scholarly journals Using multiple self‐regulated learning measures to understand medical students' biomedical science learning

2020 ◽  
Vol 54 (8) ◽  
pp. 727-737 ◽  
Author(s):  
Roghayeh Gandomkar ◽  
Kamran Yazdani ◽  
Ladan Fata ◽  
Ramin Mehrdad ◽  
Azim Mirzazadeh ◽  
...  
Keyword(s):  
Medical Students ◽  
Science Learning ◽  
Biomedical Science ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Learning Measures

scholarly journals Relationships between medical students’ co-regulatory network characteristics and self-regulated learning: a social network study

2021 ◽  
Author(s):  
Derk Bransen ◽  
Marjan J. B. Govaerts ◽  
Dominique M. A. Sluijsmans ◽  
Jeroen Donkers ◽  
Piet G. C. Van den Bossche ◽  
...  
Keyword(s):  
Social Network ◽  
Medical Students ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Learning Opportunities ◽  
Network Size ◽  
Tie Strength ◽  
Network Characteristics ◽  
Self Regulated Learning ◽  
Regulated Learning

Abstract Introduction Recent conceptualizations of self-regulated learning acknowledge the importance of co-regulation, i.e., students’ interactions with others in their networks to support self-regulation. Using a social network approach, the aim of this study is to explore relationships between characteristics of medical students’ co-regulatory networks, perceived learning opportunities, and self-regulated learning. Methods The authors surveyed 403 undergraduate medical students during their clinical clerkships (response rate 65.5%). Using multiple regression analysis, structural equation modelling techniques, and analysis of variance, the authors explored relationships between co-regulatory network characteristics (network size, network diversity, and interaction frequency), students’ perceptions of learning opportunities in the workplace setting, and self-reported self-regulated learning. Results Across all clerkships, data showed positive relationships between tie strength and self-regulated learning (β = 0.095, p < 0.05) and between network size and tie strength (β = 0.530, p < 0.001), and a negative relationship between network diversity and tie strength (β = −0.474, p < 0.001). Students’ perceptions of learning opportunities showed positive relationships with both self-regulated learning (β = 0.295, p < 0.001) and co-regulatory network size (β = 0.134, p < 0.01). Characteristics of clerkship contexts influenced both co-regulatory network characteristics (size and tie strength) and relationships between network characteristics, self-regulated learning, and students’ perceptions of learning opportunities. Discussion The present study reinforces the importance of co-regulatory networks for medical students’ self-regulated learning during clinical clerkships. Findings imply that supporting development of strong networks aimed at frequent co-regulatory interactions may enhance medical students’ self-regulated learning in challenging clinical learning environments. Social network approaches offer promising ways of further understanding and conceptualising self- and co-regulated learning in clinical workplaces.

DEVELOPMENT OF A QUESTIONNAIRE TO MEASURE CO-REGULATED LEARNING STRATEGIES DURING COLLABORATIVE SCIENCE LEARNING

2016 ◽  
Vol 15 (1) ◽  
pp. 68-78
Author(s):  
Eunice Eyitayo Olakanmi
Keyword(s):  
Learning Strategies ◽  
Help Seeking ◽  
Science Learning ◽  
Science Students ◽  
Validity And Reliability ◽  
Self Regulated Learning ◽  
Reliable Instrument ◽  
Regulated Learning ◽  
Help Giving ◽  
Effective Instrument

The purpose of this research was to develop a questionnaire that measures students’ self and co-regulated learning processes during science learning. An instrument named Co-regulated Strategies for Learning Questionnaire (CRSLQ) was developed, and its validity and reliability were analysed. Factor analytic evidence from a sample (n=214) of science students indicated that the 21 items CRSLQ consists of four constructs: monitoring, help-seeking and help-giving, efforts regulation, and planning. Cronbach’s Alpha (α) coefficients were calculated for the reliability of CRSLQ scales which ranged from 0.87 to 0.92 and 0.95 for the entire questionnaire. Additional analysis with a second sample (n=40) showed that CRSLQ was an effective instrument for measuring co-regulated learning strategies during collaborative science learning. According to these results, the CRSLQ can be used as a valid and reliable instrument in science education. Key words: collaborative learning, co-regulated learning, efforts regulation, help-seeking and help-giving, monitoring, planning, science learning, self-regulated learning.

scholarly journals Nomograms Predicting Self-Regulated Learning Levels in Chinese Undergraduate Medical Students

2020 ◽  
Vol 10 ◽  
Author(s):  
Jun Yang ◽  
Guoyang Zhang ◽  
Runzhi Huang ◽  
Penghui Yan ◽  
Peng Hu ◽  
...  
Keyword(s):  
Medical Students ◽  
Undergraduate Medical Students ◽  
Self Regulated Learning ◽  
Regulated Learning

scholarly journals Influences on medical students’ self-regulated learning after test completion

2012 ◽  
Vol 46 (3) ◽  
pp. 326-335 ◽  
Author(s):  
Sacha Agrawal ◽  
Geoffrey R Norman ◽  
Kevin W Eva
Keyword(s):  
Medical Students ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Test Completion

Self-regulated learning processes of medical students during an academic learning task

2016 ◽  
Vol 50 (10) ◽  
pp. 1065-1074 ◽  
Author(s):  
Roghayeh Gandomkar ◽  
Azim Mirzazadeh ◽  
Mohammad Jalili ◽  
Kamran Yazdani ◽  
Ladan Fata ◽  
...  
Keyword(s):  
Medical Students ◽  
Learning Task ◽  
Learning Processes ◽  
Academic Learning ◽  
Self Regulated Learning ◽  
Regulated Learning
Sign in / Sign up

Export Citation Format

Share Document