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Technologies for STEM learning

An investigation into the breadth of learning outcomes and skills developed in OpenSTEM Labs experiments

Project leader(s): 
Helen Lockett

The OpenSTEM Labs (OSL) deliver authentic practical experiences to our distance learning students in STEM subjects using real time instrumentation, data and equipment for practical enquiries over the internet. The Open University has made a substantial investment in the OSL and built up a large repository of experiments. The aim of this project is to investigate the breadth of learning outcomes developed across all the OSL experiments and develop tools to help design OSL experiments in the future, with a view to Module teams being better informed to make the right choices when considering using the OSL. The project will improve our understanding of which types of experiments, student interactions and assessments best develop which learning outcomes and skills. 

The project will start with a literature review to identify existing classifications of remote experiments and their learning outcomes. The findings from literature will be used to define a taxonomy of remote/ onscreen laboratory activities, learning outcomes and assessments.

All the Faculty’s OpenSTEM Labs experiments will then be mapped using the defined taxonomy to create a searchable database.  It is anticipated that the results will allow us to identify a set of common experiment types, learning outcomes and assessment methods, and will be used to develop a design tool that will assist with designing new activities in the future. This could be in the form of simple postcards describing activity types, learning outcomes and skills that could be used by module teams early in the module learning design process. 

The project will benefit staff by making it easier to design effective experiments that contribute to student success and progression. It will also help module teams to find information about existing OSL experiments for possible reuse. The project will benefit students by enhancing the use of the OpenSTEM Labs in our teaching.

Helen Lockett, James Smith and Kevin Gowans poster (PDF)

An investigation into the way Jupyter Notebooks enhance learning and teaching on TM351

Project leader(s): 
Sharon Dawes and Chris Thomson

TM351 (Data Management and Analysis) has used Jupyter (2019) notebooks for practical work from its inception in 2016. This web based tool enables students to embed program code and associated discussion in a notebook in the style of a lab book (Appendix B) so that they can explain what they were doing and why. Teaching materials include notebooks in the same style, to explain a concept and then show its practical application such that the example can be run. In this way students can return to a project at a later stage and if their notes were sufficient, they or another researcher can repeat the work and study how valid their assumptions were as well as whether their conclusions in a report were justified.

The project will investigate how students divide their time between theoretical reading on the TM351 module website and practical work using notebooks, both as a part of their learning, and then practice for their final report. It will explore to what extent their use of the notebooks reinforces their learning or extends their knowledge. It will look at  whether there is any relationship between  where they are currently studying and  what computing devices they have available when the student works at home, at work or on the go that might affect their ability to undertake practical work using notebooks as opposed to theoretical reading using other provided materials.

The research questions the project will answer are:

  • Does the use of notebooks effectively support students in their studies of the module learning outcomes?
  • Do notebooks allow the students to integrate theory and practice?
  • Do students have technological problems in using notebooks?
  • Does the use of notebooks dictate when and where students are able to study?
  • Is the use of notebooks restricted by accessibility constraints?

Dawes, S. and Thomson, C. (2019) project poster (PDF)

Pair Programming as a tool to enhance teaching and learning of programming at a distance

Project leader(s): 
Adeola Adeliyi


Pair programming is a key aspect of Extreme Programming (XP), which encourages informal and immediate communication over joint coding work. The technique involves two developers: one in a driver role writes the code, controlling the keyboard and mouse, and the other, the navigator, reviews the code as the driver writes it. There is now a substantial body of evidence in support of improved coding outcomes when pair programming is used in teaching (Ghorashi 2016; Mehmet et al. 2018).

Despite these proven academic benefits for collocated classroom settings, distance and online settings are yet to benefit. The isolation and impoverished learning experience some students report points to an urgent need for tools and methods that support remote pair programming in a distributed educational setting to be developed.

In a traditional instructor-led teaching environment, pair programming is relatively easy to implement. This is more challenging in distance teaching and learning situations. Some of these challenges include: 

  1. Students experiencing isolation and exclusion
  2. Problematic communication due to students having fewer interactive and communication options in a remote setting
  3. Access to code repository


To improve teaching programming at a distance, using Pair-Programming as collaborative learning tool, we will:

  1. Carry out extensive literature review on existing academic research on collaborative learning, methods and tools developed to support pair programming (both traditional and remote style) and real time coding in education (both collocated and distance settings) to identify principles of effective pair programming.
  2. Identify and/or develop tools that will support remote pair-programming taking the identified principles of effective pair programming into account.
  3. Review the current Open University teaching and laboratory practices in use for teaching computing related subjects: TM112 – Introduction to computing and information technology 2, TM129 – Technology in practice, M250 – Object-oriented programming in Java, M269 – Algorithms, data structures and computability.
  4. In conjunction with student partners, we will carry out two user studies, which will evaluate:
  1. The effectiveness of collaborative tools.
  2. The effectiveness of the method of pairing, such as voluntary, randomized, knowledge-based, demographic pairing.
  3. Evaluation of students’ experience, feedback, programming skills, and evidence of academic improvement.
  4. Improvement carried out on the methods and tools.


The evidence-based results will support improved learning outcomes when pair programming techniques are used in teaching programming at a distance.


  1. Reduce collaboration obstacles enough to make remote pair programming worthwhile and attractive to students at the Open University.
  2. Contribute to the wider academic research think-tank, the development of collaborative techniques for delivery of teaching programming at a distance.

Related resources

Adeliyi, Adeola; Wermelinger, Michel; Kear, Karen and Rosewell, Jonathan (2021). Investigating Remote Pair Programming In Part-Time Distance Education. In: 3rd Conference on United Kingdom and Ireland Computing Education Research, UKICER 2021, ACM International Conference Proceeding Series, ACM, Glasgow, article no. 6. DOI:

Adeliyi, A. (2019) project poster (PDF)