Resident learning trajectories in the workplace: A self‐regulated learning analysis

2020 ◽  
Vol 54 (12) ◽  
pp. 1120-1128
Author(s):  
Ryan Brydges ◽  
Judy Tran ◽  
Alberto Goffi ◽  
Christie Lee ◽  
Daniel Miller ◽  
...  
Keyword(s):  
Learning Trajectories ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Resident Learning ◽  
Learning Analysis

scholarly journals Understanding, evaluating, and supporting self-regulated learning using learning analytics

2015 ◽  
Vol 2 (1) ◽  
pp. 7-12 ◽  
Author(s):  
Ido Roll ◽  
Philip H. Winne
Keyword(s):  
Learning Environments ◽  
Learning Analytics ◽  
Special Section ◽  
Interactive Learning Environments ◽  
Learning Trajectories ◽  
Self Regulated Learning ◽  
Current State ◽  
Regulated Learning ◽  
State Of Research ◽  
Single Snapshot

Self-regulated learning is an ongoing process rather than a single snapshot in time. Naturally, the field of learning analytics, focusing on interactions and learning trajectories, offers exciting opportunities for analyzing and supporting self-regulated learning. This special section highlights the current state of research in the intersect of self-regulated learning and learning analytics, bridging communities, disciplines, and schools of thoughts. In this editorial, we introduce the papers and identify themes and challenges in understanding and support self-regulated learning in interactive learning environments.

Development of the Teacher Attitudes Towards Self-Regulated Learning Scale

2018 ◽  
Vol 34 (3) ◽  
pp. 193-205 ◽  
Author(s):  
Julia Steinbach ◽  
Heidrun Stoeger
Keyword(s):  
Factor Analysis ◽  
Primary School ◽  
Factor Structure ◽  
Concurrent Validity ◽  
Binary Logistic Regression ◽  
Affective Component ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Teachers Attitudes ◽  
Development And Validation

Abstract. We describe the development and validation of an instrument for measuring the affective component of primary school teachers’ attitudes towards self-regulated learning. The questionnaire assesses the affective component towards those cognitive and metacognitive strategies that are especially effective in primary school. In a first study (n = 230), the factor structure was verified via an exploratory factor analysis. A confirmatory factor analysis with data from a second study (n = 400) indicated that the theoretical factor structure is appropriate. A comparison with four alternative models identified the theoretically derived factor structure as the most appropriate. Concurrent validity was demonstrated by correlations with a scale that measures the degree to which teachers create learning environments that enable students to self-regulate their learning. Retrospective validity was demonstrated by correlations with a scale that measures teachers’ experiences with self-regulated learning. In a third study (n = 47), the scale’s concurrent validity was tested with scales measuring teachers’ evaluation of the desirability of different aspects of self-regulated learning in class. Additionally, predictive validity was demonstrated via a binary logistic regression, with teachers attitudes as predictor on their registration for a workshop on self-regulated learning and their willingness to implement a seven-week training program on self-regulated learning.

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