NC State University researchers are applying data mining techniques to analyze the effectiveness of — and make real-time improvements to — educational games. They’re creating software tools that use real-time data to assess how well students develop collaborative problem-solving skills (CPS). These algorithm-based tools can enable educational games to be more responsive and effective for learning.
The software uses constraint-based pattern mining algorithms to assess and predict learning outcomes — techniques that have yet to be applied widely in an educational context.
“One of the attractive things about this framework is that it can evolve as more students play the game and the software has more data to draw on,” says Wookhee Min, co-author of a paper on the work and a senior research scientist at NC State. “In theory, that should allow us to fine-tune in-game interventions in order to improve learning outcomes even more.”
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