Framework of Self-Regulated Cognitive Engagement (FSRCE) for sustainable pedagogy: a model that integrates SRL and cognitive engagement for holistic development of students

Abstract

In this scientific investigation, the researchers have designed and developed a new model The Framework of Self-Regulated Cognitive Engagement (FSRCE) that integrates self-regulated learning (SRL) and cognitive engagement (CE), addressing the limitations of previously developed frameworks. The FSRCE model is guided by core principles, emphasizing the dynamic SRL loop, two dimensions of cognitive engagement, individual and contextual factors, ongoing adaptation, and the integration of cognitive and behavioral engagement. In the dynamic SRL loop, the model unfolds in four phases: the forethought phase, performance phase, monitoring and feedback loops, and self-reflection phase. These phases illustrate the iterative nature of SRL and emphasize the importance of CE at each stage. The cognitive engagement depth dimension measures the intensity of cognitive involvement, while the cognitive engagement strategies dimension examines the specific strategies students employ. Individual and contextual factors, including intrinsic motivation, goal orientation, self-efficacy beliefs, and external influences, significantly shape CE within the FSRCE framework. Students’ intrinsic motivation and goal orientation drive their engagement, while self-efficacy beliefs influence their ability to regulate their learning processes effectively. Continuous adaptation and optimization are central to the FSRCE model, allowing students to adjust their cognitive engagement in response to evolving task demands and feedback. It underscores the interplay between cognitive and behavioral engagement, recognizing that both dimensions are integral to achieving optimal learning outcomes, and provides students with a blueprint for active participation in their learning, optimizing their CE, and enhancing learning outcomes, thereby shedding light on the path to more effective and meaningful educational experiences.

Keywords:

• educational psychology
• academic achievement
• sustainable pedagogy
• sustainable curriculum
• school systems
• educational assessment
• teacher education

REVIEWING EDITOR:

• Serafina Pastore, Università degli Studi di Bari Aldo Moro, Bari, Italy

SUBJECTS:

• Education & Development
• Educational Change & School Reform
• Teachers & Teacher Education
• Theory of Education
• Secondary Education
• Education Policy & Politics
• Education & Training
• Teacher Education & Training
• Education Policy
• Teaching & Learning - Education

1. Self-regulated learning (SRL) and student engagement

Self-regulated learning (SRL) and student engagement, residing at the core of the educational and educational psychology domains, are salient and closely interwoven constructs (Newman, 2023; Pintrich et al., 2000). Despite their inherent distinctions, they coalesce around a shared goal, namely, the enhancement of students’ aptitude and performance within scholastic milieus. SRL stands as an encompassing theoretical framework employed by scholars and educators to delve into the deliberate orchestration of diverse facets of learning, embracing cognitive, metacognitive, motivational, and behavioral elements (Chang, 2005; Dignath-van Ewijk et al., 2013; Wolters et al., 2005). Through the prism of SRL, students embark upon a dynamic and multifaceted journey, actively steering their learning processes, an expedition that inherently underpins their scholastic accomplishments (Roth et al., 2016; Schunk & Usher, 2011). SRL is a concept that refrains from monolithic rigidity; it is, rather, a dynamic, multifaceted, and versatile approach to learning (Cleary & Callan, 2017; Zimmerman, 2000). It engenders a cyclical and recursive paradigm, enveloping the stages of premeditation, performance, and introspection (Zimmerman, 1986, 2002). In the premeditation phase, learners conscientiously delineate their objectives, chart their course of action, and ignite their motivational ardor. During the performance phase, these strategic constructs are translated into action, and during the introspection phase, an evaluation of the efficacy of these strategies is conducted, thus illuminating the path for future learning pursuits. This rhythmic, self-reflective cycle enables students to adapt effectively to the exigencies of diverse learning tasks and contexts, and underscores the interconnectedness of cognitive, metacognitive, motivational, and behavioral aspects within the SRL framework (Kaplan, 2008; Paris & Paris, 2003; Winne, 2010). On the other hand, student engagement is a concept deeply rooted in an active learner’s involvement and commitment to pursuits pertaining to academic accomplishment. It spans the gamut of both overt, manifest factors, such as behavioral involvement, as well as subtle, internal factors, including cognitive and emotional engagement (Pintrich, 2004; Winne, 2011; Winne & Stockley, 1998). Behavioral engagement finds its expression in observable actions by students, encompassing the act of attending classes, completion of assignments, and active involvement in scholarly discourse. Cognitive engagement delves into the psychological investment and intellectual exertion that students contribute to their learning experiences, manifesting in endeavors such as critical analysis and problem-solving (Beishuizen & Steffens, 2011; Purdie & Hattie, 1996; Zimmerman & Martinez-Pons, 1988). Emotional engagement encapsulates the affective aspect of the student’s experience, encapsulating their emotions, attitudes, and emotive reactions to the realm of education (Cleary & Zimmerman, 2012; Paris & Newman, 1990; Zimmerman & Pons, 1986). Engaged students cease to be passive recipients of knowledge, assuming the mantle of active participants in their academic odyssey (Chung, 2000; Vanderstoep et al., 1996). These three facets of student engagement—behavioral, cognitive, and emotional—are intricately entwined, such that heightened engagement in one facet is emblematic of active involvement across the spectrum (Azevedo & Cromley, 2004; Roeser & Peck, 2009). For instance, a student who assiduously participates in class, as manifested through behavioral engagement, is more inclined to exhibit cognitive engagement, discernibly engaging in critical thinking and harboring positive emotional ties to the subject matter (Panadero et al., 2017; Sungur & Tekkaya, 2006).

The nexus between SRL and student engagement is a complex and dynamic liaison. SRL assumes the role of a catalyst for student engagement, whereby students, equipped with proficient self-regulation competencies, are better predisposed to set objectives, contrive learning strategies, and stoke their motivation (Adicondro & Purnamasari, 2011; Nückles et al., 2009; Wan et al., 2012; Zumbrunn et al., 2011). These self-regulatory competencies ultimately lend themselves to heightened behavioral engagement, as students judiciously allocate their time and resources, thereby facilitating the attainment of their scholastic aspirations. Furthermore, the metacognitive dimension embedded within SRL allows students to scrutinize their comprehension and make adaptive changes, consequently fostering cognitive engagement, nurturing the realms of profound understanding and analytical thought (Hadwin et al., 2007; Raković et al., 2022). As students reap the rewards of their self-regulated endeavors, a concomitant increase in emotional engagement is observed, as success begets satisfaction and an innate pleasure derived from the learning process. Student engagement, in turn, can act as an outcome of SRL. Astute and efficient self-regulated learners invariably experience elevated student engagement as a natural byproduct of their assiduous efforts. With students immersed in active involvement with the academic materials, the confluence of motivation and self-regulation yields a positive feedback loop, further amplifying engagement (Stone, 2000; Winne, 1997). Additionally, SRL and student engagement are not discrete silos; they interact in a mutually influential manner. When both SRL and engagement are elevated, they reciprocally reinforce each other, generating a more potent and efficacious learning experience. However, it is essential to acknowledge the variabilities in this relationship, contingent on individual disparities, contextual circumstances, and specific learning situations. Some students may innately exhibit high levels of self-regulation, resulting in augmented engagement, while others may cultivate self-regulation as a means to fortify their engagement. Furthermore, external variables like pedagogical methods, instructional design, and the overall classroom milieu may sway the strength of this relationship.

The mediating function of SRL and student engagement in the nexus between students’ personal attributes, external contexts, and their scholastic performance constitutes a pivotal facet of their significance in the realm of education (Ben-Eliyahu & Linnenbrink-Garcia, 2013; Butler & Winne, 1995; Dinsmore et al., 2008). Personal attributes, inclusive of prior knowledge, cognitive aptitude, and motivation, can exert substantial influence on the development of SRL. For instance, a student imbued with robust self-efficacy is predisposed to engage in self-regulated learning behaviors. Contextual factors, encompassing instructional design, teacher support, and the availability of learning resources, similarly mold the contours of SRL (Clark, 2012; Nicol & Macfarlane‐Dick, 2006; Schloemer & Brenan, 2006). An environment that fosters goal setting, inculcates metacognitive competencies, and stokes motivation is conducive to SRL, which, in turn, augments scholastic performance. Conversely, student engagement serves as a mediator in the linkage between personal attributes, contextual facets, and academic achievement. Personal attributes, such as intrinsic motivation, a fervor for the subject matter, and a sense of belonging, are poised to impact the degree of student engagement. Contextual elements, including the quality of teacher-student relations, the prevailing classroom ambiance, and the relevance of the curriculum, further exert substantial influence (Bidjerano, 2005; Pajares, 2002; Schunk, 1990). Elevated levels of both SRL and engagement create an environment conducive to optimal learning outcomes. The practical applications of this symbiotic relationship between SRL and student engagement within educational settings are abundant. Educators can leverage these insights to invigorate teaching and learning paradigms. For instance, the cultivation of SRL skills through explicit instruction in goal setting, learning strategy planning, comprehension monitoring, and motivation management empowers students to proactively engage in their learning journey (Dignath et al., 2008; Kramarski & Gutman, 2006; Schunk & Greene, 2017; Zimmerman & Kitsantas, 2005). Equally pivotal is the creation of a classroom environment that nurtures student engagement. Learning experiences should be designed with relevance and intrigue, teacher-student bonds should be fostering, and active participation in learning activities should be ardently encouraged. The infusion of technology stands as a promising vehicle for augmenting both SRL and student engagement. By endowing students with resources for self-regulation and rendering the learning process interactive and gratifying, technology becomes a potent catalyst. Personalized learning, tailored to the unique needs and preferences of individual students, can galvanize engagement and impel students to shoulder responsibility for their learning (Goh & Zeng, 2014; Järvelä et al., 2016; Panadero & Alonso-Tapia, 2014). Timely and constructive feedback emerges as a linchpin, vital for both SRL and student engagement, as it not only serves to apprise students about the effectiveness of their strategies but also propels them to persevere. Furthermore, instilling a growth mindset, one where students acknowledge that intelligence and competencies burgeon through endeavor, bears immense significance for SRL and engagement. This mindset equips students to confront challenges with alacrity, surmount setbacks, and relentlessly seek strategies for enhancing their learning (Butler, 2002; Winne, 1995; Ziegler & Moeller, 2012).

2. Self-regulated learning (SRL) and cognitive engagement

The concept of cognitive engagement assumes pivotal significance in the domains of educational psychology and self-regulated learning (SRL). To establish a meaningful nexus between the principles of SRL and cognitive engagement, it is imperative to gain an insightful understanding of what cognitive engagement encompasses and how it correlates with the learning process. Cognitive engagement can be aptly defined as the degree to which individuals deliberately employ thinking strategies during the process of learning or problem-solving within a specific task. This definition explicitly acknowledges the fluid and dynamic nature inherent in cognitive engagement, representing a marked departure from traditional views of cognitive abilities as fixed and immutable. To fully comprehend this concept, it is imperative to explore the diverse dimensions and facets encapsulated within this definition. First and foremost, cognitive engagement is characterized as a continuous process that fluctuates over time as students immerse themselves in the learning experience. This conception underscores that cognitive engagement is far from static; rather, it embodies a dynamic phenomenon that evolves as students interact with the materials and tasks presented in their learning environment. This perspective is congruent with the core principles of SRL, which underscore the active involvement of learners in the management of their learning processes (Fontana et al., 2015; Masui & De Corte, 2005; Winne, 2017; Winne & Perry, 2000). SRL posits that learning is a dynamic endeavor necessitating continuous adjustments and adaptations contingent upon the specific task and context at hand. Secondly, cognitive engagement is inextricably linked to specific subjects or learning activities. It is, therefore, context-dependent, varying from one learning task to another. For instance, a student may exhibit a high degree of cognitive engagement when grappling with a complex mathematical problem but may display lesser engagement when reading a novel. The level of cognitive engagement is influenced by the nature of the task, the student’s level of interest and motivation, and their existing knowledge and competencies (Lajoie, 2008; Sitzmann & Ely, 2011; Sperling et al., 2004). Recognizing this contextual aspect of cognitive engagement is pivotal in understanding how students approach diverse learning experiences and how educators can optimize cognitive engagement by devising engaging and pertinent learning tasks. Thirdly, cognitive engagement encompasses both qualitative and quantitative dimensions, as students allocate their cognitive resources to different learning strategies. This underscores the notion that cognitive engagement is not a one-size-fits-all concept. Students might engage in profound, critical thinking in one context, while in another, they may employ more rudimentary cognitive processes. The qualitative dimension of cognitive engagement pertains to the depth and intricacy of the cognitive processes invoked during a task. It may encompass higher-order cognitive skills such as analysis, evaluation, and synthesis or more elementary processes such as memorization and recall. The quantitative dimension, conversely, refers to the quantum of cognitive effort and resources devoted to a task. Certain tasks may necessitate intense concentration and cognitive resources, while others may entail a lesser demand. This multifaceted nature of cognitive engagement aligns harmoniously with the principles of SRL, which underscore the significance of selecting and employing apt learning strategies contingent upon the task at hand (Corno, 1986; Isaacson & Fujita, 2006; Schunk, 2008; Winne, 1996). SRL hinges upon metacognitive processes, which empower students to make deliberate decisions regarding how to engage cognitively with diverse types of content and learning contexts. Lastly, the definition underscores the cognitive facet of learning, which can transpire either unconsciously or under metacognitive control. This suggests that cognitive engagement may not invariably entail a conscious or deliberate process. Students can engage in cognitive activities without full awareness, as observed when they passively peruse a text. However, metacognitive control empowers students to consciously monitor and regulate their cognitive processes. Metacognitive awareness constitutes a central tenet of SRL, where students actively contemplate their thought processes, establish goals, formulate strategies, monitor their progress, and make the requisite adjustments (Puustinen & Pulkkinen, 2001; Rheinberg et al., 2000; Winne et al., 2002; Zimmerman, 1989). SRL furnishes students with the framework to assume control over their cognitive engagement by guiding them in the selection of suitable strategies, the monitoring of their comprehension, and the adaptation of their approach to optimize learning. This conceptualization of cognitive engagement marks a departure among researchers, transitioning from a perception of cognitive engagement as a static ability to an acknowledgement of its dynamic and ever-evolving nature throughout the learning process. This shift aligns with modern research in educational psychology that focuses on the active, malleable, and context-dependent facets of cognitive engagement (McPherson & McCormick, 1999; Pintrich & De Groot, 1990; Schunk & Zimmerman, 2012; Zimmerman & Schunk, 2012). SRL encompasses metacognitive processes, including goal-setting, planning, monitoring, and self-regulation, all of which assume a central role in steering cognitive engagement (Pajares, 2012; Young, 2005; Zimmerman & Schunk, 2011). For instance, when students delineate clear learning objectives, they are more inclined to engage cognitively in a purposeful and focused manner. Goals provide direction for cognitive engagement, assisting students in setting priorities for their cognitive resources. Similarly, the planning phase of SRL empowers students to select appropriate cognitive strategies for a given task. Effective planning entails decisions regarding the allocation of cognitive resources, including the choice of critical thinking, problem-solving, or memorization strategies. This strategic planning elevates the quality of cognitive engagement, ensuring that students invest their cognitive resources judiciously. Monitoring and self-regulation, both vital components of SRL, play a pivotal role in optimizing cognitive engagement (Eshel & Kohavi, 2003; Schmitz & Wiese, 2006; Winne & Hadwin, 2013; Zimmerman & Cleary, 2009). When students actively monitor their comprehension of a topic or their progress on a task, they can make real-time adjustments to their cognitive engagement. If they perceive a lack of comprehension or find that their existing cognitive strategies are ineffectual, they can recalibrate their cognitive engagement by selecting more suitable strategies, seeking supplementary resources, or soliciting assistance. Cognitive engagement and SRL are intertwined, as the degree of cognitive engagement impacts self-regulation, and conversely, self-regulation processes guide and amplify cognitive engagement (Barnard-Brak et al., 2010; McMahon & Oliver, 2001; Narciss et al., 2007; Winne, 2005). The dynamic nature of cognitive engagement becomes evident as students adjust and fine-tune their cognitive engagement when confronted with challenges, the acquisition of new information, and the refinement of their comprehension. Educators can leverage this insight to devise learning environments that promote optimal cognitive engagement and support students in honing their SRL proficiencies. By devising tasks that are intellectually challenging and personally pertinent, educators can kindle cognitive engagement. Encouraging metacognitive contemplation and goal-setting can further enhance students’ awareness of their cognitive processes and how to strategically engage with learning tasks. Furthermore, SRL interventions can explicitly educate students in how to engage cognitively with different content and learning contexts. These interventions equip students with metacognitive strategies for establishing goals, formulating strategies, monitoring comprehension, and making the requisite adjustments to their cognitive engagement (Bannert, 2009; Butler, 2023; McCombs & Marzano, 1990; Willy & Maarten, 2012). This approach empowers students to assume control over their cognitive processes and optimize their cognitive engagement, culminating in improved learning outcomes. The nexus between cognitive engagement and SRL also bears relevance for the evaluation of learning and the design of educational interventions. Assessments can be tailored to gauge not only what students have learned but also how they engage cognitively with the content. This furnishes a more comprehensive understanding of their learning process and can inform instructional decisions (Wolters, 2003; Zimmerman & Schunk, 2001a). By identifying students who may be disengaged or failing to regulate their cognitive processes effectively, educators can customize interventions to address these specific needs. Moreover, technology and learning analytics play a significant role in buttressing cognitive engagement and SRL. Digital platforms can provide real-time feedback to students concerning their cognitive engagement and self-regulation. For instance, learning analytics can track students’ interactions with digital learning materials and offer insights into their cognitive engagement, including which parts of the content command the most attention and where they face challenges. This data can be employed to proffer personalized feedback and recommendations, aimed at enhancing cognitive engagement and self-regulation. The dynamic nature of cognitive engagement within the context of self-regulated learning (SRL) holds a pivotal position in contemporary educational psychology and instructional design. Recognizing cognitive engagement as a continuous, context-dependent, and multifaceted process is imperative for understanding how students approach learning tasks, how educators can foster optimal engagement, and how SRL processes can be harnessed to enrich cognitive engagement (Bidjerano & Dai, 2007; Dent & Koenka, 2016; Muis, 2007; Panadero, 2017; Pintrich, 2000). The interplay between cognitive engagement and SRL is evident in how SRL processes contribute to the development and regulation of cognitive engagement. Educators and researchers can leverage this understanding to devise effective learning environments, interventions, and assessments that support students in optimizing their cognitive engagement and self-regulation (Cheng, 2011; Garcia, 1995; Meece, 2023; Pintrich, 1999). This integrated approach bears the potential to enhance learning outcomes and empower students to become more effective and self-regulated learners.

