Software requirements are important. If you are building a software product, your software requirements will describe what your software product is intended to do. Since software has the potential to do so many different things and solve so many different problems, your requirements can have different characteristics.

This blog post follows on from an earlier blog post, TM470 Considering software requirements. In this earlier blog post, I shared some questions. In this post, I would like to further refine and develop these questions.

When considering your project, it is important to ask yourself the following:

1. When in your project will you allocate time to uncovering the requirements for your project?
2. How will you go about gathering your requirements?
3. How will go you about describing your requirements in your EMA report (and to the examiner)?
4. How will you go about testing your product to check to see if it meets your requirements?

It is quite easy to answer the important first question. You would have chosen a lifecycle model for your project. Whatever approach you choose, the requirements ‘bit’ of your project should (ideally) occur not long after the start of your project.

The final question is also especially important. If you don’t define your requirements in a clear way, it may not be possible to know whether your software product meets those requirements. In other words, if you don’t have a clear picture of what you are building, you won’t know whether or not your project is a success.

Answering the second and third questions is more difficult, since it very much depends on the type of software you are creating. Arguably, the approaches you will adopt for testing will also be different too – but the key point remains - you need requirements to know what you need to test. Testing, of course, also needs to fit within your project plan.

Functional and non-functional requirements

In TM354, a software requirement (or requirement) is defined as ‘a desired feature, property or behaviour of a software system’ (according to the TM354 glossary). This term can be broken down into two types of requirement. A functional requirement is defined as ‘a specified action that a system has to perform’. In other words, what a software product should do. A non-functional requirement, by way of contrast, is defined as ‘a quality that a system must have’. Expanding this slightly, the idea of a ‘quality’ relates to a characteristic of a software product, such as its performance, security, reliability or usability.

The activity of keeping track of requirements is known, perhaps expectedly, as requirements engineering. If you feel that you need to find a way to keep track of your product requirements in a systematic way, it might be worthwhile briefly doing a bit of background reading into requirements engineering (in the context of your project) and sharing evidence of your reading within the literature review section of your project. Do remember to critical evaluate any articles and sources that you uncover. You should apply methods and techniques which help you to solve whatever problem you are trying to solve.

Scenarios

One of the reasons why software engineering is such a fascinating subject is how software can be used to solve so many different problems. Here are three examples of very different contexts in which software can be used:

1. Embedded software
2. Logistics software
3. Consumer software

Embedded software

Embedded software is software that makes physical hardware work. It is software that ‘does something’ that is often important, and is often invisible. A useful example of embedded software is the software that runs on your internet router that you may use to connect to your broadband connection (you may well have learnt more about broadband technology in other modules).

An internet router operating system must satisfy a number of important non-functional requirements: your router software must be efficient (it must not slow down your use of the internet), it must be secure, and must run effectively whilst using limited memory and processing power.

An important question is, of course, what does router need to do? From a very high level perspective, it must provide some kind of user interface that enables either yourself or an engineer to configure it so it can be used. It will also, of course, offer internet connectivity either through a wired connection, or through a WiFi interface.

This leads a lot of further questions, such as: how are these interfaces defined? Wireless and internet protocols are, of course, already very well defined. They have been created by international standards organisations (such as the IEEE), corporations and committees over a long period of time. Technology needs standards to be able to work, and software engineers who have the unenviable task of building software for consumer internet routers must know what they are.

When faced with complex functional and non-functionality complexity, software engineers need to express their requirements in a concise and clear way, and in a form that ensures they can be tested. Testing is, of course, important since we need to know whether our software does what we think it should do.

Some requirements are more important than others. With our internet router, we may be able to tolerate a slight degradation in performance if there is more than one member of our household using our broadband connection.  We would not, however, wish to compromise on security, since this would put all users at risk. In other cases, some requirements are non-negotiable. Consider, for a moment, software used to control an engine (or motor) management system for a vehicle. The consequences of that software either failing, or not functioning as expected have the potential to be catastrophic. On one hand, the driver of a vehicle might be mildly inconvenienced if they can’t get it started, but on the other hand, there could be consequences for passengers, the pedestrians and the wider environment. A notable example is the

Volkswagen Diesel Emissions Scandal which is summarised by Jung and Park (OU Library). Since software that software engineers create impacts on people and society, software engineers have a responsibility to reflect on the decisions that they make, as well as the ultimate impact of the tasks they are asked to carry out.

Before moving onto the next example, a useful question to ask is: what project model is best suited to the development of embedded software for an internet router, where all the requirements are clearly defined? If everything is known from the start of your project, a traditional waterfall project model may well be most appropriate.

Logistics software

This second category can be thought of as ‘software that manages workflow’. The term ‘workflow’ can be used to describe any series of actions that contribute towards the solving of a problem or satisfying a need. The effect of some software isn’t immediately visible to us. Our experience at a supermarket or at a restaurant is often facilitated by software. Behind the scenes, requests for products are sent to one or more suppliers. These suppliers must then find a way of delivering your order to the shop or restaurant you visit. The importance of such software becomes very apparent when there are problems, as illustrated by a cyber attack on the Co-op chain of supermarkets (BBC News)

The functional and non-functional requirements for business-to-business logistics software will, of course, have a different character when compared to the formality that is needed for very highly specified embedded software. If is, of course, really important to clearly describe what is expected, by which stakeholder (who is defined as ‘anyone who is affected by the introduction of a software system’), and in what format.

It is also useful to reflect that they ways in which requirements may be gathered. Whilst the requirements for an internet router may exist within formal standard documentations, the requirements for logistical operations may have to be discovered by studying existing business processes and ways of working. Depending on the organisation, this may be the responsibility of a business analyst. In smaller organisations, it may be the responsibility of the software engineer to ask important questions and document their findings. Software is, of course, always about people.

What project model choice would be appropriate for this category of project? The answer, of course, depends on the detail, but let us assume that we know a lot about the operation of business processes and the underlying technologies we may wish to use. In this case, we might adopt a variation of the iterative waterfall, where more communication between the different stakeholders are embedded into the planning.

Consumer software

Consider a website that supports a community coffee shop. The website shares useful information for potential customers, such as its location, a menu of cakes and drinks, and its opening times. The manager has decided that it would be useful to enhance the website to offer more functionality.  Some key ideas include a way to advertise special events, such as gallery evenings, book groups and a ‘toddler club’, and to provide a way to reserve tables during busy times, and even to allow some customers to order their coffee and cake before they physically visit the café.

Where there are requirements, there are also questions. In this scenario we might ask where our requirements come from. Do they come from the manager, or should they come from the staff who will be working in the café, or from its customers? The manager, for example, may have an idea about what may need, but might not have a very clear vision of what they want.

 The software requirements for our coffee website are a lot less clear than the requirements of a logistics product, and much less clear than the requirements for an embedded system. In each scenario, the requirements need to be discovered, but the approach for discovering those requirements are different in each example.

When we are faced with unclear requirements and have access to potential users (who may have strong opinions about what they do and don’t want) we may adopt an interactive project model where we create a series of prototypes of what a product might look like. We might even apply something called an ‘agile method’ that emphasises producing versions of working software as early as possible, whilst also fostering collaboration between developers and communication with key stakeholders.

Discovering requirements

These three scenarios implicitly suggest there are different ways of uncovering requirements. The first scenario suggests that some essential requirements are likely to exist in the form of detailed standards and protocol documents. The second scenario suggests that requirements exist within the business, and may need to be discovered, perhaps by business analysts or by working with other who have a detailed understanding of the problem area. The third scenario suggests that although end users may have a solution in mind, they might not have a clear idea about what form it might take.

Here is a summary of some methods that could be used to learn more about software requirements:

1. Study documents that are connected with the problem that is being solved. As well as standards, this could include documents that describe national or international legislation, sector guidelines, or corporate policies.
2. Look at existing products, or study what existing products are currently used to solve the problems that your software product will ideally solve.
3. Ask users. Interview them individually or by using focus groups.
4. Observe users. Study, with permission, what happens within an existing system. Alternatively, ask users to record their own observations.
5. Examine the context or wider environment of the problem to identify any further stakeholders, social or technical constraints, and concerns that need to be thought about.
6. Build a prototype which is then evaluated. The process of evaluation can then lead to the discovery of more questions, and more requirements.

The information you gather from each of these approaches must be analysed. Analysis is a critical and creative process that must also take account of ethics; it is necessary to consider the impact of a software product on individuals, communities, and societies.

