1 Introduction

Technological advances have revolutionized how people access and acquire knowledge in recent years. The ubiquity of the Internet affords access to online learning materials, artificial intelligence applications, and informative resources (Guo et al., 2023; Kim et al., 2020; Vidergor & Ben-Amram, 2020). Given this landscape, educators should continually enhance their professional expertise and commit themselves to lifelong learning. Teachers need to be equipped with extensive knowledge and self-regulated learning strategies to effectively navigate and make sense of a vast array of information (Organization for Economic Co-operation and Development, 2018). Previous research has shown that teachers’ self-regulated learning also played an essential role in their teaching and students’ learning (Harris et al., 2012; Uzuntiryaki-Kondakci et al., 2017). Teachers’ attitudes toward learning and capabilities could impact their instruction (Avalos, 2011; Gordon et al., 2007; Steinbach & Stoeger, 2016); thus, a self-regulated teacher could simultaneously elicit their students to become self-regulated learners.

The technological pedagogical content knowledge (TPACK) framework helps understand teachers’ knowledge and skills to integrate technology effectively into their teaching (Mishra & Koehler, 2006). TPACK highlights the importance of not just understanding technology tools but also how to use them in a way that is pedagogically sound and aligned with the subject matter being taught. Teachers who are skilled in SRL should effectively plan and set goals for their teaching practices, determining how and when to integrate technology and SRL strategies into the curriculum; moreover, they tend to monitor and evaluate the effectiveness of their TPACK-driven teaching practices, self-assessing whether their use of technology and SRL strategies are effectively promoting student learning and engagement, and make necessary adjustments to achieve learning objectives better (Butler et al., 2004; Eekelen et al., 2005; Peeters et al., 2014). Fostering teachers’ SRL practices, particularly within the context of the TPACK framework, could not only enhance their instructional capabilities but also promote the incorporation of SRL strategies in their teaching; in turn, it cultivates a conducive environment for students to become self-regulated learners themselves, facilitating a transformative educational experience empowered by technology and SRL principles (Hattie, 2012). To sum up, exploring the interplay between teachers’ SRL and their proficiency in the TPACK was pivotal, as self-regulation could foster the enhancement of contents, pedagogies, and integration of technology, thereby shaping teachers’ professional development and cultivating an enriching learning environment.

Although existing research has found that the application of SRL strategies in teacher education effectively enhances teachers’ TPACK and promotes teacher SRL (Huang & Lajoie, 2021; Kramarski & Michalsky, 2010; Tantrarungroj & Suwannatthachote, 2013), a detailed understanding of the interplay between these components remained unexplored. Addressing this gap is essential for optimizing teacher education and technology-enhanced learning environments in the digital era. This study investigated teacher perceptions through open-ended responses and a Likert-scale questionnaire. To capture the nuanced evidence of how teachers perceived teaching science with technology-enhanced SRL strategies, we employed path analysis to figure out the relationships between TPACK and SRL, and thematic analysis to identify teachers’ perceptions. We discussed the association between quantitative and qualitative findings. By implementing a practical and authentic course, this study demonstrated to teachers, through a workshop, how to integrate SRL strategies with technological tools in science teaching, which is suitable to address teachers’ professional development of TPACK (Jimoyiannis, 2010). That is, the workshop enabled teachers to experience firsthand the integration of SRL strategies with technological aids. This study aims to delve into this underexplored domain, offering a comprehensive examination of how teachers’ engagement with SRL strategies perceive TPACK development. In this light, this study pivots on the following questions:

  1. 1.

    What is the relationship between teachers’ self-reported SRL and TPACK?

  2. 2.

    How do teachers perceive technology-enhanced instruction and self-regulated learning before and after the workshop?

1.1 Self-regulated learning

SRL is a critical theoretical framework that comprises cognitive, metacognitive, motivational, and emotional components of the learning process (Panadero, 2017). From a cognitive perspective, Zimmerman (1986) considered how cognitive functions, like perception, memory, and reasoning, contribute to learning. On the other hand, Pintrich (1999) focused on the role of drive and desire in guiding the learning process. These SRL models emphasize how self-awareness is pivotal in successful learning regulation. When educators apply these SRL strategies to their teaching practices, they enhance their pedagogical effectiveness and model self-regulated learning behaviors to their students. Teachers can promote their instruction and empower students to take charge of their learning, helping them become more active, engaged, and successful learners. For instance, self-regulation ability benefit from instructor who employed well-structured SRL strategies, such as prompts (Xu et al., 2023), self-assessment (Panadero et al., 2023; Sui et al., 2024), peer-assessment (Pantiwati & Husamah, 2017).

Based on Vygotsky’s theory, Manning and Payne’s (1993) view of SRL teachers emphasized the active role teachers play in managing their learning and teaching process, highlighting the idea of teachers as decision-makers, reflective practitioners, and independent learners who learn from their own teaching experiences. Manning and Payne described three critical characteristics of SRL teachers: high levels of cognitive and affective functioning, proactive teaching based on metacognitive thought processes, and continuing construction of knowledge during the teacher preparation and classroom teaching phases. Self-regulated teachers strategically set teaching and learning goals, plan suitable course activities, implement effective instructional strategies, and regularly monitor and evaluate their teaching effectiveness, making revisions as needed (Eekelen et al., 2005; Huang et al., 2020). Educators have honed their skills to learn from their teaching experiences effectively and are expected to employ strategies similar to SRL, just like their students. These strategies might include seeking guidance from mentors, actively soliciting student feedback, and searching for resources that foster ongoing professional development (Butler et al., 2004; Peeters et al., 2014). Teachers who demonstrate autonomy are acutely aware of why, when, where, and how they can acquire and apply pedagogical knowledge and skills in their classrooms. Autonomous teachers strongly believe in the power of SRL and apply a mastery goal orientation in their classrooms, thereby fostering an environment conducive to developing students’ SRL skills (Gordon et al., 2007; Hattie, 2012). To sum up, self-regulated teachers play a crucial role in effective pedagogy and have extensive potential to build their TPACK.

