The more frequently and longer students spend time online, the lower the ratings of self-regulation in digital contexts. Yet, parental control and explicit teaching of digital skills can positively impact self-regulation. Technology in the classroom can enhance motivation, collaboration with peers, and engagement; however, it is not clear if the tools hamper skills like attention and self-regulation. —Frankie Garbutt
It is argued that social-emotional skills such as empathy, perspective, self-control and self-regulation are essential skills in the 21st century. However, one must consider how teaching these skills might need to be adapted at home and in school when today’s children have constant access to social media and the internet, requiring a new approach to self-regulation and self-control. The author of this study set out to find “what benefits for, and risks to, students’ cognitive and social and emotional skills are created by ubiquitous access.”
Self-rating is a means to examine the development of social-emotional skills. It “measures extraversion (sociability, engages in class activities), agreeableness (empathy, wants to help), conscientiousness (self-regulation, perseveres at activities), neuroticism (framed positively as emotional stability), and openness to experience (curiosity, appreciates new experiences).” Technology in the classroom can enhance motivation, collaboration with peers, and engagement, but it is not clear if the tools hamper skills like attention and self-regulation. At home, students’ use of digital tools is largely impacted by “time spent online, types of activities, and parental guidance.”
Changes in Self-Regulation and Social Skills Due to Technology Use
Initially, the results related to social skills showed a downward trend in the skills of self-regulation in digital and non-digital context, whereas the other skills seemed to not be affected because “ratings of the dimensions most clearly related to social skills, extraversion, and agreeableness did not have a consistent trend.“ The results of the study showed five trends:
“Self-regulation in digital contexts was significantly lower (M = 3.05, UL = 3.19) than the equivalent measures in non-digital.“
“This pattern of lower self-regulation in digital contexts compared with non-digital contexts was consistent across the ages.”
“Ratings of social skills tended to be higher than those for self-regulation.”
“Last, ratings of self-regulation in digital contexts appeared to be unrelated to personality dimensions and social skills generally.”
Implications for Schools
The authors discussed that schools can be beneficial when teaching children about self-regulation in a digital context because metacognitive skills and self-regulation are skills consistently taught, which can respectively support the students’ use of digital tools.
Moreover, “like self-regulation, the community of practice involving parents, teachers, and students had a focus on positive online interactions. In contrast, engaging in social media activities at home was associated with higher ratings of social skills in digital (but not in non-digital) contexts.”
Overall, schools are an environment in which students can learn valuable skills, such as self-regulation and social skills, in the ever increasing digital world when complimented by parental involvement and guidance at home. The authors suggest that further research should investigate how parents and schools can respectively support the building of these skills.
McNaughton, S., Zhu, T., Rosedale, N., Jesson, R., Oldehaver, J., & Williamson, R. (2022). In school and out of school digital use and the development of children’s self‐regulation and social skills. British Journal of Educational Psychology, 92(1), 236-257.
Summary by: Frankie Garbutt – Frankie believes that the MARIO Framework encourages students to become reflective, independent learners who progress at their own rate.
The change from onsite learning to online can cause students to lose motivation and efficiency in their learning. Having self-regulation skills and the use of preferred low or high-impact strategies can also affect student learning. It is crucial to understand these factors and support students by helping them with self-regulation skills and deciding on study strategies that work best for them. —Nika Espinosa
This study primarily focuses on the shelter-in-place adaptations of students in a doctor of chiropractic program. Forty-nine percent of the 105 students enrolled participated in the data collection. The researchers focused on primary study strategies, technology use, motivation and efficacy, study space and time, metacognitive planning, monitoring, and evaluating. Part of the study required the participants to give sufficient evidence.
Primary Study Strategy
When it comes to study strategies, the most frequently chosen study strategy by the students was repeated reading (low-impact) and completing practice problems (high-impact). A majority of the respondents (82%) did say that they didn’t use the same strategies during shelter-in-place that they used when they were onsite learning. Low-impact strategies such as highlighting and memorizing were frequently chosen by the respondents, whereas high-impact strategies were not as preferred. The survey also showed that the chosen primary strategies that participants used were low-impact. “These data imply that although a student selects a high- or low-impact study strategy from a list, it may not reflect the true study approach but rather indicate the 1st step in the approach.“
A majority of the students (86%) reported that there wasn’t much difference in their use of technology when the switch to shelter-in learning was made. Twelve out of the fifty-two students did say their adaptations to technology were more significant.
