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
  • Provide choice

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.

Additional References:

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: 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 

Summarized Article

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.

Additional References:

  1. 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. 
  2. 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).
  3. Dweck, C. S. (2000). Self-theories: Their role in motivation, personality, and development. East Sussex, UK: Psychology Press.
  4. 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 
  5. Schneider, W., & Artelt, C. (2010). Metacognition and mathematics education. ZDM-International Journal on Mathematics Education, 42 (2), 149–161.

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.

Summarized Article:

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.

Additional References:

  1. 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
  2. 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
  3. Huebeck, E. (2020, June 3). How did COVID-19 change your teaching, for better or worse? See teachers’ responses. Education Week. https://www.edweek.org/ew/articles/2020/06/03/how-did-covid-19-change-your-teaching-for.html