Improve learning retention, self-efficacy, learning attitude and problem-solving skills through e-books based on sequential multi-level prompting strategies

EDUCATION AND INFORMATION TECHNOLOGIES(2024)

引用 1|浏览0
暂无评分
摘要
Health education aims to change unhealthy behaviors and promote population health. However, limited teaching time and standardized materials pose challenges, prompting elementary school teachers to explore technology-enhanced teaching strategies. To cultivate proper health attitudes and behaviors among elementary school students, many researchers have widely used e-books to teach health education-related courses. Many studies have proven interactive e-books to be effective in aiding both teaching and learning. However, despite the continuous innovation of e-books in educational applications, the long-term effects of e-books have yet to be investigated, since learning memory only responds to short-term memory effects. Therefore, this study attempts to develop a sequential multi-level prompting strategy for e-book learning in a mobile learning environment for tablet computers. Students from two primary school classes were recruited for the empirical study. The experimental group used a sequential multi-level, prompting-based e-book to learn, while the control group used a conventional e-book learning approach. According to the study's results, the proposed learning strategies were found to improve the learning achievement of primary school students for cardiovascular disease, guide students in building knowledge, develop thinking and problem-solving skills, and help students transform their learning from short-term to long-term memory through post-testing of problem-solving delays. It is certain that sequential multi-level prompting strategies can help younger learners better understand and remember learning content and apply the knowledge they have gained to develop correct health attitudes.
更多
查看译文
关键词
Sequential multi-level promoting strategy,e-book,Learning retention,Self-efficacy,Learning attitude,Problem-solving skills
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要