位于
情境学习
计算思维
心理学
数学教育
计算机科学
合作学习
教学方法
教育学
人工智能
作者
Ting‐Ting Wu,Jianming Chen
标识
DOI:10.1177/07356331211039961
摘要
Many countries have incorporated computational thinking (CT) and programming languages into their science and technology courses. Students can improve their CT ability by learning programming languages. Moreover, situated learning enables students to generate knowledge and master problem-solving skills through interaction with situations. This study incorporated Webduino learning and the situated learning strategy into a programming course and analyzed its impact on high school students’ CT ability, learning motivation, and course satisfaction. A quasi-experimental research method was adopted, wherein the experimental group was subjected to the situated learning strategy and the control group was subjected to a traditional teaching method. The study results revealed that integrating Webduino programming with situated learning could effectively improve five categories of CT skills; moreover, the activity models of situated learning enhanced the value and expectation dimensions of learning motivation. In addition, satisfaction with the course content and self-identity slightly improved. However, because teachers were required to elaborate on stories to promote learner engagement with life situations, the time available for programming was limited. Thus, no significant difference was observed in teaching satisfaction.
科研通智能强力驱动
Strongly Powered by AbleSci AI