Let’s join to review and discuss the state of Learning Analytics now compared to early days.
We will be watching some of the videos from the LAK 2012 conference. Then we can talk about whether the concepts still apply, what progress has been made, or what changes have occurred in the last 6 years.
There are 3 sessions chosen that are about 20 minutes each, we can watch and discuss.
1. [LAK 2012] April 30: 2B – The Learning Analytics Cycle: Closing the loop effectively
2. [LAK 2012] April 30: 1B – Using an Instructional Expert…
3. [LAK 2012] May 1: 5B – Does the Length of Time Off-Task Matter?
I am a Senior Research Analyst at UBC Faculty of Arts and work on learning analytics and academic analytics projects in that faculty. I stepped into the world of learning analytics when I started my Master’s degree at School of Interactive Art & Technology, SFU. My research was focused on student-facing LA visualizations and dashboards. In this session, I discussed how we can support students use of learning analytics in the classroom:
“Drawing on the literature, I will talk about some of the known challenges students face when using learning analytics, particularly around the interpretation of presented information and action taking.
Then I will discuss a proposed framework (from the literature) that addresses some of the identified challenges and integrates engagement with analytics as part of the larger teaching and learning activity to support its productive use.
I will show some examples of how the framework can be implemented.“
Data Visualization Critique: A Graphic Design Perspective (Session 2)
Emma Novotny, Senior Graphic Designer in UBC Faculty of Arts has agreed to come back and lead another Visualization Feedback session (which was really great last time)!
If you have a visualization that you think could be improved, that you would like the eye of a graphic designer on, or would otherwise like feedback from Emma please submit it to Alison before the end of day on May 25th. With the visualization, please include:
The context (what project is this for?
What is the goal of the visualization?
Who is the audience?
How will it be used?
Any other detail you think is important
If you don’t have your own visualization to show but know of one that you would like to see improved send that! Emma will choose 1-3 of the visualizations and spend time on the 4th talking about her thoughts on how to improve the visualization/ what she might change/other feedback.
Towards User-Centred Analytics: User-Adaptive Visualizations
In this session, we will watch and discuss one of the keynotes from Learning Analytics and Knowledge Conference 2018 by Professor Cristina Conati, Professor, Department of Computer Science, University of British Columbia. Cristina is interested in integrating research in Artificial Intelligence, Human Computer Interaction and Cognitive Science to create intelligent user interfaces that can effectively and reliably adapt to the needs of each user.
“As digital information continues to accumulate in our lives, information visualizations have become an increasingly relevant tool for discovering trends and shaping stories from this overabundance of data. Education is not an exception, with learner and teacher visualization dashboards being extensively investigated as new means to change pedagogy and learning. Visualizations are typically designed based on the data to be displayed and the tasks to be supported, but they follow a one size-fits-all approach when it comes to users’ individual differences such as expertise, cognitive abilities, states and preferences. There is, however, mounting evidence that these characteristics can significantly influence user experience during information visualization tasks. These findings have triggered research on user-adaptive visualizations, i.e., visualizations that can track and adapt to relevant user characteristics and specific needs. In this talk, I will present results on which user individual differences can impact visualization processing, and on how these differences can be captured using predictive models based on eye-tracking data. I will also discuss how to leverage these models to provide personalized support that can improve the user’s experience with a visualization.”
Sarah is a Data scientist and Research at the UBC Centre for Teaching and Learning. Sarah has a background in data analysis and visualization from the field of bioinformatics and is applying that expertise to education research. Working with faculty members and researchers, she coordinates research projects to assess how the use of technologies or teaching methods affects student learning.
In this session will be presenting and asking for some feedback for a project she has been working on
“For the last few months I have been looking at what students do in virtual science labs mostly focusing on the strategies they use to learn from them. You may have seen visualizations of students’ clickstream data at previous Lava meetings. On Monday, I will show you some data on how students explore the interface and the physical phenomena we ask them to model. Since exploration is an important inquiry skill, I am hoping you can help me figure out how to assess how students explore. Get ready to play with some data and get in the head of students!”
