ABSTRACT
Massive Open Online Courses (MOOCs) are platforms teachers can use to seek guidance on different strategies to update their teaching skills. This study finds the effectiveness of MOOCs in developing professional performance and skills of school teachers. It tries to show the extent to which school teachers can benefit from these courses and how they apply them in their practical teaching. A mixed-method sequential explanatory (following up the quantitative findings with qualitative ones) method by using multiple data sources, including the MOOC system’s log files, final grades and the discussion forum, with additional of face to face class snapshots was used. Some of the data were analysed using statistical, correlations and clustering models, with others coded in excel to develop different themes based on reported experiences. Results indicated how TPD core features uncover school teachers’ knowledge and skills level through their learning behaviour variables for the MOOC platform, which will help to transform their pedagogical and instructional approaches while shifting their classrooms into 21st Century classrooms. Generally, this study contributes fresh insights into the literature on the importance of MOOCs for teachers’ professional growth while sustaining their work and connections for networked learning. Implications for future studies are also discussed.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Funding
Notes on contributors
Carina Titus Swai
Carina Titus Swai is a currently a PhD Student at Central China Normal University under the Educational Technology Department. Her research interests focus on using MOOCs to improve school teachers’ teaching practices and delivery by effectively integrating SCT strategies within their face-to-face classrooms. She has written and published various papers based on these areas.
Qingtang Liu
Qingtang Liu received a PhD in communication and information systems from the Huazhong University of Science and Technology, Wuhan, China, in 2005. His research interests include online learning, Teachers Training, and artificial intelligence in education. He has published more than 30 academic papers in SCI and SSCI journals, such as Computers and Education, Interactive Learning Environment, and Knowledge-Based Systems.
Linjing Wu
Linjing Wu received her PhD degree from Central China Normal University in 2013. Her research interests include educational data mining, learning pedagogies and e-learning. She has published several academic papers in different reputable journals.