1.2 Technological pedagogical content knowledge and its training

Shulman (1986) developed the concept of pedagogical content knowledge (PCK) to understand the unique knowledge and skills teachers need to teach effectively. Based on the construct of PCK, the theoretical framework of TPACK has been established (Mishra & Koehler, 2006). Mishra and Koehler (2006) integrated teacher needs of technical knowledge into the framework, which were depicted as follows: (1) technological knowledge (TK): knowledge of using technology tools, (2) pedagogical knowledge (PK): knowledge of teaching and learning methods, (3) content knowledge (CK): knowledge of the subject matter, (4) technological content knowledge (TCK): knowledge of how subject matter can represent with technology, (5) technological pedagogical knowledge (TPK): knowledge of how to use the technology of implementing different teaching methods, (6) pedagogical content knowledge (PCK): knowledge of how subject matter content can be taught in an appropriate method, and (7) technological pedagogical content knowledge (TPACK): knowledge of how teachers use technology to implement effective teaching methods for different types of subject matter content. Theoretically, teachers’ expertise in information communications and technology (ICT) was found to be overlapped in line with Mishra and Koehler’s (2006) contention. Researchers have developed and validated TPACK questionnaires encompassing varying TPACK subcomponents (Chai et al., 2011; Jang & Tsai, 2013; Koh et al., 2010). Since these fifteen years, the TPACK framework has been widely studied to examine and validate the relationships between in-service and pre-service teacher TPACK constructs (Chai et al., 2011; Cheng & Xie, 2018; Koh et al., 2013; Lin et al., 2013; Reyes et al., 2017). From Mishra and Koehler’s (2006) depiction, TPK and TCK are theoretically defined as the direct linkages to TPACK. Koh et al. (2013) examined the intra-relationships of TPACK factors. They found that teachers’ perceptions of TPK and TCK impacted TPACK more substantially than TK and PK.

Numerous studies have been conducted on TPACK training. Most past research has focused on ICT integration (Chien et al., 2012; Lee & Kim, 2014; Munyengabe et al., 2017), attitudes toward ICT (Holland & Piper, 2016; Yerdelen-Damar et al., 2017), and the professional development of TPACK (Almerich et al., 2016; Cheng et al., 2022; Jimoyiannis, 2010). Jimoyiannis (2010) emphasized that the enhancement of teachers’ TPACK in the context of science education necessitates genuine learning encounters that closely align with actual classroom scenarios. Chien et al. (2012) designed the MAGDAIRE model that crafted to enhance how pre-service teachers integrated ICT into education in collaborative learning environments. Along with four major phases modeled analysis, guided development, articulated implementation, and reflected evaluation, this model could bolster teachers’ proficiency with ICT tools and their understanding of how these tools intersect with pedagogy and content (Chang et al., 2012). Cheng et al. (2022) introduced the DECODE model, which distinguishes itself by emphasizing online teaching. This model was stemming from the MAGDAIRE model, emphasizing collaborative efforts in the design, development, and execution of instructional modules enriched with technology. While the MAGDAIRE model focuses on CK, the DECODE model aims to allow participants to learn about technology use while simultaneously understanding how to teach using technology (i.e., TPACK). The DECODE framework was initially designed for teacher science education programs to engage teachers in a collaborative environment. The DECODE framework consists of three stages: (1) DE: teacher’s DEmonstration - trainers showcase effective use of educational technology; (2) CO: participants CO-train - participants practice together using technology and collaboratively design a technology-integrated classroom, and (3) DE: participants DEbrief - participants teach with CCR, receive feedback, and summarize their learning experiences. The framework has been adopted to teach pre-service teachers how to use technology for designing courses (Cheng et al., 2022), to train STEM in-service teachers’ professional development (Wahono et al., 2022), and to cultivate pre-service teachers’ teaching competency and resilience (Rajasekaran et al., 2024). Due to the theoretical and practical aspects, this study utilized the DECODE model as the basis for the design of workshops within an authentic practice of science classrooms.

1.3 Interplay of SRL and TPACK

A teacher with a high level of SRL is more likely to be reflective, adaptive, and flexible in their teaching and technology integration approach. Empirical research highlights the positive effects of SRL support on improving teachers’ TPACK. Tantrarungroj and Suwannatthachote (2013) explored how SRL strategies like self-questioning and peer assessment could benefit pre-service teachers’ TPACK. The study found that those who received SRL strategy support showed notable improvements in their TPACK scores, indicating that SRL plays a significant role in enhancing TPACK development. In addition, using a combination of SRL strategies could effectively accelerate the growth of teachers’ TPACK development. Research pointed to the critical role of SRL in fostering TPACK performance.

Moreover, empirical research underscores the potential roles of TPK and TCK that emerged between SRL and TPACK. Kramarski and Michalsky (2010) emphasized incorporating metacognitive support into pre-service teachers’ education. Their findings suggested that such support enhanced SRL, which improves their use of hypermedia for instructional design (i.e., TCK) and their skills in pedagogy comprehension and design (i.e., TPK). They further argued that integrating these elements was critical for developing effective TPACK. Furthermore, Huang and Lajoie (2021) highlighted how TPK and TCK contributed to effective technology use in education, emphasizing that teachers with high SRL abilities tend to develop stronger TPACK skills. For instance, goal-oriented monitoring and evaluation played crucial roles in adapting teaching strategies (i.e., TPK) and content knowledge to technology integration (i.e., TCK). High performers in TPACK are shown to engage more in self-regulative activities, demonstrating a deeper understanding and application of TPK and TCK within their teaching practices. Overall, teacher education in the context of TPACK plays a role in developing teachers’ ICT knowledge, skills, and pedagogical practice. As a result, the study focuses on the three important dimensions of TPK, TCK, and TPACK in teachers’ SRL rather than a comprehensive exploration of the overall TPACK.

