transferable between many different subjects.

From 2024 and onwards, if you are applying for the Philosophy, Politics, and Economics (PPE) program, you must complete both parts of the Thinking Skills Assessment (TSA).

Conversely, if you are applying for the following courses, you will only need to take Section 1 of the TSA :

• Economics and Management
• Experimental Psychology
• History and Economics
• Human Sciences
• Psychology, Philosophy and Linguistics .

This section is composed of 50 multiple-choice questions that aim to assess your problem-solving skills, including numerical reasoning, and critical thinking skills, such as understanding argument and reasoning using everyday language.

As of 2024, the TSA is used exclusively by the University of Oxford . Previously, there were three versions of the TSA used by three different universities; TSA Oxford, TSA Cambridge, and TSA UCL.

Format of the TSA

The TSA, or Thinking Skills Assessment, is an aptitude test that is divided into two sections.

Table showing the TSA exam format

Section 1: Multiple Choice Questions

Section 1 is a 90-minute, multiple-choice assessment that aims to evaluate your problem-solving skills, including numerical reasoning, and critical thinking skills, such as understanding argument and reasoning using everyday language. This section is composed of 50 multiple-choice questions.

The scoring for this section is done on a scale of 1-100, with each correct answer earning you one mark. It's important to note that only about 10% of applicants score above 70, making a high score in this section quite an achievement. The scores are calculated on the TSA scale to one decimal place, which is an estimate of the candidate’s ability. This scoring method ensures that the scores are comparable by factoring in the question and overall test difficulty.

Sample TSA Section 1 Questions

Section 2: Writing Task

Section 2 is a 30-minute writing task that seeks to evaluate a candidate’s ability to organise ideas in a clear and concise manner, and communicate them effectively in writing. Candidates must answer one question from a choice of four.

For Oxford applicants, the essay written in this section is sent directly to the college you are applying to for them to mark. The marking scheme varies from Admission Tutor to Admission Tutor, but all tutors are looking for the ability to organise ideas in a clear and concise manner.

The TSA is designed to test the skills you should already possess, making it a challenging but fair assessment of your aptitude for critical thinking and problem-solving. It's quite different from anything you will have encountered before, making effective preparation crucial to achieving a high score.

Sample TSA Section 2 Questions

YOU MUST ANSWER ONLY ONE OF THE FOLLOWING QUESTIONS 1 . Should people be free to live in any country they wish to? 2 . Should political advertising and campaigning on social media be banned? 3 . Would a world in which no one ever experienced disappointment be better or worse than the world as it is? 4 . With technological advances like automatic captioning and immediate translation, will there soon be no need to teach different languages?

Understanding TSA Scores and Grading

This test measures an applicant's problem-solving and critical thinking skills, both of which are crucial for academic success. But what constitutes a good TSA score? Let's delve into the details.

The TSA is scored on a scale of 0 to 100, with the average score typically hovering around 60, according to data from Cambridge Assessment Admissions Testing (CAAT) . This score is derived from the applicant's raw marks, which are then converted using the Rasch Statistical Technique. This method ensures a fair scoring system that accurately reflects the applicant's abilities.

TSA Section 1 Overall Score distribution in 2023

Oxford University states that a score of 70 out of 100 would represent a "comparatively high score," although the best applicants are expected to score higher. However, achieving a score slightly below 70 wouldn't necessarily be detrimental to an application. It's important to note that a score of 80 or above is incredibly rare and would significantly boost an applicant's chances of success.

TSA Section 1 Problem Solving Score distribution in 2023

TSA Section 1 Critical Thinking Score distribution in 2023

TSA Section 1 Problem Solving and Critical Thinking Score distributions in 2023

These scores are not arbitrary. They are based on a careful analysis of past TSA results. For instance, the score distributions for the 2023 entry show that the most common scores for problem-solving and critical thinking were in the 55-70 range. This trend has remained consistent over the years, indicating the balance and consistency of the TSA.

However, a good TSA score is not the only factor considered during the admissions process. Other elements, such as the personal statement , grades, and performance during interviews , also play a significant role. Therefore, even if an applicant scores slightly below the average TSA score, they can still bolster their application through these other aspects.

Best TSA Resources and How to Prepare for the 2024 Exam

Preparing for the TSA can seem daunting, but with the right resources and strategies, you can approach the exam with confidence. Here are some of the best resources and tips to help you prepare effectively.

1. Official TSA Website : The official TSA website is a valuable resource for understanding the format of the test, the types of questions you'll encounter, and the skills you'll need to demonstrate. It also provides access to past papers, which are crucial for understanding the style of questions and for practicing under timed conditions.

2. TSA Past Papers : Past papers are an invaluable resource when preparing for the TSA. They provide a clear idea of what to expect in the actual exam and offer a great opportunity to practice your problem-solving and critical thinking skills.

3. TSA Tutoring: Hiring a TSA tutor can be a beneficial investment. A tutor who is familiar with the TSA can provide personalised guidance, help you identify your strengths and weaknesses, and offer strategies to improve. They can also provide valuable feedback on your practice essays and problem-solving questions.

4. Online Resources: There are numerous online resources available to help you prepare for the TSA. Websites like Exams Ninja and UniAdmissions offer guides, tips, and practice questions to help you get familiar with the test format and question types. However, always ensure the resources you use are up-to-date and reliable.

5. Practice, Practice, Practice: The more you practice, the more comfortable you'll become with the types of questions on the TSA and how to approach them. Regular practice under timed conditions can also help improve your speed and accuracy.

6. Review and Understand: Simply practicing questions is not enough. It's important to review your answers and understand why you got a question right or wrong. This will help you learn from your mistakes and improve your problem-solving and critical thinking skills.

7. Stay Informed: Keep up-to-date with any changes to the TSA by regularly checking the official website. This will ensure you're preparing for the test as effectively as possible.

Remember, the TSA is not about rote learning but about demonstrating your problem-solving and critical thinking skills. So, focus on understanding the concepts and developing these skills rather than memorising facts.

TSA Preparation Tips

Here is what one Oxbridge tutor had to say about how to do well on the test:

"I've had the privilege of guiding countless students through the challenging journey of TSA preparation. The key to success lies in a combination of focused effort and strategic planning. To excel in the TSA, here are my personal tips: Firstly, familiarize yourself with the exam format. Understand the structure, time constraints, and question types. Practice past papers regularly to build confidence and enhance your problem-solving skills. Utilize online resources, such as the official TSA website, to access additional practice materials and gain insights into the test's requirements. Secondly, sharpen your critical thinking abilities. TSA questions often assess your ability to analyze complex information and draw logical conclusions. Engage in thought-provoking activities like puzzles, debates, and reading intellectually stimulating articles. Cultivate the habit of approaching problems from different perspectives and practice explaining your reasoning effectively. Furthermore, prioritize time management. TSA is a time-pressured exam, so learn to allocate your time wisely. During practice sessions, set strict time limits to simulate the exam environment and improve your speed without compromising accuracy. Practice under timed conditions regularly to enhance your efficiency and decision-making skills. Lastly, embrace a multidisciplinary approach. TSA tests a wide range of skills, including mathematics, problem-solving, and data interpretation. Cultivate a diverse knowledge base by exploring subjects like politics, economics, and scientific advancements. Keep up with current affairs and engage in intellectual discussions to broaden your perspective and develop a well-rounded approach to answering TSA questions. Remember, TSA preparation is not just about memorization, but about cultivating a deeper understanding of the subject matter and honing your analytical skills. With dedication, practice, and the right mindset, you can conquer the TSA and open the doors to your academic aspirations."

The Role of the TSA in the Interview Process

A-Level tutors as well as IB tutors agree that TSA plays a significant role in the interview process at the University of Oxford. It's not just a hurdle to clear; it's an integral part of the holistic admissions process that Oxford employs.

During the interview, it's not uncommon for the TSA to be referred to. You may be asked how you think the test went, or they may disclose your score to you. This is because the TSA is used to gain a better understanding of how you think. It's designed to assess your problem-solving and critical thinking skills, both of which are crucial for academic success.

In some cases, you may even be asked about the content of the essay you wrote in Section 2 of the TSA during your Oxford interview. This provides the interviewers with a unique insight into your thought process and your ability to organise ideas and communicate them effectively in writing.

Dates, Costs, and Registration for the TSA in 2024

Here's what you need to know about the dates, costs, and registration process for the TSA. Registration for the TSA opens on 15 August 2024. The registration closes on 4 October 2024 at 18:00 (BST), which is also the deadline to apply for Access Arrangements (e.g., extra time).

The TSA will be held on 18 October 2024. Please note that these dates are designed to fit in with the Universities and Colleges Admissions Service (UCAS) cycle for applications to the University of Oxford.

Table showing the TSA key dates

To register for the TSA, you need to be registered as a candidate by a test centre. You cannot register yourself for the test. If your school or college is not already registered as a centre, they can apply to become a test centre. If you are not able to take the test at school or college, you need to find an authorised open test centre where you can take the test.

Final Thoughts

Navigating the TSA can seem daunting, but with the right preparation, you can approach it with confidence. Remember, the TSA is not just about your ability to recall facts, but rather your critical thinking and problem-solving skills. It's a unique opportunity to showcase your abilities beyond your academic grades. Utilise the resources available, consider hiring a tutor, and most importantly, practice regularly. The TSA is a significant part of your application, but it's not the only factor. Your personal statement, grades, and interview performance are equally important. So, approach your application holistically, and remember, every challenge is an opportunity to learn and grow. Good luck with your TSA preparation and your journey to Oxford!

Is the Oxford TSA hard?

The Oxford TSA is challenging as it tests critical thinking and problem-solving skills, which are not typically the focus of standard school curricula. It requires you to think outside the box and apply logical reasoning to a variety of scenarios. However, with adequate preparation, including practising past papers and understanding the test format, it is manageable.

What TSA score do you need for Oxford?

The required TSA score for Oxford varies by course and year. There's no set score that guarantees admission. However, it's worth noting that successful PPE candidates often score around 70, which is considered a high TSA score. The exact use of TSA scores in the admissions process can vary between different subjects and colleges.

How many students take the TSA?

Each year approximately 2000 students take the TSA. In 2021, 2171 students sat the TSA exam.

How do you get TSA results?

TSA results are passed to the Oxford College to which a candidate has applied. The exact use of results varies between the subjects which use the test. The University of Oxford releases results for the TSA to applicants at the end of their selection process. For more details, candidates can refer to the Explanation of Results on the Cambridge Assessment Admissions Testing website.

Need help from an expert?

The world’s top online tutoring provider trusted by students, parents, and schools globally.

Study and Practice for Free

Trusted by 100,000+ Students Worldwide

Achieve Top Grades in your Exams with our Free Resources.

Practice Questions, Study Notes, and Past Exam Papers for all Subjects!

Need Expert TSA Help?

If you’re looking for assistance with the TSA and your Oxford application, get in touch with the TutorChase team and we’ll be able to provide you with an expert TSA tutor . We’ll be there every step of the way!

Professional tutor and Cambridge University researcher

Written by: Dr Rahil Sachak-Patwa

Rahil spent ten years working as private tutor, teaching students for GCSEs, A-Levels, and university admissions. During his PhD he published papers on modelling infectious disease epidemics and was a tutor to undergraduate and masters students for mathematics courses.

Related Posts

Mathematics Admissions Test (MAT): A Complete Guide

How to Prepare for the MAT Exam

Hire a tutor

Please fill out the form and we'll find a tutor for you

• Select your country
• Afghanistan
• Åland Islands
• American Samoa
• Antigua and Barbuda
• Bosnia and Herzegovina
• Bouvet Island
• British Indian Ocean Territory
• Brunei Darussalam
• Burkina Faso
• Cayman Islands
• Central African Republic
• Christmas Island
• Cocos (Keeling) Islands
• Congo, The Democratic Republic of the
• Cook Islands
• Cote D'Ivoire
• Czech Republic
• Dominican Republic
• El Salvador
• Equatorial Guinea
• Falkland Islands (Malvinas)
• Faroe Islands
• French Guiana
• French Polynesia
• French Southern Territories
• Guinea-Bissau
• Heard Island and Mcdonald Islands
• Holy See (Vatican City State)
• Iran, Islamic Republic Of
• Isle of Man
• Korea, Democratic People'S Republic of
• Korea, Republic of
• Lao People'S Democratic Republic
• Libyan Arab Jamahiriya
• Liechtenstein
• Macedonia, The Former Yugoslav Republic of
• Marshall Islands
• Micronesia, Federated States of
• Moldova, Republic of
• Netherlands
• Netherlands Antilles
• New Caledonia
• New Zealand
• Norfolk Island
• Northern Mariana Islands
• Palestinian Territory, Occupied
• Papua New Guinea
• Philippines
• Puerto Rico
• Russian Federation
• Saint Helena
• Saint Kitts and Nevis
• Saint Lucia
• Saint Pierre and Miquelon
• Saint Vincent and the Grenadines
• Sao Tome and Principe
• Saudi Arabia
• Serbia and Montenegro
• Sierra Leone
• Solomon Islands
• South Africa
• South Georgia and the South Sandwich Islands
• Svalbard and Jan Mayen
• Switzerland
• Syrian Arab Republic
• Taiwan, Province of China
• Tanzania, United Republic of
• Timor-Leste
• Trinidad and Tobago
• Turkmenistan
• Turks and Caicos Islands
• United Arab Emirates
• United Kingdom
• United States
• United States Minor Outlying Islands
• Virgin Islands, British
• Virgin Islands, U.S.
• Wallis and Futuna
• Western Sahara

Still have questions? Let’s get in touch.

• Bespoke UCAT Tuition
• Online UCAT Course
• UCAT Question Bank
• Bespoke Personal Statement Support
• Personal Statement Portal
• Example Personal Statements
• Personal Statement Review
• Medicine Application Packages
• Medicine Interview Preparation
• MMI Interview Course
• MMI Question Bank
• Interview Preparation
• Mock Interviews
• Interview Question Bank
• Example Questions
• 100+ Questions & Answers
• Practice Interviews
• SFP Question Bank
• Online CASPer Course
• CASPer Question Bank
• Private CASPer Tutoring
• Articles & Resources
• CASPer: Complete Guide
• OET Question Bank
• 500+ Practice Questions
• Bespoke OET Tutoring
• Online OET Course
• Online OET Tutoring
• Dentistry Interview Preparation
• UCAT Prep Packages
• Dentistry Mock Interviews
• UK Dental School Questions
• US Dental School Questions
• 200+ Questions & Answers
• DFT SJT Question Bank
• DFT SJT Tutors
• 200+ DFT SJT Questions
• CASPer Complete Guide
• Oriel Question Bank
• Oriel Tutoring
• Situational Judgement Guide
• Numeracy Guide
• Practice Questions
• Online Course & Question Bank
• Private Tutoring
• Sample Paper
• Pharmacy Interview Preparation
• Pharmacy Mock Interviews
• Pharmacy Interview Question Bank
• Interview Tutoring
• UK Law School Interview Questions
• US/Canada Interview Questions
• Example Questions & Answers
• Application Support
• Articles & Free Resources
• 100+ Interview Questions & Answers
• Application & Interview Preparation
• Application Question Bank
• Free Articles & Resources
• Interview Tutoring & Mocks
• Interview Tuition & Mocks
• Dentistry Question Bank
• Nursing Question Bank
• PA Question Bank
• Medicine Interview Tips & Articles
• UK Medical School Interview Questions
• US & Canada
• Australia & NZ
• Interview Questions & Answers
• Nursing Questions & Answers
• PA Questions & Answers
• Physio Questions & Answers
• 11+ Exam Question Bank
• 11+ Exam Tutors
• 2,000+ Questions & Answers
• Bespoke 11+ Support
• 11+ Maths Practice Test
• 11+ English Practice Test
• 11+ NVR Practice Test
• 11+ VR Practice Test
• 11+ Interview Question Bank
• 200+ Interview Questions & Answers
• 16+ Interview Question Bank
• Interview Preparation & Mocks
• GCSE Biology Tutors
• GCSE Chemistry Tutors
• GCSE Physics Tutors
• GCSE Maths Tutors
• Biology Past Papers
• Chemistry Past Papers
• Physics Past Papers

Online TSA Course

• Private TSA Tutoring
• Key Information

TSA Past Papers

• TSA Essay Tips
• 200+ Questions & Answers
• Physio Questions & Answers

TSA Thinking Skills Assessment: The Complete Guide

Advice & Insight From TSA Specialists

What is the TSA exam?