When you have decided on what are requirements are, how should you represent them? Should you write them down, or are there other approaches you could use? Your decision about which approach to use may well depend on your approach to risk, and the consequences of what might happen if your software product were to go wrong.

Representing requirements

The best way to represent or to describe your requirements depends on the characteristics of your software system. When looked at very simply, there a continuum which relates to formality. On one end of the requirements continuum there are very formal requirements that could be expressed in a formal mathematical language. On the other end, the requirements may not be very well known and are expressed using some slides or images created using a prototype tool.

What follows is a summary of different approaches you can use to represent requirements:

Formal methods: One of the main difficulties of using natural language to describe software requirements is that natural language can lead to ambiguity. To get around this challenge, software researchers have invented software specification languages that are based on mathematics. One of the advantages of a formal approach is that it becomes theoretically possible to formally verify whether program code (software) logically satisfies (matches) a specification.  You would use a formal approach in safety critical systems, which are often embedded software systems. The difficulty of suing formal methods lies, of course, with their formality. Since they use a formal language, they can be very difficult to work with.

Volere shells: Although natural language can express ambiguities, one way to manage this is to control the way in which language is used. Volere shells are essentially templates which contain sections that presents a concise description of a requirement, the motivation for the requirement, and a fit criterion that can be used to measure or determine whether it has been implemented successfully. For more information about Volere shells, do consult the OU’s software engineering module and Mastering the Requirements Process by Reed, Robertson and Robertson (2024) (OU Library).

Use cases: Use cases are all about describing what happens when a stakeholder interacts with a software system with the intention of carrying out a task or completing a goal. OU module materials describe two types of use case: textual use cases and graphical use cases. Textual use cases present a set of steps that are numbered, with alternatives. Graphical use cases are described using the Unified Modelling Language (UML) and summarise actions and actors (which can be stakeholders). Use cases are given names, which allows software engineers to easily discuss them with others.

User stories: The OU software engineering module describes a user story as ‘a story written by an intended user of a system; it describes some functionality that is of value to the person(s) writing the story. It represents a user’s expectation of the system’ (TM354 module glossary, 2025). User stories can take the form: ‘As a <user> I want to <description of activity> so I can <explanation of why activity is important>’. Like use cases, user stories can be given names (or even numbers) to help groups of software engineers to discuss them between each other, and within meetings. Since software requirements are, of course, related to software testing, an approach known as Behaviour-driven Development (BDD) builds on the concept of user stories, allowing them to be embedded within software test scenarios.

Prototypes: There are many different types and forms of prototype. A very simple prototype could be created from a series of pencil sketches, or prepared using one of many user design tools. Alternatively, a prototype could be a simulation of a software product, perhaps built using a presentation tool such as PowerPoint. A prototype might also be a semi-functional product. Sometimes the terms ‘horizontal’ or ‘vertical’ are used. A horizontal prototype that shows a lot of functionality but in not much depth; a vertical prototype that shows a small amount of functionality in a lot of depth. Unlike other representation techniques, prototypes embody requirements rather having them written down. It may, of course, be necessary to add additional description, especially regarding non-functional requirements, to provide further information and context for software engineers.

Planning for implementation

You have used different approaches to gather your requirements, and you have decided on a way to represent them. The next question is: how should you prioritise your requirements? The process of prioritisation, like the identification of requirements is also a creative process. There are, however, tools that can helpful. One tool is called the MoSCoW prioritisation tool (DSDM Agile Project Framework, MoSCoW Prioritisation).

MoSCoW is an abbreviation for ‘Must Have’, ‘Should Have’, ‘Could Have’ and ‘Won’t Have this time’. The most important requirements are obviously those that your stakeholders ‘must have’. The Agile Project Framework resource offers the following direct guidance: ‘ask the question ‘what happens if this requirement is not met?’ If the answer is ‘cancel the project – there is no point in implementing a solution that does not meet this requirement’, then it is a Must Have requirement’ (Agile Business Consortium).

If you are considering running a project that adopts an iterative approach, it will be useful to highlight which requirements will be implemented within which iteration. If you have begun with a prototype, taking a practical approach, it will be necessary to convert requirements embodied within a prototype to a specific development task. Working with requirements is a process of making invisible needs visible, so they can be converted into working software.

A recommendation

If you are creating a software product include a separate requirements section in your account of project work chapter. Use your literature review chapter to show your awareness of different approaches to requirements, and use your project work chapter to show how you have critically applied your understanding to the problem that you are solving.

Use an appendix to present a summary of all your requirements. Use the body of your report to share examples of the most significant or important requirements in your project. In the reflection chapter, consider writing something about what you learnt by working with requirements in a systematic way, and which requirements were the most difficult to implement. If there were some requirements that were too difficult to implement or define, do say something about why you thought that was the case, and and what you might have done differently.

Resources

When writing your project report (your EMA) it is important and necessary to show your understanding of principles and ideas from modules you have studied before you got to your project. A number of the level three computing modules address the topic of software requirements. What follow is a very brief summary of three important modules. If you have not studied these modules during your degree, there is an opportunity to learn more about the topics they contain, and apply them to your project.

TM353 IT Systems: Planning for Success

This module helps you to consider the connection technology and people and the way in which they can both interact with each other to create a sociotechnical system. TM353 emphasises the importance of understanding broader and wider perspectives. It introduces a methodology, known as soft systems methodology and techniques such as the creation of rich pictures, which can be used to depict and explore the environment in which your software product inhabits. By considering the broader perspective, it is then possible to consider the way in which software may influence communities of users and stakeholders.

TM354 Software Engineering

TM354 introduces a number of practical tools that can be used to explore and share requirements. It describes a UML notation called an Activity Diagram which allows you to express business processes and accompanying interaction with software products. It also describes different types of use case, both textual and diagrammatic. It describes Volere Shells in quite a bit of detail, and offers some very clear examples about how to write user stories. It also draws upon the Reed, Robertson and Robertson text, and directs students to a useful interview.

TM356 Interaction Design and the User Experience

TM356 makes extensive use of a well-known textbook, Interaction Design: Beyond Human-Computer Interaction by Preece, Rogers and Sharp (OU Library). Although the text focuses substantially on the design of user interfaces in all their different forms, understanding user requirements is a fundamental theme for a very simple reason. If there is a mismatch between the user’s expectations and the design of a product, that product is not likely to be as usable as expected. If you haven’t studied the OU interaction design module, this text can be especially useful. It offers some practical guidance about what techniques can be used to gather requirements, and what approaches can be used to perform usability evaluations of prototypes.

To find your requirements, it is sometimes necessary to carry out applied research to discover what users do and need in the contexts and environments in which they inhabit. Like the software engineering module, the interaction design module discusses user stories, use cases, and also mentions Volere Shells. Notably, it adds a few further tools that can help to further uncover and develop requirement. Essential use cases are, for example, a use case that gets to the ‘essence’ of an interaction, without regard how an interaction is implemented.  Personas, scenarios and storyboards are practical tools that help us to think about who the users are, what they will be doing when they use the software, and the context in which it will be used. Understanding requirements can then lead to the design of a prototype, which then can be evaluate and then further refined.

Reflections

I’ve been thinking about writing an article like this ever since I have noticed a lack a detailed discussion about requirements in TM470 EMA project submissions. Good projects will always consider them in depth. The best projects will also answer the question ‘how should I best represent my requirements to meet the needs of my project?’. There should, of course, be evidence of studying the topic of requirements within the literature review chapter. The best projects will also go onto use requirements within a testing process to determine whether a development has been successful.

The more you start to think about requirements, the more slippery the concept becomes. It is impossible to create one simple set of rules that works for all projects. There is a simple reason. Every project is different, and every project has its own unique set of characteristics. Gathering and describing requirements are creative activities, which takes software engineers towards onto other creative activities, such as software development and testing.

Differences between projects and problems can also mean differences in software engineering culture. Culture is expressed through differences in behaviours, practices and traditions. The culture of a software company that builds real-time safety critical embedded software is likely to be different to the culture of a company that builds consumer websites. How requirements are expressed are intrinsically linked to institutional values and non-functional requirements.

A final point is that software is always subject to change. Change can occur due to technology changes, changes in government legislation or corporate processes, or changes in work practices. Businesses are, of course, subject to mergers and acquisitions, and sometimes technology and software providers are changed for economic or practical reasons. In some cases, the speed of work-place change can outstrip the necessary changes that may need to take place within information systems. Since the role that software can play within organisations continually changes, so do the software requirements.

As well as supporting TM470, this blog serves a second purpose. Some of the ideas presented within this article may find their way into the new TM113 module, which features an important software engineering component.