We hypothesized that TPK and TCK were likely intermediaries between teachers’ perceived SRL and their TPACK. Teachers who actively engage in SRL to enhance their TPK and TCK may experience an overall improvement in their TPACK. As a result, understanding the interactions between SRL, TPK, TCK, and TPACK can provide valuable insights into the professional development of teachers and the effective integration of technology in educational settings. The intermediate role of TPK and TCK in the relationship between teachers’ SRL and TPACK is a significant aspect explored in this study. Given this synthesis of findings, we posited the following hypotheses:

H1: Teachers’ perceived SRL can positively affect their TCK.

H2: Teachers’ perceived SRL can positively affect their TPK.

H3: Teachers’ perceived SRL can positively affect their TPACK.

H4: Teachers’ TCK can positively affect their TPACK.

H5: Teachers’ TPK can positively affect their TPACK.

H6: Teachers’ perceived SRL indirectly affects their TPACK through the mediation of TPK and TCK.

2 Methods and materials

2.1 Workshop design and procedure

This study is a part of a research project from an education center at a university in Northern Taiwan, conducted through online training for teacher education (i.e., teacher preparation and professional development). DECODE is basically designed to facilitate online and collaborative training workshops, aimed at enhancing science teachers’ TPACK (Cheng et al., 2022). Evidence suggests that the online DECODE model prepares teachers by enabling them to familiarize with various software and platforms and enhance their skills in assessment and instructional design, as well as in practical implementation, aligning with the TPACK framework (Wahono et al., 2020). Therefore, we organized workshops using the DECODE training model to introduce CloudClassRoom (CCR) and demonstrate its use in technology-enhanced instruction and SRL. Adapting the DECODE framework, we designed the workshops to promote the use of CCR to technology-enhanced instruction with SRL strategies and explore teachers’ perceptions about technology-enhanced instruction and SRL. CCR is a web-based interactive response system, commonly known as a clicker, which can be easily accessed on any device with an Internet browser, including Windows, macOS, iOS, and Android, without the need for additional installations (Chien et al., 2015; Liou et al., 2016). This system offers various clicker functions, such as questioning, answering, and facilitating discussions. Studies have shown that clickers have a positive impact on SRL processes. They help eliminate students’ feelings of hopelessness, encourage progress toward learning goals, and promote engagement in discussions and evaluation of chosen answers (Chien et al., 2016). Therefore, we conducted the workshops following the DECODE framework, which were opened to in-service and pre-service teachers. The content and procedure of the workshops were designed by the first author and thoroughly validated by two experts, comprising a teacher education specialist and an experienced in-service teacher.

In a three-hour online workshop, attendees were introduced to a demonstration of CCR-integrated micro-unit and engaged in SRL activities. The workshop utilized the adapted DECODE framework (Fig. 1), with the DE stage presenting a micro-unit demonstration enriched with SRL strategies. This micro-unit specifically delved into the evolution of giraffes, concentrating on the topic of the elongation of giraffe necks. This subject matter aligns with the high school natural science curriculum guidelines in Taiwan (Minister of Education, 2014). A central part of the learning activity in the DE phase involved posing questions and providing prompts related to SRL strategies. The procedures are as follows:

  1. 1.

    After discussing the concepts of evolution, the instructors posed a question to the students: “What is the mechanism behind giraffe evolution?“

  2. 2.

    Although the anticipated answer was “natural selection,“ this mechanism remains a topic of debate and is still inconclusive. Consequently, we informed the students that “natural selection“ wasn’t the definitive answer.

  3. 3.

    Participants were then grouped heterogeneously and prompted to use self-regulated strategies, including reflecting on their initial answers, help seeking with Internet and peers, and discussing them with their peers (Pintrich, 1991, 1999).

  4. 4.

    Lastly, the question was posed once more in CCR.

  5. 5.

    This interactive approach sparked diverse ideas and viewpoints, resulting in a more uncertain and varied explanation of giraffe evolution. The dynamic exchange led to spirited debates and even conflicting teacher viewpoints. To enhance the learning experience, we incorporated SRL strategies into the micro-unit, allowing participants to experience and embrace the benefits of SRL.

In the CO stage, workshop trainers guided participants to reflect with their group members on the micro-unit demonstrated during the DE stage. Trainers posed questions like, “Did you change your answer choice“ Why?“, “Which SRL strategies influenced you to change your choice?“, and “After discussing with your peers, what do you think is the role of peer interaction in learning?“. Through this series of questions, participants engaged in reflection and shared their perspectives within their small groups. Subsequently, using the CCR, participants collaborated to share their thoughts with the entire attendees. In this stage, CO signifies that participants were engaged in cooperative reflection on how technology and SRL strategies can be utilized in teaching scientific concepts (i.e., SRL-based TPACK).

Fig. 1
figure 1

The procedure of workshop

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Finally, the last DE stage involved participants summarizing (i.e., debriefing) their learning journey through the abovementioned stages. Open-ended questions were thoughtfully employed to prompt participants’ perceptions of technology-enhanced learning environments. Overall, the workshops successfully engaged participants in a self-regulated micro-unit, equipping them with the necessary skills to effectively design and implement CCR in their future instruction. The combination of interactive technology, SRL strategies, and collaborative learning fostered an enriching and empowering learning experience for all participants.

2.2 Participants

In 2022, we hosted a series of workshops titled “CloudClassRoom: technology-enhanced teaching and learning,” specifically designed for in-service and pre-service teachers in Taiwan with a focus on science education and an interest in innovative technology and its instructional applications. These workshops were offered as non-mandatory, voluntary professional development activities and were conducted online. To recruit participants, we utilized two primary methods: firstly, by advertising the workshop details on the website of a science education center for those interested in professional development; secondly, by promoting the event through a national professional development website. The workshops were conducted via Google Meet, and interested participants were required to register and were then provided with the link to join. Therefore, this approach allowed us to attract a diverse group of educators from various regions of Taiwan, including the north, west, south, and east, representing a wide range of educational levels. 358 teachers participated in the workshops, including 342 in-service teachers and 16 pre-service teachers. Out of these 358 participants, we obtained consent from 192 individuals, including 181 in-service teachers and 11 pre-service teachers (Table 1).

Table 1 Consented participants’ demographic information
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2.3 Instruments

During the workshops, three open-ended questions were strategically administered to capture teachers’ perceptions of technology-enhanced instruction and SRL. The question set was designed by the first author. The content was rigorously validated by two experts, comprising a teacher education specialist and an experienced in-service teacher. At the outset of the workshop, teachers were prompted to respond to the first open-ended question, “What was technology-enhanced learning in practice?” This initial inquiry set the stage for exploring their understanding and experiences with technology integration in the learning process. In the last DE stage, participants had the opportunity to immerse themselves in a SRL-integrated micro-unit. For the second and third questions, teachers were asked, “How could CCR-assisted learning assist and facilitate students in acquiring subject matter knowledge of evolution?” and “What self-regulated learning strategies did the CCR-integrated micro-unit provide, and how did they contribute to effective student learning?”

As previous review research mentioned (Abbitt, 2011; Panadero, 2017; Perry & Winne, 2006), self-reported surveys were the most common approach to measuring TPACK and SRL; therefore, we adopted the questionnaire, which was employed at the end of the workshop and composed of demographic information and four constructs: TCK, TPK, TPACK, and SRL. To mitigate participant fatigue and potentially enhance response rates and data quality, we shortened the questionnaire length (Weijters et al., 2010), limiting the number of items per construct to between two and five. Supporting evidence suggests that scales with as few as two items can still reliably and validly measure individual characteristics (Eisinga et al., 2013; Gosling et al., 2003). The questionnaire was based on the well-established instruments (Chai et al., 2011; Koh et al., 2013; Pintrich et al., 1993). The first author selected key items for each construct and consulted with two educational researchers — one being an education professor and the other an in-service teacher — specializing in TPACK and SRL to ensure the measurements’ alignment with the study’s goals. Subsequently, the other authors conducted a thorough review of the entire questionnaire.

The TPACK constructs were adapted from the well-established instrument (Chai et al., 2011; Koh et al., 2013) to align with the content of the workshop, such as self-regulated learning strategies and technology-enhanced instruction. Within the TCK dimension, two items focused on evaluating teachers’ proficiency using suitable software and technology to facilitate instruction. In the TPK dimension, three items were explored: integrated SRL strategies, cognition strategies, and peer learning. Additionally, two items within the TPACK dimension examined the facilitation of students’ SRL with technology and leadership in guiding peers during related instruction.

The SRL construct was adapted from the Motivated Strategies for Learning Questionnaire (Pintrich et al., 1993) to assess teachers’ self-reported metacognitive self-regulation and peer learning. Five items accounted for metacognitive self-regulation, which referred to metacognition’s control and self-regulation aspects (i.e., monitoring capability, regulating capability). Participants rated each item on a 5-point Likert scale, ranging from 1 (not at all true for me) to 5 (very true for me), with higher scores indicating a higher level of the respective construct. The items and each description are shown in Table 2.

Table 2 Questionnaire constructs and items
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2.4 Data analysis

We analyzed the collected data to address the first research question and examined the hypothesized relationships between SRL and TPACK. Path analysis was conducted the lavaan package (version 0.6.15) in R (Rosseel, 2012) to thoroughly explore both direct and indirect effects within the proposed models. We use the package to calculate a mediation model with the bootstrapping approach to employing 10,000 bootstrapping samples (Preacher & Hayes, 2008). In order to address the second research question, thematic analysis (Braun & Clarke, 2006) was conducted to examine participants’ responses to open-ended questions in the workshops.

In conducting the thematic analysis, the first author, alongside an educational researcher, engaged in a rigorous process to ensure the validity and reliability of the findings. Initially, both reviewers independently analyzed participants’ responses multiple times to establish initial coding for the inductively derived units within the qualitative data. This independent review phase enhanced the analysis’s validity by ensuring that codes were not the product of a single researcher’s bias. To address reliability, discrepancies in initial coding were meticulously deliberated upon in joint sessions, where both reviewers discussed their rationales for code assignment until consensus was reached. This iterative process ensured the reliability of the coding scheme by demonstrating that it could be consistently applied by different researchers.

