Toward Finding and Supporting Struggling Students in a Programming Course with an Early Warning System
Belinda Schantong, Dominik Gorgosch, Janet Siegmund

TL;DR
This paper presents an early warning system for programming courses that predicts student success based on cognitive skill assessments and demonstrates that targeted drill-and-practice exercises can significantly improve learning outcomes.
Contribution
It introduces a practical early warning system using simple tests to identify at-risk students and shows the positive impact of syntax drill-and-practice exercises on skill acquisition.
Findings
Cognitive skills predict programming success to a certain extent.
Early mental model development and language skills are highly relevant.
Syntax drill-and-practice exercises significantly improve student success.
Abstract
Background: Programming skills are advantageous to navigate today's society, so it is important to teach them to students. However, failure rates for programming courses are high, and especially students who fall behind early in introductory programming courses tend to stay behind. Objective: To catch these students as early as possible, we aim to develop an early warning system, so we can offer the students support, for example, in the form of syntax drill-and-practice exercises. Method: To develop the early warning system, we assess different cognitive skills of students of an introductory programming course. On several points in time over the course, students complete tests that measure their ability to develop a mental model of programming, language skills, attention, and fluid intelligence. Then, we evaluated to what extent these skills predict whether students acquire programming…
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Taxonomy
TopicsTeaching and Learning Programming · Experimental Learning in Engineering · Educational Games and Gamification
