university of edinburgh critical thinking

Critical thinking and writing

Have you ever received feedback such as “your essay is too descriptive” or “you need to show more critical analysis?” This is all too common and can be the bane of many postgraduate students. While some description may be necessary, most university assignments require work that is analytical and critical in its approach. In this post, Adekiite will share two tips on becoming more critical in writing for postgraduate school, followed by samples of descriptive versus critical writing.

1. Where is thy evidence?

Just as the popular quote goes; ‘’In God, we trust, all others must bring data’’, if your last name is not God, then it is imperative that you use strong evidence to prove your argument. Strong evidence is the bedrock of critical thinking and writing. Always keep your reader in mind and try to anticipate the questions they would ask — then provide evidence as an answer.  You can also use evidence to help strengthen your position and approve or disprove opposing points of view.

2. Show don’t tell!

Your writing needs to show your interpretation of the evidence and source material, how you have used that information to demonstrate your understanding, and your subsequent position on the topic and not just come off as a tale of multiple cities (Hello, Charles Dickens aficionados!). Resist the urge to tell stories instead of showing your position on the stories. Being critical in your writing means engaging in academic debates and research happening in your subject area. The sources you select, the way you show how they agree or disagree with other pieces of evidence, and the way you structure your argument will all show your thought process and how you have understood the information you have read. Make sure you move from description to analysis and evaluation. Give your interpretation of the facts, and explain the significance, consequences, and implications of the statements you have made.

Descriptive versus critical writing examples

The following examples show the differences between descriptive versus critical writing.

1. State what happened versus identify its significance

To write critically you will need to not only describe what happened but also identify the significance of what happened.

Descriptive example

“The data shows that the incidence (new cases) of asthma rates in children under 15 years old increased rapidly from 1977, peaking in 1993 and then declining, though rates still remain significantly higher than pre-1976 levels.”

Critical example

“The trend, from 1977 until 1993, of a rapid rise in rates of asthma diagnosis in children under 15 years, suggests that one of the causal factors was particularly prevalent during this time, but has since declined in importance or effect.”

2. Note the method used versus indicate its appropriateness

Rather than simply noting the method used, which is the descriptive approach, a critical writer will show how appropriate that method was.

“In addition to competency-based questions, the candidates were asked to complete an in-tray exercise, which required them to allocate different priority levels to tasks, as an appropriate method to measure their likely performance in the actual job.”

“In addition to competency-based questions, candidates were asked to complete an in-tray task prioritisation exercise. This was because it was considered a more effective way to measure likely performance in the actual role as much of the job would involve similar tasks, with little interaction with customers and therefore less requirement for highly developed communication skills.”

In conclusion, critical thinking and writing is a skill that can be learned. However, like every other skill, it demands time and practice. You can take a look at further examples of  descriptive writing vs. critical/analytical writing (PDF) for learning and practice.

Sources:  https://library.leeds.ac.uk/info/1401/academic_skills/105/critical_thinking/

Cottrell, S. 2003.  The Study Skills Handbook . 2nd ed. London: Palgrave

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Critical Thinking Skills

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Reading at university

Advice and resources to help you develop effective approaches to reading.

As a student you will need to develop effective approaches to reading.  The purpose of reading when you study is to improve your knowledge and understanding, so you can develop your argument and conclusions. It is not to memorise the material. Therefore you will need to make notes to help you organise and find the relevant information when you need it.

Reading lists and prioritising

Course outlines and reading lists are usually made available before a course starts. Most lists will indicate which readings are key to understanding themes within the course (essential or recommended) and those which are supplementary (further reading). You should prioritise the essential and recommended sources so you are able to participate in class or online discussions i.e., fill in any gaps in your knowledge.

Some courses provide online Resource Lists which give you quick and easy access to course resources, including e-books and e-journals.  You can also use Leganto’s Resource Lists to keep your own list using My Collection.  Not all courses use Resource Lists, but you can browse the lists for other courses.

Resource lists

Library web pages

Library online resources

It is easy to spend a lot of time looking for material in the library or online that you don't then have time to read and analyse.  It is important you are actively thinking about what you are reading and making good use of it.

