As artificial intelligence-generated content (AIGC) reshapes knowledge acquisition, higher education faces growing inequities that demand systematic mapping and intervention. We map the AI divide in undergraduate education by combining network science with survey evidence from 301 students at Nanjing University, one of China's leading institutions in AI education. Drawing on course enrolment patterns to construct a disciplinary network, we identify four distinct student communities: science dominant, science peripheral, social sciences & science, and humanities and social sciences. Survey results reveal significant disparities in AIGC literacy and motivational efficacy, with science dominant students outperforming humanities and social sciences peers. Ordinary least squares (OLS) regression shows that motivational efficacy--particularly skill efficacy--partially mediates this gap, whereas usage efficacy does not mediate at the evaluation level, indicating a dissociation between perceived utility and critical engagement. Our findings demonstrate that curriculum structure and cross-disciplinary integration are key determinants of technological fluency. This work provides a scalable framework for diagnosing and addressing the AI divide through institutional design.
Assessing student depression in sensitive environments like special education is challenging. Standardized questionnaires may not fully reflect students' true situations. Furthermore, automated methods often falter with rich student narratives, lacking the crucial, individualized insights stemming from teachers' empathetic connections with students. Existing methods often fail to address this ambiguity or effectively integrate educator understanding. To address these limitations by fostering a synergistic human-AI collaboration, this paper introduces Human Empathy as Encoder (HEAE), a novel, human-centered AI framework for transparent and socially responsible depression severity assessment. Our approach uniquely integrates student narrative text with a teacher-derived, 9-dimensional "Empathy Vector" (EV), its dimensions guided by the PHQ-9 framework,to explicitly translate tacit empathetic insight into a structured AI input enhancing rather than replacing human judgment. Rigorous experiments optimized the multimodal fusion, text representation, and classification architecture, achieving 82.74% accuracy for 7-level severity classification. This work demonstrates a path toward more responsible and ethical affective computing by structurally embedding human empathy
We report on a profession-oriented course we offered at the University of Vienna, aimed at physics education teacher students. The course on Theoretical Classical Mechanics has been conceived and designed from its outset with the explicit goal of bridging the gap between the abstract, mathematical notions employed in Theoretical Physics with the concrete future needs of prospective teachers in their profession. We aimed at countering both the negative attitudes of students towards Theoretical Physics and the interrelated skepticism of professors regarding the students mathematical proficiency. Our main findings are that these goals can indeed be achieved through a careful selection of course material and the associated mathematical tools, by closely interwoven lecture topics and exercises, and thorough planning according to principles for high-school teaching known from science education research. Establishing close connections between the material taught in the course and the students future occupation as high-school teachers has proven to be of utmost importance. This is possible without any sacrifice of mathematical rigor or of the quality of Physics presented.
In this study, the emotion and tone of preservice teachers' reflections were analyzed using sentiment analysis with LLMs: GPT-4, Gemini, and BERT. We compared the results to understand how each tool categorizes and describes individual reflections and multiple reflections as a whole. This study aims to explore ways to bridge the gaps between qualitative, quantitative, and computational analyses of reflective practices in teacher education. This study finds that to effectively integrate LLM analysis into teacher education, developing an analysis method and result format that are both comprehensive and relevant for preservice teachers and teacher educators is crucial.
Hamidreza Amiri, Samira Peiravi, Seyedeh sara rezazadeh shojaee
et al.
Abstract Background Nowadays, Artificial intelligence (AI) is one of the most popular topics that can be integrated into healthcare activities. Currently, AI is used in specialized fields such as radiology, pathology, and ophthalmology. Despite the advantages of AI, the fear of human labor being replaced by this technology makes some students reluctant to choose specific fields. This meta-analysis aims to investigate the knowledge and attitude of medical, dental, and nursing students and experts in this field about AI and its application. Method This study was designed based on PRISMA guidelines. PubMed, Scopus, and Google Scholar databases were searched with relevant keywords. After study selection according to inclusion criteria, data of knowledge and attitude were extracted for meta-analysis. Result Twenty-two studies included 8491 participants were included in this meta-analysis. The pooled analysis revealed a proportion of 0.44 (95%CI = [0.34, 0.54], P < 0.01, I2 = 98.95%) for knowledge. Moreover, the proportion of attitude was 0.65 (95%CI = [0.55, 0.75], P < 0.01, I2 = 99.47%). The studies did not show any publication bias with a symmetrical funnel plot. Conclusion Average levels of knowledge indicate the necessity of including relevant educational programs in the student’s academic curriculum. The positive attitude of students promises the acceptance of AI technology. However, dealing with ethics education in AI and the aspects of human-AI cooperation are discussed. Future longitudinal studies could follow students to provide more data to guide how AI can be incorporated into education.