After establishing a reliable coding scheme, the coded units were systematically organized into specific sub-themes through an iterative process of comparison and contrast, ensuring that each sub-theme accurately reflected the underlying data. These sub-themes were then further synthesized into higher-level themes (i.e., main themes) in a manner that aimed to capture the essence of participants’ perceptions. To enhance the analysis’s validity, we compared our thematic findings with existing literature on similar topics, thereby ensuring that our interpretations were not only grounded in the data but also aligned with established research. To further bolster the dependability and confirmability of the thematic analysis, all identified themes and the underlying rationale for their development were subjected to a rigorous review by all contributing authors. This included a critical examination of the thematic structure against the raw data to ensure that the themes were not only representative but also grounded in participants’ responses. Additionally, this review process involved evaluating the coherence of the theme development process, from initial coding to the final thematic framework, to ensure logical consistency and transparency.

3 Findings

3.1 Path analysis of SRL and TPACK factors

We conducted confirmatory factor analysis with maximum-likelihood estimation to examine the measurement model using TCK, TPK, TPACK, and SRL variables. As shown in Table 3, the internal reliability of the constructs was established through Cronbach’s alphas for TPK and SRL, and the Spearman-Brown coefficient was used to check the reliability of the two-item scale for TCK and TPACK (Eisinga et al., 2013). The skewness and kurtosis indices should be within |1| and |2|, respectively (Kline, 2011). The measurement tools in the present study met the assumption of a normal distribution.

Table 3 Descriptive statistics
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As presented in Table 4, all factor loadings exceeded 0.7 (0.75 to 0.93) which is usually considered a threshold for high contribution. Composite reliability (CR) and average variance extraction (AVE) were used to establish the reliability and validity of observed variables in the model, and the minimum acceptable AVE and CR values are 0.50 and 0.60, respectively, or above (Fornell & Larcker, 1981; Kline, 2011). In this study, AVE values were between 0.67 and 0.76, and CR values were between 0.80 and 0.91. The results indicated a good level of convergent and discriminant validity. The fitness indexes of the measurement model were obtained (χ2 = 86.4, χ2/df = 1.8, p = .001, TLI = 0.97, CFI = 0.98, RMSEA = 0.07, SRMR = 0.03), suggesting a good fit (Hu & Bentler, 1999).

Table 4 The results of the measurement model
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Significant positive correlations between the SRL and TPACK constructs were established at p < .001, which indicated that the relationships could be further examined with structural equation modeling. The structural model had a moderate model fit (χ2 = 130.4, χ2/df = 2.7, p < .001, TLI = 0.94, CFI = 0.95, RMSEA = 0.09, SRMR = 0.06), suggesting a good fit to the observed data, as evidenced by the acceptable values of various fit indices (Hu & Bentler, 1999). The results showed SRL could predict TPK and TCK, providing support for H1 and H2, respectively; however, the direct relationship between SRL and TPACK was found no significant relationship, indicating no support for H3. In line with H4 and H5, the estimates suggested positive effects of TCK and TPK on TPACK (see Table 5). While SRL had no direct influence on TPACK, strongly impacting TCK and TPK. These, in turn, substantially contributed to TPACK, indicating a mediatory role of TCK and TPK in the relationship between SRL and TPACK in line with H6 (Fig. 2). Employing the bootsrapping estimations (Preacher & Hayes, 2008), the individual indirect effects were shown in Table 6, and the total effect of SRL on TPACK, combining both direct and indirect influences, was calculated to be 0.77 (standard error = 0.04, and 95%CI = [0.69, 0.85]).

Table 5 Path coefficients
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Fig. 2
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The results of path analysis

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Table 6 Standardized indirect effects
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3.2 Teachers’ perceptions of technology-enhanced instruction and self-regulated learning

Three open-ended questions were set up, collecting the participants perceptions about technology-enhanced instruction and SRL. We used a thematic analysis of all responses, generating main themes categorized into several sub-themes. Two main themes were identified in the first question: “supporting instruction and learning” and “enhancing student motivation,” the sub-themes and examples are shown in Table 7. Three main themes were identified in the second question, identical to the first question’s main themes, and the sub-themes and examples are shown in Table 8. A new main theme emerged after the demonstration: “teacher’s preparation.” Two main themes were identified in the third question: “peer learning” and “self-regulation,” the sub-themes and examples are shown in Table 9.

The results of the first open-ended question revealed two main themes that characterize the impact of technology-enhanced learning in educational settings. The first main theme, “Supporting Instruction and Learning,” encompasses four sub-themes. The first sub-theme, “Enhancing the effectiveness of teaching and learning,” highlights how technology assists both teachers and students in achieving differentiated instruction, leading to more effective learning outcomes and streamlined teacher preparation. Additionally, the second sub-theme, “Tracking and analyzing learning and feedback instantly,” indicated that technology allows for comprehensive student assessment, enabling educators to gain valuable insights into individual student progress. This sub-theme underscores the real-time monitoring capabilities of technology, which enable educators to assess students’ learning status and gather valuable feedback quickly. This immediate feedback empowers teachers to address challenges that traditional teaching methods may struggle to overcome, such as providing real-time answer feedback and conducting fast data analysis.

The third sub-theme, “Combining instruction and assessment with multimedia resources,” emphasizes the importance of catering to diverse learning needs through adjusted teaching methods that leverage multimedia resources. This approach fosters an interactive and dynamic learning environment, enhancing student engagement and comprehension. Finally, the fourth sub-theme, “Self-regulated learning,” emphasizes the empowering effect of technology in facilitating self-paced learning for students. The second main theme identified is “Enhancing Students’ Motivation,” which consists of two sub-themes. The first sub-theme, “Engagement,” underscores how technology’s multi-representation of information captivates students and promotes active participation and focused learning. By presenting content in various formats, technology stimulates student interest and involvement in learning. The second sub-theme, “Motivation,” emphasizes that technology-integrated pedagogies offer diverse learning approaches, elevating students’ motivation levels and sustaining their enthusiasm for learning.

