Abstract Systematic reviews and meta-analyses are crucial for advancing research, yet they are time-consuming and resource-demanding. Although machine learning and natural language processing algorithms may reduce this time and these resources, their performance has not been tested in education and educational psychology, and there is a lack of clear information on when researchers should stop the reviewing process. In this study, we conducted a retrospective screening simulation using 27 systematic reviews in education and educational psychology. We evaluated the sensitivity, specificity, and estimated time savings of several learning algorithms and heuristic stopping criteria. The results showed, on average, a 58% ( SD = 19%) reduction in the screening workload of irrelevant records when using learning algorithms for abstract screening and an estimated time savings of 1.66 days ( SD = 1.80). The learning algorithm random forests with sentence bidirectional encoder representations from transformers outperformed other algorithms. This finding emphasizes the importance of incorporating semantic and contextual information during feature extraction and modeling in the screening process. Furthermore, we found that 95% of all relevant abstracts within a given dataset can be retrieved using heuristic stopping rules. Specifically, an approach that stops the screening process after classifying 20% of records and consecutively classifying 5% of irrelevant papers yielded the most significant gains in terms of specificity ( M = 42%, SD = 28%). However, the performance of the heuristic stopping criteria depended on the learning algorithm used and the length and proportion of relevant papers in an abstract collection. Our study provides empirical evidence on the performance of machine learning screening algorithms for abstract screening in systematic reviews in education and educational psychology. 

Screening Smarter, Not Harder: A Comparative Analysis of Machine Learning Screening Algorithms and Heuristic Stopping Criteria for Systematic Reviews in Educational Research

Student well-being has gained prominence on both the scientific and political agendas, as it is recognized as a crucial skill in addressing the economic, ecological, and social challenges of the 21st century. Relationships that students form with teachers and peers in the classroom are important for their academic, social, and emotional development. Building and maintaining positive relationships contributes to psychological growth and well-being. This article strives for a deeper understanding of the association between student well-being and classroom relationships from the students’ perspective. Mediation regression analysis was conducted between student well-being, teacher–student relationships, and student–student relationships to overcome limitations of prior studies using a unidimensional approach on student well-being and considering relationships in separate models. This study shows that both relationships are related to student well-being, however associations differ regarding different dimensions of student well-being and students’ individual factors such as gender, migration background, and socio-economic status. Providing a multi-dimensional approach on student well-being as well as taking both relationships into account adds to a profound understanding of processes in classrooms. Insights on these relations can help educators, schools and researchers develop strategies to foster relationships in the classroom and, in succession, enhance well-being in school. 

The role of teacher–student relationships and student–student relationships for secondary school students’ well-being in Switzerland

Autistic students often experience peer relationship difficulties. As peer acceptance and rejection may be malleable over time, we examined predictors of change in peer acceptance and peer rejection among early elementary-age autistic students. We followed 166 autistic children (mean age: 6.1 years [range: 4–8], 82.5% boys, grades preK-2nd) longitudinally across 2 school years. Social skills, internalizing problems, and externalizing behaviors were considered as predictors of change in teacher-rated peer acceptance and rejection, covarying IQ and autism characteristics. Autistic children experienced high rejection and low acceptance; 51.9% of children were rejected by peers in one or both school years. Results revealed distinct predictors for peer acceptance versus rejection: social skills predicted change in peer acceptance across school years, whereas externalizing problems predicted change in peer rejection. Internalizing problems did not predict change in either construct. Findings can assist school professionals in supporting social acceptance and acceptance for young autistic students. 

Predicting peer acceptance and peer rejection for autistic children

In this meta-analysis, we review the nomological networks of six need-supportive and need-thwarting categories, as defined by self-determination theory (SDT), and as they apply to students in educational contexts. We conducted a synthesis of 8693 correlations from 637 samples (N = 388,912). A total of 72 covariates were examined, resulting in 183 meta-analytic effects reported. Results indicate that teachers and parents who experience psychological need satisfaction and well-being are seen as more supportive. Supportive teacher behaviors correlated positively with a range of desired student outcomes, including performance, engagement, and well-being. Thwarting behaviors tended to display the opposite pattern. Our results are consistent with the theoretical expectations of SDT, yet questions remain concerning the incremental validity of these constructs. We highlight the need for further research on (a) factors that cause teachers to provide support and (b) the specific behaviors within each category to distinguish these categories and increase practical utility. 

Need Support and Need Thwarting: A Meta-Analysis of Autonomy, Competence, and Relatedness Supportive and Thwarting Behaviors in Student Populations.

The quality of teacher-student relationships has been shown to relate to adolescents’ prosocial behavior, but the motivational mechanisms underlying this association remained unclear. Based on relationships motivation theory (RMT), we examined whether the associations between teacher-student relationships (closeness and conflict) and prosocial behavior are bidirectional, and the mediating role of basic psychological need satisfaction (autonomy, competence, and relatedness need satisfaction) in these links. Data were collected from a sample of 438 secondary school students who completed a survey at two-time points over eight months. The cross-lagged autoregressive model revealed that the relation between close teacher-student relationship and prosocial behavior was bidirectional over time. Moreover, relatedness need satisfaction mediated the positive effect of close teacher-student relationship and the negative effect of teacher-student relationship conflict on adolescents’ prosocial behavior. This study highlights the importance of close teacher-student relationship and relatedness need satisfaction to foster adolescents’ prosocial behavior.

/pdf/longitudinal-associations-between-teacher-student-2xzubg9m.pdf

Longitudinal Associations between Teacher-Student Relationships and Prosocial Behavior in Adolescence: The Mediating Role of Basic Need Satisfaction

The relationships that students have with teachers and peers are important for their academic, social, and behavioral development. How teachers relate to students may affect students’ peer relation...

https://journals.sagepub.com/doi/pdf/10.3102/00346543211051428

The Teacher’s Invisible Hand: A Meta-Analysis of the Relevance of Teacher–Student Relationship Quality for Peer Relationships and the Contribution of Student Behavior:

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The Teacher’s Invisible Hand: A Meta-Analysis of the Relevance of Teacher–Student Relationship Quality for Peer Relationships and the Contribution of Student Behavior: