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What is Learning Analytics (LA)?

Learning Analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, with the goal of understanding and optimising learning and the environments in which learning occurs.

- Definition from the Society for Learning Analytics Research (SoLAR) -

Learning Analytics at PolyU

Currently, there are several Learning Analytics (LA) initiatives in our university. Below are the details of each initiative.

  • The 2019/20 to 2024/25 Strategic Plan sets out the strategic goals in five domains to be achieved through the core functions of learning, teaching and research. LA is one of the strategic priorities in the Quality of the Student Experience of Teaching and Learning domain. For further details, please visit the Strategic Plan website.

  • This cross-institutional project on conducting data-driven review of programmes involves three universities and is funded by the University Grants Committee. It aims to analyse the graduates’ experiences to identify factors that impact on student success in the four-year curriculum (4YC) and to use this information to provide better support to current students. For further details, please visit the project website.

  • This institutional LA project aims to provide teachers with a customised report on students’ usage of the Learning Management system (LMS) for their courses. The SeER is based on students’ usage statistics and is designed to monitor students’ activity and progress in their subjects.

  • The LA CoP aims to build a community of PolyU staff to explore the use of LA for the enhancement of teaching effectiveness; provide a platform for sharing experience, expertise, and good practice; foster a culture of professional development; and provide guidance to the University on LA. For further details, please visit the LA CoP website. 

  • Our university organised two LA symposia in 2019 and 2020 to discuss and explore the use of learning analytics for the enhancement of teaching effectiveness; share experiences, insights, new developments and good practice; and showcase innovative work in learning analytics to enhance student learning outcomes. Please visit the 2019 LA symposium and 2020 LA symposium websites for details.

  • The University regularly offers workshops, seminars and webinars about conducting LA for enhancing teaching and learning and recent developments in the field. These sessions aim to promote and share uses of LA and best practices and further develop staff's capacity to use LA for quality enhancement.





The Educational Development Centre (EDC) values the potential for LA to inform teaching and learning, particularly with regard to the relationship between teaching pedagogies, learners’ activities and their academic performance. Since 2015, the LA team in EDC have explored and analysed learning and teaching data from a variety of sources. These include:

  • the Learning Management system (LMS)
  • the online videoconferencing Tools (e.g. Blackboard Collaborate Ultra, Zoom, MS Teams)
  • the Video Management System
  • Student feedback on learning
  • Students’ academic performance
  • Teachers’ participation in professional development

Through analysing different kinds of data, EDC can make use of LA to enhance staff development in online teaching and learning. EDC’s research and focus on LA has resulted in tangible outcomes for the University. For example, raising awareness on LA among the university community, developing university guidelines for creation of courses on LMS, better customised training series on using LMS for staff, customised learning analytics report on students’ usage of LMS, self-developed learning analytics tool for courses on LMS, support on using LA for curriculum review, staff training on LA, etc. Our team will continue to conduct research and promote the use of LA on enhancing teaching and learning in the university.


Self-Service Portal for Different Stakeholders to Access Teaching and Learning Reports or Dashboards

In this project, a self-service portal will be established for staff to access interactive customised reports and dashboards drawing on learning and teaching (L&T) data. Useful figures and evidence will be provided for the University, faculties, departments and teachers, to gain greater understanding of L&T, which will help evaluate whether learning outcomes have been achieved.

Programme Learning Analytics Report (PLAR) for PolyU programmes

This project aims to establish a system to analyse and report on students’ academic data to support a newly-introduced policy encouraging the use of LA as part of annual programme review. As part of the annual programme review exercise, departments will be provided with a Programme Learning Analytics Report (PLAR) for each of their programmes to inform possible improvement actions.

LA for Enhancement of Virtual Teaching and Learning (VTL) at Subject Level: A Gap Analysis with Follow-up Training

This project aims to find out what data and reports are available, what data and reports are being used by teachers currently, and whether these are enough for teachers to carry out evidence-based improvements in VTL. The findings should benefit the University by showing how subject teachers are already using LA to enhancing VTL and what further support is needed to facilitate the adoption of LA.

EDC Publications and conference presentations on LA

Since the establishment of EDC’s LA team in 2015, our staff have been actively involved in LA-related educational research.