• TSA stands for Thinking Skills Assessment, and that is exactly what the exam is designed to test.
• The exam is split into two sections: section one is multiple choice and concerns problem solving and critical thinking, while the second section is an essay.
• The exam is used by Oxford, Cambridge, and UCL as an admissions test for many of its courses. In all cases, this forms just one data point and is used alongside personal statements, GCSE/A-level grades, contextual information, interview performance, and so on. The TSA does not determine who is admitted to the universities, but it is used as one point in guiding admissions decisions.

​Which courses require the TSA?

The following courses in Oxford require both Sections 1 and 2 of the TSA:

• Economics and Management
• Experimental Psychology
• Human Sciences
• Philosophy and Linguistics
• Philosophy, Politics and Economics (PPE)
• Psychology and Linguistics
• Psychology and Philosophy

  Chemistry and the joint-honours course in History and Economics require section 1 but not the essay section. (Note that applicants in History and Economics must also take the HAT, History Aptitude Test.)   If you are applying to study Land Economy in Cambridge, you will also need to take Section 1 of the TSA. At UCL, applicants for European Social and Political Studies (ESPS) and International Social and Political Studies (ISPS) also require TSA Section 1.

TSA Score Conversion

The score that you are awarded for the TSA is different from the raw mark out of 50 that you achieve in the section 1 paper. Like most A-level and GCSE examinations, the score conversion changes each year, and takes account of how difficult candidates found the paper that year.   Let’s look at the 2016 and 2015 exam scores to illustrate this:   In 2016: 1/50 = 12.8      10/50 = 39.9      25/50 = 56.3 30/50 = 61.1    38/50 = 70.1     50/50 = 107.3   In 2015: 1/50 = 16.3      10/50 = 42.4      25/50 = 57.8 30/50 = 62.5    38/50 = 70.7     50/50 = 106.3   We can see from these two that there is variation in the UMS for each year, and if you look at further score converters (available on the Admissions Testing website) you will see that this is true across all the past papers available.   It is important to note that this plays to your advantage, because it means that if a paper is objectively more difficult, then your mark will be automatically moved up.   This is all interesting stuff, but the most important part of preparing for the TSA is not focussing on what number you would have got in a given year, but rather on improving your score out of 50 (and your essay technique, if section 2 is relevant) to ensure that you do yourself justice in the exam and make the most of the time available for you to prepare.

Optimise Your TSA Performance

Learn the best TSA strategies and practice with reflective TSA questions & worked solutions.

What is a good TSA score?

It is likely that, as applicants to the country’s best universities, you are used to getting 100% in school tests, and maybe even 100 UMS in A-level and GCSE exams. It is important to realise that the standard of the TSA means that this is not our goal! Instead, we need to be more realistic about what it is possible to achieve, and equally what it is necessary to achieve in order to get an offer or interview.

• An average score is 60, so roughly 28/50
• If you can score 70, you are in the top 10% of candidates and that equates to about 38/50

  Given this information, it is important not to be disheartened when you mark your work and get lower marks than you are used to getting at A-level. Put those numbers into context, but most importantly, use the mistakes that you make on each practice paper to learn and develop your technique.

Further Reading....

​ How Do I Prepare For The TSA? TSA Essay Tips & Techniques Example TSA Essay TSA Past Papers ​TSA Essay Plans Online TSA Course ​TSA Worked Solutions

TSA Past Paper Solutions

Need help? Email: [email protected]

Preparation

Useful links, contact us / opening hours.

• Monday - Friday: 9am - 8pm
• Saturday: 10am - 4pm
• [email protected]
• (020) 3393 8934
• Blackstone Tutors Ltd International House 142 Cromwell Road Kensington London SW7 4ET

Intensive BMAT Course

Bmat timetable.

• 10:00 - 11:00: BMAT Section 1 Techniques & Practice Questions
• 11:00 - 11:15: BMAT Section 1 Mock Exam
• 11:15 - 11:30: BMAT Section 1 Feedback
• 11:30 - 11:45: Morning Break
• 11:45 - 12:45: BMAT Section 2 Key Content & Practice Questions
• 12:45 - 13:00: BMAT Section 2 Mock Exam
• 13:00 - 13:15: BMAT Section 2 Feedback
• 13:15 - 14:00: Lunch Break
• 14:00 - 15:00: BMAT Section 3 Techniques & Implementation
• 15:00 - 16:00: BMAT Section 3 Mock Exam, Feedback & Further Discussion
• 16:00 - 16:30: Exclusive Interview Insight

The BMAT Course

Sample questions, please select your exam:.

• USMLE Step 1

• Themes & Problems

Middle School Themes and Problems

• Information Technologies
• Transportation
• Distribution & Logistics
• Manufacturing
• Agriculture, Food & Natural Resources
• Free internet access
• Reality television
• Setting the minimum age to own a smartphone at 16
• Artificial Intelligence
• Digital Learning

To prepare for MS Coding competition, teams should have knowledge of concepts (software development, computer science, and coding topics) that will be on the Coding written test. They also should be familiar and comfortable with using the Scratch programming language. 

Scratch is a free visual programming language available from the MIT Media Lab ( https://scratch.mit.edu/download ). An offline version of the Scratch tool should be downloaded and available on each team’s laptop.  

Teams that advance to the semifinalist level, based on written test performance, will perform a challenge using the Scratch programming language. Semifinalist teams will receive the challenge on site and will have two hours to complete it. (PLEASE NOTE: Semifinalist teams MUST have a version of this program available for offline use, as there will be no Internet access available during the semifinalist level of the competition.) 

Examples of the types of challenges students may be asked to complete can be found at this link: https://scratch.mit.edu/starter-projects

Theme: Editorial/Commercial Photography Students must submit a portfolio of four (4) digital photographs for a magazine spread (genre of their choice) with one being vintage in appearance. 

• The three greatest examples of technology in our lives.
• Important technology examples for learning.
• Technologies that should receive the greatest funding and testing for future development.
• Forensic Entomology
• Forensic Anthropology 
• Digital Forensics

Theme: A device that promotes school safety (e.g., security, monitoring, sensing) 

Theme:  A traveling game (a game that can be played in the car on a road trip) 

• Printable: Design a bi-fold brochure 
• Wearable: A t-shirt that can be given to participants
• Digital Signage: Short video (1 ½ - 2 ½ minutes) to be shown at the STEM night event

Theme: Ethical Use of Artificial Intelligence Minimum number of videos: 4 

Design Brief:  Website for a Makerspace  

Challenge: Develop a website for a fictitious makerspace in a community. It should provide information about what equipment and services the makerspace offers, membership information, hours, and a calendar of events. It should be easy to follow and include an option to reserve equipment or space.  

High School Themes and Problems

• C (version C11)
• C++ (version C++14)
• C# (version 6.0)
• Java (version 10)
• Javascript (NodeJS version 8.10)
• Python (version 3.6)
• Ruby (version 2.5)
• Swift (version 4.2)
• https://icpc.baylor.edu/compete/preparation
• https://www.codechef.com/
• http://www.usaco.org/index.php?page=contests
• http://blog.hackerearth.com/2013/09/competitive-programming-getting-started_11.html
• https://www.quora.com/What-is-the-best-strategy-to-improve-my-skills-in-competitive-programming-in-2-3-months 

Topic: Technology in Infrastructure 

Subtopic 1: Autonomous vehicles are the answer to increasing traffic demands, especially in large urban areas. 

Subtopic 2: Current carbon and renewable energy policies have a negative impact on power grid reliability and consumer pricing. 

Subtopic 3: Manufacturing companies should be exempt from restrictions on waste production due to their contributions to society.  

Design Problem:  Research and present a modern motor home/RV/camper. 

Topic: Green energy initiatives are important to reduce the negative effects of fossil-fuels on the environment. There are many renewable energy programs promoted and listed by the Environmental Protection Agency and they promote various incentives for homeowners to include more green and clean energy solutions in their homes. 

Challenge: Develop a website that compiles information for homeowners on green and clean energy home solutions and other initiatives. The website should provide basic information, cost, tax rebate information, and clean/green energy practices. 

Any tips as to improve problem solving score in TSA?

Quick Reply

Related discussions.

• TSA Outcomes Thread
• Oxbridge tsa
• Help required from Oxford TSA Conquerors!!!
• TSA Section 1 2023 / Oxford E&M (2024 entry) thread
• Oxford PPE GCSEs
• Are the section one TSA scores looked at separately or combined
• Oxford TSA prep
• Land Economy Application Thread 2022 Entry
• UCAT - Dead End
• Low UCAT score 2023
• I am so demotivated after getting a horrendous mock grades in y13
• How I got into Westminster School Sixth Form
• TSA section 1 preparation
• [Official] Oxford PPE Applicant Thread 2022
• Tips for A*s?
• Reapplying to Oxford PPE
• UKMT Senior challenge
• Human Sciences Applicants

Last reply 1 hour ago

Last reply 1 week ago

Last reply 2 weeks ago

Last reply 3 weeks ago

Articles for you

What jobs could you do with a business degree?

Will artificial intelligence put legal graduates out of work?

Why industry placements are so important for business students

You don’t need to take a law conversion course for the SQE… but here’s why you should

TSA Preparation: Your 6-Month TSA Preparation Timeline

Written by: Matt Amalfitano-Stroud

Welcome to Exams.Ninja’s 6-Month Preparation Timeline for the TSA.

Are you beginning to think about your application to Oxford ? If so, one very important element of the process to wrap your head around is the pre-interview admissions test. For a broad variety of subjects at these unis, this involves taking the Thinking Skills Assessment. Although the TSA can seem daunting at first, particularly due to the immense time pressure, you should be able to tackle this crucial test effectively with some smart preparation. This article will give you a ‘bird’s eye view’ of the process of preparing for the TSA, with a timeline including monthly breakdowns of the most useful things to be doing.  

Join us, alongside a successful Oxford applicant and TSA Expert as we unravel the mystery that is effective TSA preparation. Let’s get started!

Understand the TSA Format

The spring of Year 12 is a good time to start familiarizing yourselves with the basics of the Thinking Skills Assessment (TSA) . Firstly, it is important to check whether the course you are thinking of applying for requires it . This information can usually be found on the course pages of Oxford’s website .

Additionally, make sure you are aware of whether your course requires that you take Section 1 – the 90-minute multiple-choice exam focused on problem-solving and critical thinking – Section 2 – the written essay-based exam – or both . Economics & Management at Oxford , for example, has recently changed the process so applicants no longer have to take Section 2 , so ensure you have the most up-to-date information by referring to the websites of the universities and the test provider.  

Next, you’ll want to take a look at how the TSA is actually laid out. This table gives a basic overview of what you can expect:

Having a go at a past paper , which are found on the test provider’s website, is the quickest way of familiarising yourself with the format and accurately assessing your initial strengths and weaknesses. It’s a first-hand look at how the paper is laid out and what the questions are like .

Outside of this, you can see what people with TSA experience have to say by looking at  videos, blogs and websites (like The Student Room ). 

How to Create a Preparation Plan

Once you’ve got a good idea of what to expect from the TSA, you can get started on creating a preparation plan. Planning out your time across several months is obviously a tough ask, and you need to allow for some flexibility , but perhaps start out by adding big deadlines such as the deadline to submit your UCAS application, personal statement submissions deadlines (internal to school or for the final application),  and dates of any mocks, as well as activities that you undertake regularly at the same time every week. Find a set period of time every week to prepare for the TSA and make sure you have access to a distraction-free environment . At this stage, an hour or two is plenty! As you progress towards the autumn, however, increase this depending on how much you think you should be doing .

Exams.Ninja Tip

You may think that beginning revision six months in advance for a single exam is excessive , but look at it like this. 

These charts show two different methods of revising . The first is a lot more fast-paced , while the second is about taking small steps over a long period of time . At the end of it, you’re going to have done the same amount of work , but is the quality of the work going to be the same if you did it all in one month compared to utilising the full amount of time available? Most likely not!

TSA Revision Begins

Considering what we currently know about the TSA, one large question looms over us: how can you actually revise the TSA?

The TSA is designed to test general thinking skills (hence the title). It doesn’t feature any specific syllabus and does not test you on any form of content knowledge . Therefore, revision isn’t going to be about learning facts or processes from a textbook, it’s all about the questions!

Before trying to take on the questions in exam conditions, you will want to spend some getting to know all the different question types . When looking through TSA questions, you should try breaking down the problem-solving and critical thinking elements into certain question types . From there, you can attempt each one and see what question types you excel at and which ones need improvement. This will act as the basis for the rest of your time revising . You can learn more about each of these in our guides for TSA Problem Solving and TSA Critical Thinking!

From our TSA Expert: 

While I was going through all of the different types of questions in the TSA, I found that I was getting through the majority of the critical thinking questions pretty easily and usually getting them correct. What I struggled with were some of the problem-solving questions , particularly those involving measures. I had originally felt fairly confident in that area, but I wasn’t achieving the results I would want in the final exam , so it was clear to me that it was an area I should dedicate some extra time to . 

Wider Reading and Numeracy Skills

This early on in the process, you do have enough time to improve your long-term numerical and critical thinking skills to enable you to perform better. 

Attempt to improve your reading speed and comprehension by reading as much and as widely as possible. Subject-related reading will of course also come in handy when writing your personal statement and during the interview process, should you progress that far.   Pieces of writing which aim to persuade you to a certain line of thinking, such as opinion pieces in newspapers, are also good ways to practise critical thinking . Think about the underlying assumptions in the argument and whether the conclusion implied by the writer follows reasonably from the stated line of argument.

To increase your speed when answering numerical questions, it can be useful to brush up on your mental arithmetic skills , such as by ensuring you know your times tables well (up to your 15 times tables as a minimum) and that you become more comfortable doing calculations in your head to save as much time as possible. Calculators are a massive “no” during your prep , as they will not be allowed in the test.

How to Use TSA Practice Questions

At this point of the preparation process, it is important to start doing practice questions . There are all sorts of places to find these, be it past papers, online articles (such as the ones you’ll find at exams.ninja ) or from external question banks. As an example, you’ll have access to 500+ TSA questions from every section with our TSA Preparation Platform!

It is a good idea to save official TSA past papers for closer to the exam , as these are better to take in timed conditions when you have more experience with TSA questions. You ideally want to take past papers when you feel confident enough to get through the test in the time limit , but you don’t want to have already seen all of the questions as this won’t provide as much value as taking on a set of questions that are new to you. 

So in the meantime, our best advice is just to carry on with individual questions! You should be at the point where you can try to answer questions without using any additional resources , as well as monitor the time taken to answer them .

For Section 1, you’ll have 90 minutes to answer 50 questions . Therefore, you should be aiming to answer one question every 90 seconds . That’s not a lot of time considering the lengths of some of these questions, but working to this time frame will give you some extra time at the end of your 90 minutes to double-check your answers and reattempt any questions you skipped over. Getting in this habit now will make things much easier in the actual exam!

Exams.Ninja Tip 

A lot of people struggle to skip past questions once they’ve already started them. It’s understandable, as it feels like you may forget about it or not have time at the end to come back to it if you leave it now. However, this is a mindset that you’ll have to learn to get past , as skipping questions you find difficult is super important for using your time effectively in the exam . 

Remember, time is very limited , so spending too much time on a question that you’re struggling to get an answer for will do nothing but lose you marks from all the other questions you would have answered in that time. Besides, assuming you’ve managed your time well , you’ll have a chance to reattempt the question once you’ve finished! 

It’s never too early to start thinking about the TSA!

The time before your exam is incredibly busy, so getting your revision started early is the smartest thing you can do.  And when you’re revising, you’ll want the best resources you can get , which is exactly what Exams.Ninja’s TSA Preparation Platform provides! You can even try it for free right now!

TSA Section 2

This is an area that we haven’t discussed in detail yet. This is because the use of Section 2 in the TSA is extremely limited – only certain Oxford applicants will be required to take it. That’s not an insignificant number of people, but it’s still important to know if you need to prepare for this or not . 

For those that are taking it, the only way you can truly prepare for this is to carry on reading and writing . The wider reading that you’ve been doing for your critical thinking practice will be just as useful here, as you can analyse how these authors have explained their arguments and try to identify the techniques they use. 

Using this knowledge, you can then give it a go yourself , writing short essays about a specific topic or argument. You could write about current affairs, topics that interest or challenge you or just attempt some TSA questions . Of course, you’ll get better practice if you stick to exam conditions and do it within the official time limits. In fact, it’s a necessity to do this at least once before your sit the exam – the last thing you want to do is leave the essay unfinished on the big day! 

30 minutes to write a full essay? That’s practically no time at all! However, consider that the word limit for this essay is just 750 , so nobody will be expecting a thorough and complete analysis of the topic.

A good way to approach this time limit is as follows: 

• Take take around 3-5 minutes to plan out your main argument and any cases you want to present for it. 
• Spend 20 minutes writing the essay.
• Give yourself 5 minutes at the end to read through everything and check for errors. 

TSA Registration Opens

This is the month when TSA Registration Opens . test booking is handled by Pearson VUE via their online portal . You’ll be able to start booking your test slot from August 15th . 

The official deadline for registration is October 4th , but you’ll want to get the ball rolling on this as soon as possible. If you need access arrangements , you will need to contact Pearson VUE customer service to book your test. They may need further details and evidence to support your application, so ensure you bear this in mind when starting the process.

Here’s a quick rundown of the registration process:

• Before registration begins, you’ll need to create a Pearson VUE account . To do this, you’ll need to provide some personal and contact details. 
• When bookings open on the 15th, you can start the process by confirming the test you’re taking and selecting your testing centre from the options available. 
• You’ll next need to choose your date and time slot for your test sitting. This will be dependent on availability at your test centre, so aim to register as soon as possible to ensure you get the slot you want . 
• Before completing the registration, you’ll need to confirm that all the details are correct. You can then submit your booking, which should be approved soon after. Make sure you’ve received a confirmation email with the correct information. 

Taking Past Papers

As we get closer to the exam date, it’s time to start attempting serious mock exams to give you an understanding of just how challenging it can be to sit the TSA in proper conditions. 

You may already have specified this in your prep schedule, but you should take some time to c onsider which papers you’re going to do and when . It’s better to save the more recent ones for closer to the exam , as they will have the most similar question types to the paper you’ll be sitting. Like most other exams, t he specification and format may change between years , so always be aware of any potential difference when taking an older paper.

Let’s go over a few key tips for taking past papers:

The importance of keeping to time limits cannot be emphasised enough. Keep a close eye on the clock and do not spend more than 100 seconds at the very most per question (though don’t track this too obsessively or you may end up wasting more time than you save!)

Once you are done with a past paper, go through the mark scheme available online and mark as strictly as possible . It can be tempting to reward yourself after narrowing the options down to two plausible options and acting as if you would have got it right in the real thing! However, it is crucial to be as strict as possible when marking yourself so you can have the best understanding of your own performance and how to improve.

Re-attempt the questions you got wrong or skipped – you should be able to crack them the second time around without the time limit. Make notes on the type of question you got wrong and the process you took to solve it, so you can adopt a similar method if a similar question comes up again. 

Keep a note of the number of right and wrong answers in each category – problem-solving vs critical thinking – so you can better understand your strengths and weaknesses and how you should perhaps allocate time in the exam.

TSA Registration Closes

As we mentioned, the TSA registration finishes at the start of October – the 4th to be exact – so ensure you’ve received your booking confirmation  before this date. 

For Oxbridge applicants , October 15th is the deadline for your UCAS application , including your personal statement. Provided you planned your time correctly , you’ll have finished all of this and had everything submitted with time to spare. But if you perhaps forgot about this aspect of the application, you will likely need to set aside your TSA revisions for a week or so to make sure this is all as good as it can be. 

Final Weeks of Revision

The TSA is not a test you can cram for . Regular practice is the only thing that will allow you to perform well and maximise your score . If you are able to successfully create a well-thought-out plan and work according to this, you will be able to perform at your best. The only last-minute advice to bear in mind is to ensure you do not let your nerves get the better of you! The time pressure and additional stresses that come from putting in an Oxbridge application can be incredibly nerve-wracking , but ensuring you prioritise your sanity will improve your TSA performance in the long run!

I found that mindfulness and meditation can be helpful techniques for calming nerves, so regularly practising this in the run-up to the exam as I did may be beneficial for you. You’re not going to be performing at your best if your head is clouded by stress or negativity, so the key to a successful application is to look after your mental health just as much as your mental skills .

Keep things in perspective going into the TSA too! Although an important part of the process, it is not the be-all, end-all and your application will be considered holistically taking into account all aspects of your academic achievements, including the circumstances in which you achieved them!

TSA Testing Day

The TSA for Oxford in 2024 can be sat on October 24th,  so it’s important to mentally prepare yourself for the TSA, so be sure to follow the following tips:

• Get enough sleep the night before.
• Plan your journey beforehand and give yourself extra time.
• Bring your ID with you, as well as some food and water.
• Get there early to sign in and get settled down.

Most importantly, stay calm in the build-up! Keep your environment as stress-free as possible so you don’t distract yourself from the task at hand!

A final word from our TSA expert:

As with any important examination, the key to the TSA would be that practice makes perfect . Sticking to this rough framework can help you to ensure your practice is as effective and time-efficient as possible and that you can balance preparing for the TSA with all the other obligations that come up during your final years of school!  

As we’ve said, all of this is just a guideline for you to build your own preparation plan from. We believe that the methods we have presented to you will be the most effective way to perform well in the exam , but you may have additional ideas for revision techniques which are massively beneficial! This is your time, so it’s down to you to make the most of it! Whatever you decide to do, we wish you the best of luck with the TSA and beyond!

If you want to learn even more about the TSA, then you can check out our Definitive TSA Guide , which covers everything you’ll need to know before you start preparing! Or if you want to learn about the TSA is scored, the TSA Scoring and Results Guide is for you!

Oxford TSA Results 2023 – The Definitive Guide to your TSA Score

Tsa section 2: the definitive guide to section 2 of the tsa 2024, the ultimate guide to problem solving in tsa section 1, the definitive guide to tsa section 1: critical thinking, your definitive guide to choosing ecaa or tsa.

Do you want the complete package TSA resources?

With the TSA Preparation Platform , you’ll be getting everything you could possibly need to get yourself ready for the TSA! You’ll get instant access to all of the following:

Training Temple- Learn the ways of the TSA in our collection of comprehensive tutorials , designed to teach you everything you’ll need to know!

Practice Dojo- With over 500 true difficulty practice questions to work through, you’ll be able to practice right through till the exam. Learn how to solve every single one with our worked solutions .

Exam Arena-  When you’re ready to take the next step, we have 19 full past papers for you to complete! Each one is fully worked and provides true exam conditions , as well as automatic, accurate marking . 

Sign up today to try the TSA  Preparation Platform for free!  

Need any help? Contact us at:  [email protected] .

Exams Ninja 2024. All Rights Reserved. T&C.   Cookie Policy.   Privacy Policy.

Transforming Problem-Solving Within the TSA

When the Transportation Security Administration needed a way to accelerate problem-solving, they turned to BMNT for help. The result was the first-ever Innovation Doctrine in federal government.

The Challenge

Created in the aftermath of 9/11, the Transportation Security Administration (TSA) is a ubiquitous site in airports today. Its systems and procedures are designed to keep passengers safe in the nation’s airports and throughout major transportation systems. With constantly changing technology and threat levels, the TSA needs to be flexible and innovative.  The COVID-19 pandemic disrupted air travel, but it reinforced TSA’s need to innovate to maintain security. Solutions and adjustments needed to happen fast. Adherence to existing policies and procedures wasn’t going to get the job done.

The TSA wanted a new approach – something to accelerate problem-solving and transform the agency, giving personnel the freedom to suggest and test innovations that would improve efficiencies for frontline security officers, as well as improve the passenger experience. The effort needed to be guided by a common framework and language so the 60,000 employees spread throughout the TSA would understand how to innovate, not just restate what needed to be done.

The Resolution

TSA Administrator David Pekoske appointed Chief Innovation Officer, Dan McCoy, to lead the effort. McCoy then turned to BMNT. Together, we created the TSA Innovation Doctrine, the first of its kind in the federal government – a living document that guides the actions of TSA staff without dictating how those actions must be taken.

The Doctrine includes an enterprise-level system for innovation that is repeatable and scalable to solve problems throughout the agency. The Innovation Pipeline ® provides a systematic approach to generate a steady flow of actionable and mission-focused ideas for testing and implementation.

The Doctrine also commits principles like small bets – allowing staff to identify problems and test low-risk, scalable solutions to determine what works best. This leads to rapid implementation, allowing TSA to quickly scale viable ideas to address the constantly changing threat landscape.

Finally, TSA is growing ecosystems of interconnected networks including public and private industry and organizations to co-evolve capabilities around a shared set of technologies and principles. 

The Innovation Doctrine is not just a license to re-imagine and solve problems as they arise, it is a permission slip to fail fast, to move closer to genuine solutions.

The Impact: MORE TRUST, RAPID PROBLEM-SOLVING, ENHANCED SECURITY

Real-world applications quickly materialized. In 2022, TSA staff discovered 6,542 firearms during routine screenings. Most of those firearms were loaded, creating a serious threat to TSA officers, airport workers and passengers. When a firearm is found, checkpoints must close, lines get longer, and passengers are delayed. In 2023, TSA’s new Launchpad team used BMNT’s sprint model to address the issue. 

The team pulled in industry and subject matter experts and within 90 days the team developed two minimum viable products (MVPs) and one prototype, which is now being tested at Dallas Fort Worth airport by the local LIFT Cell.

Other innovation efforts are also underway, thanks to the TSA Innovation Doctrine:

• Over 325 employees, ranging from frontline security officers to TSA leaders, received personalized innovation training. This helps employees identify, scope, and solve TSA challenges regardless of where they exist in the organization. Solutions are being developed locally at airports, like breakaway barriers for K-9 screening and Advanced Image Technology (ATI) officer interface improvements, and TSA leadership has the visibility they need to make accurate budget requests and invest those funds wisely. 
• Over 60 LIFT Cells have been created at airports across the country to foster local innovation networks and accelerate real solution development. Guided by BMNT’s Innovation Pipeline ® LIFT Cells have curated hundreds of problems sourced directly from their airports, specifically their teammates. Teams at airports like Los Angeles International Airport (LAX) and Helena Regional Airport in Montana (HLN) partnered with the local community, including working with high school robotics teams to 3D manufacture TSO needed faceshield during the COVID-19 pandemic.
• The TSA Innovation Team has grown to reinforce the leadership’s commitment to enterprise-wide innovation support. Since the publication of the TSA Innovation Doctrine, the Chief Innovation Officer (CINO) team includes six full-time staff, several detailed programs, and executes approximately $2,500,000 to bring solutions to officers and passengers.

• Customer Success
• workforce programs
• BMNT IN THE NEWS
• Privacy Policy

An official website of the United States government

Here’s how you know

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( Lock A locked padlock ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Innovation Across the Nation: TSA officers create solutions to improve checkpoint security

TSA has been an agile agency since its creation. Built from the ground up in the wake of 9/11, TSA had no choice but to respond and adapt to a changing threat environment.

Two decades later, the spirit of innovation is alive and well at TSA. Frontline employees – the heartbeat of the agency – are intensively involved in making practical changes that support TSA’s vital mission while further enhancing the passenger experience.

Local Innovation for TSA (Lift) Cells, hubs of innovation that are instrumental in inventing solutions to the daily challenges the workforce faces, have identified more than 250 problems they are working on to help Officers become better, faster and more efficient in protecting the traveling public and keeping passenger satisfaction high. 

Here are just a few of the innovations Lift Cells have been working on across the nation:

Walk-through metal detector barrier

A common problem for many airports across the country is they don’t have anything to block passengers from accessing the walk-through metal detector (WTMD) when officers need to step away.   

“I knew this was an issue for some airports, but I was shocked from the feedback from the other Lift Cells that this was an issue for all size airports across the nation,” said Montgomery (Alabama) Regional Airport TSA Manager Robert Allen. “The idea of the walk-through barrier originated when I was at Bellingham International Airport (BLI) in Washington. We had a barrier made of cardboard that was falling apart. One of our screening officers, Gordy Lucrisia, made a PVC barrier and brought it in. It worked great.”

When Allen moved to College Station, Texas, to work at Easterwood Airport, he noticed there was no WTMD barrier. Allen asked Lucrisia for photos of the barrier at BLI. Allen then went to work, saying, “Some of the changes I made were to paint it TSA blue and add a sign that instructed passengers and crew to please wait. The staff were thrilled with the barrier. There were even times when crewmembers coming through asked to take pictures of it.”

When Allen moved on to work at Montgomery Regional Airport, one of the first things he did was build a barrier with more enhancements.

“Again, I was shocked they had nothing blocking the WTMD,” Allen said. “I found furniture grade PVC in TSA blue. It’s a heavier-duty PVC and looks very professional. I had another member of the Alabama Lift team assist me in the construction. It has worked great, and we look forward to making them for airports in the entire state.”

Allen compared the barrier they built to a barrier you could buy on Amazon or from another vendor. The officers tested it for a day and reviewed the Amazon barrier and the one they built. “The staff did not hold back. They hated the Amazon barrier,” Allen said. “On a 1-5 scale, they gave it an average rating of 1.07. The barrier we built rated an average of 4.73.”

At the Spring 2024 Lift Summit, Allen updated other Lift Cells and said, “They were excited to go back to their home airports and look into building their own barriers.”

Backpack strap gap filler

The Helena Regional Airport (HLN) Montana Lift team worked diligently to identify problems and come up with solutions to everyday issues officers encounter at the checkpoint.

The gap filler at the X-ray entrance tunnel was posing a problem because straps were getting caught in the small crack under the post of the entrance of the X-ray. The HLN Lift team created a fix to prevent baggage from getting snagged on the conveyor belt.

“There was a gap in the side posts where the bags enter the X-ray. The gaps were wide enough where backpack straps were getting caught and causing a jam inside the X-ray machine,” said TSA Manager Michael Ellis. “The Lift team designed and 3D printed an L-shaped cover that fit perfectly around the post, covered this gap and stopped straps from getting caught there. Since it was implemented, we have never had a strap get caught again.”

Since the gap filler worked so well, Ellis took the design and samples to the 2023 Lift Summit and showed other Lift Cell teams.

“The other Lift Cell team members liked it so much, they asked if they could get some for their airports as well,” Ellis said.

These have become so popular, TSA HLN printed over 300 backpack strap gap fillers, which over 25 airports are now using.

“This is what innovation and Lift is about,” Ellis said. “Airports are sharing ideas and designs so we can help each other solve some of the many problems our officers face every day working at the checkpoint.”

Notice of Inspection toolkit

The innovation journey often begins with identifying pain points and seeking creative solutions. After attending a Lift Summit at Los Angeles International Airport (LAX), TSA Manager Kevin Peinado explored ways to improve daily workforce activities in the checked baggage area.

The storage method used for Notice of Inspection (NOI) inserts involved converting glove boxes into makeshift containers and taping them at checked bag search tables. NOIs are legal notices placed in checked baggage after TSA inspection. They tell passengers that TSA officers opened and inspected their bag and provide contact information in case travelers have questions about the search.

Not only did the old storage method look messy, but it lacked professionalism. Peinado noted, “Our Officers deserve better.”

Recognizing the need to improve, Peinado and LAX Mission Support Administrative Assistant Maria McCants brainstormed solutions. The initial step involved using a prototype of clear plastic rectangular boxes to hold NOIs and attaching them to the nearest wall. The simple change garnered positive feedback, but the quest for improvement didn’t stop there. Through interviews with officers, Peinado and McCants gained valuable insights. 

It became clear the TSA team needed additional compartments for ziplock ties, box cutters and TSA keys. Prototype 2 was born, featuring clear plastic boxes with compartments on each side. After a two-week trial period, the LAX team collected more feedback, confirming the success of Prototype 2. However, officers expressed dissatisfaction with the box being taped to the wall. 

Prototype 3 addressed this concern by adding magnets to the back of the box, making it portable. This innovation allowed officers to position the box closer to their work area and adapt quickly in case of contingencies at the checked baggage area. 

McCants created a design sketch complete with measurements to communicate the design to a 3D printing service. The sketch included details and dimensions to ensure accurate production of the prototype. The 3D printed version is more durable and easy to use. TSA conducted production and cost-benefit analyses to ensure scalability efforts align with the budget and will provide favorable return on investment.   

Peinado presented the concept during the LAX senior leadership biweekly meeting with LAX TSA Federal Security Director Jason Pantages, who supported the plan. The idea quickly spread to other terminals at LAX with requests for similar boxes. LAX Lift partnered with the U.S. Air Force’s Spark Cells, which are a decentralized network of Air Force bases around the world to execute locally generated ideas and projects. This partnership led to the 3D printing of the boxes. The latest prototype features stronger and more durable compartments. 

“The Team LAX Lift Cell journey of innovation showcases the power of collaboration, user feedback and adaptability in finding practical solutions to workplace challenges,” Peinado said. “It ultimately leads to enhanced efficiency and professionalism in the checked baggage screening area using the NOI toolkit.”

By Mike Frandsen, TSA Strategic Communications & Public Affairs

Get Daily Travel Tips & Deals!

By proceeding, you agree to our Privacy Policy and Terms of Use .

How to Fix the TSA

Ed Hewitt started traveling with his family at the age of 10 and has since visited dozens of countries on six continents. He wrote for IndependentTraveler.com for more than 20 years, producing hundreds of columns on travel and offering his expertise on radio and television. He is now a regular contributor to SmarterTravel.

An avid surfer and rower, Ed has written about and photographed rowing competitions around the world, including the last five Olympic Games.

He's passing his love of travel on to the next generation; his 10-year-old son has flown some 200,000 miles already.

Travel Smarter! Sign up for our free newsletter.

It’s been just over a decade since the Transportation Security Administration (TSA) was folded into the newly created Department of Homeland Security. A decade is plenty of time for an agency to mature, come into its own and establish a reputation — and the TSA certainly has done so, but with sometimes appalling results.

The TSA was recently the subject of an unflattering study by the Government Accountability Office (GAO) — more on that later — but it doesn’t take an expert or a longitudinal study for us to know that the TSA has some issues. If you have gone through airport security in the past few years, you know as well as any expert that it can be a complete mess.

On a recent trip, I flew out of Gate 45 in Terminal B in Newark, and it took a full hour to get through security. If I did a diagram of what happened during that hour, you wouldn’t believe it. The scene looked like a run on a bank, with every person fending for themselves; the average preschool class is better organized and more professionally managed.

On that single pass through the airport, I saw:

– Agents milling around doing nothing

– Agents at the front of the line yelling conflicting information from those at the back of the line

– Supervisors rushing around doing baggage checks instead of supervising staff

– Some lines moving quickly and others barely moving at all, based simply on how hard the specific agents cared to work

– Lines and machines opening and closing while folks were still in them, with no real directions offered to those left stranded

– Lines within lines, with more than a dozen people waiting to get through one backscatter scanner after their bags had gone through, while a fully operational regular magnetic scanner was marked with Caution tape — except for a brief window when children were allowed to go through

– Bags lying around with no owners in sight (they’d been waylaid for several minutes after sending their bags/shoes/laptops through the X-ray machines)

– Travelers left to their own devices when trying to figure out which line to get into

– Families being separated for no good reason

– Actions by agents that seemed more intended to reinforce their authority than actually to make things work, with lots of orders being shouted but no order being imposed

– Overall very few signs of a systematic or professional approach to something as supposedly critical as national security

All told, it took the TSA about an hour to get perhaps a couple hundred people through security. Seriously, our local ShopRite checkout folks can get me and five bags of groceries through a line as fast as the TSA got me and one half-empty carry-on through the scanners.

When we finally got to the gate, the airline gate agents were sympathetic, understanding and fully on our side. “What the heck is going on out there?!?” one asked incredulously. Doing such a bad job that you leave behind flabbergasted travelers and airline employees alike is business as usual for the TSA at the Newark airport: “This happens all the time,” said the gate agent. It does appear to be a pretty regular occurrence; check out the complaints at TSAStatus.net .

The GAO (and Even the TSA) Agree The GAO did a study of the TSA’s processes for reviewing employee misconduct (including offenses from failing to screen passengers to large-scale theft operations), and found them wanting. The GAO brief TSA Could Strengthen Oversight of Allegations of Employee Misconduct outlines its findings and recommendations. In short, the GAO found that, while reportable employee incidents rose more than 25 percent in the preceding year, including absenteeism, sleeping on work hours, theft and inconsistent screening of passengers, the TSA’s processes for dealing with those incidents is extremely lacking. The GAO made four recommendations regarding the reporting and adjudication process for these incidents.

The TSA agreed, stating that the agency “concurs with GAO’s recommendations to ensure that the agency establishes a process to verify that TSA staff at airports are in compliance, and is already working to implement these recommendations.”

The report not only confirms the agency’s poor traveler approval ratings, but also provides further evidence that this is a system in which it is very difficult to have any confidence, particularly when it counts. Seriously, if the 20 – 30 agents we saw can’t manage three or four security lines that serve only seven gates in Newark, with people and luggage piling up all around them and tempers flaring throughout, it is hard to believe that they are being particularly effective at their actual mission.

Finally, getting a bit more personal (perhaps at my peril), too many TSA agents seem to hate either their jobs, the public or both. Don’t think so? Check out the comments on this article from PeterGreenberg.com , in particular those from people who identify themselves as DHS or TSA employees. The amplifying social media factor notwithstanding, it is a bit stunning that these folks would go public with that kind of invective, complete with name-calling and profanity, with the name of their employer on full display.

Of course, you will run into plenty of good agents and plenty of good supervisors, but the big picture is not a rosy one. And it’s not like effective, efficient security is impossible. On recent trips through Lithuania and the Netherlands, I encountered security checkpoints that were efficient, thorough, professional and, perhaps most importantly, somewhat intimidating and no-nonsense, which would make a potential terrorist think twice about trying to sneak something onto a plane. Compared to Newark, where you wonder if you will get through the line at all because of the staff goofing off, in Amsterdam you are instead making darn sure you are not goofing off. It’s a big difference.

Lest we think it is because these airports are small that things seem more efficient, it’s not the case; in 2012, Amsterdam’s Schiphol Airport handled 51 million passengers to Newark’s 33.9 million. They’re just doing a better job.

Criminality A highly publicized element of the GAO report was the TSA’s ongoing problem with criminality in its ranks, including one employee who stole upwards of $80,000 of passenger property. When I think back to my experience in Terminal B in Newark, and look over the list of conditions I observed as laid out above, it is little wonder to me that an employee could pull something like that off. With chaos in your own ranks, including supervisors doing jobs other than supervising, something that should be impossible to do — ripping off laptops in a federal security zone — becomes almost easy.

Sloppiness Notwithstanding all of the above, the one thing that strikes me as almost miraculously undeveloped after more than a decade in existence is the TSA’s use of modern crowd control techniques. It’s one thing if the old customs halls still look like they’re stuck in the 1970s, but the TSA is new and tremendously well funded, so there isn’t really any excuse not to employ modern tactics other than lack of organizational will. Simple things like decent signage, load balance among multiple checkpoints, and clear and obvious lanes for traveler traffic are hit or miss on a national basis.

What We Want (and Deserve) In addition to the GAO’s four somewhat inside-baseball recommendations, here are my four suggestions for how to improve the TSA from a traveler’s perspective. After all, we’re the ones paying for it.

1. Consistent use of modern crowd control methods. Look at any Disney theme park — these days the lines there look shorter and go faster than they did a decade ago, even while accommodating way more people. Tons of research and actual implementation can be found on this topic, and much of it is designed to increase security, not just move people faster. The TSA needs to do its homework in this regard, system-wide.

For example, line wait times at any decent amusement park are well managed and clear. Similarly, most good subway systems indicate when the next train is due, and many U.S. highways show time estimates for upcoming exits. Similar tactics could certainly be employed at the airports secured by the TSA. Clear monitoring of processing times would be a good start, while making appropriate adjustments inside the security zone, such as opening any idle machines and alerting staff to bottlenecks so they can adjust. Additionally, airports with multiple checkpoints could have screens listing average wait times at each checkpoint, so that travelers can choose the shortest ones and the lines will be more balanced.

2. A professional but serious environment. The bluster, posturing and sometimes shaming behavior now found at too many security checkpoints needs to be replaced with a professional, serious attitude focused on mission, not emotion and conflict. When the people in charge project the intent of the whole operation, then everyone knows why they are there, what to do and how to behave. When the people in charge are goofing off, ignoring issues or engaging in power trips, then the whole thing collapses. What should be a confidence-inspiring experience becomes an us vs. them scenario, the mission gets completely lost and no one actually feels more safe. Some airport security staffs are doing a good job on this front, but it is clearly a systemic issue.

3. Sensible, efficient and workable policies with respect to individuals with special needs. Beyond thefts, the worst reports of TSA abuses tend to focus on these folks who can’t always fend for themselves given the cattle-prodding nature of the current process — such as the elderly, families, the disabled and non-English speakers.

4. Oversight and supervision that would eliminate theft, criminality and unprofessionalism. The TSA has resorted to hidden cameras and stings to catch its own thieves, but in truth a few better-placed and better-trained supervisors would likely help this issue tremendously. If the TSA says it can get millions of us through security without us doing anything illegal, certainly it can police its own staff. Doctor, heal thyself.

Are you seeing a different TSA than I am, or is your experience similar? How about overseas?

We hand-pick everything we recommend and select items through testing and reviews. Some products are sent to us free of charge with no incentive to offer a favorable review. We offer our unbiased opinions and do not accept compensation to review products. All items are in stock and prices are accurate at the time of publication. If you buy something through our links, we may earn a commission.

Top Fares From

Don't see a fare you like? View all flight deals from your city.

Today's top travel deals.

Brought to you by ShermansTravel

Ireland: Wild Atlantic Way Trips w/Air...

Great Value Vacations

10-Night Mediterranean Cruise From Barcelona to...

Norwegian Cruise Line

Ohio: Daily Car Rentals from Cincinnati

Trending on SmarterTravel

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 20 June 2024

An improved gray wolf optimization algorithm solving to functional optimization and engineering design problems

• Yihui Qiu 1 ,
• Xiaoxiao Yang 1 &
• Shuixuan Chen 2 , 3  

Scientific Reports volume  14 , Article number:  14190 ( 2024 ) Cite this article

265 Accesses

Metrics details

• Computational science

As a newly proposed optimization algorithm based on the social hierarchy and hunting behavior of gray wolves, grey wolf algorithm (GWO) has gradually become a popular method for solving the optimization problems in various engineering fields. In order to further improve the convergence speed, solution accuracy, and local minima escaping ability of the traditional GWO algorithm, this work proposes a multi-strategy fusion improved gray wolf optimization (IGWO) algorithm. First, the initial population is optimized using the lens imaging reverse learning algorithm for laying the foundation for global search. Second, a nonlinear control parameter convergence strategy based on cosine variation is proposed to coordinate the global exploration and local exploitation ability of the algorithm. Finally, inspired by the tunicate swarm algorithm (TSA) and the particle swarm algorithm (PSO), a nonlinear tuning strategy for the parameters, and a correction based on the individual historical optimal positions and the global optimal positions are added in the position update equations to speed up the convergence of the algorithm. The proposed algorithm is assessed using 23 benchmark test problems, 15 CEC2014 test problems, and 2 well-known constraint engineering problems. The results show that the proposed IGWO has a balanced E&P capability in coping with global optimization as analyzed by the Wilcoxon rank sum and Friedman tests, and has a clear advantage over other state-of-the-art algorithms.

Similar content being viewed by others

Promising directions of machine learning for partial differential equations

Laplace neural operator for solving differential equations

An algorithmic framework for synthetic cost-aware decision making in molecular design

Introduction.

Swarm intelligence algorithms are a well-known class of metaheuristic algorithms that have been used to solve various engineering problems in recent years 1 , 2 . As compared with traditional numerical computation methods, swarm intelligence optimization algorithms have unique advantages in solving the problems associated with optimal engineering designs 3 , 4 , 5 . Swarm intelligence optimization algorithms have the advantages of simple principle, low requirements regarding the nature of the function, and easily computable global optimal solution. Consequently, they are widely used in solving constrained optimization problems 6 , 7 , 8 , 9 . For example, particle swarm optimization (PSO) 10 , whale optimization algorithm (WOA) 11 , grey wolf optimizer (GWO) 12 , tunicate swarm algorithm (TSA) 13 , seagull optimization algorithm (SOA) 14 , dingo optimization algorithm (DOA) 15 , golden jackal optimization, GJO) 16 , fox-inspired optimization algorithm (FOX) 17 , and other similar algorithms have been applied to appropriately address the functional optimization and engineering optimal design problems. However, there is room for further improvement in the quality of optimal solution, problem adaptability, and optimization stability of these algorithms. According to no-free-lunch (NFL) theorem, there is no single algorithm that can be used to effectively solve all optimization problems 18 . Therefore, exploring algorithms with higher accuracy, higher generalizability, and more stable solutions has been a focus of research community.

GWO is a meta-heuristic algorithm inspired by the hunting behavior of gray wolves 12 , 19 . In the iterative process of GWO, the leader wolves (α, β, and δ) guide the followers (ω) and keep narrowing down to approach the prey. During the process of searching the prey, the leader is influenced by the position of the prey, i.e., current global optimal solution, for global exploration. On the other hand, the followers perform full local exploration 20 . This act balances the mining and exploration capabilities and greatly reduces the probability of falling in local optimal solutions. Since the GWO algorithm has a simple structure, few control parameters, and high convergence accuracy 21 , more and more researchers have paid attention to the improvement and application areas of this algorithm. First, in order to achieve a good balance between exploration and exploitation, few researchers have combined GWO with other meta-heuristics. Duan et al. proposed the collaboration-based hybrid GWO-SCA optimization algorithm cHGWOSCA, and used it solve the PV model parameter extraction and 3-constraints engineering problem. The experimental results show that this algorithm has a high-performance 22 . Mohammed et al. improved the GWO algorithm by combining the advantages of whale optimization algorithm (WOA) and proposed a hybrid WOAGWO algorithm, which is used for solve an engineering problem such as pressure vessel design 23 . Mohamed et al. applied a hybrid GWO-PSO approach to address the grid-wide optimal reactive power scheduling problems. The simulation results confirm that the use of the hybrid GWO-PSO technique induces an observable improvement in the grid performance on a large scale 24 . Fatih et al. proposed three different hybrid algorithms for fusing PSO and GWO and used them for estimating the parameters of FM acoustic wave, and addressing the process flow diagram and leather nesting problems. The corresponding results verified the validity of these methods 25 .

On the other hand, few researchers have focused on strategy improvement operators to improve the mechanism of algorithms for enhancing their performance. Long et al. proposed a new stochastic dyadic-based learning strategy to help the populations jump out of the local minima. This algorithm performs well on global optimization and engineering design optimization problems 26 . Mohamed et al. proposed an improved grey wolf algorithm KMGWO based on the K-means method, which divides the population into two clusters using K-means to improve search efficiency 27 . Chen et al. introduced cat mapping and Gaussian variational perturbation strategies to effectively improve the convergence speed of GWO algorithm 28 . Gupta et al. introduced personal best history, crossover, and greedy selection strategies in their study to strengthen the global exploration capability of the GWO algorithm, and demonstrated that the resulting algorithm has a better search efficiency, solution accuracy, and convergence effect in global optimization tasks 29 . Bansal et al. used exploratory equations and inverse learning to improve the GWO algorithm. The experimental results show that this algorithm's exploration ability is better than other meta-heuristic algorithms 30 . Amir introduced two new convergence strategies to address the global optimization problem of GWO algorithm. The resulting improved algorithms, namely I-GWO and Ex-GWO, improve the performance based on the optimality seeking mechanism 31 . Wenchuan et al. introduced the inverse learning strategy and nonlinear convergence factor in standard GWO algorithm. The authors used SVM model for parameter optimization. The results show that the IGWO-SVM model has higher accuracy, efficiency, and solution stability 32 .

Due to the advancements in machine learning and intelligent optimization algorithms, more and more scholars have focused on the application of GWO to solve different real-world problems. Mohammad proposed GWO-based estimation method for photovoltaic (PV) solar cells, namely MG-GWO, which is used to extract the parameters of a single-diode photovoltaic (PV) solar cell model. The simulation results show that the MG-GWO algorithm outperforms the traditional GWO algorithm in terms of robustness and convergence speed 33 . Yan proposed a reliable and efficient emotion recognition scheme based on single channel electrocardiogram using GWO support vector machine (X-GWO-SVMs), which can be used for emotion recognition. The comparative experiments demonstrate that X-GWO-SVM algorithm is much more efficient than the existing solutions based on deep neural networks 34 . Runqian used hybrid extreme machine learning (ELM) -GWO to solve the structural problem of combined beams. It was observed that the hybrid model of GWO-ELM has a better performance as compared to separate ELM and GWO models 35 . Kun Zhang designed a distribution estimation gray wolf algorithm for low-carbon site selection path problem in the context of carbon pricing, and proved that the gray wolf algorithm with the addition of probabilistic model learning has a better optimization ability in the site selection path problem, and the constructed model can effectively reduce the total cost and carbon emissions in the context of carbon pricing 36 . Cai Yi et al. proposed a new model by combining a reverse mixed-frequency data sampling model (R-MIDAS) with GWO algorithm and used it for predicting the returns of 27 industry stock indexes and investment decisions 37 . In summary, the GWO algorithm has the ability to balance mining and exploration, accelerate the convergence speed in global search by linear convergence, improve the optimization accuracy in local search 38 , 39 , and avoid the emergence of local extreme points in small regions 40 . However, GWO is not very efficient for problems with more local extreme value regions and complex multibarrier problems, especially for engineering optimization problems with multiple constraints. The balance between global and local search, speed and traversability in global search, and fineness and perturbation in local search requires improvement and adjustment in accordance with different application backgrounds and types of problems. Therefore, more and more scholars have focused on new algorithms and improvement strategies to obtain a method that can be generalized for all problems.

In order to explore a better way to solve engineering optimization design problems, improve the optimization search accuracy of GWO algorithm, and expand the application space of the algorithm, this paper proposes a multi-strategy fusion of improved gray wolf optimization (GWO) algorithm. First, the initial population is optimized by using the lens imaging reverse learning algorithm, which lays the foundation for the global search. Second, a nonlinear control parameter convergence strategy based on cosine variation is proposed, which coordinates the global exploration and local development ability of the algorithm. Finally, inspired by the Tunicate Swarm Algorithm (TSA) 13 and the particle swarm algorithm (PSO) 10 , a nonlinear tuning strategy of parameters and the personal history-based optimal position and the modified position update equation of the global optimal position to enhance the convergence speed of the algorithm. The IGWO algorithm, obtained by integrating the GWO algorithm with the proposed improvement strategy, underwent benchmark function testing and comparative experiments with CEC2014 function. It was then compared with other classical swarm intelligence optimization algorithms, as well as with algorithms improved by others to validate the effectiveness of the improvement strategy proposed in this paper. Moreover, the improved algorithm proposed in this work is used to solve the design problem of three-bar truss and vehicle side impact to further verify its engineering applicability.

The rest of the paper is organized as follows.Section " Basics and background " briefly describes the theory and major steps of conventional GWO algorithm. Section " The proposed IGWO algorithm " describes the proposed hybrid algorithm in detail. Section " Experimental environment and results " discusses the simulation results of the improved algorithm IGWO and evaluates its performance. Section " IGWO for engineering design problems " discusses the results of the improved algorithm IGWO, when used for solving 2 classical engineering design problems. Finally, section " Conclusions " summarizes the whole paper.

Basics and background

Gray wolves live in packs based on a rigid social hierarchy. In a pack, there is a leader known as the α -wolf, who is responsible for making decisions regarding hunting, food allocation, and resting places 12 . The β -wolves are the members of secondary level, who mainly assist the α-wolf in decision-making. The δ -wolves are members belonging to the tertiary level and perform scouting and sentry duties. The ω wolves are located at the bottom of the hierarchy and are mainly responsible for maintaining a balanced relationship within the population. The hierarchy and predation process of the gray wolf population are demonstrated in Fig.  1 .

Schematic diagram of gray wolf population hierarchy and predation processes.

Let the dimension of the solution space of the GWO algorithm used to solve the optimization problem be d and the size of the gray wolf population be N , then, the location of the i - th gray wolf is expressed as follows:

The optimal, suboptimal, and third optimal solutions in the gray wolf population are denoted as α , β , and δ , respectively, and the rest of the solutions are denoted as ω . In order to find the optimal solution or the optimal position, ω constantly updates the position based on the positions of α , β , and δ . The positions of the gray wolves are computed as:

where, t is the number of iterations, X p (t) is the position of the prey, X(t) is the position of the gray wolf after t- th iteration, A is the convergence factor, and C is the swing factor. r 1 and r 2 denote random variables between [0, 1], and a is the distance control parameter, whose value decreases linearly from 2 to 0 as the number of iterations increase and optimal solution is approached. This is mathematically expressed as follows:

where, T max denotes the maximum number of iterations.

After the prey is surrounded, the α -wolf leads β - and δ -wolves in its pursuit. During this process, the escape of the prey causes the position of the gray wolf population to change. Therefore, the gray wolf population uses the positions of α , β , and δ wolves, i.e., X α , X β , and X δ , respectively, to update their positions. The update process is mathematically expressed as follows:

where, X(t  +  1) denotes the final updated position of the gray wolf. X α , X β , and X δ represent the positions of α , β , and δ , respectively. X 1 , X 2 , and X 3 denote the prey positions estimated from the positions of α , β , and δ , respectively. Algorithm 1 presents the pseudo-code of GWO.

Algorithm 1: GWO Algorithm

The proposed IGWO algorithm

In order to improve the performance of the traditional GWO algorithm, three strategies are proposed in this paper, including optimizing the initial population, modifying the nonlinear control parameters, and searching mechanism. The traditional GWO algorithm has the ability to quickly converge to the global optimum, but it easily falls into the local minima when dealing with complex optimization problems or high-dimensional problems. This performance degradation is caused due to the low exploration capability of the original GWO algorithm 30 . By optimizing the initial population, modifying the nonlinear control parameters and the search mechanism, we can enhance the exploration ability of the algorithm, thus improving its optimization ability. In summary, these strategies make the algorithm more competitive and have stronger performance.

Lens imaging reverse learning

After iteration, the GWO algorithm leads to a decrease in the diversity of the population at a later stage, and the gray wolf population becomes concentrated near the position of the optimal individual. As a result, it is difficult to jump out from the local minima when the optimal individual falls into it, which leads to the phenomenon of premature termination of the algorithm, and also causes a decrease in the accuracy of the search for the optimal point 19 . In order to solve this problem, we introduce the reverse learning strategy, which considers both the solution and its opposites, and expands the search scope and seeks the optimal solution by performing a bidirectional search in the search space. Combining the reverse learning strategy with swarm intelligence algorithm effectively improves the algorithm's search 26 . The mathematical principle is shown in Fig.  2 .

Schematic diagram of lens imagingreverse learning.

The individual x obtains its corresponding reverse point x * based on o , which can be obtained from the principle of lens imaging:

If k  =  h / h * , then Eq. ( 8 ) can be rewritten as:

Extend Eq. ( 9 ) to the d -dimensional optimization problem and obtain reverse learning based on lens imaging principle, as shown in Eq. ( 10 ).

Therefore, in this paper, the lens imaging reverse learning strategy is used to perturb the initial population of the gray wolf population in Eq. ( 1 ) to enhance the diversity of the population and increase the probability of the algorithm jumping out of the local optimum. The mathematical expression of this strategy is:

where \(X_{\min }^{d}\) and \(X_{\max }^{d}\) denote the minimum and maximum values of the d- th vector in all the initial solutions, respectively, and \(X_{i}^{d*}\) is the lens inverse solution of \(X_{i}^{d}\) . The scaling factor k of the lens plays a crucial role in the learning performance of lens imaging. A smaller value of k generates a larger range of inverse solutions, while a larger value of k leads to a small range of inverse solutions for localized fine search. In order to effectively utilize the characteristics of the GWO algorithm, which performs large-range exploration during early iterations and local fine search during later iterations, this work proposes a conditioning factor that varies with the number of iterations. The mathematical expression of this adjustment factor is presented below:

where, t is the current number of iterations and T max is the maximum number of iterations. k plays a role in regulating the inverse solution. As the number of iterations increases, the value of k becomes larger, resulting in a smaller range of inverse solutions for lens imaging inverse learning. This conditioning mechanism enhances the fine search for localized locations during later iterations of the algorithm.

Modified control parameter

When |A|≥ 1, the gray wolves in the GWO algorithm expand the search range in order to perform a global search. On the other hand, when |A|< 1, the individuals in the gray wolf population narrow their search range to finely search for the optimal solution. From (5), it is evident that the distance control parameter a determines the value of the variable A. The value of the parameter a plays a key role in assisting the algorithm to perform global and local search. However, the parameter a decreases from 2 to 0 in a linear manner as the number of iterations increases. This linear change strategy does not accurately reflect the actual nonlinear search process, which may cause the algorithm to fall into a local optimum 38 , 39 . In response to this deficiency, this paper proposes a nonlinear control parameter convergence strategy. This is mathematically expressed as follows:

where, t denotes the current number of iterations, T max denotes the maximum number of iterations, K is the nonlinear modulation index, and a initial and a end are the initial and final values of parameter a, respectively. In order to achieve better exploitation goals, in this work, we fix the value of k to 0.3 and set the values of a initial and a end to 2 and 0, respectively. As shown in Fig.  3 , this paper compares the linear and nonlinear control parameters. It can be observed in Fig.  3 that the linear behavior of the control parameters indicates 50% for global exploration and 50% for local mining, while the nonlinear behavior of the control parameters suggests 25% for global exploration and 75% for local mining. Therefore, the use of nonlinear control parameters focuses more on mining, which improves the local search and reduces the possibility of skipping the true solution.

Linearly and non-linearly decreasing curve for parameter a.

Modified search mechanism

The information provided by α , β , and δ wolves are important factors in updating the position of ω wolves. In the traditional GWO algorithm, the average value of the estimated positions of the three best search agents ( α , β and δ ) is used to obtain the new position of the wolf 20 . Logically, the traditional GWO provides a new position at the center of mass of the convex region surrounded by the orientation points obtained by α , β , and δ wolves. Therefore, the new position of the wolf is oriented in the same direction as the estimated positions of the α , β , and δ wolves. However, this logic does not work effectively when the lead wolves are stuck in a local minima or are far from the optimum 29 . Therefore, inspired by the TSA 13 and PSO 10 algorithms, a nonlinear adjustment strategy for the parameters and a modified position update equation based on the individual's historical optimal position and the global optimal position are added to reduce the possibility of falling into a local optimum. Among them, the position update equation of TSA algorithm is shown in (14), and the position update equation of PSO algorithm is shown in (15).

where \(v_{i} = v_{i} + c_{3} *rand()*(pbest_{i} - x_{i} ) + c_{4} *rand()*(gbest_{i} - x_{i} )\) , v i is the particle velocity, rand() is a random number between (0, 1), and c 1 and c 2 are learning factors. Usually c 1  =  c 2  =  2 . pbest i (t) denotes the individual historical best position and gbest i (t) denotes the global historical best position.

In summary, this paper proposes a new search mechanism expressed as:

where X 1 and X 2 denote the prey positions estimated from the positions of α and β , respectively. b 1 and b 2 denote the individual memory coefficient and group communication coefficient, respectively. b 1  =  b 2  = 0.5. r 3  =  r 4 are uniformly distributed random numbers between [0, 1], pbest i (t) denotes the best position in the history of the individual, and randn() denotes the random perturbation term with a normal distribution. w 1 and w 2 are the inertia weights, which are expressed as follows:

where f α and f β denote the adaptation values of α -wolf and β -wolf during t- th iteration, respectively.

By embedding all the aforementioned strategies in the original GWO algorithm, a new variant of GWO called IGWO is proposed. Algorithm 2 presents the pseudo-code of IGWO containing all the strategies.

Algorithm 2: IGWO algorithm

Experimental environment and results

In this work, 23 optimization benchmark problems with different characteristics 12 , 41 , 15 optimization problems from CEC2014 30 , 42 , and two engineering problems are used to evaluate the performance of the proposed IGWO algorithm. Table 1 presents benchmark problems, including 7 single-peak problems ( F 1 -F 7 ), 6 multi-peak problems ( F 8 -F 13 ), and 10 multi-peak problems with fixed dimensions ( F 14 -F 23 ). As presented in Table 2 , 15 functions in CEC2014 are selected in this paper, including 1 single-peak function ( F 03 ), 7 multi-peak functions ( F 06 , F 08 -F 11 , F 13 , F 16 ), 1 hybrid function ( F 19 ), and 6 combined functions ( F 23 -F 24 , F 26 -F 29 ). Where Dimension ( N ) denotes the number of decision variables and Range ( D ) denotes the boundary of decision variables. The optimal values corresponding to each test function are given in Tables 1 and 2 . The single-peak test function has only one global optimum, which is useful for testing the local search ability of the algorithm. Unlike the single-peak problem, the multi-peak problem has multiple local optima. These local optima increase with an increase in the number of dimensions. The global search ability of the proposed algorithm can be tested by solving the multi-peak problem. In contrast, multi-peak problems with fixed dimensions, combined functions, and hybrid functions are used to demonstrate the exploration and exploitation capabilities of the proposed method.

The experiments performed in this work are divided into 4 parts. First, the proposed IGWO is compared with other swarm intelligence optimization algorithms and other improved GWO algorithms based on a 30-dimensional benchmark test problem.In the second part, the proposed IGWO is compared with other swarm intelligence optimization algorithms and other improved GWO algorithms based on 100, 500, and 1000 dimensional scalable test problems of F 1 -F 13 . In the third part, the proposed IGWO algorithm is used to solve the CEC2014 problem. Finally, the proposed IGWO algorithm is applied to 2 classical engineering problems.

All these experiments are performed in the same environment (parameter settings). The parameter settings of all meta-heuristic optimization algorithms are set based on the literature, as shown in Table 3 . The maximum number of iterations T max is set to 1000 for all functions, the population size is set to 30 individuals, and the population size is initialized in the same manner for all algorithms being compared in this work. All the results obtained for the benchmark problem, the CEC2014 problem, and the engineering problem are averaged over 30 epochs. The experimental results are analyzed based on two criteria: (1) the mean and standard deviation (Std) values of the best results obtained during the 30 trials of the algorithms, and (2) statistical analysis based on Wilcoxon rank sum and Friedman's tests. In addition, all the experiments are performed on the same machine with an i5 processor with 16 GB of RAM and Win10 64-bit operating system. The experiments are implemented in MATLAB.

Analysis of different strategies

In this subsection, to verify the impact of each strategy in the IGWO, three different combinations are added in the GWO algorithm such as Strategy-1, Strategy-2, and Strategy-3. In Strategy-1, only lens imaging reverse learning is added to the GWO algorithm. In Strategy-2, only a modified control parameter is added to the GWO algorithm. In Strategy-3, only a new location search mechanism is added to the GWO algorithm. IGWO means that all strategies are added to the GWO algorithm. Same benchmark problems ( F 1 - F 23 ) have been used to verify the impact of each strategy. The parameter settings are as same as in section " Experimental environment and results ", and each benchmark problem runs 30 times, individually. The specific experimental results are shown in Table 4 .

The experimental results from Table 4 demonstrate that the proposed IGWO outperforms the other three strategies on 23 benchmark problems and is capable of achieving near-optimal values on multiple problems. Strategy-3 is considered a suboptimal optimizer, yet all three strategies perform better than the original GWO algorithm. Strategy-1 introduces a lens imaging reverse learning strategy to enhance population coverage and uniformity, but the performance improvement is not significant. Strategy-2 incorporates a nonlinear convergence strategy, significantly enhancing the search ability and efficiency during the exploration process, leading to significant improvements in average fitness values and standard deviations across multiple problems. Strategy-3 introduces a new position update strategy, significantly boosting the algorithm's capability to avoid local optima, though it remains a suboptimal optimizer. The IGWO algorithm combines the advantages of these three strategies and leverages optimization performance to the highest level, demonstrating outstanding performance in function optimization.

Comparison using benchmark functions

In this subsection, the performance of IGWO is analyzed and compared with other swarm intelligence optimization algorithms based on the mean and standard deviation (Std) of 30 independent epochs. The best results are highlighted in bold. Table 5 presents the optimization search results obtained using the proposed IGWO, GWO 12 , MFO 43 , SHO 44 , TSA 13 , PSO 10 , DOA 15 , GJO 16 , SOA 17 , WOA 11 , FOX 17 , catGWO 28 , and CPSOGSA 45 for 23 benchmark functions.

The results show that the proposed IGWO outperforms other algorithms in terms of finding the optimal solution for single-peak and multimodal test functions, especially in terms of standard deviation, which has mostly improved by several orders of magnitude. It has achieved theoretical optimal values on functions F 1 – F 4 , F 9 , and F 11 , verifying that the implementation of the improvement strategy effectively improves the convergence accuracy and exploration and development capabilities of the GWO algorithm, providing more reliable solutions and technical support for solving complex optimization problems. For the multimodal problems with fixed dimensions ( F 14 – F 23 ), the IGWO proposed in this work performs better in F 15 – F 17 and F 19 – F 23 . The reason why the IGWO algorithm performs suboptimal only on F 14 and F 18 is that it relies too much on searching near the individual's historical optimal position in the early stages of iteration. Although it improves the algorithm's global exploration ability and convergence speed, it lacks exploration around the optimal position, which to some extent limits the algorithm's potential to jump out of local optima.In summary, it can be concluded that the proposed IGWO algorithm has the best ability to explore the potential regions and avoid local optima in the search space.

In order to further analyze the performance of the proposed IGWO algorithm, the convergence curves of all the benchmark functions are shown in Fig.  4 . The performance of the proposed IGWO algorithm is compared with that of GWO, MFO, SHO, TSA, PSO, DOA, GJO, SOA, WOA, catGWO, and CPSOGSA in this paper. It can be seen that the proposed IGWO algorithm outperforms other algorithms in terms of convergence speed and accuracy in most cases.

Convergence curve of the basis function.

Experiments on large-scale problems

In order to analyze the performance of the proposed IGWO algorithm on difficult optimization problems, numerical experiments are conducted on 100, 500, and 1000 dimensional problems as presented in scalable problems F 1 -F 13 , respectively. The IGWO algorithm is compared with GWO, MFO, SHO, TSA, PSO, DOA, GJO, SOA, WOA, catGWO, and CPSOGSA. For ensuring a fair comparison, all algorithms are executed under same conditions (i.e., the population size is set to 30 and the maximum number of iterations is set to 500). The results of all the experiments are averaged over 30 epochs. The specific results are shown in Table 6 .

From Table 6 , it can be seen that for 100, 500, and 1000 dimensional problems, the IGWO algorithm proposed in this paper has better performance as compared to other algorithms. In addition, as the dimensionality increases, the proposed IGWO continues to provide the best solution. Therefore, it can be concluded that the proposed IGWO is insensitive to the growth of dimensionality and has superior optimization search capability and scalability. Figure  5 depicts the convergence curves of the algorithms under 500 dimensions. From these figures, it can be seen that the proposed IGWO converges faster while maintaining a higher level of dimensional accuracy as compared to other swarm intelligence optimization algorithms. The aforementioned analysis shows that the adopted strategy is suitable for complex problems and IGWO performs more robustly for higher dimensional problems.

Convergence curves on 500 dimensional problems.

Statistical analysis

In order to determine whether the proposed IGWO algorithm is significantly better than its competitors, this paper uses a nonparametric test, i.e., the Wilcoxon rank sum test 46 , for 30, 100, 500, and 1000 dimensions. The statistical results at 5% significance level are shown in Tables 7 and 8 . In the tables, + /−/≈ denote that IGWO is better/worse/same as the algorithm being compared, respectively.

Friedman test is a nonparametric and multiple comparison test used to assess significant differences between two or more algorithms. In this work, it is used to assess significant differences in five different dimensions (Dim = 30, 100, 500, and 1000) 47 . Table 9 shows the statistical results for four different dimensions, which are sorted based on the average ranking produced by the Friedman test. It is noteworthy that the proposed IGWO consistently performs best in different dimensions.

Comparison with other algorithms on CEC2014 benchmark functions

In this section, 15 benchmark functions from CEC2014 are used to further evaluate the performance of the proposed IGWO algorithm. The names, classes, and global optima of the functions are presented in Table 2 . The dimensions and ranges of the variables are 10 and [− 100, 100], respectively. The chosen benchmark function with constraints and high computational cost is challenging as compared to the classical benchmark function.

The functions in CEC2014 provide complex shapes and multiple local optima that approximate the search space of real-world problems, thus effectively evaluating the effectiveness and robustness of the model. Table 10 shows the average fitness values (Avg) and standard deviation (Std) of fitness values obtained by different algorithms for solving the CEC2014 problem. As presented in Table 10 , the proposed IGWO ranks first in terms of fitness values on 15 CEC2014 test functions. As compared with the original GWO algorithm, the proposed IGWO algorithm shows a significant improvement in the optimality searching ability on 10 functions, and the average fitness value for the remaining 5 functions is the same as that of the original GWO algorithm. In addition, as compared with other 11 algorithms, although the solutions of some algorithms on individual functions are equal to or slightly better than IGWO, in general, IGWO outperforms the other algorithms on other functions. In summary, IGWO has better optimization seeking performance as compared to GWO in dealing with complex optimization problems.

In order to verify the statistical significance of the results of IGWO on the CEC2014 test function, Wilcoxon rank sum test is performed in this paper. In order to verify the performance of the proposed IGWO, a significance level of 5% is selected. The corresponding statistical results are presented in Table 11 . In addition, Table 12 shows the average rankings generated by Friedman's test. The results show that the proposed IGWO significantly outperforms GWO, MFO, SHO, TSA, PSO, DOA, GJO, SOA, WOA, catGWO, and CPSOGSA. The overall analysis shows that the proposed IGWO is a better optimizer as compared to other methods.

IGWO for engineering design problems

In order to highlight the performance and practical significance of the proposed IGWO algorithm, 2 classical engineering problems are used for further validation, i.e., automobile side impact design and three-bar truss design, and the results are compared with other algorithms. These 2 engineering problems are static single-objective constrained optimization problems. The example problem is generally expressed as (18).

where, F(x) is the objective function ; g i (x) is an inequality constraint, and h j (x) is an equality constraint. In this paper, a penalty function is used to effectively handle the constraints, as expressed in (19).

where, \(\Phi (x)\) denotes the final objective function, and l i and o j are two non-negative penalty coefficients. The larger the penalty coefficients, the better is the final optimization effect. The penalty coefficients in this paper are 1,000,000. ɑ and β are set to 2 and 1, respectively.

Three-bar truss

The three-bar truss design problem is one of the most classical design problems 8 . Its structure is shown in Fig.  6 . The objective of the problem is to minimize the weight of the light rod structure. The constraints of the problem include stress, deflection, and buckling. Mathematically, the three-bar truss design problem is expressed in (20). The results obtained after parameter optimization of each algorithm are shown in Table 13 .

where 0 ≤  x 1 , x 2  ≤ 1, L  = 100 cm, P  = 2 KN/cm 2 , \(\sigma\)  = 2 KN/cm 2 .

Schematic diagram of three-bar truss structure.

A comparison of the results obtained using the proposed IGWO with other swarm intelligence algorithms and the existing improved GWO algorithm is given in Table 13 . The results show that the proposed IGWO is not worse than other algorithms in solving the three-bar truss design problem, and its optimal solution corresponds to the best fitness value of 263.91802312 [0.79267752, 0.39714963]. The results show that the algorithm is able to find the design solution with the lowest cost. Therefore, it is reasonable to conclude that the proposed algorithm is feasible in solving this type of problems.

Automobile side impact design issues

The automobile side impact design problem is a classical single-objective minimization constrained design problem 9 . The design objective is to reduce the total weight of the car. The mathematical model of this problem is presented in (21).

As presented in Table 14 , the proposed IGWO outperforms other algorithms and achieves the best results. It obtains the optimal solution corresponding to the optimal fitness value of 21.39473 [0.5, 0.88641, 0.5, 1.25781, 0.64809, 0.91372, 0.5, 1, 0.52483, 1.94790, 15.3719].

In summary, the results show that the proposed IGWO outperforms other compared algorithms. It can be seen that IGWO not only improves the global search capability, but also helps to prevent the search from falling into local minima and effectively solves engineering design problems.

Conclusions

In this paper, a multi-strategy fusion improved gray wolf algorithm IGWO is proposed by combining three different strategies, including optimizing the initial population, modifying the nonlinear control parameters, and the search mechanism. These modifications effectively balance the exploration and exploitation, while maintaining a high convergence rate. In order to verify the effectiveness of the improved algorithm, the proposed IGWO is assessed using 23 benchmark test functions and 15 CEC test functions of 4 different complexity levels. The corresponding test results are statistically analyzed. The results show that the improved algorithm performs well and enhances the convergence speed and search accuracy. In order to verify the engineering applicability of the improved algorithm, in this paper, the improved algorithm is applied to the automobile side design and the three-bar truss design problems. The results show that the proposed method outperforms other swarm intelligence optimization algorithms in solving the engineering optimization problems.

Data availability

All data generated or analysed during this study are included in this published article.

Singh, S. & Bansal, J. C. Mutation-driven grey wolf optimizer with modified search mechanism. Expert Syst. Appl. 194 , 116450 (2022).

Article   Google Scholar  

Zhao, Z. Z. et al. A modifed shufed frog leaping algorithm with inertia weight. Sci. Rep. 14 , 4146 (2024).

Article   CAS   PubMed   Google Scholar  

Abdelkader, A. et al. Parameters identification of photovoltaic cell models using enhanced exploratory salp chains-based approach. Energy 198 , 117333 (2020).

Hussein, M. R. et al. Boosted mutation-based Harris hawks optimizer for parameters identification of single-diode solar cell models. Energy Convers. Manag. 209 , 112660 (2020).

Peraza, C., Valdez, F., & Castillo, O. Harmony search with dynamic adaptation of parameters for the optimization of a benchmark set of functions. In Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine , 97–108 (2020).

Liu, J. S., Yuan, M. M. & Li, Y. Solving engineering optimization design problems based on improved salp swarm algorithm. J. Syst. Simul. 33 (04), 854–866 (2021).

Google Scholar  

Sayed, G. I. & Hassanien, A. E. A hybrid SA-MFO algorithm for function optimization and engineering design problems. Complex Intell. Syst. 03 , 195–212 (2018).

Haq, T. & Koziel, S. Inverse modeling and optimization of CSRR-based microwave sensors for industrial applications. IEEE Trans. Microw. Theory Tech. 11 , 4796–4804 (2022).

Article   ADS   Google Scholar  

Wang, Y. W. et al. Improved marine predators algorithm with multi-strategy fusion and its engineering applications. Comput. Integr. Manuf. Syst. 254 , 1–21 (2022).

Kennedy, J. & Eberhart, R. Particle swarm optimization[C]//Proceedings of ICNN’95-international conference on neural networks. IEEE 4 , 1942–1948 (1995).

Mirjalili, S. & Lewis, A. The whale optimization algorithm. Adv. Eng. Softw. 95 , 51–67 (2016).

Mirjalili, S., Mirjalili, S. M. & Lewis, A. Grey wolf optimizer. Adv. Eng. Softw. 69 , 46–61 (2014).

Kaur, S. et al. Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization. Eng. Appl. Artif. Intell. 90 , 103541 (2020).

Dhiman, G. & Kumar, V. Seagull optimization algorithm: Theory and its applications for large-scale industrial engineering problems. Knowl.-Based Syst. 165 , 169–196 (2019).

Peraza-Vázquez, H. et al. A bio-inspired method for engineering design optimization inspired by dingoes hunting strategies. Math. Prob. Eng. 40 , 1–19 (2021).

Chopra, N. & Ansari, M. M. Golden jackal optimization: A novel nature-inspired optimizer for engineering applications. Expert Syst. Appl. 198 , 116924 (2022).

Mohammed, H. & Rashid, T. FOX: A FOX-inspired optimization algorithm. Appl. Intell. 51 (01), 1030–1050 (2023).

Wolpert, D. H. & Macready, W. G. No free lunch theorems for optimization. IEEE Trans. Evolut. Comput. 01 , 67–83 (1997).

Yu, X., Xu, W. & Li, C. Opposition-based learning grey wolf optimizer for global optimization. Knowl.-Based Syst. 226 , 107139 (2021).

Rodríguez, L. et al. A fuzzy hierarchical operator in the grey wolf optimizer algorithm. Appl. Soft Comput. 57 (01), 315–328 (2017).

Long, W. et al. Inspired grey wolf optimizer for solving large-scale function optimization problems. Appl. Math. Model. 60 , 112–126 (2018).

Article   MathSciNet   Google Scholar  

Duan, Y. & Yu, X. A collaboration-based hybrid GWO-SCA optimizer for engineering optimization problems. Expert Syst. Appl. 213 , 119017 (2023).

Mohammed, H. & Rashid, T. A novel hybrid GWO with WOA for global numerical optimization and solving pressure vessel design. Neural Comput. Appl. 32 (18), 14701–14718 (2020).

Shaheen, M. A. M., Hasanien, H. M. & Alkuhayli, A. A novel hybrid GWO-PSO optimization technique for optimal reactive power dispatch problem solution. Ain Shams Eng. J. 12 (01), 621–630 (2021).

Şenel, F. A. et al. A novel hybrid PSO–GWO algorithm for optimization problems. Eng. Comput. 35 (04), 1359–1373 (2019).

Long, W. et al. A random opposition-based learning grey wolf optimizer. IEEE Access 7 , 113810–113825 (2019).

Mohammed, H. et al. A new K-means grey wolf algorithm for engineering problems. World J. Eng. 18 (04), 630–638 (2021).

Xu, C. H. et al. Improved grey wolf optimization algorithm based on chaotic Cat mapping and Gaussian mutation. Comput. Eng. Appl. 53 (04), 1–9 (2017).

CAS   Google Scholar  

Gupta, S. & Deep, K. A memory-based Grey Wolf Optimizer for global optimization tasks. Appl. Soft Comput. 93 , 106367 (2020).

Bansal, J. C. & Singh, S. A better exploration strategy in Grey Wolf Optimizer. J. Ambient Intell. Hum. Comput. 12 (01), 1099–1118 (2021).

Seyyedabbasi, A. & Kiani, F. I-GWO and Ex-GWO: Improved algorithms of the Grey Wolf Optimizer to solve global optimization problems. Eng. Comput. 37 (01), 509–532 (2021).

Wen, C. & Ji, G. Y. Evaluation and application of legalized business environment based on IGWO-SVM model. Oper. Res. Manag. Sci. 32 (02), 200–206 (2023).

Alshabi, M. et al. Multi-group grey wolf optimizer (MG-GWO) for estimating photovoltaic solar cell model. J. Therm. Anal. Calorim. 144 (05), 1655–1670 (2021).

Article   CAS   Google Scholar  

Yan, X. et al. A novel exploitative and explorative GWO-SVM algorithm for smart emotion recognition. IEEE Internet of Things J. 10 (11), 1 (2023).

Ma, R. et al. Assessment of composite beam performance using GWO–ELM metaheuristic algorithm. Eng. Comput. 38 , 2083–2099 (2022).

Zhang, K. et al. Grey wolf optimizer with distribution estimation for low carbon location routing problem. J. Syst. Manag. 32 (04), 701–711 (2023).

Cai, Y., Tang, Z. P., Wu, J. C., et al . Research on the application of GWO-SVR algorithm in the prediction of reverse mixed data in stock market and investment strategy. Chin. J. Manag. Sci. 1–16.

Mittal, N., Singh, U. & Sohi, B. S. Modified grey wolf optimizer for global engineering optimization. Appl. Comput. Intell. Soft Comput. 01 , 7950348 (2016).

Long, W. et al. An exploration-enhanced grey wolf optimizer to solve high-dimensional numerical optimization. Eng. Appl. Artif. Intell. 68 , 63–80 (2018).

Rezaei, F. et al. An enhanced grey wolf optimizer with a velocity-aided global search mechanism. Mathematics 10 (3), 351 (2022).

Xin, Y., Yong, L. & Guangming, L. Evolutionary programming made faster. IEEE Trans. Evolut. Comput. 3 (02), 82–102 (1999).

Salgotra, R. et al. Marine predator inspired naked mole-rat algorithm for global optimization. Expert Syst. With Appl. 212 , 118822 (2023).

Mirjalili, S. Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowl.-Based Syst. 89 , 228–249 (2015).

Dhiman, G., & Kaur, A. Spotted hyena optimizer for solving engineering design problems. In 2017 International Conference on Machine Learning and Data Science. IEEE , 114–119 (2017).

Rather, S. A. & Bala, P. S. Hybridization of constriction coefficient-based particle swarm optimization and chaotic gravitational search algorithm for solving engineering design problems. Appl. Soft Comput. Commun. Netw. 125 , 95–115 (2020).

Derrac, J., Garcia, S. & Molina, D. A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evolut. Comput. 1 (1), 3–18 (2011).

Carrasco, J. et al. Recent trends in the use of statistical tests for comparing swarm and evolutionary computing algorithms: Practical guidelines and a critical review. Swarm Evolut. Comput. 54 , 100665 (2020).

Download references

The work was supported by the National Natural Science Foundation of China, Youth Program (Grant No. 7180040248) and the Natural Science Foundation of Fujian Province of China (Grant No. 2022J011261) and Fujian Provincial Department of Science and Technology University Industry University Cooperation Science and Technology Major Project (Grant No. 2021H6010) and Fujian Provincial Key Laboratory of Green Intelligent Cleaning Technology and Equipment.

Author information

Authors and affiliations.

School of Economics and Management, Xiamen University of Technology, Xiamen, 361024, China

Yihui Qiu & Xiaoxiao Yang

School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen, 361024, China

Shuixuan Chen

Fujian Provincial Key Laboratory of Green Intelligent Cleaning Technology and Equipment, Xiamen, China

You can also search for this author in PubMed   Google Scholar

Contributions

Y.Q.: Conceptualization, Supervision; X.Y.: Methodology; S.C.: Writing-editing. All authors reviewed the manuscript.

Corresponding author

Correspondence to Shuixuan Chen .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Qiu, Y., Yang, X. & Chen, S. An improved gray wolf optimization algorithm solving to functional optimization and engineering design problems. Sci Rep 14 , 14190 (2024). https://doi.org/10.1038/s41598-024-64526-2

Download citation

Received : 24 February 2024

Accepted : 10 June 2024

Published : 20 June 2024

DOI : https://doi.org/10.1038/s41598-024-64526-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Grey wolf algorithm
• Function optimization
• Engineering design optimization
• Exploration and exploitation

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing: AI and Robotics newsletter — what matters in AI and robotics research, free to your inbox weekly.

More From Forbes

Stumped five ways to hone your problem-solving skills.

• Share to Facebook
• Share to Twitter
• Share to Linkedin

Respect the worth of other people's insights

Problems continuously arise in organizational life, making problem-solving an essential skill for leaders. Leaders who are good at tackling conundrums are likely to be more effective at overcoming obstacles and guiding their teams to achieve their goals. So, what’s the secret to better problem-solving skills?

1. Understand the root cause of the problem

“Too often, people fail because they haven’t correctly defined what the problem is,” says David Ross, an international strategist, founder of consultancy Phoenix Strategic Management and author of Confronting the Storm: Regenerating Leadership and Hope in the Age of Uncertainty .

Ross explains that as teams grapple with “wicked” problems – those where there can be several root causes for why a problem exists – there can often be disagreement on the initial assumptions made. As a result, their chances of successfully solving the problem are low.

“Before commencing the process of solving the problem, it is worthwhile identifying who your key stakeholders are and talking to them about the issue,” Ross recommends. “Who could be affected by the issue? What is the problem – and why? How are people affected?”

He argues that if leaders treat people with dignity, respecting the worth of their insights, they are more likely to successfully solve problems.

Best High-Yield Savings Accounts Of 2024

Best 5% interest savings accounts of 2024, 2. unfocus the mind.

“To solve problems, we need to commit to making time to face a problem in its full complexity, which also requires that we take back control of our thinking,” says Chris Griffiths, an expert on creativity and innovative thinking skills, founder and CEO of software provider OpenGenius, and co-author of The Focus Fix: Finding Clarity, Creativity and Resilience in an Overwhelming World .

To do this, it’s necessary to harness the power of the unfocused mind, according to Griffiths. “It might sound oxymoronic, but just like our devices, our brain needs time to recharge,” he says. “ A plethora of research has shown that daydreaming allows us to make creative connections and see abstract solutions that are not obvious when we’re engaged in direct work.”

To make use of the unfocused mind in problem solving, you must begin by getting to know the problem from all angles. “At this stage, don’t worry about actually solving the problem,” says Griffiths. “You’re simply giving your subconscious mind the information it needs to get creative with when you zone out. From here, pick a monotonous or rhythmic activity that will help you to activate the daydreaming state – that might be a walk, some doodling, or even some chores.”

Do this regularly, argues Griffiths, and you’ll soon find that flashes of inspiration and novel solutions naturally present themselves while you’re ostensibly thinking of other things. He says: “By allowing you to access the fullest creative potential of your own brain, daydreaming acts as a skeleton key for a wide range of problems.”

3. Be comfortable making judgment calls

“Admitting to not knowing the future takes courage,” says Professor Stephen Wyatt, founder and lead consultant at consultancy Corporate Rebirth and author of Antidote to the Crisis of Leadership: Opportunity in Complexity . “Leaders are worried our teams won’t respect us and our boards will lose faith in us, but what doesn’t work is drawing up plans and forecasts and holding yourself or others rigidly to them.”

Wyatt advises leaders to heighten their situational awareness – to look broadly, integrate more perspectives and be able to connect the dots. “We need to be comfortable in making judgment calls as the future is unknown,” he says. “There is no data on it. But equally, very few initiatives cannot be adjusted, refined or reviewed while in motion.”

Leaders need to stay vigilant, according to Wyatt, create the capacity of the enterprise to adapt and maintain the support of stakeholders. “The concept of the infallible leader needs to be updated,” he concludes.

4. Be prepared to fail and learn

“Organisations, and arguably society more widely, are obsessed with problems and the notion of problems,” says Steve Hearsum, founder of organizational change consultancy Edge + Stretch and author of No Silver Bullet: Bursting the Bubble of the Organisational Quick Fix .

Hearsum argues that this tendency is complicated by the myth of fixability, namely the idea that all problems, however complex, have a solution. “Our need for certainty, to minimize and dampen the anxiety of ‘not knowing,’ leads us to oversimplify and ignore or filter out anything that challenges the idea that there is a solution,” he says.

Leaders need to shift their mindset to cultivate their comfort with not knowing and couple that with being OK with being wrong, sometimes, notes Hearsum. He adds: “That means developing reflexivity to understand your own beliefs and judgments, and what influences these, asking questions and experimenting.”

5. Unleash the power of empathy

Leaders must be able to communicate problems in order to find solutions to them. But they should avoid bombarding their teams with complex, technical details since these can overwhelm their people’s cognitive load, says Dr Jessica Barker MBE , author of Hacked: The Secrets Behind Cyber Attacks .

Instead, she recommends that leaders frame their messages in ways that cut through jargon and ensure that their advice is relevant, accessible and actionable. “An essential leadership skill for this is empathy,” Barker explains. “When you’re trying to build a positive culture, it is crucial to understand why people are not practicing the behaviors you want rather than trying to force that behavioral change with fear, uncertainty and doubt.”

• Editorial Standards
• Reprints & Permissions

Join The Conversation

One Community. Many Voices. Create a free account to share your thoughts. 

Forbes Community Guidelines

Our community is about connecting people through open and thoughtful conversations. We want our readers to share their views and exchange ideas and facts in a safe space.

In order to do so, please follow the posting rules in our site's  Terms of Service.   We've summarized some of those key rules below. Simply put, keep it civil.

Your post will be rejected if we notice that it seems to contain:

• False or intentionally out-of-context or misleading information
• Insults, profanity, incoherent, obscene or inflammatory language or threats of any kind
• Attacks on the identity of other commenters or the article's author
• Content that otherwise violates our site's  terms.

User accounts will be blocked if we notice or believe that users are engaged in:

• Continuous attempts to re-post comments that have been previously moderated/rejected
• Racist, sexist, homophobic or other discriminatory comments
• Attempts or tactics that put the site security at risk
• Actions that otherwise violate our site's  terms.

So, how can you be a power user?

• Stay on topic and share your insights
• Feel free to be clear and thoughtful to get your point across
• ‘Like’ or ‘Dislike’ to show your point of view.
• Protect your community.
• Use the report tool to alert us when someone breaks the rules.

Thanks for reading our community guidelines. Please read the full list of posting rules found in our site's  Terms of Service.

Gun violence an 'urgent' public health crisis; surgeon general wants warnings on firearms

The soaring number of children killed by firearms has created an “urgent public health crisis” worthy of the response the government took to preventing cigarette smoking or car accidents, the nation’s top doctor said in a first-of-its-kind announcement Tuesday.

In an advisory , Surgeon General Vivek Murthy said gun violence demands a public health approach rather than the polarizing political response that has numbed Americans and public officials to enacting change as gun violence became the leading cause of death in children . Public health campaigns have provided a playbook for addressing the uniquely American problem of gun violence that kills nearly 50,000 people a year, he said.

“I want people to know this is a profound public health crisis, but it is a solvable public health crisis,” he told USA TODAY. “As a nation, we are not powerless. We can do something about it.”  

Gun violence: America’s largest mass shooting is the one happening every day. But we know how to stop it

Murthy's approach involves a range of responses, including warning labels on firearms, as with other consumer products, reinstating the ban on assault weapons and laws on safe gun storage to reduce the risk of homicides and suicides . He also emphasized the increased need for mental health resources for victims of gun violence, including trauma-informed health care and school-based services. 

In a statement posted to social media Tuesday morning, a National Rifle Association official called Murthy’s advisory “an extension of the Biden Administration’s war on law-abiding gun owners.”

“The reluctance to prosecute and punish criminals on the part of President Biden and many of his allies is the primary cause of that,” said Randy Kozuch, executive director of the NRA’s Institute for Legislative Action, the organization’s lobbying arm.

The U.S. has already seen 235 mass shootings in 2024, according to the Gun Violence Archive , a nonprofit that tracks incidents involving four or more victims. Homicides and suicides, which don't get as much coverage , drive the country’s death toll.

Murthy’s call for an immediate public health response comes after similar calls for intervention from the American Medical Association and the American Public Health Association , which have long identified gun violence as a public health scourge. But Murthy's role as the nation’s top physician during two presidential administrations gives the declaration added weight.

Does it matter if we frame gun violence as a public health issue?

Murthy has issued previous advisories for public health crises, including alerts about the dangers of social media and an epidemic of loneliness. During the Obama administration, Murthy issued a crisis alert about e-cigarettes . Historically, surgeons general have issued warnings about pressing health concerns. Murthy said he believes this advisory can drive broader public awareness about the toll of gun violence in America.

“A public health approach is really fundamentally about ensuring that we are defining clearly a problem and its impact on health,” he said, adding it requires using data to understand the extent of the problem and who is most affected.

What difference does an official warning make?

Murthy’s advisory draws from the Centers for Disease Control and Prevention’s response to violence prevention, which begins with monitoring through data and research, looking at risks and requiring widespread adoption. 

The advisory highlights interventions in communities and schools and mental health support, as well as safe and secure gun storage, background checks and effective gun removal policies. The advisory also explicitly calls for banning assault weapons and large-capacity magazines for civilian use, along with restrictions on carrying loaded firearms in public spaces, concealed and open carry, and rules about using firearms in public.

The advisory calls for treating gun regulations like the U.S. does other consumer products, as it does motor vehicle standards, pesticide regulations and Food and Drug Administration approvals. Firearms do not have the same safety testing or safety features, including warning labels, as other products do.

Death rates for young people far surpass other countries

Gun violence has steadily risen in recent years. In 2022, more than 48,000 people died by gun violence, according to the advisory. That’s 16,000 more deaths than in 2010. Firearm-related suicides have increased by 20%, including a “staggering increase” in such deaths among young people, the advisory noted. 

Having guns increases the risk for all household members of dying by homicide and suicide, the advisory said. And keeping firearms unlocked also increases the risk of young people dying by suicide and accidents or suffering unintentional injuries.

In 2020, gun violence overtook car accidents as the leading cause of death among children. Firearm deaths among children and adolescents in the U.S. are six times as prevalent in the U.S. than in Canada and happen at more than 10 times the rate in Switzerland. In the Netherlands and the United Kingdom, the death rate by firearms is nearly 50 times lower than in the U.S.

Gun ownership: Supreme Court upholds law banning domestic abusers from owning guns

“Gun violence has now become a kids' issue,” Murthy said. “In my mind, that elevates the urgency and importance of us addressing this public health crisis.”

People of color are disparately affected by gun violence because they disproportionately live in poverty and in marginalized communities where they face an increased risk of shootings. 

The spillover effects of gun violence are sweeping, and not just for the victims. People who witness a shooting or lose loved ones to gun violence are more likely to experience depression or anxiety, according to the advisory. Victims' family members also face increased mental health struggles. Children whose parents die by homicide or suicide are likelier to experience depression, heart disease or cancer, and these experiences are shown to impact them through life, at school and work, the advisory said .

Mass shootings, which make up a small percentage of U.S. gun deaths, have outsized mental health consequences, causing people to worry about the risks of going to public places and events, the advisory said.

How can public health help solve the problem?

Murthy said he hopes the advisory will increase awareness and prompt health care systems and legislators to prioritize solutions.

In 1964, Luther Terry, the surgeon general for President Lyndon B. Johnson, issued an advisory that tobacco use was hazardous and caused cancer. At that time, Murthy said, cigarette smoking was “deeply embedded in the fabric of America.”

A year later, Congress enacted a law to create a warning label on cigarette products, according to the Association of Centers for the Study of Congress at the University of Delaware. Tobacco use dropped precipitously afterward , with declines in lung cancer and youth smoking, as a federal report showed.

Identifying the public health risks of smoking helped change the culture and make Americans safer. The same can be done with gun violence, Murthy said.

• Oxbridge Law 24/25 Entry
• Non-Oxbridge Law 24/25 Entry
• Oxford PPE 24/25 Entry
• Oxbridge Economics 24/25 Entry
• Oxbridge Modern Languages 24/25 Entry
• Cambridge Land Economy 24/25 Entry
• Oxbridge Psychology 24/25 Entry
• Oxbridge English 24/25 Entry
• Oxford Human Sciences 24/25 Entry
• Oxbridge History 24/25 Entry
• Oxbridge Geography 24/25 Entry
• Cambridge Philosophy 24/25 Entry
• Oxbridge Classics 24/25 Entry
• Cambridge Architecture 24/25 Entry
• Cambridge HSPS Programme 24/25 Entry
• Oxbridge Medicine 24/25 Entry
• Oxford Biomedical Sciences 24/25 Entry
• Oxbridge Engineering 24/25 Entry
• Cambridge Natural Science 24/25 Entry
• Oxbridge Maths 24/25 Entry
• Oxbridge Computer Science 24/25 Entry
• Oxford Physics 24/25 Entry
• Oxford PPL 24/25 Entry
• Cambridge Veterinary Science 24/25 Entry
• Oxford Chemistry 24/25 Entry
• Oxford Biology 24/25 Entry
• Oxford Biochemistry 24/25 Entry
• Non-Oxbridge Medicine 24/25 Entry
• Non-Oxbridge Dentistry 24/25 Entry
• IMAT Medicine 24/25 Entry
• Can’t Find Your Subject?
• Law Interview Programme
• PPE Interview Programme
• Economics Interview Programme
• Oxbridge Medicine Interview Programme
• Natural Science Interview Programme
• Engineering Interview Programme
• Maths Interview Programme
• Dentistry Interview Programme
• Medicine MMI Interview Programme
• Our Guarantee

Our Students

Student Success Stories

• University Access Scheme
• New Tutor Application Form
• Frequently Asked Questions
• How Does It Work?

Enrol on a UniAdmissions Programme by the 21st June and enjoy a £500 reduction on your fees. Schedule your consultation here today.

Secure your place on a UniAdmissions Programme by Friday, 21st June, and enjoy a £500 reduction on your enrolment fees. Schedule your consultation here today.

• +44 (0) 208 068 0438
• [email protected]

SCIENCE PROGRAMMES (25/26 ENTRY)

HUMANITIES PROGRAMMES (25/26 ENTRY)

GET STARTED

Can't find your subject?

OXFORD TESTS (25/26 ENTRY)

CAMBRIDGE TESTS (25/26 ENTRY)

MEDICINE TESTS (25/26 ENTRY)

View Our Free admissions guides & resources

How UniAdmissions Cracked The Oxbridge Formula

Applying for Oxbridge is an opportunity seldom approached correctly. So how do you enter the top 16% of a strong cohort of applicants that get an offer? Discover how UniAdmissions get 2/3 of our students in.

UCAT Registration 2024: What You Need To Know

Every year, thousands of medicine applicants take the UCAT aiming for top scores. To take the test, you must register first. This guide provides all the information you need to secure your UCAT registration.

Inside The UniAdmissions Portal: The UA Advantage

UniAdmissions students have access to the world's first dedicated Oxbridge admissions preparation platform, and this guide will help you discover exactly how the Portal will help you get your offer.

Discover all guides

ABOUT UNIADMISSIONS

Learn about who the world's first Oxbridge prep school are.

Learn about the Portal; the heart of our Programmes.

UniAdmissions' Foundation

The Foundation is our charitable arm to support disadvantaged students.

Students & Tutors

Discover who a UniAdmissions student is and our admissions criteria.

Learn about our high-performing Oxbridge tutors.

We're proud of our alumni. Read about their journey with UniAdmissions here.

Admissions Resources

Free Admissions Guides

Visit our Learning Centre and read our in-depth free guides.

We are the world's biggest Oxbridge application publisher. Learn more here.

Teachers Learning Hub

Learn about how to help your students get their place at Oxbridge.

Get Started

• Access Student Portal
• Oxbridge Programmes
• Open Day Webinar
• Tutor Application Form
• Common Questions
• Download Our Prospectus
• How to Apply TSA Critical Thinking Skills in the Test

Last Updated: 6th November 2018

Author: Adi Sen

Table of Contents

How to apply tsa critical thinking skills in the thinking skills assessment..

