Improving student inclusion through learning analytics

At the Utrecht University of Applied Sciences, students from a non-standard background often have deficiencies in their mathematics/physics/engineering skills. To improve inclusiveness, a practice support
app called Step-Wise has been set up that automatically detects these deficiencies and advises studentson which skills to practice. Through student interviews using the CIMO-logic, it has been established
that this app mainly improves the effectiveness of practice, although it also has a beneficial effect on theamount of exercises practiced and on the student motivation.

Licence: Creative Commons Attribution 4.0 International

Keywords: Inclusion, Learning analytics, Bayesian user modeling, Engineering education


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