We think in terms of reading books or articles, but often we need to think about how we want to use them.  Having a strategy can help when you have a lot of material and a limited amount of time.

Think carefully about how much you really need to use and try to focus on what you really need to read. Have in mind a set of questions you want answers to.  Write these down as a short list and keep it with you.

Methods which focus on using books and other texts in a strategic focused way are likely to make the best use of your time. 

SQ3R: Reading and making notes from part of a text

SQ3R is a well-known method for reading and making notes.  It involves surveying a text and asking questions before you start reading.  It is a particularly good strategy to use for reading textbooks. Surveying helps you get an overview and select which parts are relevant. The reading process focuses on selected parts of the text which you read and recall in turns, keeping in mind your initial questions. Finally you review the notes you have made.

It is important to stick with recalling what you have just read and making notes without looking at the original text.  This is much more effective than passive reading. 

SQ3R for reading and making notes (pdf)        SQ3R for reading and making notes (Word rtf)

You should plan to revisit your notes and test yourself on them. A gap allows a little forgetting to take place and self-testing makes you recall the material you have been studying.

Using books and articles

If you find that you need to seek out a book you haven't read before or get to grips with an unfamiliar journal article, you need a way of knowing what the whole text is about. Think of using the text rather than reading all of it in the same depth. This involves surveying the text selectively by skimming and scanning. As with SQ3R, you need ask questions throughout the process of using a text.

Using a book (pdf)            Using a book (Word rtf)   

Reading a research paper (pdf)                Reading a research paper (Word rtf)

Reading on a screen

Some studies show that we may read text less effectively on a screen for a number of reasons. If you are reading from a screen you might want to make some notes on paper, to make sure you are identifying the main points from the text and will have a summary to come back to when it comes to writing an essay or studying for an exam.  

If you prefer to make digital notes, consider using the Critical reading form method (section below). Note making should be selective. Be careful when copying and pasting chunks from the original text into a document as it can make it harder to write about it yourself and in your own words. You also need to be sure you know which words belong to the author(s) and which are your own comments or annotations.  

One Note can be used to make digital notes and to annotate a pdf. You can also highlight text and add short notes to pdfs within Acrobat Reader.

IS One Note

To help you keep focused when you read online, switch off email and social media to prevent distractions.

Making comparisons

When you are using sources by different authors you will need to compare their main ideas. Summarising your notes by theme using a framework or grid can help you make connections by allowing you to compare and contrast these ideas on one sheet. You can make your own sheets or use our blanks below. Read the method before using the blank grids.

Compare contrast frame method (pdf)              Compare contrast frame method (Word rtf)

Compare contrast frame blank (Word docx)         Compare A B and C frame blank (Word docx)

Review what you've read

Take a few minutes to ask yourself questions after reading and studying any text.  What are the author's key ideas? How does this connect to what you already know about this topic?  Are there examples or case studies you can link to these ideas?

Most important of all, can you respond to the questions you set out with and what new questions has the reading stimulated?

Using your reading

In academia, your reading and research informs your argument, not the other way round. You may find that your argument changes as you read more and find new evidence. In your writing, however, you will need to organise your thoughts and present a logical argument for your reader. The Academic writing page has a strategy for Building your argument as you go.

Academic writing

One of the key features of academic writing is acknowledging how you have incorporated other people’s ideas into your argument. It is your responsibility to make it clear where each idea or piece of information comes from by referencing it (giving your sources). This is good academic practice and is standard in university level academic writing. You should check any guidance and information provide by your course for specifics e.g. what style to use. There is general information and guidance on our webpages Referencing and citations, and Good academic practice.

Referencing and citations

Good academic practice

Critical reading

As you move through your studies deeper and more critical reading will be required for assignments and assessments.  However this does not mean you have to read every word.

One way of doing this is to interrogate the source you are using a set of questions by creating and using your own critical reading form or using a notes record sheet grid.  This can help you avoid taking lots of detailed notes you might not use. 

Critical reading form method (pdf)          Critical reading form method (Word rtf)

Reading notes record sheet (pdf)             Reading notes record sheet (docx)

Useful links

To help you get started with the Library, the Academic Support Librarians have developed LibSmart I and II, Learn courses to help you develop and enhance your digital research skills and capabilities.

