Conference Agenda

Metacognition, an ability to reflect on one’s thinking, stemmed as an early area of research interest in the 90s (Zimmerman, 1995, Hamman et al., 1996, Metcalfe and Shimamura, 1996), as a development to Flavell’s (1979) definition of metacognition as ‘one’s stored knowledge or beliefs about oneself and others as cognitive agents, about tasks, about actions or strategies’ (Flavell, 1979, p.906).

Metacognition and the application of metacognitive knowledge, skills, and strategies is one of the “ultimate goals of all learning” (Hattie, 2012, p.102, McElwee, 2009). The educational benefits of metacognition are recognised globally: from America (Murphy and Castel, 2022), to Malaysia (Kummin and Rahman, 2010), and to The Netherlands and Belgium (Meijer et al., 2013). In England, this focus has been recently enhanced due to the Education Endowment Foundation’s (EEF’s) renewed focus on metacognition (EEF, 2021).

One’s ability to apply metacognitive study strategies to their own learning, unsupervised, has long been recognised as important in education (Sperling et al., 2004, Hidayah et al., 2016, Marulis and Nelson, 2021). Research conclusions encourage educators to revitalise their instruction by embedding metacognitive practices (Sadykova et al., 2024). However, many studies do not seek the perspective of students, and some disregard their value (Kornell and Bjork, 2007, Skerritt, 2022). It is acknowledged that for a whole-school initiative to be successful it needs to be well implemented and maintained (Desimone, 2002, Freeman et al., 2014, Hudson et al., 2020), meaning that every member of the school community – students, support staff, classroom teachers, and the Senior Leadership Team (SLT) - need to be working unanimously on the same goal with the same purpose, as outlined consistently in various examples of school policy and practice guidance (Stirling and Emery, 2016, Cowne et al., 2018). This case study research brings together the opinions regarding metacognitive study strategies from multiple perspectives within the school community to strengthen the various sources of evidence and address this gap in the literature (Rowley, 2002).

Student perceptions of metacognition are addressed, but only in international research with mature learners. Conclusions suggest that metacognitive study strategies are both useful in assisting those attending lecturers in a different language to their own, and that they feel the value and benefit of these strategies too (Selamat and Sidhu, 2011). Strategies addressed in Selamat and Sidhu’s study do not form an exhaustive list of those used within English secondary education: including only summarising, planning, and testing (Selamat and Sidhu, 2011). Additionally, the age of the students means that their perceptions of metacognitive study strategies cannot be used as a comparison or indication for how the students of this study – aged 11-16 years old – perceive the use of metacognitive study strategies to be at the detriment of benefit of their educational progress. Wall and Higgins’ creation of Pupil Views Templates (PVTs) consolidates that gap, as they provide evidence for students’ metacognitive understanding and skilfulness, rather than exploring and detailing the student view of metacognition and the process (Wall et al., 2005, Wall and Higgins, 2006).

Therefore, the research questions for this doctoral study are:

1. What does the introduction of metacognitive strategies within the English department look like in current practice?
   1. How do students use metacognitive strategies within their English lessons?
   2. How does students’ metacognitive awareness relate to their self-reported metacognitive behaviours?
2. In what ways do members of the school community perceive metacognitive study strategy activities as promoting and/or hindering students’ learning in the secondary English class?
3. How do classroom teachers perceive the impact of this implementation on their practice?
4. How do members of SLT perceive the school’s implementation of metacognitive study strategy activities?

Understanding how pre-service teachers learn remains a central objective of research-based academic teacher education (Swennen, 2025). Reflection and metacognition are important aspects of pre-service teachers’ learning (Korthagen, 2016; Matsumoto-Royo et al., 2022), yet many pre-service teachers graduate without sufficiently developed capacities of reflection and metacognition, which form part of the skills needed to succeed in increasingly diverse and complex educational contexts (Michalsky, 2024; Suphasri & Chinokul, 2021). The variation in pre-service teachers’ initial reflective and metacognitive capacities highlights the need for teacher education programs that support higher-order thinking while addressing individual differences, an enduring challenge in European and global educational contexts.

Well-developed reflection and metacognition are associated with multiple positive outcomes in pre-service teacher education. Reflection supports learning and professional development (Korthagen, 2016; Li, 2025), the ability to take multiple perspectives (Toom et al., 2015), and deeper understanding of the teaching profession (Li, 2025). Metacognition enhances pre-service teachers’ own learning (Bedel, 2012), academic performance (Hong et al., 2020) and teaching practices (Matsumoto-Royo et al., 2022). These findings highlight the importance of examining how reflection and metacognition contribute to pre-service teachers’ learning characteristics, informing both the design of teacher education programs and research on individual differences in higher-order thinking.