    • Evans, J. C., Yip, H., Chan, K., Armatas, C., & Tse, A. (2020). Blended learning in higher education: professional development in a Hong Kong university. Higher Education Research & Development, 39(4), 643-656.
    • Foung, D., Chen, J. & Lin, L. (2020). Unveiling the inconvenient truth: The innovation process in implementing a university dashboard. In S. Palahicky (ed.) Enhancing Learning Design for Innovative Teaching in Higher Education (pp. 162-181). Hershey, PA: IGI Global. doi:10.4018/978-1-7998-2943-0
    • Chen, J. & Foung, D. (2020). A motivational story in Hong Kong: Generating goals for language learners and blended learning designers from a mixed-method learning analytics approach in English for Academic Purposes. In M. Freiermuth & N. Zarrinabadi. (Eds.). Technology and the Psychology of Second Language Learners and Users (pp. 491-516). London: Palgrave-Macmillan. doi:10.4018/978-1-7998-2943-0
    • Armatas, C. & Spratt, C. (2019). Applying learning analytics to program curriculum review. The International Journal of Information and Learning Technology.
    • Foung, D. & Chen, J. (2019). Disciplinary challenges in first-year writing courses: A big data study of students across disciplines at a Hong Kong university. Asian EFL Journal, 25(5.1), 313-331.
    • Foung, D. & Chen, J. (2019). A learning analytics approach to the evaluation of an online learning package in a Hong Kong university. The Electronic Journal of e-Learning, 17(1), pp. 11-24, available online at
    • Foung, D. & Chen, J. (2019). Discovering disciplinary differences: Blending data sources to explore the student online behaviors in a university English course. Information Discovery and Delivery, 47(2), 106-114.
    • Chow, J., Tse, A., & Armatas, C. (2018). Comparing trained and untrained teachers on their use of LMS tools using the Rasch analysis. Computers & Education, 123, 124-137.
    • Armatas, C., & Spratt, C. (2018). Evidence, analysis, action: Using learning analytics to direct curriculum review and improve student learning outcomes. In Warner, R, Enomoto, K., & C. Nygaard (Eds.), Innovations in teaching and learning practices in higher education (pp. 219-235). Libri Publishing, Farringdon, Oxfordshire.
    • Chan, K., Tse, A., Armatas, Christine (2018). A preliminary study: using LMS log data to evaluate the effectiveness of a professional development course in blended learning. Proceedings of the IRES 102nd International Conference (pp.52-56), Sydney, Australia.
    • Chen, J. & Foung, D. (2018). Connecting teacher-made assessments to course learning outcomes through learning analytics: an empirical model. In White, E., & Delaney, T. (eds.), Handbook of Research on Assessment Literacy and Teacher-Made Testing in the Language Classroom, pp.101-125. Hershey, PA: IGI Global. Doi: 10.4018/978-1-5225-6986-2.
    • Chen, J., Foung, D., & Armatas, C. (2018). Adopting Learning Analytics to Enrich Regular Curriculum Review and Enhancement: A Case Study of a University English Programme in Asia. In A. Pardo, K. Bartimote, G. Lynch, S. Buckingham Shum, R. Ferguson, A. Merceron & X. Ochoa (Eds.), Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge. Sydney, Australia: Society for Learning Analytics Research.
    • Armatas, C., Tse, A., Chow, J., Foung, D., Chen, J., & Chan, C.S. (2017). Exploring the relationship between the time of completing online quizzes and students' performance in academic writing. EduLearn17 Proceedings, 5306-5311.
    • Armatas, C., Chow, J., Tse, A., Chan, K., Cheng, A., Chan, C. S. & Luk, W. T. (2016). Differences in learning management system use by teachers who participate in training. Asian Journal of Educational Research, 4(5), 47-56
    • Armatas, C., Chow, J., Chan, K., Tse, A., Chan, D. & Luk, W (2016). The effect of learning management system training on teachers’ online teaching. Proceedings of the 16th ICICTE conference (pp.63-70), Rhodes, Greece. Available at
    • Tse, A., Chan, K., & Chow, J. (2020, December). The use of learning analytics in the institution during the COVID-19 pandemic [Conference presentation abstract]. The eLearning Forum Asia 2020, virtual conference.
    • Chan, K., Tse, A., & Chow, J. (2020, December). Responding to COVID-19 in transitioning to online teaching in higher education: A data analytic approach to explore the effectiveness of online teaching and learning at a university in Hong Kong [Conference presentation abstract]. The eLearning Forum Asia 2020, virtual conference.
    • Armatas, C., & Spratt, C. (2019, May). Applying Learning Analytics to Curriculum Review [Conference presentation abstract]. 2019 Symposium on Learning Analytics in Asia, The Hong Kong Polytechnic University, Hong Kong, 23 May 2019
