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Curricular Concept Maps as Structured Learning Diaries: Collecting Data on Self-Regulated Learning and Conceptual Thinking for Learning Analytics Applications
Author(s) -
Ville Kivimäki,
Joonas Pesonen,
Jani Romanoff,
Heikki Remes,
Petri Ihantola
Publication year - 2019
Publication title -
journal of learning analytics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.084
H-Index - 7
ISSN - 1929-7750
DOI - 10.18608/jla.2019.63.13
Subject(s) - learning analytics , artifact (error) , computer science , data science , learning sciences , educational technology , curriculum , analytics , mathematics education , data analysis , data collection , concept map , psychology , artificial intelligence , pedagogy , data mining , sociology , social science
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.

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