“Sixty-one percent (31/51) of respondents indicated a range in level of challenge and adaptability in finding a new study space.” Part of the challenges included not having a separate work-home space, noise, and distractions, and a lack of social interaction to support learning. “Eight respondents who selected low-impact study strategies and 4 respondents who selected high-impact study strategies as their primary strategy described positive adaptations.”
“Ninety-four percent (48/52) of respondents reported that they did not use the same amount of time studying during shelter-in-place orders as in prior academic terms in the program.” The biggest influencers were motivation and efficiency. Students’ motivation had gone down due to reasons such as pandemic stressors, lack of social interaction, and the structural shift in teaching and learning. Some reported that the work-life balance had become difficult, and a few students mentioned only finding accountability in deadlines and that their motivation was only to pass. Some students however became more efficient in their studies when they found ways to manage their own time.
Planning as a Metacognitive Strategy
Eighteen of the participants said that the most common plan they used during shelter-in learning was to create task lists and a study space to structure their learning. All of the participants that provided evidence also said that in order to set new goals, they needed to use high-impact strategies, regardless of if their primary strategy was low or high impact. “Forty-five percent (14/31) of respondents who selected a low-impact study strategy as their primary strategy described a positive or solutions-oriented plan moving forward, while 71% (15/21) of respondents who selected a high-impact study strategy as their primary strategy described a positive or solutions-oriented plan moving forward.” Those who did not provide sufficient evidence described the challenges of remote learning.
Monitoring as a Metacognitive Strategy
A majority of the participants provided evidence for monitoring their learning. Some of them however mentioned decreased confidence in studying due to either pandemic stressors or the lack of hands-on experience. A student was quoted that they relied very much on the school structure for learning. Uncertainty about the impact of their study habits was mentioned by six of the participants.
Evaluating as a Metacognitive Strategy
Seventy-seven percent of the participants expressed that high-impact strategies were more effective, but the rest described resorting to low-impact strategies due to pandemic stressors.
Williams, C. A., Nordeen, J., Browne, C., & Marshall, B. (2022). Exploring student perceptions of their learning adaptions during the COVID-19 pandemic. Journal of Chiropractic Education. https://doi.org/10.7899/jce-21-11
Summary by: Nika Espinosa – Nika believes that personalized learning is at the heart of special education and strives to collaborate with educators in providing a holistic, personalized approach to supporting all learners through the MARIO Framework.
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.
In an experiment conducted over two semesters (Fall 2019 and Winter 2020), research indicated how time management training increases self-control and time spent on activities, leading to more academic success. Not surprisingly, however, during the pandemic when time structures dissolved and learning went online, there was an increase in leisure time. —Matt Piercy
The study aimed to answer the question:
Might time management training (TMT) have an effect on student behavior when students transition from in-person to online learning?
Authors of the article, Tabvuma et al., state that “overall, our results indicate that it is not enough to have technology available and optimized for online learning. Students need to receive training and develop skills that will enable them to learn and work effectively in an online environment to overcome the challenges of learning in a less structured environment.”
Here are the major takeaways from the article:
The pandemic resulted in a great deal of change for students as established schedules and routines all but dissolved.
Social and physical distancing, lockdowns, and reduced or eliminated work commitments resulted in much more unscheduled time. With time constraints and the norms associated with campus learning removed, students had more locus of control on how they might manage their time. In effect, a new “game” was being played.
“Leisure media (e.g., YouTube, Netflix) provide unscheduled on-demand entertainment experiences that people can access at any time of their choosing.” This often leads to overuse. The authors argue that time management strategies can improve self-control in this area.
“A large literature has found that time management and time management training have a positive impact on individual wellbeing and performance, including students.”1
However, numerous limitations were noted.
For example, the control of gathering data specific to the impact of time management training (TMT) was interrupted as a result of COVID-19. Data was self-reported by students and further, students were all first-year university students in an introductory business course. Only three sessions of time management training were implemented and divided over the course of one semester.
Tabvuma, V., Carter-Rogers, K., Brophy, T., Smith, S. M., & Sutherland, S. (2021). Transitioning from in person to online learning during a pandemic: an experimental study of the impact of time management training. Higher Education Research & Development, 1-17.
