Developing a Microanalytic Selfregulated Learning Assessment Protocol for Biomedical Science Learning

• Main Authors: Roghayeh Gandomkar (Author), Azim Mirzazadeh (Author), Ladan Fata (Author), Mohammad Jalili (Author), Kamran Yazdani (Author), Gholamreza Hassanzadeh (Author), John Sandars (Author)
• Format: Book
• Published: Kerman University of Medical Sciences, 2017-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2645-3452; 2645-3452
• Keywords: self; regulated learning; microanalytic assessment method; biomedical science learning; Education; L
• Source: Strides in Development of Medical Education, Vol 13, Iss 5, Pp 440-450 (2017)

Background & Objective: Selfregulated learning (SRL) is highly task and context dependent Microanalytic assessment method measures students SRL processes while performing a particular learning task The present study aimed to design a microanalytic SRL assessment protocol for biomedical science learning Methods: This mixed method study was conducted in Tehran University of Medical Sciences Iran in 2013 The data collection tool was a microanalytic SRL assessment protocol that was designed based on the literature review expert opinion and cognitive interview with medical students and then piloted The participants consisted of 13 second year medical students The subjects were interviewed while conducting a biomedical science learning task Interviews were recorded transcribed and coded based on a predetermined coding framework Descriptive statistics were used to analyze the data Results: The microanalytic SRL assessment protocol was developed in three parts; interview guide coding framework and biomedical science learning task An interview guide was designed consisting of 6 openended questions aimed at assessing 5 SRL subprocesses of goal setting strategic planning metacognitive monitoring causal attribution and adaptive inferences and a closeended question regarding selfefficacy Based on the pilot study most participants reported taskspecific and taskgeneral processes for the subprocesses of strategic planning (92%) metacognitive monitoring (77%) causal attribution (85%) and adaptive inferences (92%) Conclusion: The developed protocol could capture the finegrained nature of the selfregulatory subprocesses of medical students for biomedical science learning Therefore it has the potential application of modifying SRL processes in early years of medical school