Frontline Learning Research (FLR) welcomes risk-taking and explorative studies that provide input for theoretical, empirical and/or methodological renewal within the field of research on learning and instruction. The journal offers a distinctive opening for foundational research and an arena for studies that promote new ideas, methodologies or discoveries. Read about what is frontline under Aims and scope

ISSN 2295-3159

Introduction to Vol. 11 No. 2 (2023)

2024-01-11

Dear reader,

I am happy to announce that a new issue of Frontline Learning Research was published just before the turn of the year. It contains four articles, centering on educational research innovation with eye-tracking and the investigation of learner agency and of learning analytics dashboards’ support of self-regulated learning.

Boels and colleagues investigate the overall research question: In what way do secondary school students’ histogram interpretations change after solving dotplot items? This question is motivated by literature within statistics education which documents student challenges in interpreting histograms, and previous research indicating the scaffolding effect of dotplot tasks. Novel in the authors’ study is the use of eye-tracking data as input for training a machine learning algorithm, which can then distinguish between students’ gaze data belonging to items before the dotplot tasks and after. Differences in gaze patterns indicate changes in students’ learning strategies.

The position paper by John and Mitra develops a new pedagogical use of eye-tracking data, focusing on learner interpretation of the eye movements made by a previous problem solver (the model). The authors extend previous research on guiding learners’ attention through gaze data, as they concentrate on affordances for supporting learners’ interpretation of the model problem solver’s reasoning process. An illustrative example from chemistry, concerning a spectral graph problem, is provided. Possibilities and constraints of the approach within various fields that require visual representations for problem solving are discussed.

Soini and colleagues explore how students grade 1-9 perceive their learning agency, and how this perception relates to teacher and peer support. Learning agency is investigated as embodied in meaning making, seeking scaffolding and problem solving. The authors develop and test a structural equation model, focusing on these elements, as well as gender and socio-economic status. Their findings show differences in learner agency in terms of grade level, gender and socio-economic status, and complex interrelations between social support and the elements of learning agency.

Silvola and colleagues report from a study concerning student evaluations of how learning analytics dashboards can support their self-regulated learning, specifically their study planning and monitoring. The authors investigate how students’ self-efficacy beliefs and resource management strategies are associated with their experiences of support versus challenges posed by the learning analytics dashboards. Findings indicate that different dashboard designs support different aspects of study planning and monitoring, and that the benefit provided by a specific design is influenced by students’ self-efficacy beliefs and help-seeking skills.
 
The full issue is found here.
 
With the warmest wishes for the new year,

Professor, Dr. Nina Bonderup Dohn
Editor-in-Chief, Frontline Learning Research

Vol. 12 No. 1 (2024): Frontline Learning Research

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