Analytics of learning tactics and strategies in an online learnersourcing environment

JOURNAL OF COMPUTER ASSISTED LEARNING(2023)

引用 2|浏览15
暂无评分
摘要
Background The use of crowdsourcing in a pedagogically supported form to partner with learners in developing novel content is emerging as a viable approach for engaging students in higher-order learning at scale. However, how students behave in this form of crowdsourcing, referred to as learnersourcing, is still insufficiently explored. Objectives To contribute to filling this gap, this study explores how students engage with learnersourcing tasks across a range of course and assessment designs. Methods We conducted an exploratory study on trace data of 1279 students across three courses, originating from the use of a learnersourcing environment under different assessment designs. We employed a new methodology from the learning analytics (LA) field that aims to represent students' behaviour through two theoretically-derived latent constructs: learning tactics and the learning strategies built upon them. Results The study's results demonstrate students use different tactics and strategies, highlight the association of learnersourcing contexts with the identified learning tactics and strategies, indicate a significant association between the strategies and performance and contribute to the employed method's generalisability by applying it to a new context. Implications This study provides an example of how learning analytics methods can be employed towards the development of effective learnersourcing systems and, more broadly, technological educational solutions that support learner-centred and data-driven learning at scale. Findings should inform best practices for integrating learnersourcing activities into course design and shed light on the relevance of tactics and strategies to support teachers in making informed pedagogical decisions.
更多
查看译文
关键词
artificial intelligence in education,learnersourcing,learning analytics,learning strategies,learning tactics,self-regulated learning
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