Social-Emotional Learning Interventions for Students With Special Educational Needs: A Systematic Literature Review

In the last decades, social-emotional learning interventions have been implemented in schools with the aim of fostering students’ non-academic competences. Evaluations of these interventions are essential to assess their potential effects. However, effects may vary depending on students’ variables. Therefore, the current systematic review had three main objectives: 1) to identify the effectiveness of social-emotional learning interventions with students with special educational needs, 2) to assess and evaluate those intervention conditions leading to effective outcomes in social-emotional competences for this population, and 3) to draw specific conclusions for the population of students with special educational needs. For this purpose, studies were retrieved from the databases Scopus, ERIC, EBSCO and JSTOR, past meta-analysis and (systematic) reviews, as well as from journal hand searches including the years 1994–2020. By applying different inclusion criteria, such as implementation site, students’ age and study design, a total of eleven studies were eligible for the current systematic review. The primary findings indicate that most of the intervention studies were conducted in the United States and confirm some positive, but primarily small, effects for social-emotional learning interventions for students with special educational needs. Suggestions for future research and practice are made to contribute to the improvement of upcoming intervention studies.

Nobody is left behind. The beauty of Service Learning

School closures due to COVID-19 have brought significant disruptions to education. Service-learning interventions have offered significant opportunities to reduce and reverse the long-term negative effects and to empower the recovery process of pupils in difficulty. The study was carried out with 869 students enrolled in the Primary Education Sciences master’s degree course at the University of Palermo. The participants have been involved in the planning and implementation of targeted educational courses designed for the “fragile” pupils from 33 different schools in Palermo. The primary level pupils were provided with a total of 60,000 hours of recovery and learning enhancement activities in remote mode. Challenging teaching activities fostered cognitive and learning development of the pupils. The results reveal that the service-learning project led to the rediscovery of the beauty of inclusion, integration, and civic responsibility.

Controlling-Supportive Homework Help Partially Explains the Relation between Parents’ Math Anxiety and Children’s Math Achievement

Previous research has shown that math homework help of higher-math-anxious parents impedes children’s math learning and facilitates the development of math anxiety. In the present study, we explored a possible explanation for this phenomenon by examining the relations between parents’ math anxiety, their math homework-helping styles (i.e., autonomy- and controlling-supportive), and their child’s math achievement. Parents of children ages 11 to 14 completed an online survey. Using path analysis, we examined the relations among parental factors (i.e., math anxiety, math ability, and homework-helping styles) and child math achievement. Parents’ math anxiety was positively related to both autonomy-supportive and controlling-supportive math homework-helping styles. Notably, controlling-supportive style partially mediated the relation between parents’ math anxiety and their children’s math achievement. Thus, it is possible that the use of a controlling-supportive math homework-helping style may explain why the homework help offered by higher-math-anxious parents is detrimental to their children’s math learning. Identifying negative relations between parent factors and children’s math outcomes is crucial for developing evidence-based math learning interventions.

An Exploratory Study of the Community Impacts of Service-Learning

Research on community impacts from service-learning has been scarce, yet this area is worth exploring in order to understand how and why service-learning can make a difference. The current research sought to validate a conceptual framework (Lau & Snell, 2020), which categorizes the impacts of service-learning on community partner organizations (CPOs) and on end-beneficiaries. Under the framework, impacts on end-beneficiaries can arise directly from service-learning interventions, but can also arise indirectly as a result of impacts on CPOs. For the research, semi-structured, one-to-one or focus group interviews were conducted with 13 CPO representatives, seeking their perceptions of positive and negative impacts of service-learning. Most described impacts were positive, including, for CPOs: achieving project goals to further the CPO’s mission; augmenting resources of the CPO; and gaining knowledge, insights, ideas and techniques. These positive impacts for CPOs appear to reflect three factors: alignment between service-learning project goals and the CPO’s mission; mutual recognition of students’ potential for transferring knowledge from universities to CPOs; and mutual understanding of students’ status as semi-outsiders, free to challenge existing practices or systems. Further studies can explore impacts from the end-beneficiary's perspective, and adopt longitudinal and action research approaches.

An Interpretable Pipeline for Identifying At-Risk Students

This paper introduces a novel approach to identify at-risk students with a focus on output interpretability through analyzing learning activities at a finer granularity on a weekly basis. Specifically, this approach converts the predicted output from the former weeks into meaningful probabilities to infer the predictions in the current week for maintaining the consecutiveness among learning activities. To demonstrate the efficacy of our model in identifying at-risk students, we compare the weekly AUCs and averaged performance (i.e., accuracy, precision, recall, and f1-score) over each course with the baseline models (i.e., Random Forest, Support Vector Machine, and Decision Tree), respectively. Furthermore, we adopt a Top- K metric to examine the number of at-risk students that the model is able to identify with high precision during each week. Finally, the model output is interpreted through a model-agnostic interpretation approach to support instructors to make informed recommendations for students’ learning. The experimental results demonstrate the capability and interpretability of our model in identifying at-risk students in online learning settings. In addition to that our work also provides significant implications in building accountable machine learning pipelines that can be used to automatically generated individualized learning interventions while considering fairness between different learning groups.

COVID-19 Projections for K12 Schools in Fall 2021: Significant Transmission without Interventions

Background: Millions of primary school students across the United States are about to return to in-person learning. Amidst circulation of the highly infectious Delta variant, there is danger that without the appropriate safety precautions, substantial amount of school-based spread of COVID-19 may occur. Methods: We used an extended Susceptible-Infected-Recovered computational model to estimate the number of new infections during 1 semester among a student population under different assumptions about mask usage, routine testing, and levels of incoming protection. Our analysis considers three levels of incoming protection (30%, 40%, or 50%; denoted as "low", "mid", or "high"). Universal mask usage decreases infectivity by 50%, and weekly testing may occur among 50% of the student population; positive tests prompt quarantine until recovery, with compliance contingent on symptom status. Results: Without masking and testing, more than 75% of susceptible students become get infected within three months in all settings. With masking, this values decreases to 50% for "low" incoming protection settings ("mid"=35%, "high"=24%). Testing half the masked population ("testing") further drops infections to 22% (16%, 13%). Conclusion: Without interventions in place, the vast majority of susceptible students will become infected through the semester. Universal masking can reduce student infections by 26-78%, and biweekly testing along with masking reduces infections by another 50%. To prevent new infections in the community, limit school absences, and maintain in-person learning, interventions such as masking and testing must be implemented widely, especially among elementary school settings in which children are not yet eligible for the vaccine.