If you are writing a literature review you will find advice about how to go about managing your reading for this on our Literature review page .

This article was published on 2024-02-26

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Data and Decision Analytics (Online Learning) MSc

Awards: MSc

Study modes: Part-time

Online learning

Funding opportunities

Postgraduate Online Learning Open Days

Join us on 22 and 23 May to learn about studying an online degree at Edinburgh.

Find out more and register for the Online Learning Open Days

Programme description

The MSc Data and Decision Analytics programme prepares you to not only be able to analyse and digest data, but also to translate this into effective decision-making in this Big Data Age.

You will learn from world-class faculty how to apply cutting-edge business analytics and computing tools to make data-driven decisions in a plethora of business areas, such as:

• human resources
• technology and equipment

The courses provide you with methodological foundations and techniques, as well as applications in business, management, and economics.

To enhance your learning experience, develop your practical skills in analytics, and prepare you for the job market, the programme uses a combination of:

• problem-based learning
• case study-based learning
• hands-on experience using prominent analytics software

Through a balance of academic theory, crucial soft skills and the very latest industry practice, the programme provides opportunities for you to gain experience in planning, designing, executing, and reporting findings to a critical audience of specialists and non-specialists.

You will also gain experience through research processes, such as:

• primary data collection from individuals
• securing their cooperation and consent
• analysing and evaluating data
• framing recommendations
• other methods of field study and data collection

You will learn how to communicate complex ideas and information in a coherent and structured manner throughout the programme courses. The programme also provides opportunities for you to engage with each other through group projects, discussion forums and peer assessment.

The distinguishing feature of the MSc in Data and Decision Analytics (online learning) is that it will expose you to unique and balanced courses in the two most important analytics areas, namely, predictive and prescriptive. This enables you to not only make use of state-of-art machine learning methods to predict and understand data behaviours, but also to effectively apply decision optimisation to make better informed decisions as current business managers. The programme combines a plethora of state-of-the-art elective courses that enable you to make use of the most innovative and efficient methods to solve data and decision analytics problems.

Scheduling your studies

You will need to set aside approximately 15 hours per week for reading, viewing lectures, tutorials, and assignments. This is an average across the duration of the entire two years, and it will vary depending on the course and also when assignments are due. Therefore, at peak times, you may need to put aside more time for your studies.

Live sessions

These sessions will be scheduled to take place between 09:00 and 18:00 GMT.

We are currently planning for live sessions to take place on Mondays and Tuesdays only. There will be a maximum of 4 hours required during these two days of the week for participating in the live online sessions.

Depending on your location this may mean attending before or after your usual day of work. We appreciate though for some it may mean requesting flexible working from your employers to attend these. Equally, if you are not able to attend some of these sessions, there will be recordings made available so you can catch up afterwards.

The courses will consist of live sessions that will be made up of a mixture of:

• computer lab sessions.

Lectures will introduce the theoretical foundation of the given subjects, while tutorials and computer labs will give you hands-on experience and allow you to practice the concepts covered by the lectures.

The programme's materials (access to videos, slides, briefings, and so on) and overall resources will be available on the online platform called Learn. Recordings of all online lectures, tutorials and computer lab sessions will be made available giving you a certain level of flexibility to study around other commitments as we appreciate that you may not be able to attend all the live sessions. Each individual course has its own Learn page. Assessment will consist of coursework. Students will submit their projects, essays, and so on through Learn and Turnitin. Feedback will also be provided through the same system.

• About Learn

Students will also interact and engage with each other through discussion forums, group projects, and other online tools.

Programme structure

The online Data and Decision Analytics MSc is delivered part-time with a start date in September each year. The programme takes 24 months to complete and combines academic study with practical application.

Please note that live sessions will be scheduled to take place on Mondays and Tuesdays during term time (c. 20 weeks each year). These live sessions will be a maximum of 8 hours per week and scheduled 9am-6pm GMT.

The programme encompasses a number of core courses and your studies will culminate with a dissertation.

