Curricular Concept Maps as Structured Learning Diaries: Collecting Data on Self-Regulated Learning and Conceptual Thinking for Learning Analytics Applications

V. Kivimäki, Joonas A. Pesonen, J. Romanoff, H. Remes, Petri Ihantola
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引用次数: 8

Abstract

The collection and selection of the data used in learning analytics applications deserve more attention. Optimally, selection of data should be guided by pedagogical purposes instead of data availability. Using design science research methodology, we designed an artifact to collect time-series data on students’ self-regulated learning and conceptual thinking. Our artifact combines curriculum data, concept mapping, and structured learning diaries. We evaluated the artifact in a case study, verifying that it provides relevant data, requires a limited amount of effort from students, and works in different educational contexts. Combined with learning analytics applications and interventions, our artifact provides possibilities to add value for students, teachers, and academic leaders.
作为结构化学习日记的课程概念图:收集自我调节学习的数据和学习分析应用的概念思维
学习分析应用中使用的数据的收集和选择值得更多的关注。最理想的情况是,数据的选择应以教学目的为指导,而不是以数据的可用性为指导。采用设计科学的研究方法,设计了一个人工工具来收集学生自主学习和概念思维的时间序列数据。我们的工件结合了课程数据、概念映射和结构化的学习日记。我们在一个案例研究中评估了工件,验证它提供了相关的数据,需要学生付出有限的努力,并且在不同的教育环境中工作。结合学习分析应用程序和干预,我们的工件为学生、教师和学术领导者提供了增加价值的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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