Self Regulated Learning (Literature Review)
In this post I’ll do a deep dive into self-regulated learning. Enjoy!
Introduction
The barrier-to-entry for self-regulated learning is high despite incredible purported benefits. A learner who has somehow discovered self-regulated learning must understand a fractured literature that lacks agreed upon concrete recommendations, set up tools for goal setting, environmental optimization, energy monitoring, and reflection, and then use and iterate on those systems and tools habitually. Self reflection and metacognitive scaffolding are effective, yet introducing students to simple practices like reflective journaling is met with confusion and apathy.
In this work we review the literature on self-regulation and propose a practical model of self regulation for individual studying. We focus on an individual Constructivist view of Education Psychology and Human Computer Interaction and discuss considerations for learners’ primary and secondary cognitive load.
Related Work
To understand the fundamental Individual Constructivist view we overview research in Constructivism and Cognitivism applied in both Education Psychology and Human Computer Interaction. Then we examine specific examples of interfaces designed for self-regulation.
Constructivism: A Constructivist view of learning theory emphasizes the learner’s role in self-generating cognitive schema. This learner-centric view can be contrasted against a Behaviorist perspective that considers learning to be training with rewards and punishments (Weller, 2020). Development of constructivism can be traced back to Piaget and Vygotsky. Piaget is often cited as the father of individually-focused Constructivism, and Vygotsky expanded on Piaget’s ideas and introduced the Zone of Proximal Development, which distributed schema generation amongst the learner’s social context. Self-regulation and metacognition, the focus of this work, have clear connections to individual Constructivism. Applications of self-regulated learning and individual constructivism result in personalized learning that takes into account a learner’s context, affect, and pre-existing knowledge. Scaffolding, which can consist of human or computerized agents that support a learner as-needed (for example strong support for novices and no support for experts), has clear connections to social constructivism. Both scaffolding and social constructivism postulate that students would learn less effectively without social support.
Cognitivism: A Cognitivist view frames learning theory in terms of cognitive architectures, for example the Attkinson-Shiffrin memory model (Atkinson and Shiffrin, 1968) and the Baddeley model of working memory (Baddeley, 1992). These computer-science inspired models beget limitations of human cognitive capacity analogous to the limitations of a computer’s memory hierarchy. Cognitive Load Theory (Sweller, 1994) has inspired research into which forms of productive cognitive loads should be encouraged and which forms of unproductive, harmful cognitive load should be minimized. Early work in cognitive load theory proposed a focus on germane cognitive load from schema creation and prescribed scaffolding as one way to maximize germane cognitive load while minimizing extraneous cognitive load. More recent work has expanded the scope of what is productive to include frustrating, open-ended project work that a student might do before being prepared for it (Reiser, Kapur, 2018, 2008).
Reflective and Experiential Cycles: Self-regulated learning, pioneered by Zimmerman (Zimmerman, 1990), experiential learning theory, pioneered by Kolb (Kolb, 2014), and reflective practice (Finlay, 2008) each recognize it is important for a learner to go through a process of self-reflecting for the purpose of iterative improvement. Important elements of these reflective models include goal setting, prompted reflection, and iterative experimentation.
Three-Step Regulation: Self-regulated learning can be broken down into a three step cyclical process: Preparation, Monitoring, and Reflection (Puustinen and Pulkkinen, 2001). Preparation consists of understanding the problem and setting goals (Landine and Stewart, 1998). Monitoring can be simple monitoring of internal states like energy, or more task-focused monitoring of nebulous concepts like progress. Reflection shares similarities to monitoring but is significantly differentiated by reflection being the primary cognitive process.
Self-monitoring: Self-monitoring requires some cognitive load (Lee, 2012) but is also prescribed by most experiential cycle variants (Kolb, 2014). While this may seem contradictory, the specifics strategies of self-monitoring can be important. Schnaubert et al. argue theoretically and experimentally that self-monitoring cog- nitive load leads to better learning outcomes (Schnaubert and Schneider, 2022). On the other hand, Biwer et al. (Biwer et al., 2023) find that students assisted by a timer may perform better than students self-regulating their own breaks. These results could be compatible, as a student could monitor learning effectiveness by ensuring high mental effort and could not monitor mental resource depletion by offloading to a timer. Results like these point to a lack of exact understanding how cognitive load and self-regulation should be used by a student.
Prerequisites to Success: Each of motivation, cognition, and metacognition is not enough on its own. For example a student who, via metacognition, is aware of their own incompetence but does not have knowledge of cognitive strategies or the motivation to experiment is unlikely to improve. This is captured theoretically by the personal aspect of social cognitive theory (Zimmerman, 1989) and analyzed in depth in self-efficacy theory, goal theory, and attribution theory (Eccles and Wigfield, 2002). These behavioral prerequisites are also observed in empirical studies: for example in a statistical survey that found measures of metacognition, motivation, locus of control, and self-efficacy to be positively correlated with academic performance in Grade 12 students (Landine and Stewart, 1998).
Scaffolding: There may be some evidence that structure and scaffolding can help. Some studies use prompts for journaling (Blake, 2005; Cornish and Cantor, 2008, Cheng and Chan, 2019). One qualitative example of the benefits comes from Corish et al., who develop best practices for integrating reflective journaling into a course while teaching a class to teachers-in-training. They note the difficulty learners encounter overcoming the ambiguity of the task without instruction and ultimately decide to provide scaffolding with a combination of prompts, feedback, and integration with a Constructivist curriculum (Cornish and Cantor, 2008). Similarly, Jarvis et al. provide nursing students with a four-step scaffolding plan with a focus on peer feedback and group discussion on journals (Jarvis and Baloyi, 2020). Although traditionally human, scaffolding can also be software (Quintana, Zhang, and Krajcik, 2005; Leinonen et al., 2016).
Interfaces: There is a rich history of research in Human Computer Interaction Design that extends to the nuances of a learner’s goals and context in education interfaces (Faghih, Azadehfar, Katebi, et al., Vuorio et al., Lohr, 2014, 2000). Zaharias et al. (Zaharias and Poulymenakou, 2007) provide a usability framework that draws on dozens of studies in interface design to provide guidelines and validation criteria for each common design principle. These principles include learnability, accessibility, and consistency. From a cognitivist perspective, the most important design considerations are the context of the learner and the intrinsic and extrinsic cognitive load the interface encourages or discourages. From a constructivist point of view, an interface based on an experiential cycle would maximize germane cognitive load in the experience phase while minimizing extraneous cognitive load.
Software: Software interfaces presented in academia tend to be based on useful models of metacognition, but tend to have rigid, prescriptive interfaces and low voluntary participation rates. Baars et al. create a mobile phone app to help with SRL and perform a study with the students of a fist year psychology course (Baars, Khare, and Ridderstap, 2022). While statistically they find some usefulness, they find most students do not use the app much. Liu et al. develop a mobile app that helps students to through self-regulated learning in conjunction with scaffolding and feedback provided by the teacher (Liu, Samah, and Salleh, 2022). Students using the app demonstrated a quantitatively better approach to self- regulated learning after using the app. Jaramillo et al develop a mobile app that teaches self-regulated learning, encourages students, incorporates gamification, and provides an avenue for feedback from teachers (Jaramillo, Salinas-Cerda, and Fuentes, 2022). Students who use the app have higher self-reported SRL skills and higher academic achievement. Broadbent et al provide students a mobile survey app to use as a diary before and after learning. They also intervened with online training to teach different aspects of self-regulated learning. Students who had training and used a diary showed improved performance compared to those who did not. However, most of the students dropped out early in the study. Puntambekar et al develop an Intelligent Tutoring System that does not have domain knowledge but instead knowledge of metacognition and self-regulated learning and therefore prompts students with questions about the structure of the problem and strategies that are not domain specific (Puntambekar, 1995). This differs from more traditional definitions and models of self-regulated learning which encompass goal setting, planning, and other metacognitive processes. Leinonen et al. design two mobile applications to facilitate self-regulated learning focused on short form video sharing (Leinonen et al., 2016). The first, ReFlex, allows the user to take short videos of themselves to give to educators and parents.
A Proposed Model
To reflect the multi-faceted nature of reflective journaling literature and provide a theoretical basis for a metacognitive interface I introduce the term Multi-Layer Metacognition, illustrated in Figure 1. In multi-layer metacognition the main cognitive activity is wrapped by several layers of metacognition. In self-regulated learning the cognitive activity would be learning or studying, the first layer would be a study "wrapper" that involves activities directly surrounding studies, and the second layer would be a reflective learning journal.
Figure 1—Multi-Layer Metacognition introduces multiple levels of abstraction and metacognition that each "wrap" the cognitive or metacognitive tasks below them. For example reflective journaling involves reflecting on itself, the study wrapper, and the studying.
First Layer Study Wrapper: The first layer of metacognition encompasses metacognitive activities that are tightly coupled with the act of studying. This includes goal setting for the study session, optimizing the study environment to prevent distractions, keeping track of time for study breaks, and recording metacognitive thoughts that occur during self-monitoring. Theory and research on goals is strongly connected to research into attention, focus, and taking breaks. With respect to goal setting, several researchers have theorized that, as an alternative to traditional cognitive resource-based theories of vigilance depletion, a person’s loss of focus on a goal may be responsible for loss of focus on a task (Ariga and Lleras, 2011). While there are other theories for vigilance depletion including factors such as executive control (Thomson, Besner, and Smilek, 2015), there does seem to be consensus in research (Ariga and Lleras, 2011) and general media that taking a break is a good idea. An example of the benefits of breaks orthogonal to standard focus depletion is Barbara Oakley’s popular idea that a brain subconsciously processes information in a different way during diffuse mode breaks from focus (Oakley, 2014). As Lee points out in their discussion of breaks in medical practice, monitoring energy levels takes cognitive load, a phenomenon they term "secondary load" (Lee et al., 2021). This is corroborated by an empirical study comparing the effectiveness of breaks initiated by self- monitoring and breaks initiated by an automatic timer that found self-regulated study sessions and breaks tended to be longer and leave the subject with less energy than timer-determined breaks (Biwer et al., 2023). Thus an interface that directly wraps studying should provide cognitive offload for monitoring tasks and facilitate goal orientation.
Second Layer Reflective Journal: Reflective journals are not diaries. The discussions so far on metacognition, self-regulated learning, and design have highlighted that self-regulated learning is a goal-oriented, cyclical task that requires high cognitive load and high motivation. As Progoff says, "the mere fact of continuously writing entries, as is done in the keeping of a diary, is not sufficient in itself to bring about deep changes in a person’s life" (Progoff, 1977). Reflective journaling seems to be an inherently constructivist task that faces challenges when prescribed in a didactic, behaviorist way. One review of eleven reflective journaling studies determined that five of the studies found descriptive rather than reflective writing, four found somewhat reflective writing, and only two found highly reflective writing (Dyment and O’Connell, 2011). When a teacher prescribes reflective journaling they may run into challenges such as lack of student training, lack of structure, writing for the instructor, journaling "to death", and ethical issues (O’Connell and Dyment, 2011). The nuance of reflective journaling combined with the difficulty in instructing its use makes it a strong candidate for scaffolding. Simple examples of scaffolding include initial prompts for journaling (Blake, Cheng and Chan, 2005, 2019), and more intensive examples include a full course dedicated to teaching a constructivist curriculum that integrate scaffolded reflective jouranling (Cornish and Cantor, 2008). Software interfaces for scaffolding are a popular idea due to their ability to personally adapt to each learner (Quintana, Zhang, and Krajcik, Leinonen et al., 2005, 2016). A good software interfaces for reflective journaling would maintain focus on the learner’s goals, enforce a structure of cycles and iteration, and allow the learner to modify their approach to reflection.
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