Extending multiple choice questions for instructor-authored mobile practice application

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By taking advantage of today's technology-aware student population, Mathtoons products improve students' performance by increasing their engagement. They use gamification of repetitive exercises to provide much needed practice. Due to the large number of students taking calculus courses, the focus has been mostly on calculus content but the technology has much wider applications. The present project goal is to use Mathtoons' technology to build an educational data mining platform for a parallel computing course. Computer science instructors are well aware that concurrent programming is a challenging topic to learn. Reusing a parallel computing simulator that was enhanced to provide automatic feedback to students, the project aims at developing a platform that will record student numerous attempts at solving classical concurrent programming problems. An analysis of the results will provide different levels of insights into the student performance. Data visualization techniques and statistical analysis will allow the instructor to offer the appropriate additional material to the right category of students e.g. student at risk will receive additional pedagogical support, overachievers will receive bonus questions, social learners will be introduced to fellow students, etc. Taking advantage of Mathtoons expertise, the platform will provide hints when students are struggling. It will also improve the feedback students receive by suggesting improvements to simplify their solution instead of providing a true or false answer. Finally, the platform will implement an automatic plagiarism detection mechanism that will be used to educate students on plagiarism and intellectual property. Moreover, it will also allow for the automatic detection of student collaborations, which will be used to further boost social learners. The platform data science approach will provide a scientific rationale to justify pedagogical methods, and will form a promising research platform.