Every day teachers manage social, emotional, and behavioural difficulties of their students, trying to create the best educational opportunities for all of them. Often, these problems affect the educational processes, increasing the stress levels of both teachers and students, disrupting the flow of lessons, and negatively impacting the school climate. Compounding these challenges, interruptions to in-person schooling caused by the COVID-19 pandemic likely exacerbated student social, emotional, and behavioural difficulties as a function of protracted social isolation, changes in the modalities of delivering educational instruction, and stress related to health concerns. A recognized way to address student social, emotional, and behavioural challenges is to encourage teachers to systematically monitor student behaviour, plan tailored interventions, gather data to test intervention effectiveness, and use data to make informed intervention decisions.
This Research Topic aims to gather multidisciplinary contributions that highlight how monitoring student behaviour can improve the management of their difficulties, particularly with the support of Information and Communication Technologies that can facilitate this task, including use of efficient automated tools for collecting informed data and observing progress during the intervention.
Suggested themes for this Research Topic include (but are not limited to):
• Case studies illustrating evidence-based practices in the monitoring and management of student's difficulties for both face-to-face and distance learning;
• The use of technologies (e.g., mobile phone apps, wearable systems, or other smart devices) to gather and/or analyse behavioural data to support informed decisions;
• Use of learning analytics to monitor students' behaviour and inform strategies to address difficulties;
• Monitoring of student social media use to identify predictors of social, emotional, and behavioural distress;
• The creation of open datasets/ontologies to identify the best interventions for addressing a student difficulty in a specific age group;
• The development and evaluation of web-based tools or mobile phone apps that apply algorithmic decision-making tools to aid teachers in selecting evidence-based interventions for student social, emotional, or behavioural difficulties;
• The use of Information and Communication Technologies to monitor the consequences of COVID-19 restrictions on student wellbeing, including the possible detrimental role of distance education on student engagement with classroom instruction and interpersonal interactions, focusing on the subsequent onset of cognitive, behavioural, and affective problems.
Every day teachers manage social, emotional, and behavioural difficulties of their students, trying to create the best educational opportunities for all of them. Often, these problems affect the educational processes, increasing the stress levels of both teachers and students, disrupting the flow of lessons, and negatively impacting the school climate. Compounding these challenges, interruptions to in-person schooling caused by the COVID-19 pandemic likely exacerbated student social, emotional, and behavioural difficulties as a function of protracted social isolation, changes in the modalities of delivering educational instruction, and stress related to health concerns. A recognized way to address student social, emotional, and behavioural challenges is to encourage teachers to systematically monitor student behaviour, plan tailored interventions, gather data to test intervention effectiveness, and use data to make informed intervention decisions.
This Research Topic aims to gather multidisciplinary contributions that highlight how monitoring student behaviour can improve the management of their difficulties, particularly with the support of Information and Communication Technologies that can facilitate this task, including use of efficient automated tools for collecting informed data and observing progress during the intervention.
Suggested themes for this Research Topic include (but are not limited to):
• Case studies illustrating evidence-based practices in the monitoring and management of student's difficulties for both face-to-face and distance learning;
• The use of technologies (e.g., mobile phone apps, wearable systems, or other smart devices) to gather and/or analyse behavioural data to support informed decisions;
• Use of learning analytics to monitor students' behaviour and inform strategies to address difficulties;
• Monitoring of student social media use to identify predictors of social, emotional, and behavioural distress;
• The creation of open datasets/ontologies to identify the best interventions for addressing a student difficulty in a specific age group;
• The development and evaluation of web-based tools or mobile phone apps that apply algorithmic decision-making tools to aid teachers in selecting evidence-based interventions for student social, emotional, or behavioural difficulties;
• The use of Information and Communication Technologies to monitor the consequences of COVID-19 restrictions on student wellbeing, including the possible detrimental role of distance education on student engagement with classroom instruction and interpersonal interactions, focusing on the subsequent onset of cognitive, behavioural, and affective problems.