    • Armatas, C. (2018, September). Learning Analytics for Curriculum Review: the P-MAI Model [Conference presentation abstract]. Higher Education Institutional Research (HEIR) UK & Ireland Conference, Dublin Ireland
    • Foung, D. & Chen, J. (2018, August). A mixed-method learning analytics study on the impact of L2 writing performance under the ability-grouping policy in higher education [Paper presentation]. 17th Symposium on Second Language Writing, Simon Fraser University, Vancouver, Canada.
    • Armatas, C., & Spratt, C. (2018, July). Applying Learning Analytics to Curriculum Review [Conference presentation abstract]. International Conference on Information, Communication Technologies in Education, Chania, Crete Greece.
    • Armatas, C., Tse, A., Chan, S.C., & Li. B., (2018, June). Developing a Learning Analytics Tool to Empower Teachers to Conduct Analyses of Learners’ Online Behavior [Conference presentation abstract]. 43rd International Conference on Improving University Teaching: New Spaces for Learning, Charles Stuart University, Port Macquarie, Australia.
    • Armatas, C., & Spratt, C. (2018, May). Enhancing learning outcomes for students through a data-driven review of the 4-year curriculum in UGC funded programs [Conference presentation abstract]. Learning and Teaching @EdUHK Festival 2018. The Education University of Hong Kong, Hong Kong.
    • Chen, J., Foung, D. & Armatas, C. (2018, March). Adopting learning analytics to enrich regular curriculum review and enhancement: A case study of a university English programme in Asia [Paper presentation]. 8th International Conference on Learning Analytics & Knowledge, Sydney, Australia.
    • Tse, A., Chow, J., Armatas, C., Foung, D., Chen, J. & Chan, C.S. (2017, July). Exploring the relationship between the time of completing online quizzes and students’ performance in academic writing [Conference presentation abstract]. EduLEARN17, Barcelona, Spain.
    • Foung, D. & Chen, J. (2017, July). How Rasch analysis enriches academic analytics: a case study of a university English course [Paper presentation]. International Conference on Open and Innovative Education (ICOIE) 2017, Open University Hong Kong, Hong Kong.
    • Chen, J. & Foung, D. (2017 June). Does streaming work? A quantitative study of university EAP subjects [Paper presentation]. Faces of English 2: Teaching and Researching Academic and Professional English, University of Hong Kong, Hong Kong
    • Chow, J., Tse, A., & Armatas, C. (2016, August). Examining teachers’ use of learning management system with the Rasch Analysis [Conference presentation abstract]. The Pacific Rim Objective Measurement Society 2016 Symposium, Xi’an, China.
    • Armatas, C. & Chan, K. (2016, June). The effect of professional staff development on LMS use: Is more necessarily better? [Conference presentation abstract]. The eLearning Forum Asia 2016, Shanghai, PRC.
    • Wai To, L., Chun Sang, C. & Armatas, C. (2015, June). Linking staff training to student engagement in blended learning through “Big” data analysis [Conference presentation abstract]. The eLearning Forum Asia 2015, Singapore.


Online Activity Analysis Tool (OAAT)

The Online Activity Analysis tool (OAAT) is an Excel add-in which empowers teachers to extract and analyse data from the institutional learning management system to understand students' online behaviours, improve their teaching and assist students to be successful in their studies. For further details, please visit the OAAT website.

Program Review Tool (PRT)

The Programme Review Tool (PRT) is an Excel add-in which uses LA to convert students' academic records from a programme into outputs to address programme review questions for academic decision-making and internal and external reporting requirements. For further details, please visit the PRT website.


The ChatAnalyser is an Excel add-in which produces a formatted chat history from online conferencing tools, generating useful figures, summaries and tables for teachers to understand students' engagement in the chat and further enhance their teaching. The ChatAnalyser and the sample data can be downloaded here.

LA Team

The Learning Analytics Team in EDC

Ms Ada Tse

Educational Development Officer

Mr Dick Chan

Educational Development Officer

Dr Christine Armatas


Mr Green Luk


Ms Livia Wong

Part-time Project Assistant



If you have any enquires, please contact us on:


6/F TU Wing, Educational Development Centre,
The Hong Kong Polytechnic University