The article discusses the impact of external and internal factors on the effectiveness of higher education systems, particularly in the context of training future law enforcement officers. It is noted that ensuring quality student training requires consideration of specific learning conditions, such as requirements for firearms and physical training. The article analyzes the role of disciplines such as «Firearms Training» and «Special Physical Training» in shaping the professional skills of future law enforcement officers. The importance of these disciplines in ensuring societal security and enhancing the combat readiness of law enforcement officers in various conditions, including wartime, is highlighted. Specifically, the necessity of firearm proficiency and the ability to effectively utilize it in situations requiring law enforcement intervention is discussed. It is also noted that preparation for armed conflicts and security maintenance requires students to have a high level of physical fitness and firearm interaction skills. In the context of contemporary challenges related to increasing crime rates and wartime, the importance of combining education with firearms and physical training to develop a well-rounded law enforcement personality is emphasized. The authors emphasize that this combination helps students become prepared for real-life situations they may encounter in their future careers. The conclusion underscores the need for continuous improvement of law enforcement professionals’ skills in contemporary conditions, including tactical-specialized, firearms, and physical training. The importance of physical education and sports as a means of promoting a healthy lifestyle is also emphasized. Additionally, it is noted that present conditions and periods of wartime require law enforcement officers to possess special skills and abilities beyond routine duties. Such situations may necessitate additional training for law enforcement personnel with elements of military preparation, including terrain orientation, grenade throwing, obstacle overcoming, engineering preparation, and other important aspects.
Abdullah Bin-Ghouth, Suha Ali Batarfi, AbdulRahman Hashim Abonemi
et al.
Abstract Background Research is an important element in the improvement of the quality of health services provided to the public. It is documented that globally; medical students apply research in their school life. In Hadhramaut University, medical students work on research in groups, and it is an important part of the curriculum. There is a formal assessment of the student’s research, but there is still a gap regarding individual viewpoints and challenges faced. This study aimed to assess perception, attitude, and practice toward research among medical students at Hadhramout University. Methods This is a cross-sectional descriptive study which was conducted among medical students. This study was undertaken in Hadhramout University in Al-Mukalla district, Yemen, during the academic year 2016–2017. A self-administered pilot-tested questionnaire was used for data collection to assess perception, attitude, and practice toward the research during the educational year 2016–2017. Results A total of 265 completed responses were received. The majority had a low Knowledge score (72%). However, the majority had a positive attitude toward research (90.9%). Eighty-three students reported participation in research work. However, (44.4%) expressed research interest. Many barriers were highlighted by students including a lack of time (78.4%) and a lack of training in statistics (75.9%). Conclusion The study identified several barriers for undergraduate medical students to undertake research. It is important that these barriers should be addressed in curriculum development, so that students can retain their motivation to engage effectively in research.
Johan Linåker, Per Runeson, Anneke Zuiderwijk
et al.
High-quality data has become increasingly important to software engineers in designing and implementing today's software, for example, as an input to machine-learning algorithms and visualisation- and analytics-based features. Open data - i.e., data shared under a licence that gives users the right to study, process, and distribute the data to anyone and for any purpose - offers a mechanism to address this need. Data may originate from multiple sources, whether crowdsourced, shared by government agencies, or shared between commercial entities, and is undoubtedly inherent to all business and revenue models across the public sector, business and industry today. In this guest editorial for the Special Issue on Collaborative Aspects of Open Data in Software Engineering, we explore the collaborative aspects of open data in software engineering. We highlight how these aspects can benefit organisations, what challenges may exist and how these may be addressed based on current practice, and introduce the four papers included in this special issue.
Zeki C. Seskir, Piotr Migdał, Carrie Weidner
et al.
In this article, we provide an extensive overview of a wide range of quantum games and interactive tools that have been employed by the community in recent years. The paper presents selected tools, as described by their developers. The list includes Hello Quantum, Hello Qiskit, Particle in a Box, Psi and Delta, QPlayLearn, Virtual Lab by Quantum Flytrap, Quantum Odyssey, ScienceAtHome, and The Virtual Quantum Optics Laboratory. Additionally, we present events for quantum game development: hackathons, game jams, and semester projects. Furthermore, we discuss the Quantum Technologies Education for Everyone (QUTE4E) pilot project, which illustrates an effective integration of these interactive tools with quantum outreach and education activities. Finally, we aim at providing guidelines for incorporating quantum games and interactive tools in pedagogic materials to make quantum technologies more accessible for a wider population.