Acknowledgements

Many thanks are given to the members of two module teams: the TM470 module team, and the TM113 module team. When I’m referring to ‘module teams’ in this section, I am also referring to tutors. I continue to hold the view that tutors are the most important people in the university.

Today or tomorrow my A334 result are released. I'm a bit on edge. I know what result I would like to get, and will probably be grumpy if I don't get what I'm hoping for. When having a quick look at all my Facebook updates, I noticed the following post from fellow colleague, tutor and student, Cath Brown, who offers some really helpful practical advice. Cath has given me permission to share her post.

A post about results  

If you got what you want - many congratulations! Go and celebrate ! 

No offence, but the rest of this isn’t for you...

a) If you passed but are disappointed with the grade

It is OK to be disappointed if it’s not what you want - you don’t have to be glad to have passed if that’s not how it feels to you 

Once you’ve had a bit of time to process it:-

1. check how much difference it makes to your final classification using my classification calculator in the group files. You may be pleasantly surprised 
2. if it’s creating a problem you could look, if your degree allows it, at doing a different module in its place and unlinking it. Student Finance does allow 120 credits of leeway above the total for the sort of thing 
3. drastic move of course - but if your degree doesn’t allow it, changing degrees is a thing 
4. IMPORTANT - if you are at the end of your degree and don’t want to get the classification this result gives you - DO NOT ACCEPT THE DEGREE OFFER!

b) if you failed

Take time to scream/cry/drink/mainline chocolate !

Then - remember lots and lots of people have failed a module and gone on to succeed.

Practicalities 

1. In many cases you can resit/resubmit (usually for early September). If you do this your grade is usually capped at a Pass 4. Have a look at the classification calculator to see if you are OK with that. You can ask for an individual support session via student support to help with your preparation (there may be more support depending on the module). If you pass the resit you can progress to next year as you originally planned.
2. if you don’t want a capped grade you can redo the entire module - all the grades are then available. 
3. or you could potentially ditch the module and do something new - see above in disappointing grade section. 

c) if you got a “pending”

There can be various reasons for this - occasionally it is the whole module, or it could be missing evidence for special circs (obviously provide it as soon as you are asked if it’s this!)

Other reasons

1. you are going to be asked to do an “additional assessment” - this is if they can’t decide which grade you are on based on what they’ve seen. Doing it can only help you 
2. In a few modules, you are going to be asked to redo a TMA or submit one you didn’t submit. This is to enable you to get over the pass threshold. It can only take you from fail to pass - it can’t make things worse 
3. Academic conduct issues such as collusion or unauthorised use of Gen AI. If it is this you will be told it is quite quickly but actually processing the case is likely to take quite a lot longer unfortunately. When it is processed you will be given the chance to explain yourself.

Your tutor and student support will not have any further information I’m afraid.

The Students Union’s Individual Representation service may be able to help if you have a case against you 

Key thing - if you are upset for any of the above reasons - IT IS NOT THE END OF THE ROAD! Whatever went wrong - there is something you can do! You can come back from it and go on to succeed!

Reflections

Cath's advice is really helpful. I didn't know that point about the additional credits that could be studied under a student loan. (The idea of taking an additional module had also crossed my mind). The only point I can add is: do feel to also seek advice from student services. After taking a bit of time to gather your thoughts and review all the guidance the university has shared with you, do give student services a ring.

Acknowledgements

Many thanks to the illustrious Cath Brown. Good luck with your own results for the module that you're currently studying.

On 5 February 2025, I was sent a link to some files that described a new student communications framework (which was then later updated in June 25). The aim of this very long document was to offer a summary of some of the messages that might be sent to students before, during and between periods of study. It also contained suggestions of messages that could be used by faculties and module teams.

Accompanying this guidance, there is also something called ‘the student communication schedule - example for ALs’. What follows is an edited summary of that guidance which has been prepared for an October presentation. Interestingly (and usefully) it also offers some useful practical suggestions about additional actions that could be carried out by tutors to support students. For concision, I have omitted some references to additional links and resources that tutors can use. Full credit for this guidance comes from the student support hub, and the team who put it together.

The schedule is introduced as follows: “it is particularly useful for new ALs and those new to online teaching. It is a set of suggestions that you might find helpful as a tutor to structure your communication with students to offer proactive support, particularly at the start of the module and ahead of the first Tutor Marked Assignment (TMA). You are not expected to adhere to it; please use the resource as required and where beneficial, bearing in mind that not all points of contact will be applicable in all situations.”

What follows is a very lightly edited version of the schedule. I have added additional notes and comments in [square brackets].

Communication schedule

Student group is allocated  

Welcome email to all students, mentioning the module website and the forum.

[I mention these in a letter, which I also attach to my first email which also contains my contact details and availability]

A few days before the module start

Post on the module forum; include an introduction and an ice-breaker activity – for example, a question that every student can respond to (e.g., ‘What is your favourite period of History that you have studied so far?’ for a History module.)

[I tend to do this just before the sending out of my introductory email, so I can share a link to the forum in my letter – I also encourage students to subscribe to the forums that will be used during the module.]

End of Week 1

• Check and encourage the use of the VLE and the forum.
• Follow-up email or phone call to students who have not replied to the welcome email.
• Email to all students introducing them to tutorials; different types of tutorials and different rooms, and what to expect, as well as that they can watch recordings and book the times and sessions that suit them.

[I mention the date of the first tutorial in my introductory letter, also suggesting that they put dates of tutorials in their diary. I mention why attending tutorials are important: it can help students to get higher scores in their assessments.]

Week 2

Check for students who have registered late and send them a welcome email. Alternatively, you can issue the welcome email to newly registered students as and when you receive a notification of a late registration.

End of Week 2

Follow up with late-registered students who have not replied to the welcome email.

Refer any students who have not replied to the follow-up contact to Student Support Team using eSRF [an electronic student referral form, which can be found on your TutorHome Page].

[I adopt a three stage approach to try to communicate with students. I begin with an email. If I haven’t heard back from them, I send a text message (I don’t personally have any concerns about sharing my personal phone number, but other tutors might not want to do this), and if I haven’t received a text message back, I give them a ring, leaving a voicemail. I only send in a referral when I have tried all three approaches.]

Week 3

Refer any late-registered students who have not replied to the follow-up contact to Student Support Team. Check Early Alert Indicators and identify students who are predicted not to submit TMA01 or receive a low grade. Reach out to them with guidance and resources if appropriate.

[In addition to using the early alerts indicator is to make sure that you had a good look at a student’s study history. The information shared on tutor home can also be a good reflection of what is summarised within the early alerts tool.]

Two weeks before TMA01

• Email to all students offering support and useful links ahead of the first assignment and encourage them to submit a dummy TMA. Remind students that they have the opportunity to submit TMA00 to test the eTMA system and formatting requirements.
• Reassure the students that, although the eTMA system may show a deadline for TMA00, there is no official deadline.
• Check the Early Alert Indicators dashboard.

[The advice about the dummy TMA is more applicable to level 1 students, but can be helpful for students on other levels. I tend to send a group email in the run up to the first TMA, encouraging students to get in contact if they have any questions.]

A week before TMA01

Email to remind students about the TMA submission deadline and methods and key resources.

One day after TMA01 deadline

Reach out to students who have not submitted their TMA to offer support.

[With this point, I could debate the use of the term ‘reach out’ – I much prefer ‘contact’, but I’ll move on. I give it a day or so after the deadline before emailing students about their TMA. If I haven’t heard from them, I give them a ring, and if I still haven’t heard from them, I send in a referral to student services.]

After TMA01 results are published

• Congratulate students on their results and remind them – particularly Level 1 – to download their marked TMAs and read the feedback on the TMA and PT3 form in addition to looking at their mark.
• Reach out to students who have failed or received low marks in their first TMA. You may wish to do this even before returning their work to offer support and talk about their next steps.

[Between this step and the previous one, I post a forum message called ‘TMA01 marking updates’, where I let students know when I’ve downloaded the TMAs, when I’m roughly halfway through the marking, and when I’ve returned everything. This way students have a sense of when I am likely to return their assignments. Emphasising the downloading and reading of the feedback is important; it is so easy to just look at the mark and not look at the feedback.]

Before the Christmas break

Email all students to check in and signpost to resources on study skills in preparation for the next TMA, as well as mental wellbeing – encourage to reach out with any questions.

[In this message, I share season’s greetings and tell students something about my availability during the festive period. I continue to check email, but during this break I’m not as responsive. Managing expectations is important.]

