@article{oai:n-seiryo.repo.nii.ac.jp:00001898,
 author = {塚本, 英邦 and 南雲, 秀雄 and 門田, 暁人 and 松本, 健一 and Tsukamoto, Hidekuni@@@Nagumo  Hideo@@@Monden  Akito@@@Matsumoto  Ken-ichi},
 issue = {4},
 journal = {日本産業技術教育学会誌},
 month = {Dec},
 note = {application/pdf, 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., 本研究では、プログラミング教育における教材の改善手法を提案し、その効果を評価する。本手法は、学習者のモチベーションを定量的に測定し、ARCS動機づけ方略と統計的検定に基づいてプログラミング教材の改善を行う。具体的には、学習者のモチベーションを、ARCSアンケートによって測定し、統計的に有意な減少が生じる授業毎の下位カテゴリーを特定する。その下位カテゴリーに対応するモチベーションを向上させる方略を、ARCS動機づけモデルの“動機づけ方略”における方略見本から選択する。方略見本に基づいて教材の改善要素を設定し、プログラミング教材の改善を行う。ケーススタディとして、本手法によって5つの改善要素を設定して教材改善を行ってプログラミング教育を試行し、特徴的な3つの改善要素における教材改善の効果を検討する。},
 pages = {73--82},
 title = {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},
 volume = {55},
 year = {2013}
}