Both reflection and metacognition are broadly regarded as forms of higher-order thinking (Ritchhart & Perkins, 2005) with theoretical intersections (Tarricone, 2011). Dewey (1933) describes reflection as the “active, persistent, and careful consideration of any belief or supposed form of knowledge,” a process further elaborated in transformative learning theory (Mezirow, 1991). Metacognition refers to thinking about one’s own cognitive processes (Flavell, 1979), while metacognitive awareness specifically denotes individuals’ knowledge of their cognition and ability to regulate it through planning, monitoring, and evaluation (Schraw & Dennison, 1994). The present study focuses on pre-service teachers perceived reflective thinking (RT) and metacognitive awareness (MA), which capture measurable dimensions of these constructs, allowing investigation of higher-order thinking.

Pre-service teachers differ in RT and MA due to variation in readiness (Kitchener, King & DeLuca, 2006), developmental trajectories (Kleka et al., 2019) and prior cognitive resources (Larmar & Lodge, 2014). These capacities are influenced by internal factors, including prior knowledge, motivation, and cognitive resources, as well as by contextual conditions that can facilitate or constrain their learning (Sargent 2015; Abrouq, 2024). Research shows variability in university students’ MA (Hong, 2020), and in pre-service teachers’ development of MA (Mendoza & Elepano, 2023; Radulović et al., 2024). Similarly, RT develops individually, with varying contextual dependency and differences across programmes (Allas, Leijen & Toom, 2020; Gahlsdorf Terrell & Sherman, 2022; Tiainen et al., 2018).

Prior research is largely qualitative or cross-sectional, with few studies examining associations between RT and MA (e.g. Adadan & Oner, 2018; Alt & Raichel, 2020; Ho & Lau, 2025; Pousi et al., 2025). To our knowledge, no prior study has investigated these capacities together using a person-centred approach in pre-service teacher education. The present study therefore empirically examines the joint structural patterns of RT and MA to understand pre-service teachers’ learning characteristics. Using latent profile analysis on repeated-measurement data, the study seeks to identify distinct subgroups and describes homogeneous profiles, providing insight into the variation and structure of higher-order thinking. Although the data are longitudinal, the present analysis is cross-sectional, emphasizing profile structures at three time points.

Accordingly, this study addresses the following research questions:

1. What kind of distinct profiles of reflective thinking and metacognitive awareness can be identified among pre-service teachers at different stages of teacher education?
2. How do the identified profiles differ in their overall patterns of reflective thinking and metacognitive awareness?

1. Introduction

Artificial intelligence (AI) is increasingly shaping educational practice by offering tools for lesson planning, content generation, assessment, and feedback. In chemistry education, AI-supported applications are used to explain complex concepts, generate instructional materials, and support differentiated learning. While existing research has begun to explore the implications of AI for student learning, much less attention has been paid to how AI influences teachers’ professional learning processes.

Teachers are not only facilitators of learning but also learners who continuously adapt their instructional practices. Self-regulated learning (SRL) provides a useful framework for understanding how teachers plan, monitor, and evaluate their professional actions. In contexts involving technological innovation, such as AI integration, teachers’ capacity for self-regulation becomes particularly important, as they must navigate new tools, evaluate their pedagogical value, and adjust their practices accordingly.

Despite the relevance of SRL for understanding teacher learning, empirical research examining teachers’ SRL processes remains limited, especially within subject-specific domains such as chemistry education. Moreover, studies that explicitly link AI use to teachers’ self-regulated learning are scarce. Addressing this gap, the present study explores how chemistry teachers who already use AI in their teaching regulate their learning and instructional decision-making processes.

This study contributes to research on self-regulated learning by extending SRL theory to teachers’ professional learning in AI-supported teaching contexts. By focusing on chemistry teachers, the study offers subject-specific insights into AI integration in science education. The findings are expected to inform teacher education and professional development initiatives aimed at supporting reflective and self-regulated teaching practices.

2. Theoretical Framework

2.1 Self-Regulated Learning

Self-regulated learning refers to learners’ active processes of goal setting, strategic action, monitoring, and self-reflection (Zimmerman, 2000, 2002). Zimmerman’s cyclical model conceptualizes SRL across three interrelated phases: forethought, performance, and self-reflection. These phases encompass key processes such as planning, task strategy use, help seeking, and self-evaluation.