3. Similarities, interrelationships, and differences between SRL and cognitive engagement

The differentiation between SRL and cognitive engagement is critical for educators and researchers. It enables a more comprehensive understanding of how students manage their learning and engage with educational content. By recognizing the unique contributions and attributes of each construct, educators can design interventions that encompass both cognitive engagement and broader self-regulatory processes, offering comprehensive support for students’ learning success. While each of the constructs possesses its unique attributes, researchers have increasingly recognized the interplay between them and the potential for cognitive engagement to play a vital role in facilitating effective self-regulated learning (Goetz et al., 2013; Kitsantas & Dabbagh, 2011; Loyens et al., 2008; McCombs, 1986; Usher & Pajares, 2008). This perspective shifts the focus from one construct subsuming the other to a more nuanced exploration of their interactions and how cognitive engagement can enhance the process of self-regulated learning. One perspective, embraced by researchers, emphasizes that SRL and cognitive engagement are distinct yet intricately connected constructs. Instead of viewing cognitive engagement as a subset of SRL or vice versa, this perspective examines how cognitive engagement contributes to and interacts with various components and phases of SRL. This approach acknowledges the uniqueness of both constructs while highlighting their interrelationships and mutual influence. For instance, Pintrich and de Groot proposed a comprehensive model of SRL that includes three fundamental components: cognitive strategies, students’ management and control of effort, and metacognitive strategies (Pintrich & De Groot, 1990). Each of these components is closely related to cognitive engagement. Cognitive strategies, such as rehearsal and elaboration, are utilized by learners to process information and actively engage their cognitive faculties. Students’ management and control of effort involve the allocation of cognitive resources to learning tasks, necessitating cognitive engagement to sustain the requisite mental effort. Metacognitive strategies enable learners to monitor their cognitive engagement levels and make adjustments based on internal and external feedback. This interconnectedness between cognitive engagement and SRL components underscores the pivotal role that cognitive engagement plays in fostering effective self-regulated learning (Kosnin, 2007; Lennon, 2010; Nodoushan, 2012; Schraw et al., 2006; Winne, 2016). Learners actively employ cognitive strategies, manage their cognitive resources, and regulate their cognitive engagement to optimize their learning outcomes. Cognitive engagement serves as a vehicle through which students enact these self-regulatory processes. This perspective on the interplay between cognitive engagement and SRL transcends a simplistic view of one construct being subsumed by the other and delves into the specific mechanisms and processes through which cognitive engagement influences and supports SRL (McCaslin & Daniel, 2013; McCombs, 2013; Wolters, 1998; Zimmerman, 1990; Zimmerman & Schunk, 2001b). Empirical studies have also embarked on exploring how cognitive engagement manifests across and within different phases of SRL. Researchers have sought to understand how cognitive engagement unfolds in the context of self-regulated learning, shedding light on the dynamic nature of students’ learning experiences. These studies have been conducted across various educational settings and subjects, revealing the versatility and relevance of the relationship between cognitive engagement and SRL. For example, Jarvela and colleagues conducted a study involving the collection of 84 hours of video recordings that captured the interactions of 44 students collaborating during a math course (Järvelä et al., 2016). These recordings were coded based on types of engagement, differentiating between cognitive engagement and socioemotional engagement, and were mapped to SRL phases (forethought, performance, and reflection). This approach allowed them to examine how cognitive engagement varies throughout different phases of SRL, providing insights into the nuanced interplay between these constructs. Similarly, Goh and Zeng conducted a longitudinal study involving four students engaged in SRL activities during English listening tests (Goh & Zeng, 2014). They tracked the learners’ engagement throughout four SRL phases: task definition, goal setting and planning, strategy enactment, and metacognitive adaptation. By examining cognitive engagement within these distinct phases, the study offered valuable insights into how cognitive engagement changes over the course of self-regulated learning. The findings revealed that cognitive engagement manifested differently across the SRL phases, irrespective of the specific SRL models utilized. These empirical investigations highlight the intricate nature of the relationship between cognitive engagement and SRL. They demonstrate that cognitive engagement is not a static or uniform construct but one that adapts to the specific demands and contexts of SRL phases. SRL components, such as cognitive strategies, students’ management and control of effort, and metacognitive strategies, are closely related to cognitive engagement, as they require learners to actively engage their cognitive faculties and allocate mental effort to learning tasks (Alexander et al., 2011; Boekaerts, 1996; Cassidy, 2011; Pintrich & Garcia, 1994; Wirth & Leutner, 2008). By acknowledging the distinct yet interconnected nature of these constructs, researchers and educators can design interventions that promote effective learning strategies and provide support that aligns with the dynamic nature of cognitive engagement and self-regulated learning.

Butler and Winne’s SRL model introduced the notion of self-regulated cognitive engagement as a dynamic and integral facet of SRL (Butler & Winne, 1995). Central to their framework is the significance attributed to monitoring as a linchpin in the realm of self-regulated cognitive engagement. In this context, monitoring alludes to learners’ cognizance of their cognitive engagement, encompassing cognitive strategies, metacognitive processes, and the depth of cognitive processing they employ. It also involves learners’ ability to discern the chasm between their prevailing cognitive engagement level and their pre-established learning objectives. The emphasis on monitoring accentuates the paramount importance of self-awareness in the realm of SRL. Learners must be cognizant of their cognitive engagement levels and the alignment of their engagement with their educational aspirations. Through vigilant monitoring, students can appraise the profundity of their involvement with the learning material, the efficacy of their cognitive strategies, and the trajectory toward the realization of their learning goals. Furthermore, the model posits that cognitive engagement is amenable to change and responsive to the goals learners embrace within the SRL framework. However, the model introduced a measure of ambiguity and potential confusion. One concern arises from the apparent interchangeability of terms in their research, where “self-regulated cognitive engagement,” “SRL,” and “cognitive engagement” are seemingly utilized interchangeably. This interchangeable usage can give rise to conceptual perplexities concerning the distinctions among these terms and their interrelationships within the SRL framework. Moreover, their model lacks a precise delineation of cognitive engagement. It encompasses a broad spectrum of cognitive processes, encompassing students’ beliefs, knowledge, and learning strategies. This expansive scope of cognitive engagement begets queries pertaining to the precise conceptualization of cognitive engagement in SRL contexts and the means by which it can be meticulously demarcated from the overarching SRL construct.