Compulsory courses

• Applied Decision Optimisation
• Applied Machine Learning
• Data Analysis and Statistics for Business
• Python Programming
• Storytelling in Data and Decision Analytics

Option courses

• Time Series
• Data Management
• Analytics of Decision Making under Multiple Criteria
• Heuristic Optimisation
• Introduction to Stochastic Optimisation
• Advanced Stochastic Optimisation

Option courses are subject to change and demand. We cannot guarantee that all option courses will run each year and occasionally there will be last-minute amendments after this date due to unforeseen circumstances such as staff illness.

The content of individual courses and the programme for any given degree are under constant academic review in light of current circumstances and may change from time to time, with some programmes and courses being modified, discontinued, or replaced.

Dissertation

• Dissertation in Data and Decision Analytics

The dissertation is an in-depth study of a topic in which you are particularly interested in within the field of Data and Decision Analytics. Undertaking the dissertation requires you to develop a deep level of analysis and understanding of the theory and processes of organisations and the business environment through the completion of a piece of individual research.

Find out more about compulsory and optional courses

We link to the latest information available. Please note that this may be for a previous academic year and should be considered indicative.

Learning outcomes

By the end of the programme, you will be able to:

• understand and critically apply the concepts and methods of business analytics
• identify, model, and solve decision problems in different settings
• interpret results/solutions and identify appropriate courses of action for a given managerial situation, whether a problem or an opportunity
• create viable solutions to decision-making problems

MSc Data and Decision Analytics learning outcomes

Career opportunities

Organisations hold more information about their business environments than ever before. Increasingly, these organisations are recognising the role of data in gaining insights and out-thinking competitors. The worldwide big data analytics market was valued at USD 37.34 billion in 2018 and is anticipated to grow at a CAGR of 12.3% to arrive at USD 105.08 billion by 2027. This will inevitably lead to further growth of the market for employees in the area of analytics.

The MSc in Data and Decision Analytics will offer you, from a range of degree backgrounds, the opportunity to equip yourself with an artillery of concepts, methods and applications of data analytics along with hands-on and practical experience in applying them. It is not just about being able to analyse and digest the data available but to then translate this into effective decision-making.

We expect the programme to open a range of career pathways in analytics for our graduates or to allow them to progress further within their existing career. Roles we anticipate to be amongst these pathways include:

• business consultants
• business analysts
• data analysts
• business intelligence & analytics consultants
• metrics & analytics specialists
• analytics associates
• solution architects
• business process analysts
• management consulting associates
• operational research consultants

MSc Data and Decision Analytics career development

Entry requirements

These entry requirements are for the 2024/25 academic year and requirements for future academic years may differ. Entry requirements for the 2025/26 academic year will be published on 11 July 2024.

Entrance to our MSc programmes is strongly competitive. You can increase your chances of a successful application by exceeding the minimum programme requirements.

• Important points to note when applying for this programme

A UK 2:1 honours degree or its international equivalent in an area related to management science, operational research, statistics, econometrics, mathematics, physics, computer science, engineering, or business and management with a distinct quantitative content.

Your background should ideally include courses and/or experience gained in topics such as linear algebra, calculus, probability, statistics, and computer programming.

If you have a UK 2:1 honours degree or its international equivalent in an unrelated subject we may consider your application if you have relevant work experience.

Work experience is desirable but not mandatory.

All students are recommended to have their own laptop for this programme.

Credit transfer from the MicroMasters in Predictive Analytics

We welcome applications from students who have successfully completed the University of Edinburgh's MicroMasters in Predictive Analytics. Learners who successfully completed the MicroMasters programme will be awarded 30 postgraduate credits towards our Data and Decision Analytics MSc (online).

• MicroMasters in Predictive Analytics

Learners who meet all the entry requirements and are successfully admitted onto the MSc Data and Decision Analytics can expect that their MicroMasters coursework will count towards their degree, comprising 20 credits of the total 180 credits of the masters programme. 10 credits would be recognised for the course in Python Programming where there is a strong equivalence between the course content and the other 10 credits would act as a discount towards the elective courses on the programme.

