Learning Analytics and Learning Design, a Marriage Made in Heaven?

Event Type: Thematic Seminar

Event Theme: Evidence-based Practice


Speaker: Prof. Bart Rienties (Professor of Learning Analytics at the Institute of Educational Technology at the Open University UK)

Date: 28 May 2019 (Tuesday)

Time: 7:00pm - 9:00pm

Venue: RLB502, Research Complex, HKSYU

Language: English

 

Remarks:

1) Refreshment will be provided. 
2) Free Admission.
3) Registration is not compulsory but recommended for seat-reservation and news update.

Summary

Learning Design (LD), the approach developed and used by the Open University (OU), is described as a methodology for enabling teachers/designers to make more informed decisions in how they go about designing learning activities and interventions, which is pedagogically informed and makes effective use of appropriate resources and technologies. In other words, LD is focused on ‘what students do’ as part of their learning, rather than on ‘what teachers do’ or on what will be taught. Within the OU, there is an increased recognition that LD is an essential driver for learning.
Recent technological developments have allowed researchers and practitioners alike to capture the digital traces of learning activities of students and teachers in Virtual Learning Environments (VLEs). This rich and fine-grained data about actual learner behaviours offer educators potentially valuable insights into how students react to different LDs. However, despite substantial progress in transferring LD from implicit to explicit, there remains a paucity of evidence for how learners respond to different LDs. 
After ten years of developing, testing, implementing and evaluating the evolving large-scale practice of LD at the OU, in this seminar I will critically review the following question: To what extent is there robust empirical evidence of the impact of learning design on educational practice and how students learn? I will first discuss how the OU implements LD, and in particular how we map our modules. Second, I will compare, contrast and review nine large-scale studies at the OU (Nguyen, Huptych, & Rienties, 2018a, 2018b; Nguyen, Rienties, & Toetenel, 2017; Nguyen, Rienties, Toetenel, Ferguson, & Whitelock, 2017; Rienties, Lewis, McFarlane, Nguyen, & Toetenel, 2018; Rienties et al., 2017; Rienties & Toetenel, 2016; Toetenel & Rienties, 2016a, 2016b) that have linked LD with LA. Finally, based upon my practical experiences and research insights, I will propose four large research questions that might inspire researchers, practitioners and institutions to enhance our understanding of LD.

 

About the Presenter

Dr. Bart Rienties is Professor of Learning Analytics at the Institute of Educational Technology at the Open University UK. He is programme director Learning Analytics within IET and head of Data Wranglers, whereby he leads of group of learning analytics academics who conduct evidence-based research and sense making of Big Data at the OU. As educational psychologist, he conducts multi-disciplinary research on work-based and collaborative learning environments and focuses on the role of social interaction in learning, which is published in leading academic journals and books. His primary research interests are focussed on Learning Analytics, Computer-Supported Collaborative Learning, and the role of motivation in learning. Furthermore, Bart is interested in broader internationalisation aspects of higher education. He has successfully led a range of institutional/national/European projects and received a range of awards for his educational innovation projects. More info at www.bartrienties.nl

Registration Instruction

Contact Information

Should you have any enquiries, Please feel free to contact: cebp@hksyu.edu