Using a 3D Simulation for Teaching Functional Skills to Students with Learning, Attentional, Behavioral, and Emotional Disabilities

The study presents results from the use of a 3D simulation for teaching functional skills to students with learning, attentional, behavioral, and emotional disabilities, attending regular schools. An A-B single-subject study design was applied. The participating students (eight eight-to-nine years old) explored the simulation (a virtual school), encountered situations in which they observed how they are expected to behave, and had to demonstrate what they have learned. Each student attended a total of four two-hour sessions. Data were collected by means of observations and semi-structured interviews. All students demonstrated improved functional skills both in terms of the number of behaviors they acquired and in terms of those that were retained and manifested in the real school environment. On the basis of the results, it can be argued that 3D simulations are a promising tool for teaching functional skills to students with disabilities.

Children’s Water Intake Lower During In-Person School Compared To Virtual School During COVID-19 Pandemic

Background: Children’s hydration is often inadequate during school potentially causing detrimental effects on cognitive performance. Previous studies investigating water intake during school lack comparison to a control group. The rise of virtual school during the COVID-19 pandemic created a unique opportunity to assess water intake during school but in a setting outside of school. Objective: Compare water intake of children attending in-person classrooms to water intake of children attending school virtually. We hypothesized water intake would be higher in children attending school virtually.Methods: A validated water intake questionnaire was sent to parents and their children (aged 10-17 years) between September 2020 and March 2021. The questionnaire asked participants how often they consumed a standardized volume of beverage types over one week. Parents indicated if children were attending school in-person or virtually. Results: 54 children indicated they were attending school in-person while 76 indicated attending school virtually (N = 130). Water intake of children attending in-person school (1688 ± 680 mL) was lower as compared to children attending school virtually (1998 ± 831 mL) (F = 5.09, p < 0.05, Figure 1). The multivariate regression examining demographics, parent water intake, and school setting as predictors of child water intake was significant (R2 = 0.33, p < 0.05). Higher child water intake was associated with older age (b = 0.29, p < 0.05), lower family income (b = -0.25, p < 0.05), higher parent water intake (b = 0.39, p < 0.05), and virtual school setting (b = 0.18, p < 0.05).Conclusion: Children’s water intake was higher during virtual school as compared to in-person school. Hydration of parents may influence children, especially when the child is attending school virtually.

Mongolian Neuroscience Society (MNS) - The 8th Annual Meeting of the Mongolian Neuroscience Society and IBRO-APRC Ulaanbaatar Associate School on Fundamental Techniques in Neuroscience 2021

In 2021, the Mongolian Neuroscience Society (MNS), together with the International Brain Research Organization (IBRO) and the Mongolian National University of Medical Sciences (MNUMS), organized two events: The 8th Annual Meeting of the Mongolian Neuroscience Society themed as "Multidisciplinary Brain Science 2021" and the IBRO-APRC Ulaanbaatar Associate School on Fundamental Techniques in Neuroscience. Multidisciplinary Brain Science 2021 aimed to bring together scientists with brain science-related backgrounds under an umbrella meeting consisting of educational lectures and academic connections. It was held with 14 invited lecturers and 20 speakers for two days virtually from August 13 to 14, 2021. The meeting was streamed live on social media, which brought together 2.6K online viewers. The goal of the IBRO-APRC Associate School on Fundamental Techniques in Neuroscience was to enable students to understand the theoretical and practical fundamentals of neuroscience. This virtual school was formed by 20 students and 16 faculty members from 5 countries. The students participated in lectures, technical talks, interactive discussions, and hands-on sessions on responsible conduct of research in neuroscience with a high neuroethical standard during the 6-day program. The events were a great success, offering a unique opportunity for the participants to get updated with current advances in brain science by global and regional experts in neuroscience and facilitate academic collaborations.

Feasibility Study to Identify Machine Learning Predictors for a Virtual School Environment: Virtual Reality Stroop Task

An adaptive virtual school environment can offer cognitive assessments (e.g., Virtual Classroom Stroop Task) with user-specific distraction levels that mimic the conditions found in a student’s actual classroom. Former iterations of the virtual reality classroom Stroop tasks did not adapt to user performance in the face of distractors. While advances in virtual reality-based assessments provide potential for increasing assessment of cognitive processes, less has been done to develop these simulations into personalized virtual environments for improved assessment. An adaptive virtual school environment offers the potential for dynamically adapting the difficulty level (e.g., level and amount of distractors) specific to the user’s performance. This study aimed to identify machine learning predictors that could be utilized for cognitive performance classifiers, from participants (N = 60) using three classification techniques: Support Vector Machines (SVM), Naive Bayes (NB), and k-Nearest Neighbors (kNN). Participants were categorized into either high performing or low performing categories based upon their average calculated throughput performance on tasks assessing their attentional processes during a distraction condition. The predictors for the classifiers used the average cognitive response time and average motor response dwell time (amount of time response button was pressed) for each section of the virtual reality-based Stroop task totaling 24 predictors. Using 10-fold cross validation during the training of the classifiers, revealed that the SVM (86.7%) classifier was the most robust classifier followed by Naïve Bayes (81.7%) and KNN (76.7%) for identifying cognitive performance. Results from the classifiers suggests that we can use average response time and dwell time as predictors to adapt the social cues and distractors in the environment to the appropriate difficulty level for the user.

Practice in a Pandemic: School Social Workers’ Adaptations and Experiences During the 2020 COVID-19 School Disruptions

In March 2020, as American PreK-12 schools shut down and moved into online learning in response to the global COVID-19 pandemic, there was little information about how school social workers (SSWs) were responding to the crisis. This study used a national online survey to understand how SSWs ( N = 1,275) adapted their school practice during the initial 2020 COVID-19 crisis. Findings from this study indicate that SSWs made swift and (relatively) smooth adaptations of their traditional practice role to the new context, though not without reporting considerable professional stress and personal challenges doing so. SSWs reported significant concerns about their ability to deliver effective virtual school social work services given their students’ low motivation and lack of engagement with online learning, as well as significant worries about how their students were faring during the first months of the pandemic. Implications for school social work practice, policy, and research are discussed.