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Given that schools are, potentially, powerful sites for influencing adolescent behaviour, it is important that there is greater understanding of the psychosocial aspects of the school climate that can be leveraged for this purpose. The research reported in this article used structural equation modelling (with data from a sample of 6120 students at Australian high schools) to examine the influence of the psychosocial school-level environment on students’ self-reported experiences of bully victimisation (i.e. being victims of bullying) and engagement in delinquent behaviours. Further, we examined whether bully victimisation mediated the relationships between school climate variables and delinquent behaviours. School connectedness and rule clarity were negatively associated with both bully victimisation and delinquency (p < 0.05), and teacher support was negatively associated with bully victimisation (p < 0.01), confirming the importance of these aspects of the school-level environment. However, affirming diversity and reporting and seeking help both had positive influences on bully victimisation (p < 0.05), raising concerns about the ways in which these aspects of the school-level environment might have been promoted. Importantly, bully victimisation was found to mediate the influence of five of the six school climate constructs on delinquent behaviours (p < 0.001). This study advance our understanding of how specific aspects of the school climate influence the prevalence of bullying and delinquent behaviour, adding weight to the call for educators to actively monitor and enhance psychosocial aspects of the school climate in order to improve student behavioural outcomes.

We use a randomised experiment to study the effect of offering half of 556 freshman students a learning analytics dashboard and a weekly email with a link to their dashboard, on student behaviour in the online environment and final exam performance. The dashboard shows their online progress in the learning management systems, their predicted chance of passing, their predicted grade and their online intermediate performance compared with the total cohort. The email with dashboard access, as well as dashboard use, has positive effects on student behaviour in the online environment, but no effects are found on student performance in the final exam of the programming course. However, we do find differential effects by specialisation and student characteristics.

In this review, we scope the role of interpersonal relationships in students' academic motivation, engagement, and achievement. We argue that achievement motivation theory, current issues, and educational practice can be conceptualized in relational terms. Influential theorizing, including attribution theory, expectancy-value theory, goal theory, self-determination theory, self-efficacy theory, and self-worth motivation theory, is reviewed in the context of the role of significant others in young people's academic lives. Implications for educational practice are examined in the light of these theoretical perspectives and their component constructs and mechanisms. A trilevel framework is proposed as an integrative and relationally based response to enhance students' motivation, engagement, and achievement. This framework encompasses student-level action (universal programs and intervention, targeted programs for at-risk populations, extracurricular activity, cooperative learning, and mentoring), teacher- and classroom-level action (connective instruction, professional development, teacher retention, teacher training, and classroom composition), and school-level action (school as community and effective leadership).

PurposeThis research investigates the relationship between e-learning service quality dimensions, student e-learning satisfaction, commitment and behaviour towards finance courses in higher education institutes of Pakistan.Design/methodology/approachDue to specific study objectives, the authors gathered sample data of 359 university students who were enrolled in the traditional learning system and shifted to the e-learning environment. The study employed partial least squares-structural equation modelling (PLS-SEM) based approach using Smart PLS version 3.0.FindingsThe results indicated that out of four e-learning service quality dimensions, three dimensions (system quality, course material and instructor quality, information technology (IT) and support service quality) positively impacted student e-learning satisfaction. The other dimension of e-learning service quality (course website quality) showed a positive but insignificant effect on e-learning satisfaction. Additionally, e-learning satisfaction was positively related to e-learning commitment, which, in turn, has a positive and significant influence on student e-learning behaviour towards finance courses.Originality/valueOverall, the study’s findings provide useful policy implications for higher education institutes, particularly in the coronavirus disease 2019 (COVID-19) pandemic.

While numerous studies have demonstrated a correlation between exclusionary discipline and negative student outcomes, this relationship is likely confounded by other factors related to the underlying misbehavior or risk of disciplinary referral. Using 10 years of student-level demographic, achievement, and disciplinary data from all K-12 public schools in Arkansas, we find that exclusionary consequences are related to worse academic outcomes (e.g., test scores and grade retention) than less exclusionary consequences, controlling for type of behavioral infraction. However, despite controlling for a robust set of covariates, sensitivity checks demonstrate that the estimated relationships between consequences and academic outcomes may still be driven by selection bias into consequence type. Implications for policy and practice are discussed.

This paper investigates the challenges experienced by some Australian school educators in implementing differentiated instruction (DI) at a large secondary school. A small-scale study was conducted using individual, semi-structured interviews with teachers and school leaders. Using thematic analysis, three major themes were identified, namely: teachers' barriers to implementing DI, school leaders' constraints to implementing DI, and pre-service to in-service exchanges and sharing about DI. Findings from teachers revealed limited school resources, student behaviour issues and inadequate time for planning and implementation. School leaders also identified time as an impeding factor but also reticence by experienced teachers to use DI. Teacher education courses are not clear about DI as a comprehensive teaching framework suitable for all students. Results highlight the need for further research at the teacher educator, teacher and school leader level to remove existing barriers, constraints, and misunderstandings about DI to ensure maximum learning opportunities for all students. [Author abstract]

The present study examined associations between the quality of teacher-child relationships and behavior problems among elementary school students using data from the NICHD Study of Early Child Care and Youth Development, a study of 1,364 children from birth through adolescence. There were two main findings. First, high-quality teacher-child relationships predicted low levels of externalizing behaviors. Second, high-quality relationships acted as protective factors, helping to prevent children with high levels of internalizing behaviors in early childhood from developing trajectories of long-term internalizing behavior problems. Teacher-child relationships may be proximal phenomena that can be targeted in interventions to help prevent behavior problems in middle childhood.

Effective classroom instruction requires monitoring student participation and interaction during class, identifying cues to simulate their attention. The ability of teachers to analyze and evaluate students’ classroom behavior is becoming a crucial criterion for quality teaching. Artificial intelligence (AI)-based behavior recognition techniques can help evaluate students’ attention and engagement during classroom sessions. With rapid digitalization, the global education system is adapting and exploring emerging technological innovations, such as AI, the Internet of Things, and big data analytics, to improve education systems. In educational institutions, modern classroom systems are supplemented with the latest technologies to make them more interactive, student centered, and customized. However, it is difficult for instructors to assess students’ interest and attention levels even with these technologies. This study harnesses modern technology to introduce an intelligent real-time vision-based classroom to monitor students’ emotions, attendance, and attention levels even when they have face masks on. We used a machine learning approach to train students’ behavior recognition models, including identifying facial expressions, to identify students’ attention/non-attention in a classroom. The attention/no-attention dataset is collected based on nine categories. The dataset is given the YOLOv5 pre-trained weights for training. For validation, the performance of various versions of the YOLOv5 model (v5m, v5n, v5l, v5s, and v5x) are compared based on different evaluation measures (precision, recall, mAP, and F1 score). Our results show that all models show promising performance with 76% average accuracy. Applying the developed model can enable instructors to visualize students’ behavior and emotional states at different levels, allowing them to appropriately manage teaching sessions by considering student-centered learning scenarios. Overall, the proposed model will enhance instructors’ performance and students at an academic level.

The gap in achievement across racial and ethnic groups has been a focus of education research for decades, but the disproportionate suspension and expulsion of Black, Latino, and American Indian students has received less attention. This article synthesizes research on racial and ethnic patterns in school sanctions and considers how disproportionate discipline might contribute to lagging achievement among students of color. It further examines the evidence for student, school, and community contributors to the racial and ethnic patterns in school sanctions, and it offers promising directions for gap-reducing discipline policies and practices.

This study examined the demographic, pre-college, environmental, and college factors that impact students' interests in and decisions to earn a science, technology, engineering, or mathematics (STEM) degree among students attending a Hispanic Serving Institution (HSI). Results indicated that Hispanic students were well represented among STEM majors, and students' decisions to declare a STEM major and earn a STEM degree were uniquely influenced by students' gender, ethnicity, SAT math score, and high school percentile. Earning a STEM degree was related to students' first-semester GPA and enrollment in mathematics and science \"gatekeeper\" courses. Findings indicate that HSIs may be an important point of access for students in STEM fields and may also provide opportunity for more equitable outcomes for Hispanic students.