News Story
5 contributions from KMi presented LAK 2017
Rachel Coignac-Smith, Tuesday 18 Apr 2017As every year, KMi presented the current results at the top-level Learning Analytics conference, Learning Analytics and Knowledge (LAK17). This year, the conference was held in Vancouver, Canada (13-17 March) and co-organised with ex-KMier Marek Hatala. Even though the acceptance rate was quite low, KMi was proud to have 5 papers accepted: 1 full paper, 3 short papers and 1 poster in the research sections and one also in the practitioners track.
On the first day of the conference, Martin Hlosta presented the novel model that is used at The Open University for identifying at-risk students, when no historical data are available for learning the model. http://dl.acm.org/citation.cfm?id=3027449
Michal Huptych showed an early version of our study materials recommender, which is based on analysing the information about successful students in the previous presentation of the same course. http://dl.acm.org/citation.cfm?id=3027426
The joint paper between KMi, IET and LTS, introduced by Thea Herodotou, showed the teachers perspective of learning analytics at large scale. This research is based on the results and interviews with tutors from the previous year. http://dl.acm.org/citation.cfm?id=3027397
Moreover, in the practitioner track, organised together with the poster section, we shared our results in scaling up the OUAnalyse from various perspectives: both with the focus on including as many courses and as many users at OU.
Tracie Farrell Frey, one KMi’s PhD students, participated in the poster section with her contribution about Seeking Relevance: Affordances of Learning Analytics for Self-Regulated Learning.
Still fresh from the conference, the OU Analyse team hope to come back to present their new results next year down under in Sydney, https://latte-analytics.sydney.edu.au/index.php/lak18-sydney-australia/
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The OU Analyse project is piloting new machine learning based methods for early identification of students who are at risk of failing.
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