4. Delineating cognitive engagement in the context of self-regulated learning

To differentiate cognitive engagement from both self-regulated learning (SRL) and self-regulated cognitive engagement, it is crucial to discern the core attributes that distinguish these terms. Cognitive engagement pertains to the degree to which learners channel their cognitive resources, exert effort, and exhibit mental involvement in the process of learning. It encompasses cognitive strategies, the depth of cognitive processing, and the active utilization of cognitive resources when confronted with learning tasks. Notably, cognitive engagement serves as a fundamental component of SRL, as it encapsulates the qualitative aspects of learners’ interactions with educational materials and the strategies they employ (Artino, 2007; Carter et al., 2020; Kremer-Hayon & Tillema, 1999; Moos & Ringdal, 2012). SRL, on the other hand, encompasses a broader conceptual framework that subsumes cognitive engagement as one of its constituents. It involves learners’ active management and regulation of diverse facets of their learning experience, spanning cognitive, metacognitive, emotional, and motivational dimensions. SRL entails a deliberate process wherein learners consciously govern their learning activities to achieve specific objectives, thus exemplifying a sense of agency and self-control in the learning process (Chen, 2002; Harris et al., 2011; Theobald, 2021; Winne, 2013; Wolters & Taylor, 2012). Within the scope of SRL, cognitive engagement is a subset within the cognitive dimension. This term, self-regulated cognitive engagement, as introduced by Butler and Winne, specifically underscores the roles of monitoring and self-regulation in cognitive engagement, particularly within the context of SRL. Self-regulated cognitive engagement revolves around learners’ awareness and control of their cognitive involvement, with the aim of ensuring that it aligns harmoniously with their learning goals. This term accentuates the iterative and self-adjusting nature of cognitive engagement when operating within the confines of SRL (Azevedo & Witherspoon, 2009; Duckworth et al., 2009; Leutner et al., 2007; Martin, 2004). The act of distinguishing these terminologies aids in clarifying their interrelationships within the overarching SRL framework. While cognitive engagement undoubtedly constitutes an integral facet of SRL, it primarily emphasizes the qualitative dimensions of cognitive involvement. On the contrary, SRL encompasses a broader spectrum of self-regulatory mechanisms, extending beyond cognitive engagement to encompass metacognition, motivation, and the regulation of emotions (Bjork et al., 2013; Boekaerts, 1995, 1997; Corno, 1989). Self-regulated cognitive engagement serves as a focused exploration within the expansive domain of SRL, accentuating the pivotal roles played by monitoring and self-regulation within the cognitive dimension of learning. To comprehend the dynamic nature of cognitive engagement within the context of SRL, an in-depth investigation into its temporal attributes is requisite. Cognitive engagement is far from a static and unchanging state; rather, it undergoes continuous evolution as learners navigate through the various phases of SRL (Boekaerts & Niemivirta, 2000; Schunk & Zimmerman, 1998; Torrano Montalvo & González Torres, 2004). Demarcating cognitive engagement from SRL and self-regulated cognitive engagement is indispensable for advancing more precise theoretical frameworks (Boekaerts, 1999; Kuo, 2010; Pressley & Ghatala, 1990; Schunk, 2005). This differentiation forms the foundation for the development of effective instructional practices and interventions designed to harness cognitive engagement for the enhancement of learning outcomes.

5. Leveraging the potential of cognitive engagement in education

Unlocking the potential of cognitive engagement in educational contexts necessitates educators to consider several implications. It is advisable to encourage learners to set specific, challenging, and attainable goals that are poised to guide their cognitive engagement. Clearly defined goals not only help mold the depth and intensity of cognitive involvement but also serve as guiding beacons throughout the learning process. Equally important is the provision of support to students in the development of effective learning strategies and approaches during the planning phase. Offering guidance in the selection of cognitive strategies aligned with their goals and the nature of the learning task is critical. To foster cognitive engagement, it is vital to create learning environments that promote active interaction with educational materials (Baggetun & Wasson, 2006; Dweck & Master, 2012; Hadwin & Oshige, 2011; Risemberg & Zimmerman, 1992). Encouraging the cultivation of skills such as critical thinking, problem-solving, and deep cognitive processing can contribute to enhanced cognitive engagement (Schunk, 2013; van Houten‐Schat et al., 2018; White et al., 2013). Emphasizing the significance of self-assessment and reflection at the conclusion of learning tasks is essential. Assisting learners in the acquisition of metacognitive skills that enable them to adapt and optimize their cognitive engagement based on their assessments is equally vital. The incorporation of feedback mechanisms that provide students with insights into the quality of their cognitive engagement should be a central element of educational practices. Such mechanisms might encompass self-assessment rubrics, peer evaluations, or feedback from instructors (Butler, 1998; Clark & Zimmerman, 1990; Pintrich & Zusho, 2007). It is important to acknowledge that different learners may exhibit various preferences and strengths when it comes to cognitive engagement. As such, individualized approaches to cognitive engagement strategies can contribute to the effectiveness of SRL. Incorporating tools and technologies that aid learners in monitoring and regulating their cognitive engagement is indispensable. Digital learning platforms, for example, can offer real-time feedback on cognitive processes and the allocation of resources, thus facilitating the self-regulatory aspects of cognitive engagement. By integrating these implications into instructional practices, educators can nurture adaptive and self-regulated cognitive engagement, empowering learners to actively engage in their educational journeys (Eilam & Aharon, 2003; Pajares & Valiante, 2002; Wang et al., 2013). Furthermore, the deeper comprehension of cognitive engagement within the SRL framework continues to guide research and practice, ultimately augmenting the quality of education and enhancing learning outcomes for students.

6. Framework of Self-Regulated Cognitive Engagement (FSRCE)

Developing a powerful and comprehensive model that effectively links self-regulated learning (SRL) and cognitive engagement requires a balanced approach, capitalizing on the strengths of existing research while addressing the limitations. Toward this end, we have developed a comprehensive model that seeks to offer a more refined framework for understanding the intricate dynamics between SRL and cognitive engagement. It has been named the “Framework of Self-Regulated Cognitive Engagement (FSRCE).” Its purpose is to advance the integration of self-regulated learning (SRL) and cognitive engagement. The dynamics of learning have intrigued educators and psychologists for centuries. How do students actively engage with the material they are learning with? How can they be motivated to regulate their learning processes and achieve their educational goals? Two fundamental constructs, Self-Regulated Learning (SRL) and Cognitive Engagement, play pivotal roles in understanding and addressing these questions. The integration of SRL and Cognitive Engagement represents an ongoing and evolving endeavor in the field of educational psychology. Both constructs have been extensively studied and have offered valuable insights into how students learn, but they are not without their challenges and limitations. To navigate these complexities, the Framework of Self-Regulated Cognitive Engagement (FSRCE) has been proposed as a unified model. The FSRCE model aims to address and overcome the limitations of previous frameworks by offering a refined and comprehensive perspective on the interplay between SRL and Cognitive Engagement. Here we discuss the FSRCE model, elucidating its components, principles, and implications. By exploring the framework in detail, we aim to provide educators, researchers, and students with a comprehensive understanding of the FSRCE model’s potential to enhance learning experiences (Figure 1).

6.1. The core principles of FSRCE

The FSRCE model is rooted in five core principles that underpin its structure and function. These principles are foundational to our understanding of how SRL and Cognitive Engagement interact within the framework:

1. Dynamic SRL Loop: The FSRCE model incorporates a dynamic SRL loop consisting of four interconnected phases: the Forethought Phase, the Performance Phase, the Monitoring and Feedback Loops, and the Self-Reflection Phase. This loop signifies the iterative nature of self-regulated learning, highlighting the continuous process of students managing their cognitive engagement throughout their learning journey.

2. Cognitive Engagement Dimensions: To address the limitations of existing models, the FSRCE framework introduces two distinct dimensions of Cognitive Engagement: Cognitive Engagement Depth and Cognitive Engagement Strategies. These dimensions allow for a more nuanced understanding of how students actively participate in the learning process and the strategies they employ.

3. Individual and Contextual Factors: Recognizing the influence of personal and contextual factors, the FSRCE framework takes into account intrinsic motivation, goal orientation, self-efficacy beliefs, and various external factors. These factors contribute to the shaping of Cognitive Engagement and its interplay with SRL.

4. Ongoing Adaptation and Optimization: An essential feature of the FSRCE model is the emphasis on continuous adaptation and optimization. Students are not bound by a static level of cognitive engagement but are encouraged to adapt and optimize their cognitive involvement based on evolving task demands and feedback.

5. Integration of Cognitive and Behavioral Engagement: The FSRCE framework addresses the distinction between cognitive and behavioral engagement. It acknowledges that Cognitive Engagement involves the depth of mental involvement, while Behavioral Engagement focuses on observable actions and participation in learning activities. By examining how these dimensions interact within the SRL loop, the model provides a more comprehensive understanding of students’ learning experiences.

6.2. The dynamic SRL loop

At the heart of the FSRCE model is the dynamic SRL loop, which serves as the backbone for the integration of SRL and Cognitive Engagement. This loop reflects the iterative and cyclical nature of self-regulated learning. It consists of four distinct phases, each contributing to the overall process of cognitive engagement.

6.2.1. Forethought Phase: task analysis and goal setting

The Forethought Phase embodies the proactive engagement of students in their learning journey. It commences when students encounter a learning task. At this point, students engage cognitively by analyzing the learning task, setting clear and specific goals, and developing plans to achieve those goals. The depth of cognitive engagement in this phase involves the extent to which students delve into understanding the task’s requirements and their proactive efforts to strategize. The more students engage cognitively at this stage, the better prepared they are for effective self-regulation in the subsequent phases. This phase underscores the importance of cognitive engagement in shaping goal-oriented behavior. Students who actively engage in this phase are more likely to set challenging but achievable goals, demonstrating an understanding of how to optimize their learning.

6.2.2. Performance Phase: self-control and strategy implementation

The Performance Phase represents the active self-regulation of cognitive engagement. It is the stage where students optimize their cognitive involvement in their learning processes. During this phase, students employ a range of self-control processes, such as self-instruction, attentional focus, and the use of various cognitive and metacognitive strategies. The depth of cognitive engagement in this phase hinges on the strategies students adopt and their ability to adapt these strategies based on task requirements and feedback. This phase emphasizes that cognitive engagement involves not only the initial depth of involvement but also the ability to allocate cognitive resources strategically. Students who engage cognitively in the Performance Phase actively control and adapt their cognitive strategies to ensure the effectiveness of their learning.

6.2.3. Monitoring and Feedback Loops

At the core of the FSRCE framework is a robust system of Monitoring and Feedback. Students actively monitor their cognitive engagement levels during both the Forethought and Performance Phases. This internal monitoring is essential as it allows students to gauge the effectiveness of their strategies and cognitive involvement. Moreover, external feedback from various sources, including teachers, peers, and learning tools, provides additional insights into the effectiveness of students’ cognitive engagement. This external feedback is instrumental in guiding students in fine-tuning their cognitive strategies and enhancing their learning processes. The Monitoring and Feedback Loops emphasize the iterative nature of self-regulated cognitive engagement. Students continuously adapt and adjust their cognitive involvement based on the feedback they receive, making it an integral part of the SRL loop.

6.2.4. Self-Reflection Phase: evaluation and adjustment

The Self-Reflection Phase in the FSRCE framework is where students assess the extent to which their cognitive engagement contributed to the expected learning outcomes. They critically evaluate their strategies, attributing their successes or failures to the effectiveness of these strategies. Cognitive engagement in this phase primarily involves metacognitive processes. This phase underscores the capacity of students to engage cognitively in the evaluation and adjustment of their learning strategies. The depth of cognitive engagement is revealed in their ability to reflect critically on their strategies, identify areas for improvement, and make informed decisions about future cognitive engagement.

6.3. Cognitive engagement dimensions

A significant advancement of the FSRCE framework is the introduction of two distinct dimensions of Cognitive Engagement: Cognitive Engagement Depth and Cognitive Engagement Strategies. These dimensions offer a more nuanced understanding of students’ cognitive involvement and provide a structured framework for analyzing and measuring cognitive engagement.

