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This commentary discusses the broader potential of student response systems (SRS) regarding their positive impact on student mental health and wellbeing. The purpose of this paper is to draw on relevant literature to illustrate the wider social and intrapersonal benefits of SRS beyond its use as an educational tool.

Tenets of social information processing theory are used in conjunction with the literature from health, sociological and psychological disciplines to explicate the mental health benefits of SRS.

SRS can make a positive contribution students’ mental health and wellbeing, thus assisting the broader pastoral support and employability frameworks of higher education institutions.

An original perspective on the use of SRS in promoting the mental health and wellbeing of university students

The purpose of this paper is to investigate the determinants of users' intention to continue to invest in cryptocurrencies. The paper also aims to examine the impact of hedonic motivation and the legal environment on perceived value in cryptocurrencies.

A questionnaire was designed to obtain data from 258 respondents in UAE. The Structural Equation Modeling – Partial Least Squares (SEM-PLS) was used to evaluate the research model and test the hypotheses.

The results of smart PLS path analysis showed that perceived value, hedonic motivation, gambling attitude, and price volatility were significant determinants of the continued intention to invest in cryptocurrency. This study also revealed that hedonic motivation enhances perceived value and improves the perception of cryptocurrencies value from user's perspective.

This study provides new insights into the literature on cryptocurrencies adoption, and delivers advanced understanding about the determinants of user's intention to continue investing in cryptocurrencies. In addition, the study provides important practical implications for cryptocurrencies companies to promote this financial technology to users by enhancing the knowledge of policy makers about how investors think and get motivated towards a continued investment of cryptocurrencies.

The research questions probe into the heart of participatory learning’s scholarly landscape. They inquire about historical trends, shifts in research interest, and regional contributions, highlighting the global reach of participatory learning discourse. The study also reaches into the most cited papers, emphasizing their pivotal role in shaping the field’s trajectory.

The research design of our study involves a retrospective analysis focused on the topic of participatory learning in education. A retrospective analysis is a methodological approach that entails examining existing literature, data, and publications within a specific field to identify trends, patterns, and insights over a defined period. In the context of participatory learning in education, this research design allows us to gain a comprehensive understanding of the evolution, contributions, and emerging directions within this pedagogical approach.

The culmination of this study lies in formulating 75 thought-provoking future research questions. These questions are designed to guide the future trajectory of participatory learning research, addressing existing gaps and propelling the field toward new horizons. The findings of the study contribute to a panoramic view of participatory learning’s evolution, global impact, and potential for reshaping education. It is a compass for researchers, educators, and policymakers navigating the intricate landscape of participatory learning in education.

Themes and topics are thoroughly explored, unrevealed the multidimensional nature of participatory learning research. The investigation spans time, revealing enduring themes while unveiling emerging areas of inquiry that capture the attention of researchers and practitioners. Current trends and focus areas are scrutinized, offering insights into the ever-evolving scholarly pursuits within participatory learning.

This comprehensive study investigates the evolution and impact of research on participatory learning in education from 1995 to 2023. The research objectives encompass a broad spectrum, including trend analysis, geographical distribution assessment and identification of influential papers, thematic exploration, and the formulation of future research questions. Through a meticulous examination of published literature, this study aims to shed light on the development of participatory learning as a transformative educational approach.

This study’s originality lies in its comprehensive analysis of participatory learning in education from 1995 to 2023, revealing temporal trends, global contributions, influential papers, thematic nuances, and emerging trends. By amalgamating these dimensions, it offers a holistic view of participatory learning’s evolution, impact, and future directions, enriching the understanding of this transformative educational approach and guiding further research and practice.

This study examines the relationship of principals’ systems thinking (PST) to student outcomes of academic achievement and school violence. The investigation relies on the contingency theory, according to which effective leadership is contingent on the nature of the situational influences to which managers are exposed. Specifically, the study investigates the influence of school structure – bureaucratic vs organic – on the relationship between PST and student outcomes of academic achievement and school violence after accounting for students’ socioeconomic backgrounds and principals' demographics.

A three-source survey design with self-reported and non-self-reported data was used, with a sample of 423 participants from 71 elementary schools in Israel. The sample included senior management team members and teachers. The data were aggregated at the school level of analysis.

Hierarchical regression analyses showed that organic school structure moderates the relationship between PST and student academic achievement, and bureaucratic school structure moderates the relationship between PST and school violence beyond the impact of students’ socioeconomic backgrounds.

This study provides important evidence for the benefits of aligning PST with school structure for improving student outcomes beyond the impact of students’ socioeconomic backgrounds. In addition, the study suggests principal system thinking leadership to achieve effective student outcomes that circumvent the effects of inequality on disadvantaged student groups.

A number of recent artificial intelligence (AI)-enabled technologies, including summarisers, paraphrasers and the cutting-edge chatbots not only have outstanding potentials in modern educational systems but also could lead to a dramatic paradigm shift in the whole education process. This study aims to explore the factors that shape the academic community’s desire and intention to use AI conversational chatbot technology, with a particular focus on the leading ChatGPT.

This study uses a mixed method approach to explore the educators’ adoption of chatbots through an empirically validated model. The model, known as the “Educators’ Adoption of ChatGPT”, was developed by integrating the theoretical foundations of both the Unified Theory of Acceptance and Use of Technology and Status Quo Bias (SQB) frameworks, as well as insights gathered from interviews. The relationships within this model were then tested using a quantitative approach. The partial least squares-structural equation modelling method was used to analyse 243 valid survey responses.

The outcomes of the analysis indicated that perceived educators’ effort expectancy, educators’ autonomous motivation, perceived learners’ AI competency, perceived educators’ competency, innovative behaviour towards technological agility and perceived students’ engagement are significant determinants of educators’ intention to use chatbots. In contrast, perceived unfair evaluation of students, perceived students’ overreliance and perceived bias/inaccuracies were shown to have significant impacts on the resistance to use the technology, which typically implies a negatively significant influence on the educators’ use intention. Interestingly, perceived fraudulent use of ChatGPT was proven insignificant on the resistance to use chatbots.

This study makes a significant contribution to the field of educational technology by filling the gap in research on the use and acceptance of AI-enabled assistants in education. It proposes an original, empirically validated model of educator adoption, which identifies the factors that influence educators’ willingness to use chatbots in higher education and offers valuable insights for practical implementation.

The study intends to evaluate students’ intention to shift from cash payment to mobile payment system for academic fee payments through push, pull and mooring framework. Push factors comprise risk and service-related factors, pull factors consist of subjective and aspect-based factors and mooring factors include cost and cognitive factors.

Sample of the study consists of around 296 undergraduate and postgraduate students from different higher educational institutions located in India. The questionnaire for data collection comprises 21 Likert scale-based items distributed among seven constructs. Partial least square structural equation modeling is used to identify the significant factors influencing students’ intentions.

Five of the factors, namely, risk, service, subjective, aspect and cognitive significantly influence student’s intention to switch to mobile payment system for academic fee payments. Moderation analysis indicates that the impact of the push and pull factors on switching intention towards mobile payments has a more positive influence among male students.

This study is probably the only study that tested the specific push, pull and mooring factors influencing intention to switch to mobile payment from cash payment in the Indian education system based on the incentive, Fogg behavior and status quo bias theory for academic fee payment.

This research addresses a need in early childhood education for evidence-based teaching strategies that build emotional self-regulation skills in young children. The intervention assessed in this study focused on increasing the emotion vocabulary of preschool-aged students.

This mixed-methods, quasi-experimental study evaluated the impact a dialogic reading approach combined with direct instruction of emotion words during a shared book-reading activity had on students' emotion vocabulary knowledge. The study was conducted in a licensed daycare center in a suburb of Chicago, Illinois, with ten four- and five-year-old students. Pre- and post-session surveys assessed the intervention's impact on the students' receptive and expressive vocabulary knowledge, and observation notes captured the students' responses to the intervention activities.

The results showed significant increases with small to medium effect sizes between the students’ pre- and post-session survey scores for both receptive and expressive emotion vocabulary knowledge, a strong positive correlation between the level of student engagement during the intervention and their emotion vocabulary assessment scores, and the impact other variables had on the intervention’s effectiveness.

This research provides information on a culturally adaptable and quickly learned teaching strategy that could be used to build emotional self-regulation skills in the early childhood classroom.

This research uniquely applies this intervention as a universal strategy with preschool-aged children.

The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners’ computational thinking.

By analyzing the mechanism of action of ITF on the development of computational thinking, an ITF strategy and corresponding ITS acting on the whole process of programming problem-solving were developed to realize the evaluation of programming problem-solving ideas based on program logic. On the one hand, a lexical and syntactic analysis of the programming problem solutions input by the learners is performed and presented with a tree-like structure. On the other hand, by comparing multiple algorithms, it is implemented to compare the programming problem solutions entered by the learners with the answers and analyze the gaps to give them back to the learners to promote the improvement of their computational thinking.

This study clarifies the mechanism of the role of ITF-based ITS in the computational thinking development process. Results indicated that the ITS designed in this study is effective in promoting students’ computational thinking, especially for low-level learners. It also helped to improve students’ learning motivation, and reducing cognitive load, while there’s no significant difference among learners of different levels.

This study developed an ITS based on ITF to address the problem of learners’ difficulty in obtaining real-time guidance in the current programming problem-solving-based computational thinking development, providing a good aid for college students’ independent programming learning.

Construction education rarely addressed the importance of disseminating knowledge on infrastructure equity, thus impeding progress toward creating equitable and sustainable developments. This study aims to investigate the existing sustainability courses under the American Council for Construction Education (ACCE) accredited construction management (CM) programs to examine the integration of infrastructure equity topics and assess improvement in CM students’ knowledge and awareness to address this issue through an intervention.

To achieve these objectives, this research reviewed the sustainability course descriptions of the ACCE-accredited undergraduate and graduate CM curricula. Furthermore, the study implemented a workshop within a CM sustainability course that taught the students about the key concepts of infrastructure equity as well as how to address this issue by leveraging the Envision infrastructure rating system.

The course review results showed that most sustainability courses lack topics such as infrastructure equity and social sustainability. Moreover, the analysis of pre- and postworkshop surveys indicated that guided training could improve the students’ understanding as well as boost their confidence to address and mitigate infrastructure inequity issues.

The findings of the study are valuable for increasing awareness of infrastructure equity and facilitating the future construction workforce with the required expertise to develop equitable infrastructure systems.

Although many universities have begun to provide artificial intelligence (AI)-related courses for students, the influence of the course on students' intention to participate in the development of AI-related products/services needs to be verified. In order to explore the factors that influence students' participation in AI services and system development, this study uses self-efficacy, AI literacy, and the theory of planned behaviour (TPB) to investigate students' intention to engage in AI software development.

The questionnaire was distributed online to collect university students' responses in central Taiwan. The research model and eleven hypotheses are tested using 151 responses. The testing process adopted SmartPLS 3.3 and SPSS 26 software.

AI programming self-efficacy, AI literacy, and course satisfaction directly affected the intention to participate in AI software development. Moreover, course playfulness significantly affected course satisfaction and AI literacy. However, course usefulness positively affected course satisfaction but did not significantly affect AI literacy and AI programming self-efficacy.

The model improves our comprehension of the influence of AI literacy and AI programming self-efficacy on the intention. Moreover, the effects of AI course usefulness and playfulness on literacy and self-efficacy were verified. The findings and insights can help design the AI-related course and encourage university students to participate in AI software development. The study concludes with suggestions for course design for AI course instructors or related educators.