| 言語種別 | 英語 |
|---|---|
| 発行・発表の年月 | 2023/09/14 |
| 形態種別 | 学術研究論文 |
| 査読 | 査読あり |
| 標題 | Estimating Learning Task Duration: Modelling Within an Intentional Activity Framework |
| 執筆形態 | 単著 |
| 掲載誌名 | International Journal of Emerging Technologies in Education |
| 掲載区分 | 国外 |
| 出版社・発行元 | International Association of Online Engineering |
| 巻・号・頁 | 18(17),136-152 |
| 総ページ数 | 16 |
| 担当区分 | 筆頭著者 , 最終著者 , 責任著者 |
| 著者・共著者 | Jason Byrne ◎ |
| 概要 | This paper investigates the problem of estimating optimal task duration. The study specifically focused on e-learning, higher education, language learning and self-study contexts. The problem of duration was approached through secondary analysis that made use of an intentional activity framework. The model uses six basic building blocks to enable the timing of any given intentional learning task. It will provide organisational clarity to conference presenters, EdTech developers, lecturers, materials designers, and teachers. It can help to predict the phase in the lecture or lesson cycle when well-intentioned learners go off task. The study supports both the six-minute e-learning video rule and the ten-minute rule for lectures, providing insight as to why these rules generally seem to be effective. |