Early January

Email all students to welcome them back after the study break. Encourage them to book tutorials. Check VLE use and Early Alert Indicators and reach out to those who are less likely to submit their next TMA, as well as those who didn’t do well in the previous one.

A week before a TMA

Email to remind students about the TMA submission deadline and methods and key resources. Check Early Alert Indicators to reach out to any students who might need additional support or encouragement.

After a TMA

Report any students who have not submitted to Student Support Team. Email these students to encourage a conversation and signpost to information about their options.

[Just as with TMA01, I post a forum thread which has a title ‘TMA0x marking updates’, posting again when I’m roughly half way through my marking.]

After TMA results are published

Reach out to students who have failed or received low marks in their TMA and offer support on next steps.

[There is an awful lot of ‘reaching out’ going on (!) An accompanying point is: do ask students who appear to be struggling whether they would like to have an additional support session. This is a one-to-one meeting, where a tutor can go through difficult and important parts of the module. It is also an opportunity to talk about study skills, and signpost students to useful resources. Do refer to this article about the different study skills resources and toolkits that are available]

After the Easter break/before the next TMA

Email to all students to welcome them back after the break. Remind students about the next TMA submission deadline and methods and key resources. Check Early Alert Indicators to reach out to any students who might need additional support or encouragement.

Before the EMA [or examination]

Email all students with resources on the EMA or preparation for exams. Encourage contact and engagement with tutorials. Check Early Alert Indicators to reach out to any students who might need additional support or encouragement.

[Before an exam preparation session, I tend to share a summary of what a session will contain. I also mention that ‘students who attend these preparation tutorials are likely to gain higher scores in their exam’ (which is probably true, since different types of examinable component assessment always helps). After running an exam preparation session, I share any resources I prepared to forums, along with links to recordings.]

After EMA/exams

Email students to congratulate them on the completion of their module and encourage [them] to reflect on their progress. Explain when they can find guidance on next steps.

Best practice notes

The following points were also shared in the schedule:

• Regularly check in and personalise interactions to make students feel valued and understood.
• Take time to get to know your students and encourage them to share any concerns or additional needs.
• Define your availability, response times, and scope of support from the start.
• Ensure to check the students list on TutorHome regularly for any changes in students’ circumstances.
• Ensure that your emails are comprehensive, but succinct and consider using plain English; provide clear feedback that helps the student grow.

A final recommendation (if it works for you) is to make use of the group email tool that is found in your student list. The reason for mentioning this is that it keeps a copy of the message that is sent, which can then be viewed by colleagues in the student support teams.

Reflections

Before I was sent this schedule, I was thinking of writing my own version. I have also made a note of another version of a communication schedule that was created by a fellow tutor who taught on postgrad modules. My colleague, Arosha Bandara, used a spreadsheet to help guide his messages. Although this sounds terribly cold and impersonal, I got the impression from a presentation he gave at a tutor development event that he spend a lot of time personalising every email that he sends out. The best practice tips matter.

Unlike Arosha, I don’t have a detailed systematic framework to guide when I sent out messages to students. The process of reading, editing and sharing this framework has helped me to reflect on my own practice. A key reflection being that this schedule is useful. It is going to help me to become a better tutor. Also, just as you can customise any email, you can also customise your own communication strategy to reflect the module that you tutor, and your own personal style.

Acknowledgements

The headings within the schedule, and the actions that are described have all been produced by the student communication hub (as far as I am aware). All mistakes and errors should be attributed to that team, but I’m also happy to take some blame for any transcription and editing mistakes which may appear within this blog (there are likely to be many).

Exams are always a challenge. Remote exams for TM354 Software Engineering students can be especially challenging since students are sometimes asked to draw diagrams. Students are asked for diagrams, since diagrams and sketches are important communication tools. Software is invisible, and diagrams represent a useful way of sharing information and design ideas with fellow software engineers.

This short blog posts shares some practical tips when preparing diagrams for your TM354 exam. What is presented here is a set of suggestions. You should pick and choose the ideas that work best for you, and choose an approach that you feel most comfortable with. The biggest and most important point is that you need to be prepared. When you come to take your exam, there should be no surprises.

Understand the types of diagrams

TM354 makes use of a graphical language called the Unified Modelling Language (UML). Make sure you are familiar with the different types of diagrams you might be asked for.

Consider using diagram tools

Since UML is a well known language, there are quite a few tools out there that can help you to produce UML diagrams. It is okay to use a tool to help you to produce a diagram, but before you take an exam, you should have a very good idea about how to use it. You should be able to use it fluently and be confident in using it. You don’t want to be in a situation where you battle with your tools during a timed exam.

Consider creating a template

If you know what types of diagrams you might be asked for, and what tool you might want to use, consider creating a template for every type of diagram that you might use. This isn’t cheating; this is effective preparation. When you need to create a new diagram, open up your template and modify it to meet your needs.

Consider sketching by hand

If you don’t like tools, you can always use pen and paper to create your diagrams. You can even dispense with using a ruler, but they can be pretty useful. You don’t get any marks for neatness (but you do get marks for the expression of ideas within your diagram). When you’ve finished your sketch, you can either take a digital photograph of it, or scan it (if you have access to a digital scanner), and then paste your diagram into your exam script.

A key point to remember: in TM354 you don't get any extra points for neatness. You get points for showing you understand how your diagram can be used to communicate concepts about software.

Avoid the Word drawing tool

Microsoft Word is a great tool. It offers a lot of useful features, including a drawing tool. Whilst useful for some tasks, the Word drawing tool is useless for creating UML diagrams. A bit of practical advice: avoid it like the plague. You can spend more time on choosing the style of boxes and arrows than communicating the elements of software that are the focus of your question.

Avoid GenAI

This point should be obvious. For some tasks, GenAI may be able to produce diagrams. GenAI doesn’t know what is in the module materials. This means that the diagrams it can create are invariably wrong or incomplete. Don’t use GenAI for assessment tasks unless you’re explicitly asked to do so.

Master your process

If you use a tool to create your diagram, make sure you know how to transfer your diagram to your exam script. If you need to take a screenshot (and you’re using Windows), push the Print Screen button, and crop the image using the Paint application. If you are creating a diagram by hand, make sure you can easily transfer a digital photograph from your phone to your Word document. Figuring out your process can save you time (and a whole lot of stress).

Practice

My final point: creating diagrams is a skill. Find the time to practice. There are a lot of TM354 past papers that can be downloaded from the Open SU shop.

Good luck in your exam!

Acknowledgements

Many thanks to members of the TM354 module team and TM354 module tutors. Thanks are extended to Mike Giddings and Richard Walker.

On 11 June 2025 I attended a continuing professional development event concerning Generative AI that was intended for tutors. The ALSPD team has set up an online conference site to complement the session. What follows is a set of notes I have made during the session, along with some accompanying thoughts and reflections.

Keynote Address: Reclaiming the Pace of Digital Productivity in the Age of AI

The opening keynote was by Maren Deepwell. The abstract of her talk emphasised the pace of digital content production, and mentioned the need for uncovering our own ‘critical cadence’. A key phrase I picked up on was, of course, digital literacies. This is now morphing into a related idea of AI literacies where we become more aware of the ethical, cultural and social implications of AI tool use.

I made a note of a couple of links from OpenED Culture projects:

• Dimensions of AI Literacies: AI Literacies Applied
• Dimensions of AI Literacies: a diverse and interconnected set of competencies.

Moving on from AI Literacy, a further theme that was highlighted was digital wellbeing; a term I’ve not heard before, but one that can mean different things to different people. It can relate to the use of technology for healthcare and physical activity, or it could be linked to the notion of a ‘digital detox’, which is a phrase that I struggle with. We were introduced to a resource called the Data Detox Kit which contains a number of guides.

Another curious term was ‘digital rewilding’, which I had never heard before. There was a reference to a site called HackThisCourse. I spent a few minutes looking at this page, and was puzzled; I couldn’t immediately grasp what it was all about – but it does look as if it relates back to the theme of digital pedagogy, and creative uses of digital technology. This point, of course, links to the emergence of GenAI.

An important role of a keynote is to challenge and to guide. An interesting question is: what is next? We were directed to Helen Beetham’s substack, which features articles and podcasts about AI.

A key question asked: what does digital capabilities for the AI age look like? During the presentation, I noted that GenAI can be useful if you’re in a position to critically evaluate what it produces.

