Projects per year
Clustering algorithms, pattern mining techniques and associated quality metrics emerged as reliable methods for modeling learners’ performance, comprehension and interaction in given educational scenarios. The specificity of available data such as missing values, extreme values or outliers, creates a challenge to extract significant user models from an educational perspective. In this paper we introduce a pattern detection mechanism with-in our data analytics tool based on k-means clustering and on SSE, silhouette, Dunn index and Xi-Beni index quality metrics. Experiments performed on a dataset obtained from our online e-learning platform show that the extracted interaction patterns were representative in classifying learners. Furthermore, the performed monitoring activities created a strong basis for generating automatic feedback to learners in terms of their course participation, while relying on their previous performance. In addition, our analysis introduces automatic triggers that highlight learners who will potentially fail the course, enabling tutors to take timely actions.
|Title of host publication||Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2016|
|Editors||Christo Dichev, Gennady Agre|
|Publication status||Published - 18 Aug 2016|
|Event||International Conference on Artificial Intelligence: Methodology, Systems, and Applications: Artificial Intelligence: Methodology, Systems, and Applications - Varna, Bulgaria|
Duration: 7 Sept 2016 → 10 Sept 2016
|Series||Lecture Notes in Computer Science|
|Series||Lecture Notes in Artificial Intelligence (subseries)|
|Conference||International Conference on Artificial Intelligence: Methodology, Systems, and Applications|
|Abbreviated title||AIMSA 2016|
|Period||7/09/16 → 10/09/16|
- clustering quality metrics
- pattern extraction
- k-means clustering
- learner performance
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- 1 Finished
Rage: Realising an Applied Gaming Eco-system
Westera, W., Georgiadis, K., Saveski, G., van Lankveld, G., Bahreini, K., van der Vegt, W., Berkhout, J., Nyamsuren, E., Kluijfhout, E. & Nadolski, R.
1/02/15 → 31/07/19