6.3.1. Cognitive Engagement Depth

Cognitive Engagement Depth is the dimension that measures the intensity and depth of cognitive involvement throughout the SRL loop. It assesses the degree to which students immerse themselves in the learning process. The dimension takes into account the students’ commitment to understanding the task, their mental investment in goal-setting and planning, their capacity to adapt strategies, and their metacognitive involvement in self-reflection. A higher level of Cognitive Engagement Depth signifies a more profound mental commitment to the learning process. It is indicative of students who actively immerse themselves in their learning tasks, consistently striving to optimize their cognitive engagement.

6.3.2. Cognitive Engagement Strategies

Cognitive Engagement Strategies, the second dimension, focuses on the types of strategies students employ during their learning process. These strategies can range from shallow and surface-level, such as rehearsal and memorization, to deep and transformative, such as elaboration, critical thinking, and problem-solving. This dimension enables the examination of the specific strategies students employ within the different SRL phases. The Cognitive Engagement Strategies dimension underlines the importance of considering the specific strategies used during the SRL loop. It acknowledges that not all cognitive strategies are equal and that students’ choice of strategies significantly impacts their cognitive engagement. A higher level of Cognitive Engagement Strategies indicates a deliberate and sophisticated approach to learning.

6.4. Individual and contextual factors

The FSRCE framework recognizes the influence of personal and contextual factors that shape students’ cognitive engagement within the SRL loop. Understanding how these factors impact cognitive engagement is crucial for designing effective learning environments and interventions.

6.4.1. Intrinsic motivation and goal orientation

Students’ intrinsic motivation and goal orientation are central components of the FSRCE model. Intrinsic motivation serves as a driving force behind students’ cognitive engagement, pushing them to actively participate in the learning process. Goal orientation, including mastery goals and performance goals, significantly influences the strategies students employ to engage cognitively. Students with mastery goals tend to focus on deep, understanding-driven strategies, while those with performance goals may opt for surface-level strategies to achieve high grades. This dimension highlights the need to consider the motivational aspect of cognitive engagement. Students who are intrinsically motivated and possess a mastery goal orientation are more likely to engage deeply and effectively with the learning material.

6.4.2. Self-efficacy beliefs

Self-efficacy beliefs, another influential factor within the FSRCE framework, play a substantial role in shaping students’ cognitive engagement. These beliefs are rooted in students’ perceptions of their ability to engage cognitively and regulate their learning processes effectively. High self-efficacy fosters a proactive and confident approach to learning, enabling students to invest more deeply in their cognitive engagement. The FSRCE model emphasizes the importance of fostering students’ self-efficacy beliefs. When students believe in their capability to engage effectively, they are more likely to invest in deeper cognitive engagement throughout the SRL loop.

6.4.3. Contextual factors

Contextual factors, such as teacher support, peer collaboration, and the availability of learning resources, significantly influence students’ cognitive engagement. A supportive learning environment that encourages active participation and provides access to relevant resources can enhance students’ cognitive engagement. Recognizing the impact of external factors, the FSRCE framework highlights the importance of creating conducive learning environments. Educators and institutions should aim to optimize these contextual factors to facilitate and enhance students’ cognitive engagement.

6.5. Ongoing adaptation and optimization

An inherent feature of the FSRCE model is the emphasis on continuous adaptation and optimization of cognitive engagement. Students are not limited to a fixed level of cognitive engagement but are encouraged to adapt and optimize their cognitive involvement based on the evolving demands of the learning task and the feedback they receive. This principle underscores the dynamic and responsive nature of the FSRCE framework. Students are empowered to actively adjust their cognitive engagement, thereby optimizing their learning processes as they progress through the SRL loop.

6.6. Integration of cognitive and behavioral engagement

In acknowledging the distinction between cognitive and behavioral engagement, the FSRCE framework offers a more comprehensive understanding of students’ learning experiences. It recognizes that Cognitive Engagement encompasses the depth of mental involvement, while Behavioral Engagement focuses on observable actions and participation in learning activities. By examining how these dimensions interact within the SRL loop, the model provides a holistic view of students’ learning experiences. It emphasizes that effective learning involves both cognitive and behavioral engagement and that the integration of these dimensions is crucial for achieving optimal learning outcomes.

6.7. The power of FSRCE

The Framework of Self-Regulated Cognitive Engagement (FSRCE) represents a powerful and unified model that bridges the domains of Self-Regulated Learning (SRL) and Cognitive Engagement. By emphasizing the cyclical nature of SRL, introducing two dimensions of Cognitive Engagement, considering individual and contextual factors, and emphasizing ongoing adaptation, the FSRCE model offers a comprehensive framework for understanding the complex interplay between SRL and Cognitive Engagement. This framework has the potential to revolutionize educational practices and interventions. It empowers educators to foster an environment that nurtures and sustains students’ cognitive engagement throughout their learning journeys. It offers students a blueprint for taking an active role in their learning, optimizing their cognitive engagement, and achieving enhanced learning outcomes. The FSRCE model is a testament to the evolution of educational psychology. It brings us closer to unraveling the mysteries of student learning by unifying and refining our understanding of SRL and Cognitive Engagement. In the ever-evolving landscape of education, FSRCE represents a beacon of guidance for educators, researchers, and learners on the path to more effective and meaningful educational experiences.