The MicroMasters must have been completed within two years of starting on the Data and Decision Analytics MSc, with September 2024 the last entry date when the credits will be accepted. Completing the MicroMasters will not guarantee acceptance and the standard University admissions process and criteria will apply. Decisions on admission to the programme lie solely with the University.

If you would like the 20 credits to count towards recognised prior learning, when applying you should upload your MicroMasters certificate to your application.

Students from China

This degree is Band B.

• Postgraduate entry requirements for students from China

International qualifications

Check whether your international qualifications meet our general entry requirements:

• Entry requirements by country
• English language requirements

Regardless of your nationality or country of residence, you must demonstrate a level of English language competency at a level that will enable you to succeed in your studies.

English language tests

We accept the following English language qualifications at the grades specified:

• IELTS Academic: total 7.0 with at least 6.0 in each component. We do not accept IELTS One Skill Retake to meet our English language requirements.
• TOEFL-iBT (including Home Edition): total 100 with at least 20 in each component. We do not accept TOEFL MyBest Score to meet our English language requirements.
• C1 Advanced ( CAE ) / C2 Proficiency ( CPE ): total 185 with at least 169 in each component.
• Trinity ISE : ISE III with passes in all four components.
• PTE Academic: total 70 with at least 59 in each component.

Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS , TOEFL, Trinity ISE or PTE , in which case it must be no more than two years old.

Degrees taught and assessed in English

We also accept an undergraduate or postgraduate degree that has been taught and assessed in English in a majority English speaking country, as defined by UK Visas and Immigration:

• UKVI list of majority English speaking countries

We also accept a degree that has been taught and assessed in English from a university on our list of approved universities in non-majority English speaking countries (non-MESC).

• Approved universities in non-MESC

If you are not a national of a majority English speaking country, then your degree must be no more than five years old* at the beginning of your programme of study. (*Revised 05 March 2024 to extend degree validity to five years.)

Find out more about our language requirements:

Fees and costs

If you receive an offer of admission, either unconditional or conditional, you will be asked to pay a tuition fee deposit within 28 days to secure your place on the programme:

• £1,500 (this contributes towards your tuition fees)

The fee does not include the cost of textbooks for core and option courses so you should budget an additional amount for this required expenditure.

As this is an online programme, you will also require, and need to budget for, relevant IT equipment and broadband internet in order to pursue your studies.

See the programme website for more information on fees and deposits.

Tuition Fees

Scholarships and funding, uk government postgraduate loans.

If you live in the UK, you may be able to apply for a postgraduate loan from one of the UK’s government loan schemes.

The type and amount of financial support you are eligible for will depend on:

• your programme
• the duration of your studies
• your tuition fee status

Programmes studied on a part-time intermittent basis are not eligible.

• UK government and other external funding

Other funding opportunities

We offer a 10% discount on postgraduate tuition fees for alumni who have graduated with an undergraduate degree from the University of Edinburgh.

We also offer a 10% discount on postgraduate tuition fees for students who have previously matriculated on a "Visiting Programme" as an undergraduate student and completed a minimum of one semester of study at the University of Edinburgh.

The Scholarship and Student Funding site provides a list of programmes not covered by the discount scheme.

Search for scholarships and funding opportunities:

• Search for funding

Further information

• Enquiry Management Team
• Phone: +44 (0)131 650 9663
• Contact: [email protected]
• Programme Director, Douglas Alem
• Phone: +44 (0)131 651 1036
• Contact: [email protected]
• University of Edinburgh Business School
• 29 Buccleuch Place
• School: Business School
• College: Arts, Humanities & Social Sciences

Select your programme and preferred start date to begin your application.

MSc Data and Decision Analytics (Online Learning) - 24 months (Part-time)

Application deadlines.

If the programme is not full by the final application deadline, we may be able to consider applications submitted after that date. If we are still accepting applications following the final deadline, we will clearly indicate that on the programme's application page.

• How to apply

You must submit one reference with your application.

You will be required to supply a number of documents as part of your application. This includes:

• an official transcript
• degree certificate
• one reference
• personal statement
• English language qualification

Find out more about the general application process for postgraduate programmes: