From Distraction to Reaction: Exploring Self-Regulated Learning and Off-Task Thoughts in Online Learning from Videos Daniel Ebbert1,* 1 Centre for Change and Complexity in Learning, University of South Australia, Adelaide, Australia Abstract Self-regulated learning (SRL) plays a crucial role in online learning success. However, students inevitably encounter off-task thoughts (mind wandering or task-related interference) that can disrupt the learning process. Although SRL and off-task thoughts have been studied independently, their interaction has not been extensively explored. This research project investigates the relationship between SRL and off-task thoughts in the context of learning from videos. A multi-method approach will be employed, comprising a conceptual paper, meta-analyses, case study, two experiments, and comparative analysis. The conceptual paper will present a model illustrating how off-task thoughts may trigger reactive self-regulation during learning. The meta-analyses will synthesize findings on the occurrence and impact of task-related interference and off-task thoughts. A naturalistic case study and two controlled experiments will collect self-caught thought reports during actual and simulated video learning, respectively. The case study will explore whether students rewind videos after mind wandering. The experiments will test whether the anticipation of learning activities at pauses in the video leads to increased awareness of off-task thoughts and whether rewinding a video following off-task thoughts balances out the negative effect of mind wandering. Comparing the case study and both experiment results will assess the generalizability of findings across contexts. A comparative analysis will also examine the association between SRL and off- task thought frequency in naturalistic and controlled settings. This research project aims to provide theoretical and empirical insights into the interaction between off-task thoughts and SRL when learning from videos. Keywords self-regulated learning, mind wandering, metacognition, meta-awareness, off-task thought1 1. Introduction and task-unrelated thoughts are called task-unrelated thoughts (TUT), while stimulus-independent and task- Learners often find their minds drifting to unrelated related thoughts are known as task-related interference matters when striving to acquire knowledge. Research (TRI). indicates that during educational pursuits, students A recent meta-analysis revealed that TUTs occur experience off-task thoughts approximately 30% of the about 30% of the time during educational activities and time [1]. As such thoughts are unavoidable, it is crucial negatively correlate with learning outcomes [1]. to consider their impact when examining the learning Although a comparable meta-analysis on the frequency process. Consequently, off-task thoughts can hinder the and impact of TRI on learning has not been conducted, acquisition of knowledge [2]. How learners adjust their some studies suggest that TRI may have a neutral or learning strategies to accommodate current even positive effect on learning outcomes [5], [6], [7]. circumstances, including distractions, falls under the Nevertheless, learners encounter off-task thoughts domain of self-regulated learning [3]. Distractions like during the learning process and must adapt their off-task thoughts can manifest during learning, learning strategies accordingly. necessitating learners to adapt to these disruptions in Given the detrimental effect of mind wandering on real-time. learning outcomes, various laboratory studies have aimed to reduce the frequency of mind wandering 2. Background among learners. In the context of learning from videos, this has been achieved through the use of interpolated 2.1. Off-Task Thoughts testing [5], [7], [8]. Other learning activities, such as Off-task thoughts can be categorized based on stimulus- generative activities like self-explanations, have dependency and task-relatedness [4]. Within the scope positively influenced learning outcomes [9]. However, of this research project, the focus lies on stimulus- the impact of these activities on the frequency and type independent thoughts, which can be further classified as of off-task thoughts remains unknown. It is also possible task-unrelated or task-related. Stimulus- independent ∗ Corresponding author. © 2025 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). daniel.ebbert@mymail.unisa.edu.au (Daniel Ebbert) 0000-0003-3666-7205 (Daniel Ebbert) CEUR ceur-ws.org Workshop ISSN 1613-0073 Proceedings for students to become aware of their mind wandering, regulated learning, theories on off-task thoughts, and a phenomenon known as meta-awareness. the concept of metacognition, which will be presented Meta-awareness refers to the conscious recognition in a conceptual paper. A key aspect of this model posits of one's thoughts [10]. This concept is rooted in that a self-regulated learner's reaction to the realization metacognition and is a form of metacognitive of being off-task is contingent upon the type of off-task monitoring [11]. When students engage in thought they experienced. While the frequency and metacognitive monitoring, they actively reflect on their relationship with learning outcomes have been recent thoughts, potentially becoming aware of any off- established for TUT [1], this information is lacking for task thoughts. The information gained from this self- TRI and the overarching category of off-task thoughts reflection can then be utilized to adjust their thoughts (TUT + TRI), which motivates the first two research through actions designed to refocus their attention on questions. the task at hand. This process is known as metacognitive control. Students continue studying until they engage in • RQ1: What is the frequency of TRI, and how metacognitive monitoring once more, which may are these thoughts associated with learning trigger further metacognitive control. This cyclical outcomes? metacognitive monitoring and control process forms the • RQ2: What is the frequency of off-task foundation of self-regulated learning [12]. thoughts, and how are these thoughts associated with learning outcomes? 