How preparation-for-learning with a worked versus an open inventing problem affect subsequent learning processes in pre-service teachers

Instructional Science(2022)

引用 4|浏览14
暂无评分
摘要
A worked-out or an open inventing problem with contrasting cases can prepare learners for learning from subsequent instruction differently regarding motivation and cognition. In addition, such activities potentially initiate different learning processes during the subsequent (“future”) learning phase. In this experiment ( N = 45 pre-service teachers), we aimed to replicate effects of earlier studies on learning outcomes and, on this basis, to analyze respective learning processes during the future-learning phase via think-aloud protocols. The inventing group invented criteria to assess learning strategies in learning journals while the worked-example group studied the same problem in a solved version. Afterwards, the pre-service teachers thought aloud during learning in a computer-based learning environment. We did not find substantial motivational differences (interest, self-efficacy), but the worked-example group clearly outperformed their counterparts in transfer ( BF +0 > 313). We found moderate evidence for the hypothesis that their learning processes during the subsequent learning phase was deepened: the example group showed more elaborative processes, more spontaneous application of the canonical, but also of sub-optimal solutions than the inventing group ( BF s around 4), and it tended to focus more on the most relevant learning contents. Explorative analyses suggest that applying canonical solutions to examples is one of the processes explaining why working through the solution leads to higher transfer. In conclusion, a worked-out inventing problem seems to prepare future learning more effectively than an open inventing activity by deepening and focusing subsequent learning processes.
更多
查看译文
关键词
Invention as preparation for learning,Worked example,Teacher education,Assessment of learning strategies,Think-aloud,Learning processes
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