Process analysis of teachers’ self-regulated learning patterns in technological pedagogical content knowledge development

Highlights

• Teachers' self-regulated learning has a predictable effect on learning about technological pedagogical content knowledge.

• This study identified diverse patterns relating to teachers' SRL in response to the levels of TPACK achievements.

• High TPACK performers are more goal-oriented, engaging more in monitoring, and perform more iterative in SRL processes.

• Lower performers only partially engaged in SRL while learning about TPACK.

Abstract

Self-regulated learning (SRL) has a predictable and instrumental effect on learning complicated knowledge. This study investigates the role of SRL in acquiring technological pedagogical content knowledge (TPACK), an important aspect of teachers' effective technology use. The present study identified several regulatory procedural patterns used by teachers in the context of their TPACK achievements. A computer-based context, nBrowser, was used to facilitate teachers lesson planning around technology usage. Teachers log file data were analyzed using process mining approaches. Findings indicate that high TPACK performers are more likely to perform self-regulative activities (e.g., monitoring) in developing TPACK compared to the low performers. Higher TPACK performers are more goal-oriented, demonstrate more monitoring and are more iterative in using all SRL processes in contrast to low performers who only partially regulate their problem solving. Such findings support previous research. This study adopts a novel approach for understanding the relations between SRL and TPACK. It offers opportunities to examine how teachers enact SRL as they move from the beginning to later stages of designing lessons and provides insights to researchers who study SRL in TPACK domains. Furthermore, the findings can assist educational designers in developing interventions for promoting TPACK development by concentrating on teachers’ SRL abilities.

Introduction

Self-regulated learning (SRL) is an essential concept in the field of educational psychology. The notion is derived from research on metacognition and discusses how learners deploy metacognitive knowledge and skills to monitor and regulate their cognitive, motivational, and behavioral processes in learning (Pintrich, 2000; Winne & Hadwin, 1998). SRL has a pervasive, predictable, and instrumental effect on learning. Successful SRL enables students to engage in a recursive cycle of analyzing task conditions, constructing goals, monitoring learning strategies, and evaluating the effectiveness of the strategies (Azevedo & Cromley, 2004; Mega et al., 2014). However, dysregulation hampers learning, including failures to update one's standards and adapt to the demands of the task, deploy effective strategies, as well as make accurate judgments of one's progress (Azevedo & Feyzi-Behnagh, 2011). Such findings have been documented in research conducted across disciplines such as science (Deekens, Greene, & Lobczowski, 2018), mathematics (Kramarski & Friedman, 2014), medicine (Lajoie, Poitras, Doleck, & Jarrell, 2014), and psychology (Sonnenberg & Bannert, 2015).

In the context of teacher technology education, technological pedagogical content knowledge (TPACK, Mishra & Koehler, 2006) plays a crucial role in teachers' effective uses of educational technology for teaching. It serves as a heuristic conceptual framework instructing teachers on how to combine their extensive technological knowledge with their content and pedagogical knowledge in an effort to make abstract subject topics more concrete and to assist students in constructing new knowledge (Mishra & Koehler, 2006). However, developing TPACK is complex in that teachers need to consider students’ specific needs as well as the constraints of learning contexts when performing technology-integrated practices (Angeli & Valanides, 2009).

Investigations into the relations between SRL and learning in TPACK commences with Kramarski et al.’s (2009, 2010) study wherein three metacognitive prompts were provided to student teachers during different phases of learning TPACK in a web-based context. Their findings demonstrate that participants obtained higher TPACK comprehension and performance of lesson design with SRL scaffolds in the planning and evaluation phases. In a study of TPACK in secondary in-service teachers Chen and Jiang (2019) found that teachers' SRL capacities play a different role in building TPACK, with planning capacity as the factor that exerts an exceptional influence. Poitras (Poitras, Doleck, Huang, Li, & Lajoie, 2017; Poitras & Fazeli, 2016)) contributes to this field of research by including a computer-based learning environment (CBLE) that is designed to facilitate teachers' SRL and TPACK. Poitras, Fazeli, and Mayne (2018) built a structural model to test several information seeking and acquisition behaviours (e.g., site visits using a CBLE), as predictors for TPACK, assuming that teachers who regulated their information seeking and acquisition behaviours could result in better TPACK performance. Another study using this CBLE analyzed preservice teachers' lesson plans and corroborates the arguments that teachers with high SRL abilities outperform those with lower SRL in terms of TPACK achievements (Huang, Li, Poitras, & Lajoie, 2020). Despite significant findings, further examinations of the relations between SRL and TPACK are needed.

There is necessity to probe further into teachers' self-regulatory processes to establish a sound understanding of the relations between SRL and TPACK. The underlying assumption is that SRL is temporal and dynamic in the way it changes over time and in different contexts (Taub, Azevedo, & Mudrick, 2018). Deeper insight into how SRL is performed can provide opportunities to explain why teachers succeed or fail in learning about TPACK. Studies looking into teachers' SRL processes in TPACK is still somewhat limited in the existing literature. Accordingly, the present study aims to fill this gap through modeling teachers' self-regulatory processes as they conduct a technology-infused task and will present inferences about the relations between SRL and TPACK temporally. The findings will provide insights as to how teachers enact SRL as they move from the beginning to later stages of designing lessons and provides insights to researchers who study SRL in TPACK domains. Furthermore, the findings can assist educational designers in developing interventions for promoting TPACK development by concentrating on teachers’ SRL abilities.