7. Future research and way forward

The development of the Framework of Self-Regulated Cognitive Engagement (FSRCE) represents a significant advancement in our understanding of the interplay between Self-Regulated Learning (SRL) and Cognitive Engagement. While this research has laid a strong foundation, it is important to consider the implications for future research, as well as the potential applications and practical implications of the FSRCE framework. One key avenue for future research is the need for empirical validation of the FSRCE framework. Although the framework is built on a synthesis of existing research, it is essential to conduct empirical studies to test its validity and applicability in real-world educational settings. Such studies could involve the development of assessment tools and instruments designed to measure the various dimensions of cognitive engagement as outlined in the framework. Researchers can then utilize these tools to investigate the relationships and interactions between cognitive engagement and SRL. Longitudinal studies that track students’ cognitive engagement and self-regulation over time would provide insights into the dynamic nature of these constructs and how they evolve throughout the learning process. Furthermore, researchers should explore the implications of the FSRCE framework for the design of instructional interventions and educational practices. By aligning instructional methods with the principles of the framework, educators can create learning environments that facilitate and enhance students’ self-regulated cognitive engagement. Future research should focus on identifying effective strategies and interventions that promote optimal cognitive engagement within each phase of SRL. This could involve the development of innovative pedagogical approaches, technology-enhanced learning environments, and feedback mechanisms that encourage students to regulate their cognitive engagement effectively. The FSRCE framework invites researchers to delve deeper into the mechanisms that underlie cognitive engagement and its role in SRL. While the framework offers a comprehensive overview, further studies can investigate the specific cognitive and metacognitive processes involved in each dimension of cognitive engagement. For instance, research could explore how different types of cognitive strategies impact the depth and intensity of cognitive engagement. Investigations into the neurocognitive aspects of cognitive engagement and SRL could provide valuable insights into the brain processes underlying self-regulation and engagement. Moreover, examining the influence of cognitive engagement on students’ affective states, such as motivation, emotion, and interest, can shed light on the emotional dimensions of SRL and its interaction with cognitive processes. Another avenue for future research is the exploration of individual and contextual factors that influence cognitive engagement. While the FSRCE framework recognizes the importance of factors like intrinsic motivation, goal orientation, and self-efficacy beliefs, researchers should delve deeper into how these variables interact and shape cognitive engagement. For example, studies could investigate how students’ motivational profiles impact their cognitive engagement in different learning contexts. The influence of cultural and contextual factors on cognitive engagement should also be explored, as these elements can significantly affect students’ self-regulatory practices. The FSRCE framework presents an opportunity to revisit the concept of engagement as a learning outcome. Future research should focus on developing valid and reliable measures to assess the cognitive and behavioral dimensions of engagement as integral aspects of the learning process. This could involve the creation of assessment tools that capture the active participation of students in their learning and problem-solving activities. By treating engagement as an integral part of learning rather than a separate endpoint, researchers can gain a more holistic understanding of how students engage with academic tasks. Moreover, research should investigate the role of cognitive engagement in fostering higher-order thinking skills and critical thinking. The FSRCE framework suggests that students who are deeply and intensively engaged in the learning process are more likely to employ higher-level cognitive skills. Empirical studies can examine the relationship between cognitive engagement and the development of critical thinking, problem-solving, and decision-making abilities. This exploration can inform educational practices aimed at enhancing students’ cognitive and metacognitive processes. Additionally, future research should consider the potential for individual differences in cognitive engagement. Not all students will engage with learning tasks in the same way, and understanding these differences is crucial for tailoring educational interventions. Investigating factors such as personality traits, learning styles, and cognitive abilities can offer insights into why some students may be more deeply engaged than others. Researchers can then develop strategies to accommodate diverse learning profiles and optimize cognitive engagement for all students. The integration of technology and digital learning environments presents a compelling avenue for future research. With the rapid advancement of educational technology, researchers can explore how digital tools, simulations, and virtual learning environments influence cognitive engagement and SRL. The FSRCE framework can serve as a guide for investigating the design of technology-enhanced learning experiences that promote self-regulated cognitive engagement. These studies can uncover how the interplay between cognitive engagement and digital tools affects learning outcomes. Finally, the FSRCE framework can pave the way for the development of educational policies that promote active cognitive engagement in students. Policymakers can use the principles of the framework to guide curriculum development, assessment practices, and teacher training. By recognizing the significance of cognitive engagement and SRL, educational policies can align with the best practices in fostering optimal learning experiences. The journey we embarked on in this research paper, from the critical examination of existing models to the development of the FSRCE framework, has illuminated the complex interplay between SRL and Cognitive Engagement. The way forward is clear—empirical validation, practical application, deeper exploration, and policy alignment. This research is a stepping stone toward a future where education is not just a transmission of knowledge but an active, engaged, and self-regulated process that empowers students to become lifelong learners. With the FSRCE framework as our guide, we invite the educational community to join us on this exciting journey toward enhancing student learning experiences and preparing them for the challenges and opportunities of the 21^st century.

8. Conclusion

In this research article, we embarked on a journey to unravel the intricate relationship between Self-Regulated Learning (SRL) and Cognitive Engagement, culminating in the development of the Framework of Self-Regulated Cognitive Engagement (FSRCE). By critically examining existing literature, identifying limitations, and synthesizing insights from multiple models and studies, we have contributed to a deeper understanding of the dynamic interplay between these constructs and have proposed a powerful model for future exploration. Through this model, we have broadened the horizons of educational research, providing a compass for educators and students on their shared educational journey, while also fueling the curiosity of future researchers and fostering an environment of inquiry, reflection, and growth in the field of education. As this paper concludes, we look to the future with optimism, aware of the transformative potential of the FSRCE framework. Education is a voyage, and the FSRCE model is a map that can guide us toward uncharted territories, fostering a deeper understanding of the complex processes that shape how students learn, engage, and ultimately succeed. We invite educators, researchers, and policymakers to embrace the FSRCE model and embark on their journey to unlock the full potential of education, fostering a new generation of empowered, self-regulated, and cognitively engaged learners.

Figure 1. The Framework of Self-Regulated Cognitive Engagement (FSRCE) model.

The figure shows the FSRCE model that is rooted in five core principles namely Dynamic SRL Loop, Cognitive Engagement Dimensions, Individual and Contextual Factors, Ongoing Adaptation and Optimization, and Integration of Cognitive and Behavioral Engagement. Each of these core components are put inside a circle in the diagram with arrows showing relationships and interconnectedness between them.

Data availability statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Ashraf Alam

Ashraf Alam is a Ph.D. Scholar at IIT Kharagpur. He holds a master’s degree in education and a bachelor’s degree in computer science and engineering from the University of Delhi. Over the course of Ashraf’s academic journey, his research and teaching interests have inclined toward the philosophy and sociology of education and in areas of research ethics, educational psychology, and educational technology. He works at the crossroads of research and action for sustainable development, focusing on policies that impact the vulnerable. Currently, he is researching the different facets of ‘Positive Education’ at the Rekhi Centre of Excellence for the Science of Happiness at IIT Kharagpur under the esteemed guidance and patronage of Prof. Atasi Mohanty.

Atasi Mohanty

Atasi Mohanty, PhD, is an Assistant Professor at the Rekhi Centre of Excellence for the Science of Happiness, Indian Institute of Technology Kharagpur, India. Her research interests include positive youth development, social psychology, youth mental health, the science of happiness, prosocial behavior, happiness at the workplace, sustainable health and wellbeing, positive psychology, organizational behavior, Indian psychology, and sustainable entrepreneurship. She is currently guiding 14 Ph.D. research scholars.