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Our LAVA meeting this week (Wednesday June 10, 3pm PT, on Zoom) will be led by Fabian Froehlich.

Fabian Froehlich joined the Faculty of Education as a graduate student in 2018. Specializing in Media & Technology Education Studies Fabian’s research focuses on inclusive instructional design through educational technology. He is a SOTL-specialist (Scholarship of Teaching and Learning) at the Centre of Teaching and Learning Technology and worked for the Learning Analytics Team of UBC as a videographer.

From Fabian:

The presentation summarizes findings of my master-thesis: social network analysis as a progressive tool for learning analytics. In order to investigate the following research question: “Do students presented with social network analysis data on online course discussions adjust their engagement behavior?”. A quasi-experiment was conducted relying on an embedded mixed-method research design. Students (n=18) participated in three online discussions. Two online discussions allowed students to access social network analysis visualizations through Threadz, a Canvas plugin. The overall inquiry focuses on how this exposure of learning analytics data might influence the students. 

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If you would like to attend but are not part of the LAVA emailing list, please contact Alison Myers (alison.myers@sauder.ubc.a) for the Zoom information. You can also request that Alison add you to the LAVA mailing list, where we share information about upcoming LAVA sessions.

 

Next week (Wednesday May 27^th, 3pm), Craig Thompson from the Learning Analytics Team will be leading our LAVA session,  where he will share some recent work done to analyze course enrolment patterns.

We will be meeting in a Zoom meeting room. For more information and access to the Zoom meeting, please contact Alison Myers

From Craig:

The aim of the work was to uncover groupings of courses that students commonly took while pursuing an undergraduate Biology degree at UBC. This analysis will be used to inform curricular review, for example by highlighting unofficial specializations that students are choosing, which could become officially supported and recognized degree variants. This presentation will include an overview of relevant data mining theory and algorithms, as well as specific findings from applying these methods to course enrolment data at UBC.

This week’s LAVA session will be led by Stoo Sepp (Manager, Learning Design in the Faculty of Education’s Educational Technology Support team). The focus of the session will be on Interaction Treatments.  Stoo will be providing an overview and leading a discussion on how Learning Analytics and Learning Design theory can be advanced by this idea.

From Stoo:

First proposed in 1989, Interaction Treatments refer to the types of interactions that typically occur in technology-enabled learning environments. Applying this concept to the field of learning analytics, we can extend it to incorporate more contemporary theorizing around types of interactions, while refocusing on the ‘L’ in Learning Analytics. In this session, a brief overview of the concept of Interaction Treatments will be presented, along with types of learning analytics used to inform pedagogical action. Finally we’ll have a discussion about how these concepts relate to instructor intention and the design of learning experiences.

For this session, we are asking for feedback on the upcoming Learning Analytics Hackathon. We will walk through what the approach is this year and what has been developed so far. We will also ask for the group’s feedback! If you want to take a look at the github repo which will be the home-base for the hackathon, please do! The overall goal for the hackathon is for students with any level of programming experience to be able to participate and learn, so it will be useful for us to have some fresh eyes from people with various levels of experience as we make our final adjustments ahead of the hackathon.

More information about the hackathon can also be found on the registration page.