Education and Information Technologies最新文献

Globally, physical education curricula are progressively integrating intelligent physical education systems, a breakthrough in physical technology. These systems utilise advanced data analytic and sensing technologies, significantly enhancing the interactivity and personalisation of physical activity, thus improving students’ athletic performance and health management. However, existing literature primarily focuses on the technological implementation of intelligent physical education systems and lacks sufficient discussion on the behavioural motivations behind students’ adoption of these systems. To address this study gap, this study designs a survey questionnaire based on the Technology Acceptance Model (TAM) and its six extended external variables: self-efficacy (SE), subjective norms (SN), technological complexity (TC), facilitating conditions (FC), knowledge acquisition (KA), and knowledge sharing (KS). This study aims to investigate the key factors that influence undergraduates' use of intelligent physical education systems, particularly in the context of rapid advancements in physical technology. The results indicate that ATU, PU, SE, and KS have direct effects on university students' BI to use intelligent physical education systems. Additionally, PEU, SN, KA, TC, and FC exert indirect effects on students' BI to engage with these systems. This study not only provides deep insights into the adoption factors of intelligent physical education systems for the academic community but also offers robust theoretical and practical support for the implementation of intelligent physical education systems in higher education institutions. Furthermore, the results will serve as a crucial reference for policymakers and educational technology developers, aiding them in better understanding and promoting the application and widespread adoption of intelligent physical education systems in higher education.

Contemporary technological advancements offer new possibilities for enhancing user creativity. We aimed to explore how technology can boost student creativity to meet the twenty-first century’s demand for innovative talent. Based on the 4P model of creativity (person, process, product, and press) and constructivist theory, a virtual reality (VR) creative enhancement system was designed, developed, and evaluated. The study recruited 47 participants, randomly assigned to either the experimental group (23 participants) using a VR system with haptic vibration feedback via electroencephalography (EEG) or the control group (24 participants) using a standard VR system. Participants’ creative performance, attention level, motivation, and cognitive load were assessed. The data were analysed using analysis of variance (ANOVA) as the statistical approach. The findings revealed that participants in the experimental group exhibited superior outcomes compared with those in the control group in terms of creative performance, attention level, and cognitive load. However, no significant difference was observed in motivation, with the control group scoring slightly higher. Our findings suggest that changing the learning environment, improving attention, reducing cognitive load, and setting up activities involving invention can effectively enhance students’ creative performance. This study provides a new technologically supported approach to creativity education, with potential applications for cultivating innovative talent in higher education.

ChatGPT has been demonstrated to possess significant capabilities in generating intricate human-like text, and recent studies have established that its performance in theory of mind (ToM) tasks is strikingly comparable to a nine-year-old child’s. However, it remains unknown whether ChatGPT outperforms children of this age group in Chinese writing, a task credibly related to ToM. To justify the claim, this study compared ChatGPT with nine-year-old children in making Chinese compositions (i.e., science-themed and nature-themed narratives), aiming to unveil the relative advantages and disadvantages by human writers and ChatGPT in Chinese writing. Based on the evaluative framework comprising of four indices (i.e., fluency, accuracy, complexity, and cohesion) to test writing quality, this study added an often-overlooked index “emotion” to extend the framework. Afterward, we collected 120 writing samples produced by ChatGPT and children and used the confirmatory factor analysis (CFA) and structural equation modelling (SEM) for data analysis and comparison. The results revealed that this age group of children surpassed ChatGPT in fluency and cohesion while ChatGPT transcended the children in accuracy. With respect to complexity, the children exhibited better skills in science-themed writing, but ChatGPT better in nature-themed writing. Most importantly, this study unlocked the pioneering discovery that children display more potent emotional expressions than ChatGPT in Chinese writing, providing an instance of evidence that ChatGPT is really even poorer than a nine-year-old child in ToM to some extent.

With the increase in life expectancy and the rapid advancement of digital technology, older adults often face challenges where formal learning opportunities are scarce. Consequently, they are compelled to rely on instructional videos for continuous learning. However, many older adults struggle with low self-efficacy and motivation. Although previous studies on instructional videos have investigated how the design of video lectures can promote learners’ self-efficacy, these studies predominantly focus on young populations. The present study aims to test the interaction effects of a lecturer’s age (young vs. older adults) and the type of learning content (Traditional Chinese Medicine (TCM) health preservation vs. digital technology) in instructional videos. The results indicated that in instructional video lectures on TCM health preservation, older adults demonstrated better learning performance when instructed by an older lecturer compared to a young one. Conversely, in instructional video lectures on digital technology, older adults exhibited better learning performance, higher motivation, and greater activation in FEFs, dlPFC, and SMC, when instructed by a young lecturer compared to an older one. Our findings have significant implications for the design of instructional videos for older adults.

Classroom response systems (CRS) represent an innovative educational technology that can be used to promote active learning and student engagement. This study explores the effectiveness of CRS in enhancing student learning and performance across various engineering courses related to heat engines. During five academic years, CRS have been used weekly in six subjects that belong to two bachelor’s degrees and one master’s degree to promote continuous learning. The performance of the students in the CRS benefits the student by up to + 10% in the final mark. In this period, data from more than 1,000 students has been collected, including key performance indicators (KPIs) derived from Kahoot!, such as the number and correctness of responses and time spent answering, and other evaluations such as theory and numerical problem exams results. The objective of the study is to find the KPI that best identifies the knowledge acquisition by the students. In order to do so, the correlation of the KPI with the final exams is analysed by means of the correlation of determination and the root mean square error. The findings reveal that KPIs based on the number of questions asked exhibit stronger correlations with exam results compared to those based on responses or correctness. The study also highlights the positive impact of CRS on student engagement, classroom dynamics, and exam preparation, supported by student feedback. In essence, this research provides insights into the relationship between CRS metrics and academic outcomes, offering valuable considerations for the integration of technology in engineering education.

Recognized as an important teaching approach, blended teaching has been widely applied in English language instruction within university settings. Nonetheless, discrepancies exist in the reported results regarding the efficacy of blended teaching approach on university students’ English learning outcomes. This study employs a comprehensive three-level meta-analysis method, analyzing 373 distinct effect sizes from 207 empirical studies. The three levels correspond to the sampling variance, the variance among effect sizes within individual studies, and the variance between different studies, allowing for a nuanced understanding of the factors influencing learning outcomes. Our findings reveal a significant overall positive impact of blended teaching on English learning outcomes. Specifically, we identify that the relationship between blended teaching and language achievement is nuanced, moderated by variables such as duration of implementation and interaction type, while remaining unaffected by teaching method, form of learning and blended mode. Additionally, we observe that the relationship between blended teaching and learners’ personal characteristics is moderated by duration of implementation, teaching method and blended mode, yet remains independent of form of learning and interaction type. These findings are poised to inform and enhance English language pedagogy within the framework of blended teaching method.

Educators in higher education institutions swiftly transitioned from face-to-face to online and remote classes to mitigate physical contact risks and ensure student and faculty safety during the pandemic. However, this abrupt shift presented both personal and institutional challenges in redefining the expectations and roles of instructors and learners in online teaching and learning activities. Despite the critical importance of understanding faculty perspectives on these teaching modality changes, limited research exists on the factors associated with faculty perspectives on transitioning from face-to-face to online teaching, particularly with a diverse sample. This study aims to address this gap by exploring factors associated with faculty perspectives on teaching modality changes in health professions education programs, utilizing a novel self-reported instrument. An online survey was distributed to assess various aspects, including teaching, social, and cognitive presence, self-efficacy, transition experience, and favorability towards online teaching. Data were collected from 117 faculty members across six U.S. institutions in 2021. Exploratory factor analysis revealed four distinct underlying factors: Community of Inquiry (CoI), self-efficacy, commitment, and favorability of online teaching. Results from multiple linear regression models indicated that previous online teaching experience was statistically significantly associated with the CoI score. The findings underscore the importance of professional development initiatives and the establishment of best practices in online teaching to support faculty in navigating and succeeding in the post-pandemic online teaching environment.

Despite continued research into the Community of Inquiry (CoI) framework, the best way to measure each presence of the framework, and in particular social presence, has not been effectively settled in prior research. The purpose of this study was to evaluate the validity of the social presence items in the CoI framework and its subscales, as well as to determine the strongest contributors to the social presence construct. An online survey of 413 students in online courses in the U.S. was administered to assess the validity and structural framework of the social presence construct. The findings from the current survey suggest that social presence is most strongly predicted by affective expression, and that all three subscales explain approximately 72% of the variance in social presence. The implications of this variance and future research items suggest that emotional expression is one of the more important factors for instructors to focus on in online courses to promote social presence.

This study addresses the emerging challenges in mathematics education, emphasizing the integration of innovative teaching strategies and tools amidst the evolving educational landscape. The study begins with an analysis of prevalent e-learning and communication systems in distance education, pinpointing their limitations and identifying the gaps in effective remote mathematics instruction. In response, we introduce a novel educational platform designed to facilitate real-time mathematics teaching over the Internet, aiming to replicate the interactive essence of traditional classroom settings within a digital domain. The system features a suite of tools including a mathematical editor, a virtual whiteboard, audio-video communication capabilities, a virtual library, and an evaluation support module, all accessible via a standard web browser. The platform’s effectiveness was assessed through its application in regular mathematics classes at two secondary schools in Romania, as well as in a private tutoring scenario. The paper presents the findings of these preliminary studies, offering insights into the usefulness and usability of the platform and its potential to seamlessly integrate into existing educational frameworks without compromising the quality of instruction.

Although researchers recognize the importance of discussing support for math learning within online learning communities, there is a lack of relevant network classifying methods and analyses at the group level to understand the behavioral differences between groups with varying levels of activity, including their mathematical literacies. In this research, we investigated different groups within a large asynchronous online discussion community for middle school students, focusing on their interaction patterns and the quality of their mathematical engagement. First, we employed an extended Surprise detection algorithm that evaluates interaction quality to classify users into core, periphery, and extra-periphery groups. Following this classification, we performed social network analysis to understand the interaction patterns among these groups. For discourse analysis, we used topic modeling methods to analyze the socio-semantic network structure of the discussions. To assess differences in math literacy and discussion success rates among the groups, we applied the Mann-Whitney U test. Findings indicate that each group is more responsive to its members, with the core group demonstrating a balanced response pattern. X-periphery students primarily engage in casual chats and open queries, indicating a more focused participation aimed at immediate learning needs. Notably, the X-periphery group exhibits the highest math literacy and discussion success rates, suggesting that lower activity levels do not hinder communication efficiency. These findings highlight the importance of considering group dynamics and roles in designing online math learning activities to foster effective communication and support, offering practical insights for sustaining online learning communities through tailored discussion activities.