TSA Critical thinking skills are one of the requirements expected of applicants to demonstrate when taking the test. The TSA (Thinking Skills Assessment) is a key part of Oxford and UCL admissions for those hoping to study subjects including PPE and Psychology.

The written exam tests many of the skills required to succeed whilst at Oxford like communication ability, writing skills as well as critical thinking skills; the latter will be the focus of this article.

What are the TSA Critical Thinking Skills?

The TSA critical thinking skills are most tested in Section 1 of the TSA, where they make up half the questions in the paper (the other half being problem-solving skills). These questions require you to analyse and form judgements using the provided data, which is usually in the form of a passage of text. Candidates are being tested on their ability to think constructively and it is akin to verbal reasoning. In contrast to problem-solving skills, there is no need for mathematical ability.

Cambridge Assessment Admissions Testing explains why critical thinking is included in the TSA:

We have TSA guides for each of the sections to help you develop your understanding of the test:

In the next section, we’ll go through an example TSA question and show the thinking skills that are required.

Example of a TSA critical thinking skills question

Whilst many people claim to have been abducted by aliens, the most likely reasoning would be sleep paralysis. In this state of sleep, the dreamer might hear strange noises, lights, and movement that they associate with the experience of being abducted. Most all recorded experiences, such as these, coincide with the people who say they’ve been abducted by aliens.

Sleep paralysis is fairly common and is experienced by three out of ten people. The phenomenon could explain the sensations reported by many who have claimed to have been abducted, therefore, we can come to the conclusion that aliens are not really abducting people and have not actually come to Earth.

From the argument above, which of the following is an underlying assumption that the argument is making?

Alien abductions are rarer than people think.

Dreaming about being abducted is unusual.

Others who also believe they’ve been abducted by aliens haven’t reported it.

People who are abducted rarely remember their experiences.

People will always remember their dream if it’s about being abducted by aliens.

Analysis of the Question and Answers:

This question has been taken from the TSA specimen paper and is one of the final questions. Typically, both the critical thinking and the problem-solving questions increase in difficulty as the paper goes on, so this is representative of one of the tougher questions that you might encounter on the paper.

• TSA Historical Results and Scoring

We’ll now go through the possible answers and reveal which is correct.

The article makes no mention of the rarity of alien abduction; it flat out denies they occur at all in the very last sentence (‘we can conclude that aliens have not come to Earth’) and so this is at odds with the answer and is clearly not the assumption.

The article seeks to explore why people think they have been abducted by aliens. The commonness or unusualness of alien abduction dreams is not relevant to this analysis.

Answer C:  

The correct answer; the conclusion is that aliens have not carried out abductions by explaining away the reported symptoms and conditions; it there excludes the possibility of unreported abductions having different symptoms. This is most highlighted by the sentence ‘Most all recorded experiences such as these coincide with the people who say they’ve been abducted by aliens.’

Answer D:  

The article makes no mention of people forgetting their abduction experiences and, as such, this is not a right answer.

Answer E:  

Again, a fairly irrelevant statement. Some candidates may pick E instead of C, but the logic underpinning C more clearly applies to the passage.

Is your goal to score highly on the TSA?

The   UniAdmissions TSA Programme  will rapidly boost your score and  triple your chances of succeeding  in your application.

Our expert tutors guide you through past papers in mock exam scenarios so that you are well-prepared by the time your exam comes around. UniAdmissions helps students refine and hone their abilities so that they’re exam-ready on test day for all aspects of the TSA.

UniAdmissions students placed at Oxford And Cambridge

Continue learning about Oxbridge...

Economics degree entry requirements uk.

If you're thinking about studying an economics degree in the UK, you'll need to be aware of the various entry…

Economics University Rankings UK: 2024 Results

When it comes to selecting a university, many students place an emphasis on university rankings. Economics course rankings for the…

Cambridge Announces The ESAT To Replace The NSAA & ENGAA

In 2023, it was announced by the University of Cambridge that many of their established admissions tests would stop being…

Successful Personal Statement For Economics & Management At Oxford

Writing an Economics and Management Personal Statement for Oxford? If so, you’re in the right place! In this post, we…

Oxbridge Interview Invitations Guide

The waiting period between submitting your UCAS application on the 15th of October and receiving an Oxbridge Interview invitation is…

Which UK Universities Use Interviews?

Which of the universities I applied to require Interviews? Read on to learn which universities and their courses require Interviews,…

The Secrets to Oxbridge Admission.

• We cracked the Oxbridge formula . Find out what we discovered here.
• Looking for application support? Don't work with a random tutor. This is what you need to know first.
• Get up-to-date Oxbridge advice with our webinars. Follow our Open Days led by our experts and stay updated.
• Begin your Oxbridge journey with UniAdmissions through our programmes of support by clicking here.

How would you like to speak to an Admissions Consultant?

BrainFlex+: Tricky Puzzles 4+

Play, learn, improve, brainflex, co., designed for iphone.

• 5.0 • 1 Rating

iPhone Screenshots

Description.

Get Smarter with Brain-Boosting Puzzle Games! Train your cognitive skills like memory, logic, and problem-solving through our fun and challenging brain games. Based on cognitive research, these tricky puzzles will give your mind a workout while keeping you entertained. Unique Puzzles: • Block Escape - control small blocks to find a best route from chaotic obstacles, improving your thinking ability; • Pointer Rotation - aim the pointer at the disc quickly and accurately, which is an excellent and interesting reaction training; • Logic Connection - use your imagination and logical ability to connect 1000+ different but closely related pictures; • Double Ring Rotation - control two rings to make timely and correct reactions, exercising your left and right brains concurrently. Super Assistance: • 30+ unique brain teasers for all ages and levels • Personalized daily training and progress tracking • Increasing difficulty to continually challenge you Excited? Try This App to Start Brain Training! Elevate your brainpower and unlock your full potential. User Agreement: https://plusbrainflex.com/userEn.html Privacy Policy: https://plusbrainflex.com/Privacy.html If you have any questions or suggestions, contact us([email protected]).

Version 1.2

Our update contents: 1. New game for brain training added: Logic Fill, a game use your logical thinking to solve puzzles and fill in the grids according to the clues. 2. New game for reacion training released: Miner Master. Seize the opportunity and grab the brightest treasure!

Ratings and Reviews

App privacy.

The developer, BrainFlex, Co. , indicated that the app’s privacy practices may include handling of data as described below. For more information, see the developer’s privacy policy .

Data Used to Track You

The following data may be used to track you across apps and websites owned by other companies:

• Identifiers

Data Not Linked to You

The following data may be collected but it is not linked to your identity:

• Diagnostics

Privacy practices may vary, for example, based on the features you use or your age. Learn More

Information

English, Simplified Chinese

• Developer Website
• App Support
• Privacy Policy

Solving Major Problems: Major Bleeding and Major Surgery for Patients on Anticoagulants

• Chantel Dockstader, MD

T his interactive session posed real-life scenarios for hospitalists who frequently deal with difficult anticoagulation questions and grounded it all with the evidence.

The first case discussed was an elderly female on a direct oral anticoagulant (DOAC) for atrial fibrillation (AF) and acetylsalicylic acid (ASA) for coronary artery disease (CAD) who is admitted for symptomatic anemia. Despite an esophagogastroduodenoscopy, colonoscopy, and capsule endoscopy, no source of bleeding is found. The question is, when would you restart a DOAC? It was quickly noted that the ASA should be discontinued. Considerations weighed should include the risk of re-bleeding, and the risk of venous thromboembolism (VTE) along with the patient’s own goals of care. Two retrospective studies were reviewed with one meta-analysis. The American and Canadian gastrointestinal societies, along with the European guidelines, all support a “sweet spot” for resumption of seven to 14 days after bleeding has resolved.

The second case discussed the management of a high VTE-risk patient in the perioperative setting. Is bridging needed? And what about post-op VTE prophylaxis? Hospitalists should consider the patient’s thrombotic risk based on their history of VTE. A recent VTE occurring within the last three months, and especially within the last month, is considered high-risk, while a VTE that occurred more than 12 months ago is considered low-risk. This assessment should be balanced with the procedural bleeding risk, with, for example, major orthopedic surgery posing a high bleeding risk and pacemaker implantation posing a low risk. The evidence reviewed here was a summary of many observational studies including the PROSPECT and BRIDGE trials. The American College of Clinical Pharmacy recommendations were discussed, including the recommendation to bridge with heparin over no heparin bridge for high-VTE-risk patients on vitamin K antagonists (VKA). In line with the recommendations, it was suggested to wait at least 48 to 72 hours before resuming low molecular weight heparin bridging in patients having a high-bleed-risk surgery or procedure. During this pause of full bridging anticoagulation, deep vein thrombosis (DVT) prophylaxis doses of resumed low molecular weight heparin can be given.

The third case illustrated the need for more shared decision making regarding anticoagulation when the evidence is weak or lacking. Shared decision making incorporates clinical evidence and the patient’s unique circumstances, along with their values, to arrive at a decision that is best for that individual patient. It’s an ethical imperative and our patients value it. Some barriers noted were time pressure, discomfort around challenging communication, assumptions about the patient’s poor health literacy, and prognostic or clinical uncertainty. We can improve shared decision making by fostering awareness of choices, introducing options, assisting patients in the evaluation of options based on their goals and concerns, discussing potential harm or benefit, and finally offering a recommendation and assisting patients in following through. Several decision aids for AF might be helpful for patients to visualize risk, however, they are not useful when weighing cerebrovascular accident risk versus bleeding risk.

The fourth case was a young person with a mechanical aortic valve replacement on warfarin who suffered a traumatic intraparenchymal bleed requiring urgent surgical intervention. What should be used to reverse the warfarin? Rapid reversal is required, and thus four-factor prothrombin complex concentrate should be used rather than fresh frozen plasma, with the suggested additional use of intravenous vitamin K in a dose of 5 to10 mg. An open-label, noninferiority, randomized, clinical trial was discussed which showed a much faster reversal of international normalized ratio with prothrombin complex concentrate, versus frozen plasma, for warfarin-related major bleeding. A follow-up question was posed. When should anticoagulants be restarted after intracranial hemorrhage in AF? There have only been three small, randomized, controlled trials so far. Two of these trials showed an increase in intracerebral hemorrhage when anticoagulant (AC) treatment was resumed, and one trial showed an increase in stroke when AC treatment was not resumed. Due to the low quality of data, guidelines on this matter are very non-committal.

The final case discussed perioperative AC in a patient with chronic kidney disease (CKD) or end-stage-renal disease (ESRD) on a DOAC. The patient was going to have a high-bleeding risk procedure. When would you hold and restart the DOAC? CKD and ESRD are both associated with an increased risk of VTE along with an increased bleeding risk. The COMBINE AF database meta-analyses were discussed. They show that there’s no difference in major bleeding between DOAC and warfarin across all degrees of renal function, that DOACs are superior to warfarin for all patients, and that the benefit increases as renal function worsens, along with a mortality benefit with DOACs as compared to warfarin for patients who have a glomerular filtration rate less than 77. The RENAL-AF trial, although small, showed there was no difference between major bleeding events for those on standard 5-mg versus 2.5-mg reduced-dose apixaban. For stage 5 CKD or ESRD patients in the perioperative setting, there is a lack of high-quality evidence. It is suggested to extend the pause duration of holding DOACs three to four days before major surgery and to restart 72 hours after the procedure.

Overall, the cases discussed underscore the importance of individualized decision making, considering both clinical evidence and patient preferences, to optimize anticoagulation therapy in the many complex clinical scenarios we encounter as hospitalists. 

Key Takeaways

• Patients with gastrointestinal disease on AC for AF should restart 7 to 14 days after bleeding resolves.
• Patients on VKA therapy who are at high risk for VTE and require VKA interruption should be bridged, with the bridge resuming 48 to 72 hours after the procedure; during the pause DVT prophylaxis can be given.
• Patients value shared decision making and our offered opinion; it’s our ethical duty to have these conversations even when clear guidance is lacking.
• DOACs are better than warfarin for CKD or ESRD patients; in these patients the pause duration is for three to four days before surgery with restart 72 hours after.

Dr. Dockstader

Dr. Dockstader is a med-peds-trained academic hospitalist practicing adult medicine at the University of New Mexico in Albuquerque, N.M. She is also the director of clinical documentation in the department of medicine, and the secretary for SHM’s New Mexico chapter.

Share: 

Comment on this article cancel reply.

Your email address will not be published. Required fields are marked *

Related Articles

Challenging anticoagulation scenarios: how to have smooth sailing through choppy waters, july 1, 2024.

Keeping abreast of updates in anticoagulation guidelines is important for physicians to provide optimal patient care. Multiple changes to recommendations for anticoagulation have been made in the...

Is 7 Really the Magic Number for RBC Transfusion?

  Over the past decade, there has been widespread adoption of restrictive red blood cell (RBC) transfusion guidelines.1,2 As a result, RBC transfusions have significantly decreased per...

Can Pentoxifylline Improve Healing of Lower Extremity Ulcers?

Case The patient, Mr. D, has been experiencing swelling in his legs for several years, and seven months prior, he noticed that his skin had started to develop ulcers. He has class 3 obesity, type 2...

Use of Amiodarone with Apixaban or Rivaroxaban Increases Risk for Bleeding-related Hospitalizations

Clinical question: Does the use of amiodarone in patients with atrial fibrillation increase the risk for bleeding-related hospitalizations when used with apixaban or rivaroxaban? Background:...

• Arnold School of Public Health
• Location Location
• Contact Contact
• Colleges and Schools
• 2024 News Archive

I Am Public Health: Xiaowen Sun

July 1, 2024  | Erin Bluvas,  [email protected]

Xiaowen Sun discovered her love of biostatistics and public health during her master’s program. She had already studied mathematics for her bachelor's degree, and graduate school taught Sun new ways to apply what she had learned.

Originally from China, Sun grew up in Zibo – a city famous for its BBQ. The Zibo BBQ Association tallied more than 1,270 BBQ restaurants at last count, and the city hosts hundreds of thousands of hungry customers at its local food markets during seasonal festivals.

The move was not a big leap for Sun when she decided to attend Shandong University of Technology for her undergraduate studies, but her next step would take her across the world. At the University of Missouri in the United States, Sun enrolled in a master’s program focused on statistics.

I knew that USC's biostatistics program would provide me with the skills, knowledge and connections necessary to advance my career in clinical research and public health.

“My fascination with public health and biostatistics began during my master’s studies, where I was first introduced to statistical methods and their applications in real-world problems,” she says. “I was particularly drawn to survival analysis due to its critical role in medical research and public health.”

Her coursework and research projects led Sun to discover the potential of machine learning and deep learning to revolutionize data analysis. She was intrigued by the abilities of these methods to work with large-volume data sets that were high dimensional and non-linear. The application of these methods to help solve complex health care challenges cemented her commitment to the field.

Sun chose the Arnold School’s Ph.D. in Biostatistics program to elevate her analytical skills in clinical research. The curriculum was the perfect fit for her interests, and the Department of Epidemiology and Biostatistics offered numerous opportunities to be involved in varied projects led by enthusiastic faculty.

“The program’s focus on hands-on projects and real-world applications was highly appealing, and its reputation and the strong network of alumni also played a crucial role in my decision,” Sun says. “I knew that USC's biostatistics program would provide me with the skills, knowledge and connections necessary to advance my career in clinical research and public health.”

She found a mentor in her dissertation advisor, biostatistics professor Jiajia Zhang .

“Under her guidance, I have gained a deep understanding of advanced statistical methodologies and their applications in public health research,” Sun says. “She taught me how to approach complex data problems with a meticulous and analytical mindset, ensuring precision and accuracy in my work. Moreover, Dr. Zhang has provided invaluable career advice, helping me to set and achieve my professional goals.”

As a graduate research assistant with the South Carolina SmartState Center for Healthcare Quality , Sun amassed the research experience she was looking for by contributing to collaborative projects. She also spent a summer interning at Novartis with the pharmaceutical company’s immunology department.

Since last fall, Sun has been working at the MD Anderson Cancer Center at the University of Texas as a research biostatistician. She will wrap up her dissertation research over the next several months and plans to graduate later this year.

“My degree from USC has equipped me with a comprehensive understanding of biostatistics and its applications in clinical research,” Sun says. “The advanced coursework and hands-on projects have significantly enhanced my analytical skills, enabling me to tackle complex data challenges effectively.”

Study Biostatistics

Biostatisticians improve public health by unraveling the true story hidden within increasingly complex data. Our graduates hold positions in universities, research institutes, governmental agencies such as CDC, NIH, state health departments, and in private industry including pharmaceutical companies and even financial institutions.

Challenge the conventional. Create the exceptional. No Limits.