Summary by: Matt Piercy—Matt appreciates how at the heart of the MARIO Framework is a passion to develop relationships and a desire to empower students to uncover their purpose while building upon strengths Further, Matt is inspired by how the MARIO team supports educators and is quickly and nobly becoming a collaborative force in pursuit of educational equity.
Aeon, B., & Aguinis, H. (2017). It’s about time: New perspectives and insights on time management. Academy of Management Perspectives, 31(4), 309–330. https://doi.org/10.5465/amp.2016.0166
Temptation can hamper engagement and perseverance directed towards a specific task and cause distractions that can impact the learning process of a student. One way to maintain motivation for a given task is to allow students to choose their tasks and activities based on their interests. Another way is to foster self-efficacy, which enables the student to believe that they are capable of maintaining a high level of motivation and focus. —Shekufeh Monadjem
Attractive Alternatives: Temptation vs Engagement
When working on important tasks, there are always attractive alternatives that tempt us away from our work, be it social media, talking to a friend or even cleaning the house. In their study, Kim,Y., (Washington University), Yu, S.L., (Ohio State University) and Shin, J. (Seoul National University) explored how the effects of self-efficacy can impact the notion of temptation over a period of time. “As students’ learning does not happen in a vacuum, target tasks should be examined in relation to the distracting tasks to better depict motivational challenges that students face within the educational context.”1
“When the attractiveness of an alternative exceeds that of the current task, students feel tempted, and the motivation for the alternative rises.”2 Even if students have high motivation for a certain academic task, they may not engage in the learning if there is another task that is more motivating or attractive to them.
Researchers suggest that the presence of temptation can hamper engagement and perseverance towards a given task by distracting the student to the extent that it will adversely affect their learning process. Milyavskaya and Inzlicht (2017) “found that simply experiencing temptation led to depletion and lower goal attainment.”3 Fries and Dietz (2007) “suggested that the negative impact of temptations comes from lowering motivation for the learning activity. Students often succumb to temptation and fall into the trap of task-switching or procrastination.”4
Self-Regulated Learning and Student Motivation
Self-regulated learning (SRL) can improve “the ability to concentrate on the target task in the presence of tempting alternatives”5 Self-regulated learners are more likely to maintain their motivation and sustain their engagement on a current task, instead of being distracted by other alternatives.
The current study focused on the aspect of self-efficacy for SRL, which is a crucial aspect of SRL. “Abundant evidence suggests the strong link between self-efficacy, motivation, and performance. If students perceive themselves as capable of planning, managing, and regulating their own academic activities, they are more likely to have higher confidence in learning and mastering their activities.” Previous research suggests that higher levels of self-efficacy for SRL can contribute to “higher academic self-efficacy, higher achievement, and less school dropout.”6
One way to maintain student motivation is to allow students to make their own choices and decisions. “It is important to provide meaningful choice opportunities to students to promote their interest, on-task engagement, and persistence.”7 Teachers have also realised that choice provides students a sense of responsibility and self-control, thus making students more involved and engaged in academic activities. This is especially important and effective for students with low interest or SRL skills.
Kim, Y. E., Yu, S. L., & Shin, J. (2021). How temptation changes across time: effects of self-efficacy for self-regulated learning and autonomy support. Educational Psychology, 1-18.
Summary by: Shekufeh Monadjem—Shekufeh believes that the MARIO Framework builds relationships that enables students to view the world in a positive light as well as enabling them to create plans that ultimately lead to their success.
Academic researcher Yeo-eun Kim participated in the final version of this summary.
Hofer, M. (2010). Adolescents’ development of individual interests: A product of multiple goal regulation? Educational Psychologist, 45(3), 149–166.
Hofer, M. (2007). Goal conflicts and self-regulation: A new look at pupils’ off-task behaviour in the classroom. Educational Research Review, 2(1), 28–38.
Milyavskaya, M., & Inzlicht, M. (2017). What’s so great about self-control? Examining the importance of effortful self-control and temptation in predicting real-life depletion and goal attainment. Social Psychological and Personality Science, 8(6), 603–611.
Fries, S., & Dietz, F. (2007). Learning in the face of temptation: The case of motivational interference. The Journal of Experimental Education, 76(1), 93–112.
Baumann, N., & Kuhl, J. (2005). How to resist temptation: The effects of external control versus autonomy support on self-regulatory dynamics. Journal of Personality, 73(2), 443–470.
Caprara, G. V., Fida, R., Vecchione, M., Del Bove, G., Vecchio, G. M., Barbaranelli, C., & Bandura, A. (2008). Longitudinal analysis of the role of perceived self-efficacy for self-regulated learning in academic continuance and achievement. Journal of Educational Psychology, 100(3), 525–534.
Black, A. E., & Deci, E. L. (2000). The effects of instructors’ autonomy support and students’ autonomous motivation on learning organic chemistry: A self-determination theory perspective. Science Education, 84(6), 740–756.
Research suggests that teacher reprimands do not decrease students’ future disruptive behavior or increase their engagement levels. Instead, teachers should focus on proactive classroom management strategies, such as explicitly teaching classroom expectations, using behavior-specific praise, and reinforcing positive behavior as a way to encourage desired behavioral outcomes in the classroom. —Jay Lingo
Students with Emotional and Behavioral Disorders (EBD)
“Many teachers resort to using reprimands in attempts to stop disruptive student behavior,” particularly amongst those students with emotional or behavioral challenges.
Students with emotional and behavioral disorders (EBD) may experience many challenges in school and often present commonly identified characteristics including aggression, attention and academic problems, antisocial behavior, low classroom engagement, high rates of disruptive behaviors, and mental health challenges.
“The ways in which teachers and students interact can affect outcomes for students with EBD. There can be positive outcomes if the teacher–student interactions are positive and teachers have been able to increase the on-task behavior, or engagement, and decrease disruptions of students in their classrooms.”
While teacher reprimands may suppress misbehavior momentarily, they do not appear to be effective in decreasing students’ disruptive behavior or increasing their engagement over time. Limitations and implications are also discussed.
Reprimands: How Effective Are They?
Caldarella et al.’s study emphasizes that the “ways in which teachers and students interact can affect outcomes for students with EBD. Teachers who deliver low rates of negative feedback (e.g., reprimands) and high rates of positive feedback (e.g., praise) may be particularly effective with students with EBD when providing multiple teaching and learning opportunities that enhance students’ engagement.”
Furthermore, reprimands have been linked to escape-motivated behaviors, aggression, and further disruptive behavior. The use of reprimands for students with or at risk for EBD can be especially problematic, given the specific challenges faced by these students. The current study found that teacher reprimands did not appear to decrease future disruptive behavior or increase future engagement for students at risk for EBD, or vice versa.
The results of the study show that although they may temporarily suppress misbehavior they do not result in long-term positive behavior change. This might be because reprimands do not directly teach students the skills needed to improve their behavior, and thus, students may continue to exhibit negative behavior and continue receiving reprimands. Another problem is that reprimands are reactive: a student acts disruptively and a teacher reprimands the student.
The Alternative to Reprimands
Instead, the focus should be on effective teaching techniques and proactive behavior management strategies to decrease disruptions and increase engagement.
“Reprimands are meant to stop misbehavior. However, in the current study, teacher reprimands did not appear to help decrease future classroom disruptions or increase future engagement of students at risk for EBD.” This should not be surprising, as harsh reprimands in schools have been associated with negative side effects such as anger, fear, escape, and avoidance rather than improved student behavior. In addition to being harmful to teachers and their students, reprimands prove less effective than positive classroom behavior management strategies. “Teachers who use reprimands also report higher levels of emotional exhaustion than their peers who do not.”
Given the findings of the current study, along with those of previous researchers, it is recommended that teachers replace reprimands with proactive classroom management strategies, such as clearly teaching classroom expectations, reinforcing positive student behavior, and using behavior-specific praise, as primary responses to student misbehavior and disengagement.
Caldarella, P., Larsen, R., Williams, L., Wills, H., & Wehby, J. (2020). “Stop Doing That!”: Effects of Teacher Reprimands on Student Disruptive Behavior and Engagement. Journal of Positive Behavior Interventions, Vol. 23 (2). DOI: 10.1177/1098300720935101.
Summary by: Jerome Lingo— Jerome believes the MARIO Framework is providing structure and common meaning to learning support programs across the globe. Backed up with current research on the best practices in inclusion and general education, we can reimagine education…together.
Key Takeaway: Across three studies, students’ belief in a growth mindset only predicted increased engagement in math learning for those students who also had sufficient metacognitive skills to monitor their own learning. Thus, metacognitive skills, when paired with a growth mindset, provide complementary skill sets and may be particularly beneficial for students in low socioeconomic school settings. However, the impact of these interventions could vary depending on contextual factors, such as socioeconomic status and teacher-student relationships, and should be taken into consideration. —Kristin Simmers
In their article, “More Than Growth Mindset: Individual and Interactive Links Among Socioeconomically Disadvantaged Adolescents’ Ability Mindsets, Metacognitive Skills, and Math Engagement,” Wang et. al (2021) (University of Pittsburgh) emphasize the following key ideas in relation to Self-Regulation:
Self-Regulated Learning (SRL) shows motivation can help learners; however, metacognitive skills are likely needed for students to fully engage with learning and monitor their overall progress.
Recent research suggests the impact of growth mindset may be context specific. Students from low socio-economic status (SES) contexts are more likely to demonstrate fixed mindsets about academic ability and are more likely to benefit from developing growth mindsets.
If students lack sufficient metacognitive skills, a growth mindset alone may not increase learner engagement. As Wang et. al states, “Metacognitive skills may be necessary for students to realize their growth mindset.”
Positive teacher-student relationships are likely a significant factor in supporting the development of metacognitive skills and a growth mindset, as well as promoting academic engagement.
Teachers should create environments that support metacognition and growth mindset within their specific contexts.
Self-Regulated Learning (SRL)
To help further understand the lens of SRL in the context of metacognition and growth mindset, Zimmerman and Moylan’s (2009)1 SRL model proposes three phases of the learning process: forethought (before learning), performance (during learning), and reflection (after learning). In this model, metacognition is present in each stage, and it is plausible that students who are metacognitively able to monitor their learning process may also be more motivated to persevere and demonstrate a growth mindset. Conversely, if a student does not have sufficient metacognitive skills, simply believing in a growth mindset may not significantly improve student learning engagement.
Math Metacognitive Skills & Growth Mindset
Flavell (1987)2 defines metacognition as the awareness and regulation of one’s thoughts, and Zimmerman & Moylan (2009)1 identify planning, monitoring and evaluating as three skills generally involved in metacognitive regulation. Meanwhile, Dweck (2000)3 defines growth mindset as a belief that intelligence is malleable, rather than fixed. Thus, the study shared in the article suggests that motivation may be beneficial to students, but metacognitive skills are also likely needed in order for students to optimally engage with math learning.4
Ultimately, academically vulnerable students may particularly benefit from metacognition & mindset interventions.4,5
Wang, M. T., Zepeda, C. D., Qin, X., Del Toro, J., & Binning, K. R. (2021). More Than Growth Mindset: Individual and Interactive Links Among Socioeconomically Disadvantaged Adolescents’ Ability Mindsets, Metacognitive Skills, and Math Engagement. Child Development. https://doi.org/10.1111/cdev.13560
Summary By: Kristin Simmers—Kristin supports the MARIO Framework’s efforts to connect teachers and researchers to improve student learning.
Zimmerman, B. J., & Moylan, A. R. (2009). Self-regulation: Where metacognition and motivation intersect. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Handbook of metacognition in education (pp. 299–316). New York, NY: Routledge.
Flavell, J. H. (1987). Speculation about the nature and development of metacognition. En F. Weinert y R. Kluwe (Eds.), Metacognition, motivation, and understanding (pp. 21-29).
Dweck, C. S. (2000). Self-theories: Their role in motivation, personality, and development. East Sussex, UK: Psychology Press.
Rosenzweig, E. Q., & Wigfield, A. (2016). STEM motiva- tion interventions for adolescents: A promising start, but further to go. Educational Psychologist, 51, 146–163. https://doi.org/10.1080/00461520.2016.1154792
Schneider, W., & Artelt, C. (2010). Metacognition and mathematics education. ZDM-International Journal on Mathematics Education, 42 (2), 149–161.
Key Takeaway: School leaders, educators and teachers will benefit greatly from professional development in relation to “(i) creating environments that are high in emotional support, (ii) fostering children’s ability to develop, practice and enhance self-regulation skills, and (iii) promoting children’s oral language development in the early years” (Walker And Graham, 2021). —Matt Barker
Walker and Graham (2021) (Queensland University of Technology) present findings from the first year of a longitudinal project following 240 students in a primary school serving disadvantaged communities. The study aims to investigate relationships between “child characteristics, classroom interactions, and the quality of the teacher-student relationship.”
The authors identify that child characteristics, including gender, the ability to self-regulate, and language competence, impact teacher-child relationships. Specifically, “(i) girls, (ii) children who are better able to self-regulate, and (iii) children who are less hyperactive were more likely to have a close relationship with their teachers.”
The findings of the study suggest that children with higher language scores clearly correlate with “school readiness, self-regulation, both child and teacher-rated relationship quality, and [fewer] problem behaviours.” Children with lower language scores correlate with “fewer school readiness skills, poorer self-regulation, more problem behaviours and less close and more conflictual relationships with teachers.” The authors suggest that underlying language difficulties could also drive less positive relationships between students and teachers.
The authors note that a child’s attitude towards their teacher has a greater influence on teacher-student relationships than a child’s attitude towards school. Moreover, “the quality of classroom interactions, in particular emotional support, enhanced the development of close teacher-student relationships. A lack of positive emotional support contributed significantly to conflictual teacher-student relationships.”
The authors’ findings support those of Buyse et al. (2008)1 in identifying a link between child behavior issues and teacher-student conflict. The authors additionally note that “classroom climate is also linked with teacher-student relationship quality.” Of note, classes with high instructional support have more teacher-student conflict. The authors speculate that children who are at high risk are “likely to enter school with lower self-regulatory and language skills and may therefore be less able to respond to the greater intellectual and linguistic demand that is associated with higher levels of instructional support, leading to higher rates of teacher-student conflict.”
Schools and classrooms that have high emotional support have the following characteristics:
Little conflict between teachers and peers
No shouting/punitive management measures
In addition, teachers:
Are responsive to the emotional and learning needs of students
Are warm and calm
Smile and laugh
Provide effective individualised support
Soothe students as needed
Engage socially with genuine interest
Provide opportunities for independence and responsibility
Create learning activities that harness students’ interests
To support the development of self-regulation skills, teachers can provide opportunities “to engage in repeated practice of activities which develop the core components of self-regulation such as working memory, cognitive flexibility and problem-solving.”
To support the development of a child’s oral language, teachers can use a rich vocabulary in “elaborative social and instructional conversations.” This is supported by the modelling of “conceptually and intellectually rich instructional language,” where the teacher takes time to both pause and explain the vocabulary.
Summarized Article: Walker, S., & Graham, L. (2021). At-risk students and teacher-student relationships: student characteristics, attitudes to school and classroom climate. International Journal of Inclusive Education, 25(8), 896-913.
Summary by: Matt Barker—Matt loves how the MARIO Framework empowers learners to make meaningful choices to drive their personalized learning journeys.
1. Buyse, E., Verschueren, K., Doumen, S., Van Damme, J., & Maes, F. (2008). Classroom Problem Behavior and Teacher-Child Relationships in Kindergarten: The Moderating Role of Classroom Climate, Journal of School Psychology, 46 (4), 367–391. doi:10.1016/j.jsp.2007.06.009.
Key Takeaway: In addition to implementing the best interventions for students who are qualified for learning support, providing effective learning strategies needed to avoid the misidentification of English language learners (ELLs) in special education has never been more crucial. Implementing six effective vocabulary acquisition strategies (VAS) within the frameworks of self-regulated and multimedia learning may not only have promising effects on the language acquisition of ELLs but it may also prevent ELLs being falsely identified for special education eligibility. —Michael Ho
Ortogero and Ray (2021) searched, gathered, and analyzed eight research articles to examine the research question: In light of the COVID-19 pandemic, what recent vocabulary acquisition strategies (VAS) are feasible for e-learning and effective in reducing the over-representation of ELLs in special education?
Here are the major takeaways:
Nearly 12% of English language learners were identified as having a disability in 2016.1 This has prompted educators to use technology effectively to teach a second language; integrate the second language into content areas; use the first language to teach the second language; and focus on other language learning strategies, such as vocabulary acquisition strategies (VAS).
Vocabulary acquisition is essential among English language learners because they need to constantly acquire the meaning of unknown words when speaking, listening, reading, or writing. Having a strong literacy foundation is a prime indicator of academic success among English language learners.
“The following VAS for ELLs were found to be effective: (1) using L1 (first language) to teach L2 (second language), (2) Content and Language Integrated Learning, (3) designing culturally relevant activities in both L1 and L2, (4) pre teaching vocabulary multimodally using explicit word learning strategies, (5) multimedia use, and (6) promoting self-regulation.” Ultimately, these strategies can be taught in an online learning mode and may prevent the overrepresentation of English language learners in special education.
During and even after the COVID-19 pandemic, the six VAS strategies work best in the Self-Regulated Multimedia Cognitive Learning Model, which balances the use of technology and multimedia with self-regulation. It begins with pre-teaching vocabulary using explicit word learning strategies, followed by content and language integrated learning and culturally relevant learning activities. By using L1 to teach L2, the students’ vocabulary acquisition will be further enhanced. Ortogero and Ray (2021) mention “Implementing the six effective VAS within the frameworks of self-regulated and multimedia learning may have promising effects on educators continuing their efforts of effectively instructing ELs (English learners) amid an increased e-learning culture.”
Many stakeholders worry about the potential detrimental effects of learning through technology. In order to address this issue, self-regulation skills, such as setting goals and monitoring one’s learning, need to be emphasized during online learning.2 Ortogero and Ray (2021) refer to Huebeck’s 2020 study3 and emphasize that “teaching and promoting self-regulation skills can help curb technology’s distracting features and lead to a culture of learning English as a second language amid the COVID-19 pandemic that has driven educators to embrace technology.”
This study had some limitations. First, the search methods were only conducted by the first author, and the eight studies reviewed used self-reporting instruments only. In addition, a few studies did not indicate whether all instruments used were in the participant’s first language. Other VAS learning strategies related to the Cognitive Academic Language Proficiency (CALP), such as using open questions, wait time, and code-switching, were also not included.
Experimental studies examining the effects of VAS on English language learners is recommended for further research, in order to address response bias. Comparing the effects of various native languages may explain why certain VAS are more effective than others. Finally, the effects of VAS pre, during, and post COVID-19 could determine the impact the pandemic has had on English language learners.
Ortogero, S. P., & Ray, A. B. (2021). Overrepresentation of English Learners in Special Education Amid the COVID-19 Pandemic. Educational Media International, 1-20.
Summary by: Michael Ho — Michael supports the MARIO Framework because it empowers learners to take full control of their personalized learning journey, ensuring a impactful and meaningful experience
Research author Shawna P. Ortogero, Ph.D., was involved in the final version of this summary.
National Center for Education Statistics. (2018). English language learner (ELL) students enrolled in public elementary and secondary schools, by home language, grade, and selected student characteristics: Selected years, 2008-09 through fall 2016. Institute for Education Sciences.https://nces.ed.gov/programs/digest/d18/tables/dt18_204.27.asp
Pintrich, P. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 451–502). Elsevier Inc. https://doi.org/10.1016/B978-012109890-2/50043-3
Zimmerman outlines his personal connections to his work and motivations for engaging in this type of research, stating, “My career path to understanding the source and nature of human learning started with an interest in social processes, especially cognitive modeling, and has led to the exploration of self-regulatory processes. My investigation of these processes has prompted the development of several social cognitive models: a triadic model that synthesized covert, behavioral, and environmental sources of personal feedback, a multilevel model of training that begins with observational learning and proceeds sequentially to self-regulation, and a cyclical phase model that depicts the interaction of metacognitive and motivational processes during efforts to learn.” In this article, empirical support for each of these models is discussed, including its implications for formal and informal forms of instruction. This self-regulation research has revealed that students who set superior goals proactively, monitor their learning intentionally, use strategies effectively, and respond to personal feedback adaptively not only attain mastery more quickly, but also are more motivated to sustain their efforts to learn. Recommendations for future research are made.
Zimmerman’s work is key to MARIO’s vision of self-directed learning and the process through which metacognition and metacomprehension develop. Throughout the entire Framework, one can find echoes of Zimmerman’s discussion of the development of self-regulation.