Inclusive and emotionally supportive classrooms pivotal in supporting positive student-teacher relationships during school transition

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: 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:}

_{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}
_{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}

Article Abstract

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.

MARIO Connections

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.