Table 7 Main themes and sub-themes of “What was technology-enhanced learning in practice?”
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The results of the second open-ended question, employed in the debriefing stage, yielded valuable insights into the impact of CCR-assisted learning on various aspects of instruction and student motivation. The first main theme, “Supporting Instruction and Learning,” comprises three sub-themes. The first sub-theme, “Peer Instruction,” highlights the significance of peer discussions in clarifying concepts and fostering reflective learning. Through interactions with their peers, students gain a deeper understanding of ideas, and even less expressive students find a voice by engaging in textual exchanges during discussions. The second sub-theme, “Tracking and Analyzing Learning and Feedback Instantly,” underscores the advantages of real-time interactions with CCR technology. Teachers can swiftly clarify and reinforce concepts through immediate feedback, making it particularly beneficial in subjects like mathematics. The third sub-theme, “Self-regulated Learning,” emphasizes how CCR facilitates effective learning through group discussions, challenging activities, interactive answers, and a process of inquiry and reflection. This approach stimulates critical thinking and self-monitoring among students, contributing to a more engaged and reflective learning experience.

The second main theme, “Enhancing Students’ Motivation,” encompasses two sub-themes, which share a high commonality with the previous main theme of the first question. The final main theme, “Teacher’s Preparation,” comprises two sub-themes. The first sub-theme, “Well-designed Lessons,” emphasizes the role of teachers in systematically designing courses and questions that leverage CCR-assisted teaching to construct students’ knowledge and understanding effectively. The second sub-theme, “Appropriate Guidance,” underscores the importance of teacher guidance in helping students make the most of CCR technology for their learning journey.

Table 8 Main themes and sub-themes of “How could CCR-assisted learning facilitate students to acquire the subject matter knowledge of evolution.”
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The results of the third open-ended question, employed in the debriefing stage, provided valuable insights into the significance of peer learning and self-regulation in the learning process. The first main theme, “Peer Learning,” encompasses two sub-themes. The first sub-theme, “Peer Instruction,” highlights the benefits of allowing students to learn from each other through peer discussions. This approach encourages students to clarify concepts and share their knowledge, promoting a transition from known ideas to unknown ones. Additionally, heterogeneous grouping facilitates scaffolding among students, where those with higher proficiency levels support and assist their peers, fostering a collaborative and supportive learning environment. The second sub-theme, “Engagement,” underscores the role of discussions, guided by teachers, in stimulating critical thinking and active problem-solving among students. Through meaningful dialogues and the teacher’s facilitation, students are encouraged to think deeply and engage actively in learning.

The second main theme, “Self-regulation,” consists of two sub-themes. The first sub-theme, “Self-monitoring,” highlights students’ ability to regulate their learning progress autonomously. By self-monitoring, students gain insights into their learning approaches, enabling them to make adjustments and improvements as needed. The second sub-theme, “Self-reflection,” emphasizes the importance of students understanding their peers’ perspectives during discussions and reflecting on their learning experiences. This process of reflection enhances metacognition and deepens students’ understanding of the subject matter.

Table 9 Main themes and sub-themes of “What self-regulated learning strategy did the CCR-integrated micro-unit provide and how to help students learn effectively.”
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4 Discussion and conclusions

4.1 Direct and indirect effects on TPACK

This study underscored the relationship between SRL and TPACK factors. We paved the way for a more comprehensive understanding. First, SRL was found to influence TCK and TPK directly. The findings suggested that teachers more skilled in SRL were better equipped to acquire and apply TCK and TPK. The relationships make sense because teachers who can regulate their learning effectively are more likely to seek out and engage with relevant resources and information, leading to a deeper understanding of content (i.e., TCK) and pedagogy (i.e., TPK) in a technological context. Second, the findings revealed that TCK and TPK acted as complete mediators in the association between SRL and TPACK; namely, while SRL may not have a direct impact on TPACK, its influence on TCK and TPK was pivotal, and it can indirectly affect TPACK through these mediators. In essence, SRL sets a foundation that fosters the development of TCK and TPK, significantly contributing to TPACK. The findings echo the positive influence of teachers’ self-regulation on TPACK. Previous research has hinted at the importance of SRL in the professional development of TPACK. For instance, Kramarski and Michalsky (2010) suggested that training in TPACK was significantly practical when complemented by SRL support. Likewise, Tantrarungroj and Suwannatthachote (2013) underscored the performance enhancement of pre-service teachers on TPACK when self-regulated instruction was provided. This study affirms these assertions and provides path analysis evidence to support their validity. Moreover, despite the overall model showing no significant direct effect of SRL on TPACK, when considering the positive influence exerted through TCK and TPK, SRL ultimately contributes positively to the development of TPACK due to the complex interplay of these factors. Third, the strong predictive power of TCK and TPK on TPACK echoed previous studies that evaluated the relationships between these variables (e.g., Koh et al., 2013; Lin et al., 2013; Pamuk et al., 2015). This robust correlation suggests that improved TCK and TPK can enhance TPACK. Additionally, for these teachers, TCK (β = 0.80) was observed to have a positive influence on the formation of their TPACK than TPK (β = 0.77), in line with Singapore teachers (Koh et al., 2013).