OnTask: A platform to provide timely, personalized, and actionable feedback to large cohorts
Craig Thompson is a Research Analyst working on the UBC Learning Analytics Project. In this presentation, Craig will provide an overview of the recent literature on mass-personalized feedback, and give a technical demo of OnTask.
“OnTask is a tool that enables instructors to give targeted, customized messages based on the metrics that they set for their courses. This allows instructors to provide students with timely and personal feedback that can scale to large courses. Feedback can range from targeted remediation suggestions for students at-risk to enrichment opportunities for high achieving students.
We are going to have a very informal LAVA meeting this week where we will be: debriefing on the Hackathon (what were some of the student output, what went well, what didn’t), discussing the schedule for the summer, and we would like to hear about potential meeting topics from you!
If you can’t join, send an email to Alison. – any thoughts on the hackathon? What should the summer look like (more or less meetings, new schedule)? What is something you are working on or would be willing to lead a meeting on?
Please join us for the 3rd UBC Learning Analytics Hackathon on March 10th and 11. The Hackathon is organized by UBC Learning Analytics Pilot and LAVA.
“The Hackathon seeks to explore in what ways learning data can be used to benefit students. Participants will have access to open learning data sets and will work towards developing, designing, and proposing tools, reports, and visualizations that could be used to improve student learning and experiences.
If you have the desire to explore educational data, or to even just learn more about learning analytics, data analysis and/or visualization then we are looking for you to join us! This event brings together students, researchers, faculty, staff, and any other interested individuals to get hands-on experience with analyzing and working with learning data.
The hackathon is free but registration is required (please register before March 7th).
Workshops (No experience is necessary!)
*Design Track *
Designing Learning Analytics for Students
Intro to Data Visualization with Tableau
Data Wrangling with R.
Advanced Data Visualization with Jupyter and Python“
Alison is a Research Analyst at UBC Sauder School of Business. Working on a variety of data projects, she has been using Tableau for creating interactive dashboards and visualizations.
” In this meeting, I will be reviewing some of the functionality of Tableau for those of you interested in seeing how it works/diving a bit deeper into the capabilities. I’m not going to start from ground 0 (download tableau, import data, drag and drop functionality). If you have any specific questions of “how can I do this”, or “I tried to do this but couldn’t” then please send those along to me and I will try to make sure to answer them, or to provide you with some resources that will be useful.
Hopefully, the other Tableau experts (Sanam Shirazi, Leah Macfadyen) will also be joining us, and I expect them to jump in and correct me in my examples, or offer their alternatives. I’ll try to review some basics about calculated fields, fixed calculations, special data type functionality, parameters and some principles about visualization. Hopefully, I will introduce enough vocabulary for you to have something to Google later rather than go into depth in any specific area. One useful thing to remember – it’s really easy to do one thing in about 10 different ways, so your experience may be different than mine!
If you don’t have it installed – download a free trial here. If you’ve never used Tableau, there are some introductory materials available to you on this page as well. I would start here for anyone with no experience. Or, just download and begin to play.”
Alison will be running a Tableau workshop in the Learning Analytics & Open Data Hackathon 3.0. If you are interested in participating, sign up here for the upcoming hackathon.
Data Visualization Critique: A Graphic Design Perspective
Emma Novotny is a Senior Graphic Designer at UBC Faculty of Arts. Before starting at UBC, Emma Novotny worked in Toronto as a graphic designer in the Knowledge Translation Department at St. Michael’s Hospital. There she designed web and print-based tools and infographics for patients and primary care providers. She has also worked at a small design studio called Tennis (formerly ALSO Collective) where she produced branding, editorial, and web projects for a range of clients in the healthcare, not for profit, and arts and culture industries.
In this session, Emma will provide feedback on a couple of data visualization projects based on her own expertise. She will choose 1-3 of the visualizations that were submitted to her by LAVA folks and spend time on talking about her thoughts on how to improve the visualization/ what she might change/other feedback. She will also use the time to give some general information regarding visualizations.