2.2. Self-regulated Learning The developed model will provide a theoretical Self-regulated learning provides a framework for foundation, which the meta-analyses will enhance. understanding the emotional, motivational, and Collectively, these components will elucidate the cognitive aspects of learning [3]. This research project is frequency with which students encounter each type of underpinned by the COPES model of self-regulated off-task thought and, consequently, the need to respond learning [13], as it elucidates the role of metacognition to such off-task thoughts. To investigate these dynamics in self-regulated learning and how students adapt their further and evaluate their practical implications, the learning process to the current task. According to Winne context of video-based learning has been selected as the and Hadwin [13], self-regulated learning occurs across focus of subsequent studies. four interconnected stages. These stages are task definition, goal setting and planning, enacting study 3.2. Exploring self-regulated learning tactics and strategies, and metacognitively adaptive and off-task thoughts during studying. During the third stage, as students implement study tactics and strategies, they frequently alternate video learning between cognition and metacognitive monitoring [14]. The theoretical assumption of mutual influence between Students will likely recognize their off-task thoughts self-regulated learning and off-task thoughts led to the during this stage and modify their learning behavior overarching question, "What is the 2-way relationship based on this realization. This research project explicitly between self-regulated learning and off-task thoughts in explores this self-regulated learning phase, as no video-based learning?" The overarching research existing model currently describes how off-task question has been broken down into specific research thoughts influence self-regulated learning. questions. 3. Research Approach • RQ3: How does self-regulated learning influence off-task thoughts when learning This research project consists of two parts. The first part from a video? is theory development, complemented by a meta- • RQ4: How does self-explanation during video analysis. Together, these inform the second part, watching influence off-task thoughts exploring self-regulated learning and off-task thoughts compared to interpolated testing? while learning from videos. • RQ5: Does rewinding a video after off-task thoughts offset the negative effect of off-task 3.1. Theory Development and Meta- thoughts on learning outcomes? Analysis • RQ6: Is the relationship between self- By synthesizing the existing literature, a model will be regulated learning and off-task thought constructed to illustrate how off-task thoughts influence frequency consistent across study designs? the learning process and how students might respond upon realizing they have experienced off-task thoughts. The fact that most research on off-task thoughts and This model will draw upon the COPES model of self- learning has been conducted in controlled laboratory settings motivates RQ3. The observation that attempts 4.3. Case Study to reduce off-task thoughts during video-based learning have primarily relied on interpolated testing has The third research question will be examined through a inspired RQ4. The lack of research investigating case study, which aims to overcome a significant whether a learner's response to their off-task thoughts limitation of many studies on the interaction between can balance out the negative effects of off-task thoughts off-task thoughts and learning, namely their reliance on motivates RQ5. RQ6 is motivated by apprehensions controlled laboratory environments. In the context of regarding the generalizability of findings obtained from learning from videos, this limitation meant that learners laboratory-based research in naturalistic settings. were not allowed to react to realizing their off-task thoughts, even if they desired to. This study addresses this issue by requesting students to watch course videos 4. Methodology and report their off-task thoughts as they become aware A multi-method approach will address the aim and of them. Unlike other studies on off-task thoughts, research questions, comprising a conceptual paper, students in this case study can interact with the video meta-analyses, a case study, and two experiments. The player while learning. This interaction allows them to data collected from the case study and both experiments react to the realization of their off-task thoughts. The will be combined to analyze and compare the frequency resulting trace data, consisting of thought reports and of off-task thoughts and assess the potential impact of video interaction data, can be analyzed using learning self-regulated learning on these thoughts. In the case analytics techniques such as sequential pattern mining study and experiments, participants will be asked to and multilevel modelling to model and understand provide self-caught free-text thought reports and metacognitive processes. In addition to measuring complete subscales from the self-regulation for learning students' self-caught off-task thoughts, participants will online (SRL-O) questionnaire [15]. be asked to complete SRL-O subscales. The findings from this study will provide insights into the frequency 4.1. Conceptual Paper of off-task thoughts in a naturalistic setting and whether students react to the realization of being off-task by, for The theoretical connection between self-regulated example, rewinding the video. learning and off-task thoughts will be explored by developing a conceptual paper. This paper will build upon the COPES model of self-regulated learning, 4.4. First Experiment theories on off-task thoughts and learning, and The fourth research question will be addressed through metacognition. By synthesizing the existing literature, a an experiment to compare the effect of interpolated model will be constructed to illustrate how off-task testing and self-explanation writing on the self-reported thoughts influence the learning process and how frequency of off-task thoughts. The experiment will students might respond upon realizing they have include three conditions: two experimental conditions experienced off-task thoughts. (interpolated testing and self-explanations) and a control group. Participants will complete SRL-O subscales and a 4.2. Meta-Analyses pre-test, watch a video while reporting off-task thoughts (self-caught), engage in a filler task, and then take a post- Research questions one and two will be addressed test. The results from this study will provide insights through meta-analyses. A systematic search and into which learning activity (interpolated testing or self- screening of the existing literature on TRI will be explanations) leads to better learning outcomes and conducted. Subsequently, the frequency and effect size whether the frequency of off-task thought realization of the relationship between TRI and learning outcomes differs between the two experimental conditions and the will be extracted and included in the meta-analysis. control group. Furthermore, the TUT frequencies and effect sizes on learning outcomes will be extracted from the identified sources and combined with the TRI data from 4.5. Second Experiment off-task thought frequencies and effect sizes, which can The fifth research question will be investigated through be used for a meta-analysis. an experiment examining whether students' rewinding This information will shed light on the prevalence of the video they are learning from following their off-task TRI and off-task thoughts and the magnitude of their thoughts balances out the negative effects of off-task impact on learning outcomes. thoughts. The experiment will include three conditions: two experimental conditions (optional rewind following off-task thought, mandatory rewind following off-task thoughts) and a control group. The participants for the study will be recruited using 7. Contribution Prolific, and the study will be conducted online. Participants will complete an SRL questionnaire, be The primary objective of this research project is to introduced to the concept of off-task thought, and, investigate how off-task thoughts influence students' depending on conditions, will be instructed to rewind learning processes during online video-based learning. the wind they are learning from following their off-task The developed model will provide a theoretical thoughts. While watching the video, participants will foundation enriched by the meta-analyses on TUT, TRI, provide self-caught thought reports. After watching the and off-task thoughts. These components will video, they will answer a knowledge test. collectively describe the frequency with which students Data analysis will involve comparing the groups on encounter each type of off-task thought and, their knowledge test performance to assess whether consequently, the need to react to such occurrences. The video rewinding following off-task thoughts offsets the case study will then explore if and how students respond negative effect of off-task thoughts. when they become aware of their off-task thoughts. One possible reaction students might undertake is to modify 4.6. Comparison of Off-Task Thought the learning task by incorporating interactive learning Frequency Across Study Designs activities. The first experiment will test which learning activities influence the frequency of off-task thoughts. Once the case study and both experiments are The second experiment will test if rewinding a video completed, research question six can be addressed. The following off-task thoughts balanced out the negative data from the three studies will be combined. By effect of off-task thoughts. The comparative analysis merging the data, the frequency and types of off-task will examine how the frequency of reported off-task thoughts can be compared between the studies based on thoughts in an experimental setting can be compared to the participants' SRL-O questionnaire scores. This a naturalistic setting. combined data can provide insights into students' self- In summary, this research will contribute to the regulation in different contexts. They may reveal existing literature by elucidating the interaction whether students with similar scores on the SRL-O between off-task thoughts and self-regulated learning, subscales exhibit a similar or different frequency of self- how students might influence the frequency of their off- caught off-task thoughts across study designs. task thoughts, and how their reaction following off-task thoughts could influence learning outcomes. 5. Status Furthermore, this research provides evidence of learning The current status of this research project is that the and expands learning theories, which can be used to conceptual paper is being prepared for submission. The inform the development of interventions to enhance meta-analysis and the case study have been written, learning outcomes. submitted, and are under review. The experiment results were published in the proceedings of the Nineteenth Acknowledgements European Conference on Technology Enhanced Professor Shane Dawson, Associate Professor Negin Learning [16]. The data collection for the second Mirriahi, Associate Professor Srecko Joksimovic, and Dr experiment is in progress. Natasha Wilson , all from the University of South Australia, supervise the research project. 6. Ethical Considerations The conceptual paper has been written in Ethical considerations have been prioritized in this collaboration with Caitlin Mills from the University of research project. The Human Research Ethics Minnesota and Phil Winne from Simon Fraser Committee of the University of South Australia has University. The meta-analyses have been conducted granted ethical approval for the case study and the first with Andrew Zamecnik from the University of South experiment. The Institutional Review Board of the Australia. The second experiment will be conducted in University of Minnesota has approved the second collaboration with Caitlin Mills and Aaron Wong from experiment. the University of Minnesota. To protect participants' privacy, personal Daniel Ebbert is supported by an Australian information collected during the case study will be de- Government Research Training Program international identified prior to data analysis, and only anonymous (RTPi) Scholarship. data will be gathered for the experiment. Only data from informed consent participants will be utilized in the case References study and experiments. [1] A. Y. Wong, S. L. Smith, C. A. McGrath, L. E. 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