In this research, a statistical remediation method for teaching materials in programming education has been proposed, and its effects have been evaluated. In this method, the teaching materials are systematically improved upon through quantitative measurements and analyses of the motivation of students so that a distinct improvement can be measured irrespsctive of the knowledge and experience of the teachers. Specifically, the motivation score of the students for each of the 12 subcategories of the ARCS motivation model was measured in each lesson, and the subcategory of a particular lesson in which the score decreased significantly from a previous one was identified. The remediation strategies corresponding to these subcategories were then looked up on lists of “motivation strategies” in the ARCS model, and are used to improve upon the teaching materials. By applying this method to a programming coures, five weak points in the teaching materials were indentified and they were subsequently improved upon by using remediation strategies. The effects of the remediation strategies have been confirmed in three of these weak areas of the subsequent programming course.
ARCS動機づけ方略と統計的検定に基づくプログラミング教材の改善とその評価
nsu2018034.pdf
(798.77KB)
機関リポジトリ概要