While SRL research has traditionally focused on students, teachers also engage in self-regulated learning as they design instruction, respond to classroom challenges, and reflect on their practice (Butler, 2002). Teachers’ SRL has been shown to play a critical role in instructional quality and professional development, particularly in complex teaching environments.

2.2 Teachers’ SRL in Technology-Rich Contexts

Technology integration presents both opportunities and challenges for teachers’ self-regulation. Digital tools may support planning and reflection, yet they also increase cognitive demands and require continuous adaptation (Dignath & Büttner, 2018). AI tools, in particular, introduce new forms of support by generating instructional content and feedback, potentially influencing how teachers plan lessons, seek assistance, and evaluate instructional outcomes.

From an SRL perspective, AI may function as a strategic resource that reshapes teachers’ regulatory processes. However, empirical evidence examining these processes remains limited, especially in science education contexts. This study addresses this gap by examining chemistry teachers’ SRL processes in AI-supported teaching.

3. Purpose and Research Questions

The purpose of this exploratory qualitative study is to investigate how the use of AI in chemistry teaching influences teachers’ self-regulated learning processes.

The study addresses the following research questions:

1. How do chemistry teachers describe their planning processes when integrating AI into their teaching?
2. How does AI use shape teachers’ task strategies during instructional design and implementation?
3. How do teachers engage in help-seeking behaviors while using AI for chemistry teaching?
4. How do teachers evaluate and reflect on their AI-supported teaching practices?

There are several approaches which are mentoring, coaching, and supervision to support pre-service teachers (PSTs) during the field experience (Lawson et al., 2015). Alternately, the literature has utilized the terms mentoring, coaching, and supervision (Ambrosetti et al., 2014). The approaches to mentoring and coaching for PSTs differ in terms of their objectives and the specific areas of support they aim to provide (Orland-Barak, 2014). Coaching usually focuses more on goals and less on sharing personal experiences or offering advice. Subsequently, in certain areas of the educational context, the adoption of an enhanced coaching framework has significantly increased (O'Bree, 2008). Several coaching techniques have been developed to provide PSTs with instructional help throughout their school-based practicum experience (Becker et al., 2019). Coaching draws upon sociocultural theory by framing learning as a socially mediated and interaction-driven process. In this theory, Vygotsky (1978) acknowledged that learning is mostly the outcome of the novice's interactions with the social and cultural background in addition to what the more experienced person contributes to them. According to this theory, individuals can create knowledge by interacting with one another. Collaborative conversations help people build their own viewpoints and serve as role models for others within the context of coaching (Dale, 1994).

In the 1990s, a review of studies on coaching revealed that there were two primary types of coaching such as, expert peer coaching and reciprocal peer coaching (Ackland, 1991; Lu, 2010). In reciprocal peer coaching (RPC), peers develop non-hierarchical relationships by disclosing their professional strengths and shortcomings (Cox, 2012). RPC allows coaches to adopt a more cooperative approach in contrast to receiving feedback from an authoritative figure (Ladyshewsky & Ryan, 2002). Bailey (2006) asserts that feedback enhances teacher awareness, hence promoting positive adjustments in their instructional behaviour. According to Britton and Anderson (2010), one of the most important aspects of peer coaching is the facilitation of professional dialogues among peers. These dialogues generate opportunities for reflection, that subsequently aids peers in reconsidering their experiences from a variety of perspectives. Similarly, coaching has shown beneficial effects in encouraging teachers to embrace new viewpoints, develop insights through shared experiences and engage in self-reflective learning (Zwart et al., 2009). As a result, it has been used in pre-service teacher education since the early 1980s after researchers became intrigued by the benefits it provided for in-service professional growth (Lu, 2009; McAllister & Neubert, 1995).

This study contributes to improving the teacher education literature by clarifying how teacher candidates interpret their teaching experiences within reciprocal peer coaching approaches and how reflective teacher learning is dynamically fostered. The purpose of this study is to examine the emerging patterns of coaching dialogues within reciprocal peer coaching cycles carried out by teacher candidates during faculty-based microteaching and to reveal how peer coaching interactions contribute to reflective teacher learning. Consequently, the study aims to qualitatively analyze PSTs focus on during pre- conference and post-conference, how they provided feedback to each other, and what kinds of changes were observed in reflective patterns throughout coaching cycles. The following research questions are examined:

(1) What types of feedback moves do pre-service teachers use during pre-conference and post-conference dialogues in RPC cycles?

(2) How do these dialogues facilitate pre-service teachers’ reflective sense-making across coaching cycles?