Learning Analytics

This project is funded by a Learning and Education Advancement Fund (2016–2019) —
Office of the Vice-Provost, Innovations in Undergraduate Education, University of Toronto

The focus of the Learning and Education Advancement Fund (LEAF) program is to enrich the learning experience of undergraduate students in first-entry Divisions across the University and to provide academic units with a mechanism for developing and enhancing the research, assessment, and application of high-impact teaching practices within learning environments at the University. The Fund is intended to support projects that will anticipate, leverage and create positive changes in both the modes and mechanisms of undergraduate education at the University of Toronto.

Predictive and Adaptive Learning Analytics in Online and Hybrid Course Delivery

Our project makes use of predictive and adaptive learning analytics with the broader goal of contributing to the re-invention and re-imagining of undergraduate education through the enhancement of the delivery of LIN204H5 English Grammar. This is a high-enrolment course that is delivered both as a fully online course and as a hybrid course taken by many international students as well as native English speakers and Linguistic program students to enhance their understanding of the structure and usage of English. The project’s specific aims are 1) to enhance student assessment and feedback processes to ensure all students receive optimal support and direction to achieve their learning goals; 2) to support independent, engaged, and self-regulating learners through the implementation of learning analytic tools; 3) to engage in the community of practice and support pedagogical change where best practices in online pedagogy are not yet well established. This will be achieved through the dissemination of the methodology and mechanisms developed within the project; and 4) to increase the University’s presence in high-quality e-learning.

Dr. Eugenia Suh

Eugenia Suh is a postdoctoral fellow with the Department of Language Studies. She completed her PhD in Linguistics, analyzing the use of nominal inflectional morphology in Korean heritage language acquisition. She has been involved with LIN204 English Grammar since it was first developed into an online course and works closely with me to analyse, develop, and improve course assessments. For this project, Eugenia compiles and analyses large amounts of student performance and usage data to assess the effectiveness of the assessments and to identify possible gaps in student learning. The results then inform the kind of online course structures she develops in order to further improve learning.

Crystal Chow

Crystal works with us as a course builder, adapting and creating online low-stakes assessments for students. She comes to us via the UTM Work Study program. Crystal is completing her fourth and final year at UTM, with a major in Linguistics and another in Chemistry. She speaks English, French, Cantonese, and Mandarin, and is interested in knowing about even more languages. Next year, she plans to pursue postgraduate studies in Linguistics in Hong Kong or Vancouver.