+++ Welcome to the 7th Learning Analytics Hackathon! +++
The LAKathon this year will take place online in the course of two days. The discussions will take place both synchronously in the virtual room in Gather.Town and asynchronously on our online platform at https://www.lakathon.org/. Each LAKathon theme this year has a virtual table, and own discussion group with a forum and a whiteboard which can be used within Gather.Town.
Make sure to:
(1) REGISTER to the online platform (if you have not done that yet) and join the preferred thematic group -> https://www.lakathon.org/register/
(2) JOIN the virtual LAKathon room on Gather.Town -> https://gather.town/i/Fb5p4ncv
(Please consider your email should be registered to the LAK conference to be allowed on GatherTown)
Clarification about TIME: the discussions on Gather.Town table will all start on Monday, 12 April 2021, 09:00:00 CEST/GMT+1/UTC+2. However, the participants connect from various location worldwide at different time zones. Feel free to join the Gather.Town at a reasonable time in your time-zone, otherwise check the progress in the discussion group or the whiteboard.
In case you have problems send us a message at https://www.lakathon.org/contact/ or an email at firstname.lastname@example.org
If you use Twitter, use the hashtag #LAKathon https://twitter.com/hashtag/LAKathon
Looking forward to interesting discussions. Enjoy the LAKathon!
The LAKathon organisers.
(Table A) Multimodal Learning Analytics
Discussion group: https://www.lakathon.org/groups/multimodal-learning-analytics/
Welcome! There are some initiatives like GOFAIR that propose and investigate how to make research data findable, available, interoperable, etc. To make this happen across multiple disciplines is in our opinion extremely unpractical. First, the amount of metadata needed to make the research data interoperable across fields is vast. Second, after conducting research and publishing a paper most researchers do not want to invest effort in making their data not only public and findable but also adding all the metadata to it to make it interoperable. Third, in the case of LA and probably many other fields, without specialised software, well-defined methods, scripts, etc. the data is practically useless. The purpose of this LAKathon theme is to design an e-portfolio for researchers, that can be used to organise, store and share their research resources (not only their data). Atezaz Ahmad will be present at Table A on Gather.Town since Monday morning GMT+1, providing explanations and guiding the work. Jan Schneider will join efforts Monday and Tuesday afternoon. Our working plan is completely open at the moment, we plan to adapt and refine the plan based on the suggestions of participants.
(Table B) OERs Quality Prediction
Discussion group: https://www.lakathon.org/groups/oer-quality-prediction/
This challenge focuses on Open Educational Resources (OER) quality predictions. These predictions are critical to offering high-quality learning resources effectively for learners in personalized open learning environments. In this challenge, we will work together to set up an OER quality prediction framework, and prototype a quality prediction model. Gábor Kismihók and Mohammadreza Tavakoli will be present on Monday and Tuesday at GMT+1 at the Table B on Gather. Town.
(Table C) Video Conferencing Analytics
Discussion group: https://www.lakathon.org/groups/video-conferencing-analytics/
Over the last decade, remote learning has started to become more and more common. However, the COVID-19 pandemic has quickly transformed into the most common educational format. Moreover, social and collaborative learning activities have been depicted as one of the main components of active learning, but authors have addressed that these activities might suffer during remote learning. In this challenge, we set ourselves to explore the potential of video conferencing analytics to support teachers implementing social and collaborative activities during remote learning.
(Table D) Privacy & Anonymisation
Discussion group: https://www.lakathon.org/groups/privacy-anonymisation/
Higher Education’s response to COVID included an accelerated rush to scale online learning and related services. Online services generate digital traces that once processed trigger Learning Analytic Interventions. There are numerous reasons to anonymise or pseudo-anonymise the traces. For example, synthetic or anonymised data may be used to minimise ethical, legal, and privacy risks associated with the release of data to infrastructure developers, LA practitioners, and Lecturers. During this hackathon, we will review best practices, algorithms, and architectural design patterns. Addressing the question: How do we minimise privacy sensitive information within the context of a standardized, highly scaled LA infrastructure? Alan M Berg, Jarno Vrolijk and Stefan T Mol will be present at Table D on Monday and Tuesday GMT+1 on Gather.Town.
(Table E) Digital Infrastructures
Discussion group: https://www.lakathon.org/groups/digital-infrastructures/
Robust digital infrastructures must be set in place when online teaching is blended with a physical presence. Video conferencing tools have become a widespread practice for online communication and collaboration. However, many small and medium educational institutions still lack adequate digital infrastructures to support their online learning initiatives including HW, LMSs, safe cloud storage, intranet channels for internal communication, netiquettes and privacy-preserving policies, etc. In this LAKathon challenge, we brainstorm how Learning Analytics can support educational institutions to improve provision and access to quality education. Daniele Di Mitri will be present at Table E on Gather.Town on Monday and Tuesday GMT+1.