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Learning Analytics

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Learning analytics

Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for the purposes of understanding and optimizing learning and the environments in which it occurs. (1st International Conference on Learning Analytics & Knowledge 2011)

 

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Learning analytics at PolyU

  • LA in University's Strategic Plan
    • LA is a strategic priority to enhance the quality of student experience in teaching and learning in the 2019/20 to 2024/25 Strategic Plan.
    • Website
  • LA for Programme Review
    • This cross-institutional project, funded by the University Grants Committee and involving three universities, use data-driven approach to examine graduates’ experiences and identify factors for student success in the curriculum.
  • Community of Practice on Learning Analytics (CoP LA)
    • The CoP LA is a platform for PolyU staff to share and learn about LA for improving teaching effectiveness. It also fosters professional development and provides guidance to the University on LA.
    • Website
  • LA Symposia
    • The University held two LA symposia in 2019 and 2020 to showcase and discuss LA for enhancing teaching effectiveness. The symposia featured experiences, insights, new developments and good practice in LA to improve student learning outcomes.
  • Workshops, Seminars and Webinars
    • The University regularly organises sessions on LA and its recent developments. These sessions aim to promote and share LA uses and best practices and enhance staff's capacity to use LA for quality improvement.
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Learning Analytics in EDC

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 EDC LA team has collected and analysed various types of learning and teaching data, such as:

  • Data from the Learning Management system (LMS)
  • Data from the online videoconferencing Tools
  • Data from the Video Management System
  • Student feedback on learning
  • Students’ academic performance
  • Teachers’ participation in professional development

By examining these data sources, EDC can apply LA to design and deliver effective staff development programmes for online teaching and learning. EDC's LA research and initiatives have produced significant benefits for the University. Our team will continue to explore and advocate the use of LA to enhance online teaching and learning in the University.

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Learning Analytics Projects in EDC

  • LA for Enhancement of Virtual Teaching and Learning (VTL) at Subject Level: A Gap Analysis with Follow-up Training (Completed)
  • Self-Service Portal for Different Stakeholders to Access Teaching and Learning Reports or Dashboards
  • Programme Learning Analytics Report (PLAR) for PolyU programmes
  • Analytics for Learning: Pilot use of student-facing dashboards to support self-regulated learning
  • Supporting teachers’ VTL enhancement via Intelligent Learning Analytics Dashboards
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Learning Analytics Platform for PolyU Staff

The Learning Analytics Platform (LAP) is an online one-stop platform that provides senior management, Deans, Heads, programme leaders, teachers and staff with useful visualisation and reports on learning and teaching data from multiple sources. The LAP aims to help staff understand students' learning process and learning experience at the university. The LAP can be accessed by staff and authorised administrative staff via https://www.polyu.edu.hk/edc/lap

 

 

EDC PUBLICATIONS AND CONFERENCE PRESENTATIONS ON LA

  • 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 www.ejel.org
  • 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. https://doi.org/10.1108/IDD-10-2018-0053
  • 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 http://www.icicte.org/Papers_ICICTE2016/2.3%20017_Armatas-edit%20.pdf
  • Tse, A., & Chan, D. (2021, June). Learning Analytics During COVID-19 and Beyond [Conference presentation]. The Teaching and Learning Innovation Expo 2021, virtual conference.
  • Tse, A., & Chan, A. (2021, June). An Exploration of Student and Teacher Accesses to Online Learning Platforms [Conference presentation]. The HKAECT 2021 International Conference, virtual conference.
  • 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.

Enquiries

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For any general enquiries or support regarding LA, please contact learn.analytics@polyu.edu.hk

For advice or consultation, please contact:

Ms Ada Tse, ada.sk.tse@polyu.edu.hk,  2766 4414

Mr Dick Chan, chun.sang.chan@polyu.edu.hk,  2766 6304

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