4.2 Initial perceptions of technology-enhanced environment

We could get insight into teachers’ views through qualitative data. At the beginning of the workshop, we aimed to understand what teachers thought of technology in education. “Enhancing the effectiveness of teaching and learning” indicated a generally positive attitude towards adopting technology due to its perceived effectiveness (Davis, 1989; Venkatesh & Davis, 1996). Contrary to traditional methods, technology allows tracking students’ activities automatically and generating real-time reports (Henrie et al., 2015; Yen et al., 2018). The participants perceived this feature as necessary in supporting instruction and learning. The integration of multimedia in teaching, an essential technological affordance, was also noted (Chai et al., 2011; Mayer & Girwidz, 2019; Mishra & Koehler, 2006). Previous research underscored that technology features required high self-regulation and provided opportunities for SRL (e.g., Azevedo et al., 2004). Besides, the participants viewed that technology allows students to learn at their pace in the context of SRL. Engagement and motivation were necessary to allow students to indulge in the classroom, appearing to be generally compatible with the surrounding literature (Henrie et al., 2015; Sui et al., 2024). Before formally demonstrating the topic, the teachers already demonstrated strong TPACK. They understood how to use technology to bolster pedagogy and deploy multimedia resources for more effective instructional strategies and content delivery. Furthermore, they saw a technology-enhanced environment as a conduit to facilitate SRL and boost student motivation.

4.3 Perceptions following the workshop

Participants shared their perceptions of its affordances after their experience with the evolution-themed CCR-integrated micro-unit. In supporting instruction and enhancing motivation perceptions, two main themes (MT2-1 and MT2-2) mirrored those identified in the first question (MT1-1 and MT1-2). A new theme, “Peer instruction,” surfaced within the “supporting instruction and learning.” Participants explained that aiding students in understanding each other?s concepts, reflecting on peers’ ideas, and encouraging sharing contributed to a peer learning system. Reasonably, participants had experienced the CCR micro-unit integrated with the peer learning strategy. These insights align with the empirical (Chien et al., 2015) and review (Chien et al., 2016) studies. Furthermore, we speculated that engaging teachers in this setting activated a co-regulatory process, defined as “the temporary coordination of self-regulation among oneself and others” (Hadwin et al., 2011, p.68), among teachers during their self-regulation phases. Thus, teachers viewed the integration of peer learning within the micro-unit as a significant enhancer of collaborative environments. Peer learning was perceived as a coordinating mechanism that bolstered student interactions and collective work efforts, emphasizing the CCR’s effectiveness in creating a dynamic and interactive learning atmosphere. Expectedly, participants had undergone the CCR micro-unit that integrates the peer learning strategy.

Teachers’ observations regarding technology affordance further underscored their strong TPACK knowledge. Another main theme (MT2-3) emphasized the importance of teachers’ preparation. While teachers initially did not view preparation as a critical factor in a technology-enhanced environment, exposure to a micro-unit with SRL strategies led them to appreciate the importance of well-prepared lessons and adaptive instruction. Theoretically, well-designed lessons and appropriate guidance with technology could provide adaptive scaffolding, which activates students’ prior knowledge and allows students to use SRL strategies (Chien et al., 2016; Song & Kim, 2021; Yen et al., 2018), especially science learning (Azevedo & Cromley, 2004; Azevedo et al., 2004; Sui et al., 2024), corresponding with participants views in practice.

As for the final question, participants were prompted to identify the SRL scaffolding they observed in the demonstration. They pinpointed “peer learning” and “self-regulation” as features of the CCR-integrated micro-unit. The results echoed the micro-unit design, consisting of questioning, peer discussion, and repeated questioning. The participants were encouraged to reflect on the evolution concepts discussed, allowing them to engage in metacognitive self-regulation. The identified themes echo that students’ discussions assist in sharing the monitoring and controlling processes with peers and in prompting themselves to detect and correct misunderstandings (Chien et al., 2016). Furthermore, the findings affirm the value of peer learning, underscoring its role in fostering a symbiotic relationship between co-regulation and self-regulation, echoing the concepts of socially shared regulation (Hadwin & Oshige, 2011; Rohrkemper, 1989).

Essentially, the stronger a teacher’s self-regulation skills, the better equipped they are to develop and utilize TPACK (Eekelen et al., 2005). In light of the identified themes among open-ended questions, we found a possible relationship between teachers’ TPACK and SRL. The development of self-regulation was likely to enhance teachers’ capacity to adapt and evolve their TPACK, integrating technology more effectively within their pedagogical repertoire. For instance, participants did not perceive the importance of teacher preparation until they experienced the micro-unit. They might have undergone the self-regulation processes and view preparations as the needs in technology-enhanced environments.

4.4 Association between quantitative and qualitative findings

The qualitative insights into teachers’ perceptions that CCR-assisted instruction facilitated learners in acquiring subject matter knowledge and the strategies for effective SRL provide practical examples of how technological pedagogies are applied. These practices not only support the quantitative findings but also offer depth to the understanding of how SRL influences TCK and TPK. For example, peer instruction (MT3-1) and self-regulation (MT3-2) highlighted in the qualitative data illustrate the mechanisms through which SRL may enhance TCK and TPK. The qualitative findings further enrich this understanding by shedding light on the practical applications and benefits of technology-enhanced learning, which underpin the quantitative results. Teachers showed that technology could support instruction and learning such as subject matter knowledge and SRL in line with the effect of SRL on TPK; in addition, combining instruction and assessment with multimedia resources align with the effect of SRL on TCK quantitatively measured. Furthermore, teacher preparation is a pivotal bridge from TPK and TCK to TPACK. Teachers not only showed understandings of systematically designing courses and utilizing CCR to enable students to construct knowledge and concepts effectively, but also recognized the importance of providing appropriate guidance to facilitate effective learning among students. Through well-designed lessons and strategic guidance, teachers are equipped to enhance the integration of technology, pedagogy, and content knowledge, fostering an environment where students can engage deeply with the subject matter and develop their learning strategies. In summary, the qualitative findings offer context and depth to the statistical relationships uncovered, illustrating how SRL, through its influence on TCK and TPK, contributes to the integration of technology into teaching and learning processes (i.e., TPACK) effectively. This holistic approach underscores the importance of considering both quantitative and qualitative data to fully understand the complexities of integrating technology in education and the role of self-regulation in optimizing this integration for the development of TPACK.