Session 1 - Short Talks

Teaching and assessing students' use of GenAI

Jonquil Lowe, Senior Lecturer in Economics, from the Faculty of Arts and Social Sciences (FASS) asks the question: “what exactly should we be teaching and assessing about GenAI?” I noted three important suggestions which relate to taching: include acceptable and ethical use, cover generic Gen AI skills, and discipline specific skills. I noted the suggestion that perhaps every module might need a Gen AI aspect, which would change and develop as student moved to higher levels of study. I also noted an interesting point that Gen AI may offer useful guidance for students for whom English is not their first language.

Within the chat, a link to an OpenLearn course was shared: Getting started with generative artificial intelligence (AI) 

Online academic misconduct 2025: real location, face to face assessment the only effective response

Next up was David Pell, Associate Lecturer from FASS. David was refreshingly direct in his opinions. In comparison to collusion, plagiarism, essay mills, GenAI is something that is different; it is ‘huge’. It is described as a useful tool for potential cheaters. David shared a direct opinion, and one that I agree with, which is: only real life, proctored assessment provides a guarantee against academic misconduct.

Some research was shared:

• University of Reading: AI exam submissions can go undetected – study (BBC)
• An OU study: Developing robust assessment in the light of Generative AI developments
• Richards et al.(2024) Bob or Bot: Exploring ChatGPT’s Answers to University Computer Science Assessment
• Fleckenstein et al. (2024) Do teachers spot AI? Evaluating the detectability of AI-generated texts among student essays

The very clear point is that GenAI can produce text that is not detectable by educators.

Session 2: The AI Hydra in Assessment - a Nine Point Response to the Nine-headed Beast

The next session, by Mark Campbell, Associate Lecturer, STEM, presents a model of potential responses to GenAI. These are: progression, policing, procedures, pilots, principles and strategy, polities, plans, programmes and modules, and practices.

In addition to these useful responses, I also made a note of the following resources:

1. OU Generative AI Staff Development
2. JISC Innovation resources: Embrace artificial intelligence (AI) with confidence
3. AI maturity toolkit for tertiary education
4. OU being digital resources (library services)

Session 3 – Short Talks

Transformative Teaching with AI - re-purposing the meaning of student-centred learning

Denise Dear, Associate Lecturer, STEM moves from the topic of assessment to the topic of teaching, and asks “how lecturers can use AI to enhance student topic knowledge retention, increase student engagement, improve student confidence, reduce student stress levels and assist students as a revision tool”. I haven’t used any of these tools as a part of my teaching, so I was curious about how it might be applied.

GenAI was presented as a potential study buddy. It has the potential to provide summaries of passages of text, may be also to provide suggestions about essay structures (which, as an arts student, terrifies me), and generate interactive quizzes. In other words, there is potential that it can provide support that is tailored to the needs of individual students.

During the session tutors were asked: how do you use it? Answers include case scenarios, sample computer code, scenario simulations, generating personas – but a word of caution was highlighted: it gets maths wrong. (LLMs also have no idea how to play chess; they know about language, but they cannot reason).

The discussion of teaching led us back to assessment. How do we assess learning? In an activity, some answers were: viva voce assessments, feedback from small group work, asking students to make an audio recording.

Generative AI and Good Academic English

The final session of the day was by Claire Denton, Associate Lecturer, FASS. Use of GenAI can suggest a lack of confidence with academic English. Telltale signs may be the use of a generic tone, no references to module materials and no supporting evidence. Or alternatively, students might begin with their own voice, which will then switch where text from AI is woven into their answer. A question that tutors face is: how do students provide feedback to students when this happens?

Anyone from any faculty can access the various subject sites. There is something called the Arts and Humanities Writing Centre which contains some useful writing resources. The site also provides a link to good academic English, and a phrase bank. (There are, of course, other study skills resources available. I’ve shared a summary of some of them through this article Study Skills Resources: what is available?)

Claire shared some great tips that could be shared to students, including: if you have spent some hours looking at a piece of writing, stop. Take your time to read it aloud. You will then pick up if you need additional punctuation, have used too many of the same words, or have repeated the same point you have made earlier. The key point is, of course, if tutors spot that GenAI might have been used, there may lie opportunities to provide additional help and guidance.

Reflections

The tone of this event implies that GenAI is going to be profoundly transformative. With this in mind, I remember the tone (and the enthusiasm) that accompanied the development of MOOCs and Open Educational Resources, and the view that they both had the potential to fundamentally change the nature and character of education. I've not heard MOOCs mentioned for a while. A lot of froth has been created in the wake of the emergence of GenAI.

Some of the important themes I picked up on from this session were importance of policies, the challenges to academic conduct and integrity, as well as the potential opportunities that targeted GenAI may present. It was interesting to hear GenAI being pitched in terms of being a ‘study buddy’. This is an interesting use case, but I’m also mildly worried by the fact that these free tools are remembering every single interaction we have ever had with them. 

I’m a GenAI sceptic. In my time as a computer scientist, I have seen AI bubbles come and go. In the 1970, researchers claimed they had solved all the key problems, and it was just a matter of scaling up until we get our own personal robotic butler. When it comes to GenAI I do feel that we’re approaching the Peak of Inflated Expectations and it won’t be long before we crash into the Trough of Disillusionment (see: Gartner hype cycle, Wikipedia). If we’re not at the GenAI hype peak already, we probably will be in 18 months time. (I'll be very happy to eat these words if proved wrong).

I remember a computer book from the mid 1980s. It contained a program that you type into your home computer, so it would ‘talk back to you’. It was written in a programming language called BASIC and was only three or four pages long. It recycled your words; it was a simpler version of a 1967 computer program called ELIZA. I once described GenAI as ‘ELIZA on steroids’. GenAI is seductive, since LLMs uncannily reflect back to us echoes of our own humanity. Looking to the bigger picture, philosophers still can’t really define what intelligence is. I don’t know who said it, but I always return to the phrase that ‘AI is really clever people getting really dumb machines to do things that look clever’.

All this takes me to a mild (and yet) important constructive criticism of the event: it was significantly light on ethics. We need to slow down and ask the question: who runs and owns these GenAI tools? What are the consequences for us, and for society when these are used? To what extent does a LLM create a model of its users? How are these models shared? What terms and conditions have we signed up to? There is, of course, the slightly important issues of transparency and copyright. It is likely that these words are, in some way or other, hoovered up by a LLM engine.

Out of curiosity, I asked Copilot the following question: “Who is Chris Douce and what does he think about artificial intelligence?” Here’s the answer: “Chris Douce is a Senior Lecturer in the School of Computing and Communications at the Open University. He has a background in software engineering and educational technology, with a focus on distance learning and accessibility. Regarding his views on artificial intelligence (AI), Chris Douce has expressed interest in how AI can be integrated into educational technologies to enhance learning experiences. He has discussed the potential of AI to provide personalized learning and support for students, particularly in distance learning environments. However, he also emphasizes the importance of ethical considerations and the need to address challenges related to accessibility and inclusivity”. That’s a pretty good summary, but I think it is, perhaps, an understatement.

One of the useful aspects of this session was the sharing of links to many related resources and references. There is always homework to do. Now, that’s something that GenAI can’t directly help me with. It’s down to me to do the work. Anything else would be cheating.

Addendum

I shared this post with a colleague, who recommended two interesting resources; a book and a podcast:

Book: Bender, E. M. & Hannah, A. (2025) The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want. Bodley Head.

Podcast: Mystery AI Hype Theater 3000 by Bender and Hannah (Distributed AI Research Institute)

Acknowledgements

Many thanks to all the presenters, and for the team who facilitated the event. Thanks are also extended to David Hales.

Whilst wearing my student hat I went to a careers event that took place on 12 June 2025 for students who were studying arts and humanities modules. I attended because I was curious; I wanted to know what would be covered in sessions like these.

What follows is a set of rough notes I made during the session. The aim of the session was to explore and to find ways to identify what skills employers look for, to learn more about career options for students studying arts and humanities qualifications, and to share resources.

Activities

The session began with an activity, where we were asked a question: what skills do you think employers want from you? This was linked to some research by an organisation called the Bright Network. In their most recent survey (at the time of writing) the top three ‘skills’ identified were: ‘interest in the business’, resilience, commercial awareness.

The next activity we were asked to create what is called a ‘skills calling card’. The idea was that we choose an image, list our top 3 employability skills, and rate them out of 100. In other words, imagine creating your own card for a game of ‘skills top trumps’.

This led to some questions, namely, how might you demonstrate or evidence your top skills by way of examples? This being, of course, being linked to how you pitch yourself within a job applications, CVs and interviews.

