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About LA

What is LA?

Learning analytics involves the measurement, collection, analysis and reporting of data about learners for the purpose of understanding and improving learning. It has many applications including:

1. Developing models to predict learner outcomes and student performance;

2. Identification of students who are struggling and understanding what can be done to assist them; and

3. Assessing the usefulness of learning materials and resources, evaluating the effectiveness of the curriculum and assisting in evidence-based decision making relating to improving students’ learning experience.

Developing models to predict learner outcomes

Identifying of students' needs and struggles

Assessing the usefulness of materials

As such, learning analytics are an important tool in the quality assurance/quality enhancement process for any educational provider. Teachers can make use of learning analytics to inform their teaching practices such as using the assessment data and student profile to evaluate whether a teaching practice is effective for a certain group of students. Curriculum leaders can make use of learning analytics to drive curriculum development including the use of assessment results in different cohorts to identify the weakness of students in general. Administrators can make use of learning analytics to predict student achievements. This can be achieved by analyzing student admission scores and student assessment data to identify the best-fitted students for the programme.

Source from CoP website
About LA


PolyU has released a new Strategic Plan for 2019/20 to 2024/25. The Strategic Plan sets out the strategic goals in five domains to be achieved through the core functions of learning, teaching and research. Learning analytics is one of the strategic priorities in the domain “Quality of the Student Experience of Teaching and Learning” (Strategic Priorities 4d of this domain). In order to provide a supportive environment for students to review and reflect on their learning, the university encourages teachers or faculties to make use of learning analytics to identify student learning problems early in the semester (e.g., identify the weakness of students, predict student achievements, inform teaching practices, drive curriculum development, etc.). Through learning analytics, both educators and students can gain new insights in the learning process and can further improve the quality assurance/quality enhancement of teaching and learning experiences.
For further details, please visit here.


The University initiated the Student Lifecycle Management Platform (SLMAP) project to establish its long-term internal analytics capability for monitoring and improving student experience. A central platform will be developed that integrates the academic and non-academic information of students. This platform will allow the University to utilise the wealth of student-related data for continuous enhancement of student engagement and experience. It will also support the institutional planning and the development of policies and strategies related to student lifecycle, curriculum and student support services.


The Subject e-Engagement Report (SeER), an institutional learning analytics (LA) project, was initiated in 2017, to provide teachers with a customized learning analytics report on students’ usage of the Learning Management system (LMS) for their courses. The SeER, which can be accessed in the LMS, is a simple interactive report in Excel providing visualizations and tables of weekly usage figures for commonly used LMS tools. It also includes an individual student dataset that can be downloaded for analysis in other applications and a list of students with low LMS usage in the class, along with a list of students who have never logged into the LMS course. The SeER is based on students’ usage statistics in the courses in Learn@PolyU and is designed as a tool for monitoring students’ activity and progress in their subjects. This can help alert teachers to students with low activity in subject websites and subject teachers can then follow up with, or provide advice to, these students in a timely and effective way.

Learning analytics &
the Communities of Practice


PolyU established thematic Communities of Practice (CoPs) to bring groups of enthusiastic colleagues around the campus together, foster a culture of peer support and nourish pedagogic development and scholarship for enhancing the quality of learning and teaching in the university. “Conducting Learning Analytics to Inform Teaching and Learning” is one of the six CoP developed in 2016-2019. The aims of this CoP are to build up a community of PolyU staff to explore the use of learning analytics for the enhancement of teaching effectiveness, provide a platform for sharing experience, expertise, and good practice, foster the culture of professional development and provide advice to the University on matters related to the use of learning analytics for quality enhancement.
For further details, please visit: https://www.polyu.edu.hk/CoP/analytics/


LA Reseach done by edc

EDC values the potential for LA to inform teaching and learning, especially, in respect to the relationship between teaching pedagogies, learners’ activities and their academic performance. Since 2015, EDC have explored and studied the students’ learning data such as the Learning Management system (LMS), students’ feedback and student performance to make use of LA to enhance the staff development on using LMS and online teaching and learning. Through the research and studies done and effort paid in promoting LA, encouraging outcomes are observed in the university. For example, upraising awareness on LA in the university, university guideline for LMS courses creation, better customized training series on using LMS for staff, customized learning analytics report on students’ usage of LMS, self-developed learning analytics tool for LMS courses, support on using LA for curriculum review, staff training on LA, etc. EDC will continue to perform research and promote making use of LA on enhancing teaching and learning in the university.

Evan, J., Yip, H., Chan, K., Armatas, C. & Tse, A. (In press). Blended learning in higher education: professional development in a Hong Kong university. Higher Education Research & Development.

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. Paper presented at 43rd International Conference on Improving University Teaching: New Spaces for Learning, Charles Stuart University, Port Macquarie, Australia.

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.

Chan, K., Tse, A., Armatas, Christine (2018, February). 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.

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. Paper presented at EduLEARN17, Barcelona, Spain.

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

Chow, J., Tse, A., & Armatas, C. (2016, August). Examining teachers’ use of learning management system with the Rasch Analysis. Paper presented at the Pacific Rim Objective Measurement Society 2016 Symposium, Xi’an, China.

Armatas, C., Chow, J., Chan, K., Tse, A., Chan, D. & Luk,W (2016, July). The effect of learning management system training on teachers’ online teaching. Paper presented at the 16th ICICTE conference, Rhodes, Greece. Available at http://www.icicte.org/Papers_ICICTE2016/2.3%20017_Armatas-edit%20.pdf

Armatas, C. & Chan, K. (2016, June). The effect of professional staff development on LMS use: Is more necessarily better? Paper presented at the 11th eLearning Forum Asia (eLFA 2016), Shanhai, PRC.

Wai To, L., Chun Sang, C. & Armatas, C. (2015, June). Linking staff training to student engagement in blended learning through “Big” data analysis. Paper presented at the10th eLearning Forum Asia (eLFA 2015), Singapore.

LA Tool

Learning analytics tool

Two Excel tools are developed. One is called Program Review Tool for analysing institutional data. Details can be found here. The other tool is call OAAT (Online Activity Analysis Tool) for analysing the LMS data.

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Oct 10, 2018 | Workshop

First step in learning analytics: Data Preparation and simple visualization with R studio and SPSS

What can you know from students’ assessment results? Learning analytics can be a simple and easy way for colleagues to find out more, even if you do not have a statistical background. .

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6/F TU Wing,

Educational Development Centre, The Hong Kong Polytechnic University