4.5 The role of DECODE

In the DECODE-based workshop, it is essential to highlight the teachers’ perceptions. Based on the qualitative results, the training’s structure and application have shown participants’ understanding and attitudes toward technology-enhanced instruction and SRL. Firstly, there was a possible shift in teachers’ perception of technology in education. At the beginning of workshops, participants acknowledged the value of technology for enhancing teaching and learning effectiveness, recognizing its ability to track students’ activities, generate real-time reports, and integrate multimedia into teaching. However, the practical demonstration of CCR-integrated micro-unit allowed participants to experience firsthand how these technological features could foster a dynamic, interactive learning environment that actively engages students and promotes self-regulation. Secondly, the DECODE framework provided a potential framework that guided teachers using technology with SRL experiences. Following the practical demonstration, teachers recognized peer instruction as a crucial component, signifying an enhanced awareness of co-regulation in their instructional practices. In addition, they acknowledged the importance of dedicated teacher preparation in promoting SRL. Thirdly, the findings revealed teacher’s recognition of the relationship between TPACK and SRL. We speculated that teachers with a higher degree of SRL might perceive the interplay of SRL and TPACK and facilitate the development and application of TPACK. The DECODE-based workshops played a role in teachers’ perceptions of technology in education and its potential to foster SRL. The DECODE framework gave science teachers the tools to integrate technology effectively into their teaching (Cheng et al., 2022; Rajasekaran et al., 2024; Wahono et al., 2022) and challenged them to think deeply about how these tools can foster student self-regulation.

4.6 Limitations

The study acknowledges several limitations. Initially, the established relationships rely heavily on teachers’ perceptions of TPACK and SRL, gauged solely through a self-reported questionnaire, rendering it vulnerable to social desirability bias (Fisher, 1993). This limitation is particularly relevant given the study’s focus on teachers’ perceptions, which are inherently subjective and may not fully capture the complexities of implementing technology-enhanced instruction and SRL strategies in the classroom.

The study only delved into the examination of TCK, TPK, and TPACK, overlooking comprehensive constructs of TPACK variables such as PK, CK, TK, and PCK. Besides, individual self-efficacy is usually discussed with the use of technology and SRL (Sui et al., 2024; Yi & Hwang, 2003). The exclusion of these dimensions may limit the comprehensiveness of our findings, as they play significant roles in integrating technology into teaching and learning processes.

While the study successfully delineates the mediating role of SRL in the relationship with TPACK, it leaves the intrinsic mechanisms contributing to the full mediation largely unexplored, warranting further investigation in this promising avenue of research. The process of coding and identifying themes, despite the involvement of multiple reviewers, remains inherently subjective and is susceptible to the influences of the researchers’ individual biases, backgrounds, and inclinations. Such subjectivity may cultivate divergent interpretations of identical data sets, subsequently impacting the themes identified.

Given these constraints, It is recommended that future research endeavors should first incorporate previously unexplored factors such as PK, CK, TK, and PCK to examine their interactions and impact on SRL. Secondly, it is advised that future studies undertake a deeper analytical exploration, which could involve conducting detailed interviews and observations within authentic classroom settings to better understand teachers’ perceptions regarding technology-enhanced instruction and SRL.

Moreover, the conclusions explicitly drawn reflect the perspectives of Taiwanese teachers participating in the workshops. In terms of generalizability, we could expect that if Taiwanese teachers are engaged in the training, they would gain an understanding of the role of SRL strategies in a technology-enhanced environment. While the insights garnered offer valuable contributions to understanding the interplay between SRL and TPACK, the extent to which these findings can be extrapolated to other educational contexts, cultures, or settings may be limited.

4.7 Conclusions

This research elucidates the pivotal role of SRL in augmenting TPACK, contributing to a nuanced understanding of the interplay between SRL and TPACK. The study underscores that SRL influences TCK and TPK directly, which serve as comprehensive mediators for TPACK. The findings suggested that teacher’s adept in SRL exhibited enhanced acquisition and application of TCK and TPK, stemming from their proficient ability to regulate learning, engage with pertinent resources and integrate technology effectively in pedagogical contexts. Thus, building teachers’ self-regulated learning could be the primary goal in teacher professional development and education. Moreover, this study provided essential insights into teachers’ perceptions of technology-enhanced environments, mainly focusing on TPACK and SRL and the role of DECODE in shaping these perceptions. The qualitative analysis has elucidated five main themes influencing teachers’ views of technology in education. Our results highlighted that initial perceptions of the technology-enhanced environment were generally positive, with teachers recognizing the value of technology in enhancing the effectiveness of teaching and learning. They acknowledged the ability of technology to track student activities, generate real-time reports, integrate multimedia into teaching, and foster an interactive and lively learning environment. Following the DEmo and COreflection stages, the teachers’ perceptions were expanded and refined. They identified new themes, such as peer instruction, emphasizing the role of technology in facilitating peer learning systems. The importance of teacher preparation in using technology effectively was also underscored, highlighting the value of adaptive scaffolding in promoting SRL strategies. It was evident that exposure to the DECODE framework and a practical CCR-integrated micro-unit facilitated this perception shift. Teachers were guided through a practical demonstration of how technology can be strategically used to enhance learning experiences. Therefore, DECODE could act as a potential framework for teacher professional development of SRL and TPACK. As the digital era progresses, teacher professional development programs must continue emphasizing these aspects, fostering a culture of self-regulation and technological pedagogical practice.