Author: Marko Prodanovic

Join us on Wednesday July 07th at 3pm-4pm PST for our next LAVA session held by Dr. Julie Wei form the Faculty of Arts.

Reframing Student Evaluation of Teaching (SEoT): Using Student Comments to Unlock Hidden Themes

From Julie:

Student evaluation of teaching (SEoT) has been implemented for decades by many universities including UBC. This has created and is still creating huge amount of student feedback comments that pour in course and teaching evaluation survey, however this type of data has not been used widely, probably because it is time-consuming to review the unstructured data. In this presentation, Dr. Julie Wei will share a project she initiated and led at the Faculty of Arts by employing both students’ original comments and the explicit suggestions automatically extracted from them by using Natural Language Processing (NLP) approach. This could quickly provide instructors and decision-makers with useful information that could help further identify the areas that need to improve and thus help promote quality teaching and student success in the long run.

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These sessions are being held via Zoom. To attend this session, or to be added to our mailing list to receive information about future sessions, please contact Alison Myers (alison.myers@sauder.ubc.ca).

Our first LAVA meeting of the year will take place on Wednesday Feb. 10th at 11am-12pm PST, and will be led by Dr. Christopher Brooks.

From Dr. Brooks:

Abstract: As a field at the intersection of social and data sciences there is a strong need for quality instrumentation of teaching and learning. Yet, much of the work done in the field of Learning Analytics to date has not considered instrumentation directly, and instead has been built upon data which is the byproduct of learner activities, sometimes even pejoratively referred to as “data exhaust”. In this talk I will describe both a need for and an agenda toward exploring learning analytics instrumentation directly, where the creation, employ, and improvement of data collection instruments are of central interest. I will discuss methodological, architectural, and pragmatic considerations when it comes to the instrumentation of learning analytics systems, and give specific thoughts on the need to understand and improve upon instrumentation choices when making theoretical and methodological decisions.

Bio: Christopher Brooks is an applied Computer Scientist who builds and studies the effects of educational technologies in higher education and informal learning environments. Dr. Brooks has a particular domain focus on data science education and methodological interests in predictive modelling, learning analytics, and collaborative learning. He has published widely in the areas of educational technologies and human computer interaction, and has been awarded several best papers (LAK, AIED, CHI, CSCW) with collaborators. At the University of Michigan School of Information he directs the activities of the educational technology collective (etc), a group of postdoctoral scholars, graduate students, undergraduate students, and other collaborators.

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This presentation will take place on Zoom. If you would like to attend but are not part of the LAVA emailing list, please contact Alison Myers (alison.myers@sauder.ubc.ca) for information.

We’ll be having an off-cycle LAVA meeting today, November 25^th, at 11:30am, where we will have presenters join us from UMIT in Austria!

Elske Ammenwerth, Eva Kaczko, Verena Dornauer, and Lisa-Maria Norz, members of LACOI: Representation of a Community of Inquiry in Cooperative Online-based Courses through Learning Analytics will join us to share their work and to learn about the LAVA community. We will learn about the ongoing Learning Analytics Community of Inquiry project and some details about specific research avenues of that project including: regulation of learning in CoI (Community of Inquiry), Cognitive presence – toward automatic measurement, and Social presence – toward automatic measurement by social network analysis. Following an initial presentation and discussion from LACOI, members from LAVA will also share some of their work and projects.

Some more information about LACOI, from the project website: https://iig.umit-tirol.at/index.php/en/projects/24-ongoing-projects/263-2020-2023-lacoi-representation-of-a-community-of-inquiry-in-cooperative-online-based-courses-through-learning-analytics

Wider research context: From a socio-constructivist point of view, learning requires activity, self-regulation, and cooperation among students. Online-based learning environments in higher education offer great flexibility to students, but are challenging in fostering such cooperative learning. The Community of Inquiry (CoI) is an established and effective framework on fostering effective cooperative learning in virtual learning environments. Learning Analytics provides approaches to measure the CoI. However, an automated analysis and visualization approach of the CoI is still lacking which prevents real-time monitoring of courses. In addition, it is unclear which actionable advice can be derived from CoI analysis to directly improve teaching and learning. Our idea is to build CoI dashboards using learning analytics. We will then evaluate whether this has an impact on teaching, learning process, or learning outcome.

