Professional development in self-regulated learning: Shifts and variations in teacher outcomes and approaches to implementation

2022 ◽  
Vol 111 ◽  
pp. 103619
Author(s):  
Timothy J. Cleary ◽  
Anastasia Kitsantas ◽  
Erin Peters-Burton ◽  
Angela Lui ◽  
Kim McLeod ◽  
...  
2015 ◽  
pp. 257-282
Author(s):  
Elena Ciga ◽  
Emma García ◽  
Mercedes I. Rueda ◽  
Harm Tillema ◽  
Emilio Sánchez

2021 ◽  
Vol 19 (1) ◽  
pp. 18-34
Author(s):  
Flavio Manganello ◽  
Francesca Pozzi ◽  
Marcello Passarelli ◽  
Donatella Persico ◽  
Francesca Maria Dagnino

This paper reports on usage and impact on learning achievements of a dashboard developed to help monitor self-regulated learning behaviours in an online professional development path. The design of the path as well as of the dashboard were grounded on a pre-existing conceptual framework distinguishing between four different types of self-regulated learning behaviours taking place in professional learning networks and underpinning professional practice sharing. One of the objectives of the path was to promote such behaviours among participants, and the dashboard was designed to support their self-monitoring. Data were collected through usage log files analysis, a survey, and pretest and posttest. The results shed light on participants' actual usage of the dashboard, their opinion regarding its usefulness in relation of its capability to measure and support their SRL processes, and the dashboard's actual impact on their learning achievements. Moreover, some limitations in the current configuration of the dashboard emerged, which can guide further development.


2016 ◽  
Author(s):  
Bodong Chen ◽  
Yizhou Fan ◽  
Guogang Zhang ◽  
Qiong Wang

The present study examines behavioral patterns, motivations, and self-regulated learning strategies of returning learners—a special learner subpopulation in massive open on- line courses (MOOCs). To this end, data were collected from a teacher professional development MOOC that has been offered for seven iterations during 2014–2016. Data analysis identified more than 15% of all registrants as re- turning learners. Findings from click log analysis identified possible motivations of re-enrollment including improv- ing grades, refreshing theoretical understanding, and solving practical problems. Further analysis uncovered evidence of self-regulated learning strategies among returning learners. Taken together, this study contributes to ongoing inquiry into learning pathways in MOOCs, offers insights for future MOOC design, and sheds light on the exploration of MOOCs as alternatives for teacher professional development.


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