Bidirectional remote connections among virtual ICT laboratories ranging over multiple network segments

Since Covid-19 has been prevalent over the world, it has become important for us to observe the following three countermeasures: Actually, these countermeasures have made it impossible to put various kinds of scientific experiments into practice especially in Japanese senior high schools, because scientific experiments necessarily require many students to gather in the inside of one laboratory and to keep academic conversations with each other. In this talk, we introduce a system of constructing virtual ICT laboratories which enables each student participating in a certain ICT experiment to deploy each network application such as a web browser or an e-mailer and to observe the others' ICT settings simultaneously. This system can be realized by the simultaneous combined use of Zoom and Cisco Packet Tracer. Assuming that this system is applied to two network students which are geographically located far from each other, we can classify this system into the following: Finally, we should be careful of the fact that it is one thing to realize Case 1 and quite another to realize Case 2. In other words, While, in the network circumstances following Case 1, two students have only to apply wireless LAN routers for bidirectionally connecting their own PCs to each other, in the network circumstances following Case 2, they have to employ some other network application such as NAT traversal. © 2022 ACM.

Classifying the Students' Behavior on e-Learning System using Fine-Tuning K-NN Method

monitoring the student's behavior is challenging for teachers in online learning, which is crucial to solving. It is because, in this pandemic period, online learning is required to minimize the spreading of coronavirus. However, research in this domain is not much. This study provides an alternative to this problem by classifying students' behavior in the e-Learning system, where the k-NN is applied to mine the students' behavior. In addition, this paper also tests the proper parameters to improve the performance of k-NN: k and distance. The experimental result shows that the best performance on the cross-validation technique is reached by Euclidean distance and, on the percentage-split, is achieved by distance-Manhattan. These are indicated by the highest accuracy level obtained by neighbors of five and 20 fold, about 96.9% on the cross-validation technique. On the percentage split technique, the highest accuracy level, about 95.3%, is reached by neighbors of four and split 50%. In this best performance, four students are misclassified on the cross-validation and six on the percentage split. © 2022 IEEE.

Technology-Enhanced and Student-Centered Learning as a Method to Foster Students' ICT Competence and Problem Coping Skills

The aim of this research-to-practice full paper is to present the results of most recent analyses of the long-term school pilot project named "learning office approach". The learning office represents an alternative branch of a technology-oriented vocational secondary school in Europe encompassing the grades K9-K13 and has been implemented at the IT department in 2016. Students of a learning office cohort have flexible course schedules allowing them to choose between several subjects on a daily basis, which in turn enables differentiation and individualization: Students seeking help or striving to deepen their knowledge and skills may visit chosen subjects more often. Since learning office subjects do not rely on lectures and direct instruction, teachers become facilitative coaches helping students become self-responsible learners and study in a self-driven, self-directed way, which in turn fosters their 21st century skills.The COVID-19 pandemic and resulting emergency remote teaching strategies demonstrated the supreme importance of digital competences and self-efficacy: Students were abruptly required to work autonomously with digital systems and study at home in a self-driven way. Since the learning office heavily relies on students working with digital educational material and tools in a self-directed and student-centered way, the question arises if learners show indications of increased ICT competences and self-efficacy in the learning office.This paper evaluates the interplay of students' self-reported ICT skills, school-specific self-efficacy, and academic performance in the learning office approach and traditional classrooms. Based on an extensive literature review, a questionnaire was developed and distributed among all 552 students of the grades 9-13 and students' final grades of the winter term 2021/22 were analyzed. The results show a significant increase in self-perceived problem coping skills and ICT competences in the learning office approach, including the sub-scales "general ICT self-concept", "communication", "process and store", and "generate content". We conclude that technology-enhanced student-centered approaches, such as the learning office, are a viable method to foster students' 21st century digital skills. © 2022 IEEE.

Food insecurity in school-aged children

Food insecurity in the United Kingdom has been described as a 'public health emergency' which has been exacerbated by the onset and continuation of the COVID-19 pandemic. Drawing on research evidence and a reflective account from a current primary school teacher, this chapter highlights the multifaceted impacts of food insecurity for children in schools. It also draws attention to some important considerations around food, education and food-related interventions for practitioners supporting children in schools. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Assessment of a Poverty Simulation in Medical Education

Purpose: According to the US Census 2019 Income and Poverty report, 10.5% of the population lives below the poverty line, and approximately 10.5 million individuals below 18 years were in poverty in 2019. Children and adolescents in poverty are at risk for poor developmental and psychosocial outcomes, presenting a significant financial burden for families and the general public. Yet low-income populations continue to face barriers to healthcare, leaving them vulnerable to worse health outcomes. Unfortunately, medical students may adopt unfavorable attitudes toward low-income patients due to lack of empathy, poor understanding, and burnout, which negatively affects patient care. A poverty simulation module was included in the medical student curriculum at our institution to improve understanding and empathy toward low-income patients. Methods: IRB approval was obtained prior to data collection. Participants included medical students in one US medical school from 2018 to 2021. In 2021, students participated virtually due to the COVID-19 pandemic, though the objectives and methods remained the same as in person. Participants were placed in a poverty simulation, roleplaying as one of 26 different families facing poverty across four, 15-minute weeks with limited resources and additional social and medical challenges. Students completed a pre-simulation and post-simulation survey with free response and 23-items questioning perceptions of socioeconomic barriers (Perceptions), confidence in handling low-income populations (Confidence), and likelihood of addressing poverty (Likelihood). Each category was scored on a numeric scale that was summed together. The difference in scores between pre- and post-simulation survey responses was measured for significance using Wilcoxon and paired t-tests. The virtual simulation scores of 2021 were also compared with in-person scores from 2018 to 2020. Student free responses were then categorized into 10 topics and measured for variation with standard t-tests. Results: The post-simulation survey results showed increased scores from 2018 through 2021 with an average difference of +1.21 for Perceptions, +1.29 for Confidence, +3.27 for Likelihood. Only Confidence and Likelihood score increases were found to be significant with p-values ranging from 3.66E-17 to 9.95E-05 across all years (p < 0.05). The Perceptions category showed no significant difference from 2018-2020, except 2021 which showed a p-value of 1.26E-04 (p < 0.05). For in-person versus virtual simulation, there was a significant difference in average sum difference across all categories of 7.31 and Z score of <0.0001 (p <0.0001). Students’ free responses commonly focused on the difficulty of budgeting in poverty with no significant variation between years (p < 0.05). Conclusions: A significant improvement was seen in confidence when treating low-income populations and likelihood of addressing poverty in several iterations of a poverty simulation among medical students. This study is limited by variance in student responses, issues with pre- and post-simulation survey matching, and response restriction to numbered scales as opposed to free response. The results of this project encourage the continuation of this simulation among medical students and its expansion to other health professional programs. Sources of Support: ELS Staff at University of Southern Florida Morsani College of Medicine.