Informace o publikaci

Towards Performance Prediction Using In-Game Measures

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ARNAB Sylvester IMIRUAYE Odafe LIAROKAPIS Fotis TOMBS Gemma LAMERAS Petros LAGUNA Angel MORENO-GER Pablo

Rok publikování 2015
Druh Článek ve sborníku
Konference Proc. of Toward Justice: Culture, Language, and Heritage in Education Research and Praxis (AERA 2015)
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www http://www.fi.muni.cz/~liarokap/publications/AERA2015.pdf
Popis The efficacy of a learning process is influenced by the quality of teaching, learning support and environment. This requires effort in tracking how students learn. This paper explores the use serious games in order to help understand the learning process, where interaction data during a play-learn session can be captured. The focus is on the use of ingame data, analyzed using Learning Analytics techniques, and discusses the potential of such an approach to predict learners’ performance. Gameplay data were collected from various play-learn sessions based on a First Aid Game. Results indicate that in-game measures can help to understand students’ progress and predict their performance, providing opportunities for individual support to be provided to learners.

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