#LAK17 – it’s all about multimodality

The 2017 edition of the Learning Analytics & Knowledge conference beat all the previous records with 344 submissions from 1000 authors and 415 participants, the acceptance rate of the full paper was 34%.

Multimodality is the main focus

The trending topic of #LAK17 is undoubtedly multimodality. Two keynotes out of three Sanna Jarvela and Sydney D’Mello focus on multimodal data for learning. The topic is also reflected in many studies presented during the parallel presentations.

Two workshops focus specifically on the challenge of collecting and analysing multimodal learning data: the Learning Anaylitcs across Digital and Physical spaces (CROSS-LAK).

Also the Multimodal Learning Analytics Challenge (MMLA) focus on techniques to analyse multimodal learning datasets.

PhD presentation

In the second of the pre-conference takes place the LAK Doctoral Consortium sponsored by SoLAR where I present my PhD project “Digital Learning Projection: learning state estimation from multimodal learning experiences”.

The presentation addresses several aspects of the topic of multimodality in learning.

The PhD was also presented during the poster session of the conference, the poster is presented here below.

Learning Pulse full paper

Along the lines of multimodality  I present my first full paper published in the LAK17 proceedings “Learning Pulse: a machine learning approach for predicting performance in self-regulated learning using multimodal data”.

The full text of the paper and presentation are both available online.

Other presentations from OUNL

The Open Universiteit is very active at #LAK17: Maren Scheffel presents a paper evaluating a Learning Analytics feedback in a self-regulated learning environment.  Ioana Jivet co-presents a paper on how to raise MOOC completion rates by studying cultural factors of participants.

Author Daniele Di Mitri

I am 25-year-old Learning Technologist. Born in Bari (Italy) , now living in the Netherlands where I moved to study a master Artificial Intelligence at Maastricht University. I am currently writing my master thesis in Predictive Learning Analytics at the TELI research centre of the Open Universiteit. My expertise is in Machine Learning techniques on learning (big) data. Founder of the web startup dimstud.io and Educational Activist in the Lifelong Learning Platform.

More posts by Daniele Di Mitri

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