Careers

The activities led to the question: what can you do an arts and humanities qualification? There was a discussion about job roles and employers. I was stuck by a particular statistic, that 85% of jobs are open to students who have any degree, which was attributed to an organisation called the institute of student employers.

We were directed to some useful resources: Prospects, which as a section about ‘what you can do with your degree, and the OU jobs platform, opportunity hub. I like Prospects. It is through Prospects that I gained an opportunity for doctoral study, which eventually took me to the OU.

We were encouraged to carry out some further activities in our own time. One was to look through job adverts to identify what skills employers are looking for, what examples can you draw upon to evidence the skills that you might have. Another activity was to look at career paths of OU Alumni through LinkedIn.

Resources

We were introduced to a number of useful resources:

• A badged open course, about having a freelance career in the creative arts (OpenLearn)
• The FutureYou pages presents a summary of ten core employability skills and attributes.

It is interesting that these attributes have been only related to Faculty of Arts and Social Sciences modules. They can, of course, also be applied to modules from other faculties.

A reminder was given that all students have access to the Careers and Employability Service, which can be found through the Help Centre. The services provides advice for about writing of your CV and preparing for an interview. You can also book in an appointment with a professional career advisor.

Acknowledgements

Many thanks to the presenter and the facilitator, and the careers team who devised this session up.

One of the new level 1 computing modules on the BSc (Honours) Computer Science with Artificial Intelligence qualification goes by the catchy title TM113 Computing fundamentals 2: programming, databases, software engineering. It accompanies TM110 Computing fundamentals 1: concepts and Python programming.

As suggested by its title, this new module has three strands. What follows are a set of links and resources that may be useful to anyone who might be potentially interested in tutoring this module. If you have tutored TM112, the Python element will be familiar to you, but the software engineering and databases less familiar (although you may be familiar with databases, if have had any awareness of TM254 Managing IT: the why, the what and the how).

Programming

If you are familiar with software development but not with Python, the following OpenLearn and Cisco resources might be useful:

• OpenLearn: Simple Coding (Level 1: Introductory, 2 hours)
• Cisco: Python Essentials 1 (30 hours, beginner)
• Cisco: Python Essentials 2 (40 hours, intermediate)

Databases

Within OpenLearn, there is the following:

• OpenLearn: Data and processes in computing (Level 2: Intermediate, 14 hours)

Another useful resource that has been mentioned is:

• SQL Zoo

Software engineering

Turning to the theme of software engineering, there are a couple of OpenLearn resources that have been derived from existing OU modules. 

• OpenLearn: Approaches to software development (Level 3: Advanced, 9 hours)
• OpenLearn: Software development for enterprise systems (Level 3: Advanced, 8 hours)

Other resources

If you have never tutored an OU module before, the following module can be very helpful:

• Being an OU Tutor in STEM: Computing and Communications (Level 3: Advanced, 6 hours)

If you are an existing tutor, a really useful thing to do is to take advantage of the university’s fee waiver.

Reflections

The OpenLearn resources can certain be useful, and you can demonstrate awareness of the materials by gathering an informal badge (which can be added to a CV). What has really helped me to become a better tutor has been the fee waiver. This could be applied to computing modules, or modules from other faculties.

Acknowledgments

Thanks are extended to Anthony Johnson who shared some of those resources during a very early module team meeting.

2 May 2025

Finally, a negative covid test.

Despite having a covid addled brain, over the last couple of days I’ve managed to corral together quite a significant bunch of quotes from a range of different sources for my EMA which is due at the end of the month. The reason for doing this is to try to figure out what different critics think about the two texts I’ve chosen, before going ahead and doing a final re-read of my choices, and finally coming to a view about what I think. The challenge I’m facing is that that I’ve never felt that I’ve been any good at history. A bit of a blind spot I have is knowing much about all the various British kings and queens. This said, the more I read, the more bits of it start to make sense. An interesting reflection is that some of the themes from level 1 are now beginning to find their way to level 3.

Here's my plan: let everything sit with me for a couple of days. When I’ve done that, re-read through my 18 pages of notes and quotes, then re-read the texts, and then start to write the EMA; I already feel as if I have a macros structure – it is the detail that need to figure out, and that is pretty important.

6 May 2025

Today is a day of two tutorials. I went to one that took place at around noon. It had focus on drama and the EMA. I think I have more of an understanding about the purpose of the EMA, and what it is looking for, but I’m less certain about how I go about making an argument that works with both of the texts that I’ve chosen. I’ve gone from feeling confident, to less confident.

There’s one tutorial tonight, and another one tomorrow. When I’ve attended both of them I’ll probably start to write, after having a quick look at another couple of references that I’ve picked up from the lunchtime tutorial. I guess this oscillation between certainty and uncertainty accompanies becoming familiar with the principles that underlie a discipline that I haven’t (yet) completely grasped its fundamentals. I feel like I’m getting there.

7 May 2025

Last night’s tutorial was quite helpful in terms of unpicking the EMA question. I’m going to keep with my texts, since I like them. Our tutor said it’s okay to go with our favourites. 

I have two things to do today: to attend a book 2 summary tutorial that takes place in the evening, and to then try to dig out a couple of extra references to read (although I know I have loads). I think I’m a couple of day away from starting to write my EMA.

10 May 2025

Well, I’ve downloaded those extra resources, and I’ve transferred them to my Kindle, and have thoroughly scribbled on them. I now need to transcribe all my quotes into my notes document. I also have another task, which is to dig out some critical reviews of one of the texts that I’ve chosen. 

Following a determined morning of TMA marking, I’ve just come out of another two A334 EMA preparation tutorials. I missed the majority of the first one, but I’ve downloaded the slides. My to my dismay, one of the presenters shared yet another reference which looks to be of interest. I seem to be creatively procrastinating, doing everything else except for the writing of the EMA.

After the tutorials, I’ve had a listen to an EMA preparation audio which has been prepared by the module team. It didn’t contain any surprises, which is a good thing. I’ve also made a note to listen to another few resources, which can be found on the page ‘learning event summaries’. I think that is going to be this evening’s job, along with some further TMA marking.

What I’m now more certain about is what I’m not going to include within my EMA.

The countdown clock to the final submission date is ticking louder. I don’t yet feel as if I know my chosen texts backwards yet, which is making me feel slightly uncomfortable. I’m nearly there with one of them, but I need to work on the other. I’m sure I’ll get there.

15 May 2025

Well, I’ve got my TMA 5 back. A mixed result. Certainly not one of my best. It is a shame, since I did feel (whilst writing it) that I had submitted a good essay. My tutor left me some helpful feedback. The main comment was that it’s structure (for a literature essay) was a little unconventional. Reflecting on this, I can see his point. It could have been presented differently, to integrate together the philosophical ideas and text from Confessions. Had I done this, I would have produced a more readable essay. I am, however, very secure in my understanding of the sublime, but I am slightly frustrated that I spent so many hours working through Confessions.

I was doing a bit of travelling yesterday. I read a few more critical sources. Whilst reading these, I gathered up a few more ideas that I could use in my EMA. Whilst traveling, I have missed an EMA preparation surgery, but my tutor has already emailed his group saying that a recording is available.

My plan for the next few days, leading up to the weekend (which is going to be an EMA writing weekend) is: continue to read critical sources. By the time I get to Saturday morning, I should be more or less ready to write.

16 May 2025

I’ve just listened to that ‘EMA surgery’ tutorial that was run by my tutor. I’m going to attend another day school event that is taking place tomorrow, which is all about drama and close reading. The more events that I attend, and the more general reading that I do, the less confident I feel in my ability to write an essay that meets the assessment criteria. I want to write something interesting, which does the texts justice, but I’m feeling a long way away from that. Perhaps this is a lull of confidence that one has whilst building up towards something that is going to finish soon. It’s a curious feeling.

No matter what happens on the day school tomorrow, I’m going to be starting my writing. I can’t carry on reading more and more, although I do feel as if I’m learning more and more. I need to figure out what my position is, and get into the texts to choose some sections to demonstrate close reading. I’ve got a rough idea of what I want to write, but the difficulty is that I don’t think it is what the module team are looking for – and I don’t really know how to get out of that rut.

I think the key in all this will be the importance of cutting, which was a significant point mentioned in our surgery.

Addendum: towards the end of the day, another resource was suggested to me; a series of podcasts by Emma Smith called Approaching Shakespeare. I’m hoping to listen to one of them, just in time for the EMA.

