Mind wandering has the potential to negatively impact the process of learning and has become more prevalent with the increased practice of online learning. Self-regulation interventions may be able to decrease mind wandering and should be widely taught to students. —Ashley M. Parnell
Self Directed Learning and Mind Wandering
“Mind wandering, the direction of attention away from a primary task, has the potential to interfere with learning, especially in increasingly common self-directed, online learning environments.” Given the prevalence and negative consequences of mind wandering, this shift towards “self-directed learning environments with minimal supervision and maximal learner control has escalated the importance of the self-regulation of attention to ensure successful learning.”1
Self Regulation to Combat Mind Wandering
Self-regulation can be defined as the ability to manage one’s thoughts, feelings, and actions to achieve a learning goal. “Decades of empirical evidence supports self-regulation’s role in enhancing learning, as well as strategies that may be taught and used to combat mind wandering and encourage on-task focus.”
In response, the current study sought to examine the extent to which mind wandering harms training outcomes in self-directed learning environments, as well as to compare various strategies to prevent off-task thought. Drawing from three core theoretical perspectives on the causes of mind wandering, researchers created three intervention conditions, each focusing on more than one self-regulation strategy as summarized below.
Objective & Intervention Strategies
Current concerns hypothesis: Mind wandering occurs when personal concerns and goals are more valued than the primary task
Increase value of the task and decrease other concerns/distractors by:Goal settingEnvironmental structuring (i.e., identification & removal of environmental distractions)
Executive failure hypothesis: Mind wandering is a failure of executive control
Use proactive executive control to direct focus on-task through:Planning of learning activities & objectivesMetacognitive monitoring (constant evaluation of one’s learning progress)Use reactive executive control to suppress cues that trigger mind wandering through:Implementation intentions (i.e., If-then self statements)Time management Environmental structuring
Meta-awareness hypothesis: Mind wandering results from not being aware of the contents of consciousness.
Increase awareness of consciousness through:Mindfulness (attention to & awareness/ acceptance of the present moment)Metacognitive monitoring
Researchers tested these three interventions in two experiments: a field study with 133 working adults and a lab study with 175 college students where participants completed a self-directed online Excel training. While self-regulation interventions and excel training conditions remained the same across studies, setting, timing, and participants differed.
Researchers reported the following findings based on the two studies conducted:
Mind wandering during training negatively impacts self-directed learning outcomes including knowledge, self-efficacy, and trainee reactions to training.
The negative effects of mind wandering were notably stronger in Study 2, which incorporated less self-pacing and reported lower motivation levels.
Short, one-time, online intervention was not enough to alter use of self-regulation strategies.
Interventions largely failed to impact trainees’ self-regulation, mind wandering, or learning relative to the control group. However, the ineffectiveness of the self-regulation interventions does not indicate that the selected self-regulatory strategies were ineffective in deterring mind wandering.
Correlational results indicated that strategies strongly associated with decreased mind wandering include: “a) practicing mindfulness by being present in the moment, b) forming and utilizing implementation intentions, c) intermittently monitoring performance using self-directed evaluative questions, and d) structuring the learning environment to minimize distractions.”
Considerations & Implications for Practice
Results warranted consideration of the following implications for practice:
Motivation levels matter in training/learning. Designing and delivering self-directed learning in ways that do not bore or overwhelm learners, and incorporating motivational incentives, may decrease mind wandering and, subsequently, the harmful effects of mind wandering.
Initial, albeit limited, results identify strategies that may decrease mind wandering: mindfulness, metacognitive monitoring, implementation intentions, and environmental structuring. Given self-regulation’s inherent role in online learning, efforts to develop effective interventions to teach and develop these self-regulation strategies and skills should continue.
Randall, J., Hanson, M., & Nassrelgrgawi, A. (2021). Staying focused when nobody is watching: Self‐regulatory strategies to reduce mind wandering during self‐directed learning. Applied Psychology. 10.1111/apps.12366
Summary by: Ashley M. Parnell — Ashley strives to apply the MARIO Framework to build evidence-based learning environments that support student engagement, empowerment, and passion, and is working with a team of educators to grow and share this framework with other educators.
Academic researcher Jason Randall participated in the final version of this summary.
Johnson, R. D., & Randall, J. G. (2018). A review of design considerations in e-learning. In D. L. Stone & J. H. Dulebohn (Eds.), Research in human resource management (pp. 141– 188). Information Age Publishing.
Although students with learning disabilities (LD) may experience difficulties throughout their academic career, they can develop strategies to overcome them—at times, without professional guidance. Yet, “active use of mentorship, coaching and support service units for students with LD will also contribute to ensuring greater success in higher education.” —Frankie Garbutt
Firat (Adiyaman University, Turkey) and Bildiren (Adnan Menderes University, Turkey) were intrigued by the increase in number of students with learning disabilities amongst university students overall. They wanted to know how these students may experience difficulties when compared to neuro-typical students because only a small percentage of students with LDs eventually graduate from university.
What Was Measured
The researchers collected a range of qualitative data on one student with learning disabilities (defined as ongoing problems with literacy and numeracy as well as verbal language use). They measured the strengths and weaknesses of the student throughout his academic life (from preschool to university) and how the student worked to build methods to overcome barriers to their academic progress.
The participant’s strengths over his education career included motor development, problem-solving, social skills, a desire to develop, and self-advocacy. His weaknesses throughout his educational career included subject content, social skills, executive functioning, and metacognitive skills.
Many of the difficulties he experienced in primary school continued through university, while one of his specific weaknesses in preschool, social skills, became a strength in his university years.
He was able to develop strategies to succeed on his own by studying lessons, improving memory methods, and learning to speed read. Interestingly, the student had not been identified with learning needs until he entered university and took a course on learning disabilities. Alongside his academic career, the participant learned to grow his self-esteem with activities outside the classroom like “chess or wrestling.”
Recommendations and Limitations
“Socio-emotional and academic difficulties experienced by students with LD may also continue throughout their university education. In this context, academic staff may receive additional training for increasing their awareness on the requirements of students with LD and for learning how they can support these students better.”
There are limitations to this research because “the study was carried out with a single student in the final year of his university education. Accordingly, the opinions of a greater number of students could be examined to yield more generalisable insights.”
Furthermore, the study data relied on interviews with the participant which may be tainted by him not accurately remembering the strengths and difficulties he experienced throughout his academic career. “The acquired data are limited by the self-awareness level of the student. Hence, this can be taken into consideration in future studies and the opinions of the student can be taken together with those of their peers, students, and family members.”
Fırat, T., & Bildiren, A. (2021). Strengths and weaknesses of a student with learning disabilities: from preschool to university. Journal of Further and Higher Education, 45(7), 958-972.
Summary by: Frankie Garbutt- Frankie believes that the MARIO Framework encourages students to become reflective, independent learners who progress at their own rate.
Key Takeaway: Universal Design for Learning (UDL) creates and supports personalized learning experiences that build learner independence, agency, and engagement. Maintaining student engagement, establishing a consistent learning routine, and monitoring progress and making instructional changes are ways to successfully apply UDL principles when teaching problem-solving skills remotely to students with autism spectrum disorder (ASD). —Ashley Parnell
Summary: The shift to digital learning environments has provided an opportunity for special educators to use technology to deliver effective, high-quality instruction. Specifically, substantial research supports the use of Video-based Instruction (VBI) for teaching mathematics to students with ASD.
In this article, Cox, Root, and Gilley describe how one special education teacher, Mrs. Shaw, plans to “utilize VBI through free online platforms (i.e., SeeSaw, Loom) to implement a mathematical problem-solving instructional strategy (i.e., Modified Schema-based Instruction; MSBI) for students with ASD while at home.” On demand (i.e., asynchronous) videos will be used to deliver explicit strategy instruction, while allowing for flexibility (i.e., time, place, & pace) and opportunities to differentiate instruction based on individual student needs and preferences.
MSBI is an evidence-based practice for teaching mathematical problem-solving to students with mathematics-related disabilities and challenges. Supporting executive functioning skills and flexibility, MSBI provides a structured sequence of problem-solving strategies that can be applied across scenarios including: 1) identifying problem structure based on important features, 2) representing that information on a schematic diagram (i.e., graphic organizer), 3) making a plan, and 4) carrying out the plan and checking for reasonableness.
The study encourages teachers to merge/draw upon current research on TAI and evidence-based practices when planning for virtual problem-solving instruction, making sure to consider how the following high-impact instructional strategies can be maintained and addressed within remote learning environments.
Maintaining Student Engagement. “Students must be engaged in order to make progress on learning goals…The UDL framework helps teachers proactively consider barriers students may face during learning, and intentionally design instruction to reduce potential barriers.” Mrs. Shaw will increase engagement by contextualizing word problems within real-world themes relevant to student interest and background. Using VBI allows special educators to maintain principles of explicit instruction (i.e., modeling, quick pace, active student responding,etc.) while SeeSaw provides flexible opportunities and methods for students to demonstrate their learning, further enhancing student engagement.
Establishing a Consistent Learning Routine. Cox et al. emphasize the importance of predictable and consistent learning routines for students with ASD during remote learning. Screencasting tools such as Loom can be used to create a sequence of scripted video models that follow a model—guided practice—independent practice format. Visual supports including graphic organizers and checklists also provide structure and systematically guide students in following the problem-solving routine and daily schedule. Instructional videos and visual supports can be embedded within digital engagement platforms (e.g., SeeSaw) to establish clear and consistent expectations and routines.
Monitoring Progress and Making Instructional Changes. Aligning with the UDL framework, “Instructional data is used both to increase support when needed as well as challenge and progress through phases of learning.” Mrs. Shaw will view online work samples and student screen recordings during work completion, features available in Seesaw, to analyze errors and guide instructional decision making and modifications. Technology can be further leveraged to increase or decrease support (i.e., 1:1 Zoom sessions, targeted video models, fading of visual supports, self-monitoring tools).
Cox, S., Root, J., & Gilley, D. (2021). Let’s See That Again: Using Instructional Videos to Support Asynchronous Mathematical Problem Solving Instruction for Students With Autism Spectrum Disorder. Journal of Special Education Technology, 36(2), 97-104.
Summary By: Ashley M. Parnell – Ashley strives to apply the MARIO Framework to build evidence-based learning environments that support student engagement, empowerment, and passion and is working with a team of educators to grow and share this framework with other educators.
Key Takeaway: This article provides educators with a manual on how to utilize positive and proactive behaviour management strategies to improve student engagement in virtual environments using platforms like Zoom or G Suite. Consistent, clear routines and expectations, explicit teaching of the desired behaviour and opportunities for communication between students and teacher have resulted in higher engagement and learning outcomes. —Frankie Garbutt
“High-levels of classroom engagement and on-task behaviour have been linked to positive outcomes for students,” says Renee Speight (University of Arkansas) and Suzanne Kucharcyzk (University of Arkansas) in this article of the Journal of Special Education Technology. The authors argued that strategies of Positive Behaviour Interventions and Supports (PBIS), used to” facilitate improvements in student engagement,” should be adjusted to the virtual environments as part of teachers’ “instructional repertoire.”
Speight and Kucharczyk outline that PBIS is a “system of support involving direct instruction of expected behaviours and modification of the classroom environment through antecedents and consequences to promote student demonstration of expected behaviours.”
The following strategies have been identified as “high-leveraging practices for inclusive educational environments:”
Creating clear routines: This applies to aspects of a lesson like readiness to learn, instructional routines as well as task submission. Such routines will “minimize the labour required to re-create learning processes with the shifts from in-classroom to virtual learning.”
Explicit instruction on expected behaviours: “Teachers should identify three to five behaviours critical to a positive and productive virtual learning session” and “steps should be taken to explicitly teach” these. This could be complemented by visual depictions of the expected behaviours
Prompting and acknowledging expected behaviour: Once behaviours are identified and taught, teachers should “use precorrection” (like prompting) “at the onset of instructional sessions or shifts in teaching arrangements, such as when students move into breakout sessions.” To individualize prompting, teachers could use the chat feature in Zoom or G Suite.
Opportunities to respond: Teachers should consistently create opportunities to respond “to increase active engagement” by using tools such as “polls and participant nonverbal responses” as well as “Google Forms.” To allow for equal participation, students should be given wait or thinking time prior to responding.
Access to reinforcers: Reinforcement of “desired behaviour changes” ought to be “guided by student preferences which can be determined by using preference assessment” through tools like Google Forms. In virtual sessions, it is crucial that access to reinforcers are regular and miscellaneous.
The authors concluded that the practices of PBIS, embedded into the virtual learning setting, can result in students demonstrating expected behaviours and facilitating “high levels of engagement and learning.”
Speight, R., & Kucharczyk, S. (2021). Leveraging Positive Behavior Supports to Improve Engagement in Virtual Settings. Journal of Special Education Technology, 36(2), 90–96. https://doi.org/10.1177/0162643421992704
Summary by: Frankie Garbutt — Frankie believes that the MARIO Framework encourages students to become reflective, independent learners who progress at their own rate.
This work, a second edition of which has very kindly been requested, was followed by La Construction du réel chez l’enfant and was to have been completed by a study of the genesis of imitation in the child. The latter piece of research, whose publication we have postponed because it is so closely connected with the analysis of play and representational symbolism, appeared in 1945, inserted in a third work, La formation du symbole chez l’enfant. Together these three works form one entity dedicated to the beginnings of intelligence, that is to say, to the various manifestations of sensorimotor intelligence and to the most elementary forms of expression. The theses developed in this volume, which concern in particular the formation of the sensorimotor schemata and the mechanism of mental assimilation, have given rise to much discussion which pleases us and prompts us to thank both our opponents and our sympathizers for their kind interest in our work. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Piaget’s introduction of the term “schema” and discussion of how children assimilate new information, from the earliest of stages primarily through the sensorimotor system, has influenced MARIO’s conception of the developmental continuum of learning. This continuum is embedded within the structure of both the elementary and secondary frameworks.