This research was conducted with the aim of mediating the role of job motivation in the relationship between stress coping strategies and social-emotional competence in primary teachers. The cross-sectional research method is correlational. The statistical population of the present study was made up of all the teachers who were teaching in the elementary school of Tehran in 1400-1401, and among them, 350 people were selected by multi-stage cluster sampling method. In this research, tools of coping strategies (Lazarus and Folkman, 1985), job motivation (Robinson, 2004) and social-emotional competence (Boyatzis, 2007) were used, all of which had acceptable validity and reliability. In order to analyze the data, SPSS-V23 and Lisrel-V7.8 software were used. In order to respond to the research hypotheses, structural equation modeling was used. The research findings showed that the model has a good fit. The results showed that strategies to deal with stress have a direct effect on teachers' social-emotional competencies (p<0.05). Strategies to deal with stress have an indirect effect on primary teachers' job motivation (p<0.05). Career motivation has an indirect effect on social-emotional competencies of elementary teachers (p<0.05). Also, the results showed that the indirect effect of stress coping strategies with social-emotional competencies through the mediation of job motivation in primary teachers was confirmed with 95% confidence. Therefore, paying attention to the mentioned variables helps researchers and therapists in prevention and designing more suitable treatments.Key words: social-emotional competence, strategies to deal with stress, job motivation
Madeleine O'Keefe, Ellen Bechtol, Jim Madsen
et al.
The IceCube Neutrino Observatory at the South Pole has tremendous emotional appeal -- the extreme Antarctic environment coupled with the aura of a pioneering experiment that explores the universe in a new way. However, as with most cutting-edge experiments, it is still challenging to translate the exotic, demanding science into accessible language. We present three examples of recent successful education, outreach, and communication activities that demonstrate how we leverage efforts and sustain connections to produce engaging results. First we describe our participation in the PolarTREC program, which pairs researchers with educators to provide deployments in the Antarctic, and how we have sustained relationships with these educators to produce high-quality experiences to reach target audiences even during a pandemic. We then focus on three activities from the past year: a summer enrichment program for high school students that was also modified for a 10-week IceCube after school program, a virtual visit to the South Pole for the ScienceWriters 2020 conference, and a series of short videos in English and Spanish suitable for all ages that explain traveling, living, and working at the South Pole.
With the advent of commercially available Mixed-Reality(MR)-headsets in recent years MR-assisted learning started to play a vital role in educational research, especially related to STEM (science, technology, engineering and mathematics) education. Along with these developments it seems viable to further frameworks and structured design processes for MR-based learning environments. Instead of a widely applicable framework for designing educational MR applications, we here consider the case of virtually enhancing physical hands-on experiments in STEM, where students are given a certain problem to solve, and how to design these. For this focused realm, we suggest an empirically driven problemand user-centred design process for MR applications to get novices to act more like experts and exemplify it for a specific experiment and problem set containing a non-trivial electric circuit with capacitors and coils.
We present an Open Educational Resource system that instructors can use to assign automatically graded, randomized, and scaffolded assessment questions for astronomy classes.
Lucken Bueno Lucas, Rosa Shizue Abe, Simone Luccas
et al.
Este artigo aborda o ensino da termorregulação animal a partir de uma sequência didática baseada nos estudos de Zabala e em cuidados metodológicos da transposição didática (Chevallard). A sequência foi implementada com alunos do 7º ano do Ensino Fundamental (anos finais) de uma escola pública da região norte do Paraná. As atividades por eles desenvolvidas, ao longo da sequência, foram analisadas segundo os pressupostos da Análise Textual Discursiva. Os dados evidenciaram as contribuições da sequência para a aprendizagem da termorregulação animal, sobretudo considerando o contingente progressivo de respostas cujos conteúdos se apresentaram mais próximos das noções fisiológicas recentes nas atividades finais da proposta didática.
Palavras-chave: Termorregulação animal; sequência didática; transposição didática; ensino de Ciências.
Nasrin Shokrpour, Shima Sheidaie, Mehdi Amirkhani
et al.
BACKGROUND: Given the relationship between positivity interventions and psychological problems, this study aimed to investigate the effect of positive thinking training on stress, anxiety, depression, and quality of life of hemodialysis patients.
MATERIALS AND METHODS: This is a quasi-experimental and interventional study conducted on 70 hemodialysis patients referred to Fasa hemodialysis centers, Iran, between April 2019 and October 2019. Patients were selected using a simple sampling method and randomly divided into control (n = 35) and intervention (n = 35) groups. The intervention group was trained on positive thinking skills in eight sessions of a workshop. Before and after the intervention, stress, anxiety, depression, and quality of life in both the groups were measured using the Depression, Anxiety, and Stress Scale-21 and Short Form-36 Questionnaire. Data were analyzed using paired t-test, independent t-test, Kolmogorov–Smirnov, and Chi-square tests.
RESULTS: There was no significant difference in the mean scores of stress, anxiety, depression, and quality of life in the two groups before the intervention.(P > 0.05), and in the control group, there was no statistically significant difference before and after the intervention (P = 0.092, P = 0.228, 0.280, respectively). In the intervention group, the mean score of stress and anxiety decreased from 23.65 ± 4.12 to 16.68 ± 4.41 (P < 0.001) and from 17.77 ± 5.15 to 14.57 ± 4.18 (P = 0.002), respectively, and that of the patients' quality of life also increased from 35.19 ± 10.07 to 55.98 ± 11.71 (P < 0.001). However, the mean score of depression did not change significantly after the intervention (P = 0.689).
CONCLUSION: According to the results of this study, the use of positive thinking intervention programs with other methods for hemodialysis patients' care and treatment is recommended as a nonpharmacological, cost-effective, and uncomplicated method.
Special aspects of education, Public aspects of medicine
ABSTRACT This article develops knowledge about the meaning and value ascribed to educational proficiency in the recruitment of full professors. Hiring processes reflect standards that organize academia and notions of academic scholarship, its value and quality, and agents involved have an institutional gate-keeping function. The empirical data, external peer review letters, is drawn from an old comprehensive research-intensive university, offering educational programmes within a broad range of scientific domains. Although a large variety of aspects are ascribed to educational proficiency, and variations do occur across scientific domains and reviewers, the main finding is a restricted notion. A special value is assigned to the scope of doctoral supervision and teacher training. Internal individual classroom performance is focused, while scholarly interaction is less emphasized. Reviewers primarily serve as gatekeepers of disciplinary research, not the education thereof, thus educational proficiency is no game changer in the context of academic scholarship.
Y. Ocaña-Fernández, Luis Alex Valenzuela Fernández, William Eduardo Mory Chiparra
et al.
This article focuses on the analysis of the spectrum related to the field of digital competencies in the higher education landscape, trying to focus on the most outstanding aspects of the technological landscape and its aspects. Emphasis is given to issues related to information and communication technologies and their gravitational role in educational work, taking into account the mechanisms that allow to strengthen the importance of digital literacy and inclusion. On the other hand, the panorama of artificial intelligence and its relationship in the training of professionals according to the demands of an increasingly technological environment are reviewed.
During the last ten years advances in open-source digital technology, used especially by data science, led to very accessible ways how to obtain, store, process, analyze or share data in almost every human activity. Data science tools bring not only transparency, accessibility, and reproducibility in open science, but also give benefits in open education as learning tools for improving effectiveness of instruction. Together with our pedagogical introduction and review of Jupyter as an interactive multimedia learning tool, we present our three-years long research in the framework of a complex mixed-methods approach which examines physics teachers' perception of Jupyter technology in three groups: Ph.D. candidates in physics education research (PER) ($N = 9$), pre-service physics teachers ($N = 33$) and in-service physics teachers ($N = 40$). Despite the fact that open-source Jupyter notebooks are natural and easy as email or web, the results suggest that in-service teachers are not prepared for Jupyter technology and open analysis, but positively accept open education data presented via another open-source data science tool, R Shiny interactive web application, as an important form of immediate feedback and learning about the quality of their instruction. Simultaneously our instruction results in the frame of the Flipped Learning also indicate that young beginning PER researchers and pre-service physics teachers can master key digital skills to work with Jupyter technology appreciating its big impact on their learning, data and statistical literacy or professional development. All results support the ongoing worldwide effort to implement Jupyter in traditional education as a promising free open-source interactive learning tool to foster learning process, especially for the upcoming young generation.