19 May 2025

I’m nearly done. I spent Saturday morning in the day school, and a bit of the afternoon creating an EMA document and starting writing. On Sunday, I got properly stuck in. Although I didn’t do any significant essay planning other than creating a skeleton structure within my EMA document, I did have a rough idea of what I was going to write about.

On Saturday evening, I was wracked with self-doubt and questioning. I felt as if the two texts that I had chosen wouldn’t work together and that perhaps there might have been better choices. By the time I got to Sunday evening, this had changed; I had found a way to make them complement each other – I can now see (and hopefully the examiner will see) how they are related to each other.

My next step is to leave everything for a few days, to let my thoughts settle, and then turn to the final bits of editing. I’m 200 words shy of a final word count. Although I think I know what I want to add, I’m currently too close to what I’ve written to make an objective decision about what might work more effectively. I’m looking forward to getting everything in and finishing. The EMA writing has been a bit of a roller coaster.

20 May 2025

It was nearly 3am in the morning. I had been thinking about my EMA. I had a vague notion that I should strengthen some of the points that I feel I had been implicitly trying to make in my essay. I came to the view that I needed for foreground a couple of points. In the space between wakefulness and sleep, I sent myself a sketchy email from my phone, put on the latest episode of In Our Time, which was about the development of copyright, and fell asleep on the sofa.

Yesterday evening I submitted my unedited EMA, with the view that if were I to suffer a catastrophic IT failure, something would be in the system. I have a printout of it. Either tomorrow or the day after, I’m going to do my final edits, and try to take account of the vague ideas that I’ve sent myself.

I’m really looking forward to getting this all done. I’m also looking forward to summer, my final module, and reading George Elliot.

22 May 2025

An update has gone in.

I can’t seem to leave my EMA alone. Last night I had a thought about an additional sentence I could add, which may have clarified one of the points that I was trying to make. A quick set of edits, and then a resubmission.

I dipped in and out of the ‘write now’ tutorial. I felt as if I started to overthink, and question every single sentence I had written. I should try to relax.

23 May 2025

I can’t leave it alone. I made another couple of edits and resubmissions. Mostly typographical changes; cutting a word here, adding a word there. I think I’m only going to relax when the submission day has ticked over.

Here’s a few curious numbers which I thought I would share:

My Kindle A334 category contains 84 items. This includes set texts, module materials, critical sources and secondary readings.

I have collected 43 presentations (PDFs or PowerPoints) from the various tutorials that have taken place during the course of the module. Some of these are module wide events, other are tutorials events. I can’t say for certain whether I’ve been to all of these, but I’ve certainly been to a good number of them.

I went a bit overboard with my EMA reading, downloading 33 articles which relate to the EMA question (in one way or another) and both of the set texts. There’s a huge amount of scholarship and opinion out there. A challenge that I’ve had is deciding on what I think, and trying to express it with a degree of confidence. The process of reading, and writing for the assignments is, of course, a very big bit of the learning.

The official module guidance is that students should spend around 16 hours per week on their studies (I’ve not looked this up; it might even be more, but this number is sticking in my memory for some reason). I don’t think I’ve done as much as 16 hours (I feel as if I’m experienced student), but it’s not too far from it. There were some weeks that were lighter than others.

It’s one more day closer to the end of the module.

It’s time to get back to my day job. 

29 May 2025

Well, this is it; the final day of the module presentation.

Over the last week and on long(ish) cycle rides, I’ve been trying to think about what else I could have included in my EMA. I’ve got nothing. I’ve submitted no further updates or corrections. It’s time to let it go.

How I feel about these level 3 modules is different to how I feel about level 2 modules. I was surprised at how well I did in the level 2 modules. This led me to gaining a feeling of confidence. In turn, I became thoroughly invested in wanting to do well for the level 3 modules, although they were clearly harder.

There’s one thing that I still need to focus on, and a couple of take away points that strike me as really important. 

The thing that I need to focus on is to develop a more detailed understanding of the notion of ‘an argument’ and what this means in literature essays. I understand that it means adopting a particular point of view, expressing that view, and backing it up with evidence (from texts and sources) to substantiate that view. What I’ve struggled with is the interpretation of essay titles and choosing a point of view. I don’t (yet) have the confidence to go too far from the core of the essay since I don’t want to go off topic. There’s a subtlety to all this that I haven’t yet resolved. All this might well depend on the question that is asked and how I relate to it.

Here's my couple of take away points. With English essays, whilst it is important to clearly demonstrate your understanding of texts and critics to satisfy essential learning outcomes, essay structure is even more important. How you write your essays is more important than what you say within your essays. This makes sense. After all, it’s all about communication and how you express yourself.

I’ve added ‘results day’ into my diary. I’ve started an A335 blog. I’ve also looked at what other modules I might be able to study if I don’t get the grade that I’m hoping for from this module. You see, I’m now thoroughly invested.

Many thanks to my tutor (who has been very good), the module team, and fellow A334 students (you lot on the WhatsApp group have been amazing). It’s been hard work. I feel as if I've learnt a lot.

Your TM470 project can be about pretty much anything, providing that it

• has a significant computing component, and
• allows you to draw on your earlier level studies to enable you to demonstrate and to further develop your knowledge and skills.

Drawing on a point that I share in my introductory tutorials, your project should address a non-trivial question and one that is reasonably difficult without an obvious answer; you should have a problem that needs a solution.

Projects can also be:

• Development projects – you create something.
• Research projects – you find something out.
• Evaluation projects – you do comparison, or test something out.

Typically, your project will have elements of each of these projects.

Your title that you choose should reflect the aims and objectives of your project. It should ideally suggest whether it is development, research or evaluation project. Your project title should also be concise. If it is more than ten words, you might want to think of how to simplify it. You need something that is concise, and prepares your examiner for what they will encounter.

Here are some titles of projects that have been inspired from the various projects that I have seen over the years:

• Knowledge management system for field engineers
• Web application for management of school transportation
• An app to help a restaurant to buy organic produce
• Web application for selling of art to art galleries
• An accessibility evaluation of museums in a city
• Development of a test automation framework for a company
• An app used to provide information and guidance to carers
• Financial reporting app for a market trader
• Rugby club, soccer club or cycling club management tool
• A legal case management system
• An app used to recommend reading resources to parents
• Evaluating the potential effectiveness of a new network architecture

Returning to the earlier point, your project should solve a problem that is non-trivial.

Acknowledgements

Thanks are extended to fellow tutor Karl Wilcox who inspired some of my tutorial slides, which may well have influenced this post. I now have no idea which are his words, and which are mine. I think Karl made the very useful point that your project needs to be both significant and non-trivial. These two points clearly stuck with me.

Software engineering is done by people, but what people do to build software depends on the nature of software that is to be created. The culture of individuals, technologies and organisations also plays an important role too.

At the turn of the century, there was a new idea about how to build software; something called agile development. This led to the creation of something called the Manifesto for Agile Software Development If you’re interested in software development and want to know something about what ‘agile’ means, you need to have a look at the manifesto.

I first learnt about agile through something called eXtreme Programming (Wikipedia), and then something called Scrum (Wikipedia) (Don’t use Wikipedia in your TMAs; always use official references). In my eyes, the notable characteristic about agile (or Agile; there’s a difference between small ‘a’ agile, and large ‘A’ agile) is that it is all about people. Agile (in its different forms) helps to establish rituals which can, in turn, help software engineers to talk about that ‘invisible stuff’ which is software.

I recently asked a colleague, Advait Deshpande, who was the chair of an agile practices microcredential what the latest trends were in agile software development. He was kind enough to share links to some interesting articles and resources.

Articles about agile

 Here are some review articles that might be useful to anyone who is starting to study agile:

Edison, H., Wang, X., & Conboy, K. (2021). Comparing methods for large-scale agile software development: A systematic literature review. IEEE Transactions on Software Engineering, 48(8), 2709-2731. Available at https://ieeexplore.ieee.org/abstract/document/9387593/

Vallon, R., da Silva Estácio, B. J., Prikladnicki, R., & Grechenig, T. (2018). Systematic literature review on agile practices in global software development. Information and Software Technology, 96, 161-180. Available at https://www.sciencedirect.com/science/article/pii/S0950584917302975

Other resources

Advait also shared the following two links, which he gives me permission to share here: UK Government: Agile delivery - Agile tools and techniques.

The notion of ‘agile’ has moved beyond software, but to business. It is important to distinguish between the two. This second link emphasises what agile might mean within a business context: Agile Business Consortium: Business Agility.

Post (or peak) agile

Once, agile was the new thing on the block. Now agile has become mainstream. An accompanying question is: have we reached post (or peak) agile? Also, what comes next? One of the criticisms of agile is that it is best suited to smaller teams, which puts a limit to how it can be applied to bigger projects. There have been several attempts to address this:

• Large scale Scrum
• Disciplined Agile Delivery (DAD)
• Scaled Agile Framework (SAFE)

Advait directed me to a talk that was hosted on YouTube that had a provocative title:

• Agile is Dead by Pragmatic Dave Thomas

I know Dave Thomas from a book I have on my shelf at home; a book called ‘the pragmatic programmer’ – it is a good read, and is packed filled with some very practical advice. His talk about agile is worth a watch. He presents a critical view of the ‘agile industry’ in a humorous and engaging way. It is worth a watch. He talks about the origins of the agile manifesto, as well as ‘large agile’. An important point is that when thinking about how to create software, we need to think critically too.

Reflections

When I was learning about software engineering as an undergraduate, I was introduced to something called the software development lifecycle (or SDLC). There are different models; there’s a waterfall model, a spiral model, and there was something called SSADM which bored me to hears. It was only after I graduated that I later learnt about agile in all different guises.

When I started working as a software engineer, the company that I worked for didn’t have a software development process, so we had to make one. Culture and experience are themes that can influence decisions about what is done. I was lucky enough to work with someone who had had a lot of experience, for which I was really thankful for.

We set up policies and processes. We also applied techniques that had an agile flavour, bits of pair programming, and aspects of test driven development. Our processes needed to work for both the products and the people who were developing the software. We needed to be pragmatic to get things done.

Acknowledgements

Thanks are extended to Advait Deshpande. I really appreciated the chat and all the links he shared.

One of the most useful features of Microsoft Word is its flexible style system. Using Word, your words can be written any number of fonts and font sizes. If you decided you need to change the style or size of what you have written, you have a choice: you can either change the words themselves (by selecting them and picking another font or font size), or you can change the font of the style that is used with your all your words. Knowing about Word styles can help you to work more efficiently.

When you begin writing a document, you typically write words with the ‘Normal’ style. Word also provides a set of heading styles. These heading styles are linked to a number of other bits of Word functionality. Most notably:

• The Word document navigation view, and
• The Word table of contents creation tool.

Whenever you create a heading for a section, apply a Word heading to that session. If you then open up the document navigation view (which you can find in the view menu), you will see a clickable summary of your document.

When you have edited your document, and you need a table of contents, click on the references menu, and then on the table of contents button. This button will give you a couple of options to choose from. This references menu hints at some of the more advanced features in Word, including the ability to provide cross references between sections (which avoids you from having continually figure out what the correct page number should be if you add or remove a bit of text), and a way to define entries for an index.

Further guidance

The following pages from Microsoft offer some further guidance:

• Use the Navigation pane in Word
• Insert a table of contents

A further resource that looks to be useful is this useful summary sheet from the University of Aberdeen: Working with long documents.

If you are a TM470 student, you might find the following blog article helpful: TM470 TMA and EMA template.

For my sins, I’ve found myself on four module teams; two in production (TM113, TM253) and two in presentation (TM354, and TM470). The two production modules are a part of an important new qualification the university is producing.

What follows is a set of notes I’ve made that relates to this new qualification. For the official word about the R88, my recommendation is to have a look at the R88 qualification webpage. 

Firstly, a bit of context: a full time degree is made up of 360 academic credits. The equivalent of one year of study at a brick university is 120 credits. The OU also reflects this, and has three levels of study. Degree classification scores are calculated from results from levels 2 and 3. Level 1 is about skills and knowledge development, but level 1 modules do need to be passed. All modules on this qualification are 30 credits. 

Here is a quick summary of what I know.

Level 1

TM110 Computing fundamentals 1: concepts and Python programming

This is the first module to study. It is likely to include some maths just to prepare everyone for the first maths module that follows. Unlike TM111, it makes use of a textual programming language from the outset. Different themes are interleaved with each other. There are two TMAs and an end of module TMA. 

TM113 Computing fundamentals 2: programming, databases, software engineering

The first presentation of this module is planned for October 2026. This obviously has three related components, and like TM110, the topics are interleaved with each other. This uses the same programming language as before, but uses a different programming environment: Visual Studio Code.  Like all these modules, there is a focus on skills development and employability.

TM129 Technologies in practice

This module has three ten point sections: a bit about robotics and AI, a section about virtual machines and the Linux operating system, and a bit about networking. In AI machines will, invariably need to talk with each other. Knowing something about networking is important.

MST124 Essential mathematics 1

This module is produced by the School of Maths and Stats. It builds on ideas that were introduced in TM110.

Level 2

TM253 Programming and software engineering

This new module is planned for October 2027. This picks up where TM113 left off. It is likely to introduce students to a programming language that is different from Java, and is likely to help students do understand more about software design and architecture. There is also likely to be a significant emphasis on object-oriented software (but other programming paradigms might also get mentioned).

TM258 Introduction to machine learning and artificial intelligence

This is a new module which introduces a range of different AI techniques. I know nothing more than this at the moment, but I’ll hazard a guess to say that ‘search’ is likely to be covered.

M269 Algorithms, data structures and computability

It could be argued that M269 is the most computer science of all these computer science modules. It covers the fundamentals, which means searching and sorting.

M249 Practical modern statistics

Stats is important within machine learning (as well as computer science). The module description says that it covers “time series, multivariate analysis, and Bayesian statistics”. 

Level 3

TM342 Investigating intelligence and ethics

As a postgrad student, I studied a module that had the title ‘natural and artificial intelligence’ that was led by the school of psychology. It was a subject that I really enjoyed. I’m looking forward to learning more about what is going to be covered in this module.

TM343 Artificial intelligence in practice

I don’t know anything about this module, other than I know it is going to be hands on, and may well cover the subject of natural language processing (in some way or another).

TM358 Machine learning and artificial intelligence

This is an existing module which is a part of the BSc (Honours) Data Science qualification. The module description says: “you’ll learn about various machine learning techniques but concentrate on deep neural learning”. In other words, neural networks.

TM470 The computing and IT project

This is what is called a capstone module. Students who take this programme are required to complete a project that is likely to have an AI flavour to it. This is also one of the modules that I tutor. I’ve written quite a few articles about TM470 in this blog.

Other qualifications

There are a number of other related qualifications which are worth knowing about:

• Q62 BSc (Honours) Computing & IT
• Q67 BSc (Honours) Computing & IT and a second subject
• R60 BSc (Honours) Cyber Security
• R38 BSc (Honours) Data Science

Reflections

It’s really exciting to be working on the software engineering bit of two new modules. 

In some ways, this takes me back to my undergraduate days where I studied computer science. On the programme, there was a single AI module (which was a third year module) which I quite enjoyed. Things have, of course, moved on a huge amount; there are new techniques and new technologies. I was only taught about symbolic AI, and nothing about statistical approaches. I only came across neural networks as a postgraduate student in the mid-1990s.

It is interesting to see how mathematics is introduced in this programme. It begins slowly with material in TM110. This reflects my own experience as an undergrad. I never studied maths at A or AS level, so I went to a ‘gentle start’ class. This led onto a 'discrete mathematics' class, which could be termed ‘bits of maths that could be useful for those studying computer science’. I didn’t like it much. To this day I remember proofs, matrices (which is useful for computer graphics), and a lot of probability (lots of questions about playing cards). The equivalent of my discrete maths class is, of course, MST124. Given the importance of statistics in machine learning, there is then M249. 

It’s also important to reflect that software engineering has changed since I studied it. Computing is now everywhere, and that is a characteristic that makes it such an interesting subject. It is in your devices, in your appliances, and in the cloud. A personal objective is to work with others to create materials that not only give the materials industrial relevance, but also to share with students what it means to study software engineering as an academic subject.

Looking back to my time as an undergraduate, one of the modules that I recognise most clearly in M269, the data structures and algorithms module. Some fundamentals never change. What does change is how they are used, and how they are realised. I remember reciting Dijkstra’s algorithm in an exam, just as if it were an ode. I also remember getting a bit baffled by the big O notation, which features in M269.

One of the areas that I know I’m weak on is statistics. When I’m through studying my current module, I may well find my way back to maths.

Disclaimers

This qualification (along with all the others) is subject to change and development.

Acknowledgements

Acknowledgements are due to the School of Computing and Communications directors of teaching who have played an important role is establishing this new qualification.