Research questions:

1. Is it possible to develop a comprehensive, automated representation and visualization of the Community of Inquiry (CoI) and its three dimensions for individual online-based courses by combining and extending approaches from learning analytics?
   
2. Does the visualization of the CoI in a teacher dashboard, combined with actionable advice, has any impact on teaching?
   
3. Does the visualization of the CoI in a student dashboard, combined with actionable advice, has any impact on student self-regulation, learning process, or learning outcome?
   

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If you’d like to attend future meetings, be added to the email list, or would like to present to the LAVA group, please contact Alison (alison.myers@sauder.ubc.ca).

Our first fall LAVA meeting will be next Wednesday October 14 from 3-4pm (Vancouver time), on Zoom. In honor of the virtual Tableau conference Alison will be giving a Tableau demo!

From Alison:

I will very briefly go over the basics of Tableau, but will spend most of the time talking about some of the new features of Tableau 2020.3 (ahem, dynamic parameters), as well as some good old Tableau tips and tricks that I use. If there is anything you are curious about or would like me to cover either you can let me know in advance or I can try to answer during the session.

The final 20 minutes will be saved for Q/A, open discussion and sharing Tableau tips/tricks

Other Resources

We walked through this LAVA Demonstration workbook: https://public.tableau.com/profile/alison.myers3113#!/vizhome/LAVADemoWorkbook2020-10-14/StudentInfo

This is a great workbook to pick apart to understand more options for how to work with set and parameter actions! https://public.tableau.com/en-gb/profile/andy.kriebel#!/vizhome/SetParameterActionsCatalog/ColoringBetweenTwoDateswithSetAction

 

 

Our LAVA meeting this week (Wednesday August 19, 3-4pm PT, on Zoom) will be lead by Craig Thompson from the UBC Learning Analytics Project.

At this session, Craig will present on the newly developed Student Time Zones tool:

Student Time Zones Tool Guide

From Craig: This is a new LTI tool, developed by Andrew Gardener and Justin Lee, to give instructors an early insight into students’ scheduling availability this fall. We’ll briefly walk through the tool, and then open the floor for comments, suggestions, and discussion.

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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.

Our LAVA meeting next week (Wednesday August 5, 3-4:30pm PT, on Zoom) will be led by Dr. Andrew Gibson from Queensland University of Technology.

Presentation description (originally posted here):

Andrew Gibson from Queensland University of Technology (QUT) will outline recent research work that uses Reflective Writing Analytics (RWA) to help gain insights into pre-service teachers capacities with respect to assessment. The research involves capturing regular personal reflections from pre-service teachers over a period of time using web-based software called GoingOK. These reflections are analysed using natural language processing technologies, in a socio-technical pragmatic approach where socio-cultural interpretive research informs the development of the analysis, and iterations of analytics inform the emergence of the interpretation. Andrew will provide examples of the RWA and present a case for using similar approaches in other learning analytics research.

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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.

Our LAVA meeting this week (Wednesday July 8, 3pm PT) was led by Firas Moosvi. Firas presented on Dash, its features, and how to get an app up and running.

Links below:

Slides

Github Repo

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If you would like to attend future LAVA sessions but are not part of the 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.

Our LAVA meeting this week (Wednesday June 24, 3pm PT, on Zoom) will be led by Gabriel Smith and Warren Code from the Faculty of Science. They will be presenting “Difficulty and Gender Analysis of Course Grades: A Dashboard”

From Gabriel and Warren:

Inspired by the work of the SEISMIC group (https://sites.google.com/umich.edu/SEISMIC/working-groups/key-projects) on demographic effects in introductory STEM courses, we have developed a dashboard (in R Shiny) to explore course performance in introductory courses in the Faculty of Science relative to grade averages over other courses taken, both in general for a course to give a sense of the relative “difficulty” of a course, and also with respect to the gender of the students.  With data drawn from 1^st and 2^nd year Science courses across a sample of recent years, we will provide a live demonstration of our dashboard (with obfuscated course names) which has a “macro” level to show patterns in disciplines or types (lecture vs. lab) of courses and a “micro” level to drill down into one chosen course at a time.  We will discuss our choices in visualization and modelling in adapting the approach of the SEISMIC group, and offer a brief overview of trends we have observed so far.

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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.