Advocates of AI in Education (AIEd) assert that the current generation of technologies, collectively dubbed artificial intelligence, including generative artificial intelligence (GenAI), promise results that can transform our conceptions of what education looks like. Therefore, it is imperative to investigate how educators perceive GenAI and its potential use and future impact on education. Adopting the methodology of collective writing as an inquiry, this study reports on the participating educators’ perceived grey areas (i.e. issues that are unclear and/or controversial) and recommendations on future research. The grey areas reported cover decision-making on the use of GenAI, AI ethics, appropriate levels of use of GenAI in education, impact on learning and teaching, policy, data, GenAI outputs, humans in the loop and public–private partnerships. Recommended directions for future research include learning and teaching, ethical and legal implications, ownership/authorship, funding, technology, research support, AI metaphor and types of research. Each theme or subtheme is presented in the form of a statement, followed by a justification. These findings serve as a call to action to encourage a continuing debate around GenAI and to engage more educators in research. The paper concludes that unless we can ask the right questions now, we may find that, in the pursuit of greater efficiency, we have lost the very essence of what it means to educate and learn.

The integration of Internet of Things (IoT) technology in the agricultural sector using advanced sensor systems has garnered significant interest in the recent year, especially in promoting food security. This study shows an application of this to Spondias purpurea (Philippine Pias Prunes), an important fruit in the Philippine Archipelago. The developed system places significant importance on the connection of Internet of Things (IoT) devices and the Google Cloud Platform. This integration enables real-time monitoring, data storage, and analysis, therefore providing valuable insights into enhancing the drying process and mitigating spoilage by maintaining moisture levels within the recommended range of 12-14%. The technology provides farmers with the opportunity to extend the shelf life of the prunes, reduce food wastage and increased profitability. While the system focused on Spondias purpurea, the system is highly adaptable and scalable to other fruits and crops. The research employed a DHT11 sensor that is linked to a Raspberry Pi Microcontroller, together with a Google Cloud-Based Platform for the purpose of data storage and processing. Results of the experiments indicate that the temperature measurements remain consistent at varying conditions. Moreover, the humidity levels remain to be high while the prune’s moisture content continue to be steady. To enhance the system's functionality, future endeavours should focus on integrating the system with other agricultural processes. Additionally, it is recommended to broaden the scope of the cost-benefit analysis by considering aspects such as the initial investment, maintenance costs, energy consumption, and potential rewards in terms of product quality, loss reduction, and increased output.

Technology-enhanced learning (TEL) has revolutionized the way students learn. In health professions education, TEL is particularly impactful as it ensures that future healthcare professionals are well-prepared to meet the demands of modern medical practice. Given the continuous advancements in educational technology, there is a pressing need to examine the integration of these technologies in this field. Therefore, this chapter reviews the current trends and applications, including artificial intelligence, smart classrooms, extended realities, digital game-based learning, mobile learning applications, metaverses, the Internet of Medical Things, robotic telepresence, telemedicine training, and virtual simulations. Doing so guides educators, policymakers, and technology developers in creating more engaging, efficient, and inclusive educational environments. Overall, the chapter underscores the necessity of ongoing research and thoughtful technology integration to prepare competent, knowledgeable, and adaptable health professionals for the ever-changing demands of the healthcare field.

The quick-service restaurant (QSR) industry has grown significantly over the last 10 years, accounting for nearly one-third of all restaurant revenues, making it a fiercely competitive sector. In order to remain competitive in the marketplace and subsequently expand, businesses need to recognize the importance of service quality and customer satisfaction. Using the SERVQUAL model as the base framework, this research aims to determine the factors that influence customer satisfaction. Using the quantitative descriptive correlational method, the study examined the data from 300 Millennial customers of QSR. A mediation analysis was conducted using Partial Least Square – Structural Equation Modelling (PLS-SEM) to test the mediating effect of corporate image and customer trust. The results found that service quality, customer trust, and corporate image influence customer satisfaction. Moreover, corporate image and customer trust mediate the relationship between service quality and customer satisfaction. Furthermore, customer trust is a mediator between corporate image and customer satisfaction. The findings suggest that Millennial customers are no longer dependent on service quality but are also putting a premium on corporate image and trust. With these findings, QSR owners, business strategists, marketing practitioners, and store personnel must offer the highest level of quality service, must ensure that the image as seen by customers is not tarnished, and must exhibit authenticity, honesty, and transparency.

The global shortage of skilled programmers remains a persistent challenge. High dropout rates in introductory programming courses pose a significant obstacle to graduation. Previous studies highlighted learning difficulties in programming students, but their specific weaknesses remained unclear. This gap exists due to the predominant focus on the overall academic performance evaluation. To address this gap, this study employed cognitive diagnostic modeling (CDM) to profile the skill mastery of programming students. An empirical analysis was conducted to select the most appropriate model for the data, and the linear logistic model (LLM) was determined to be the best fit. Final examination results from 308 information technology (IT) and 279 computer science (CS) students were analyzed using the LLM. Unfortunately, findings revealed that programming students exhibited proficiency primarily in code tracing and language proficiency but displayed deficits in theoretical understanding, logical reasoning, and algorithmic thinking. From a practical standpoint, this deficiency in fundamental skills sheds light on the factors contributing to academic failures and potentially eventual dropout in programming education. When comparing the student population by academic program, CS students demonstrated superior mastery compared to their IT counterparts, although both groups exhibited a lack of mastery in code tracing. These deviations underscore the pressing need for tailored educational strategies that address the unique strengths and weaknesses of each student group. Overall, this study offers valuable insights into programming education literature and contributes to the expanding application of CDM in educational research.

This study introduces a centralized Business Management System (BMS) tailored for small and mediumsized enterprises (SMEs), with an innovative approach due to the integration of a foot traffic detection system through video processing. The system allows businesses to access common business management features such as point of sales, staff scheduling, inventory management, and reports. With the integration of YOLOv7, foot traffic detection for customer count is made possible through LACAD. By automating data collection and providing foot traffic counts, alongside graphical reports, the system empowers SMEs to make better decisions for their businesses. This research highlights the strategic advantage of leveraging foot traffic insights to drive performance and competitiveness in the modern business landscape. As a guide for the study the researchers used Scrum methodology. The study was then evaluated through a quantitative survey using FURPS with 12 IT professionals and 7 beneficiaries as the respondents where the calculated total weighted mean for both the respondent types resulted in 4.60 which means that the users “Strongly Agree” with the system's overall components.

The growing adoption of renewable energy, particularly photovoltaic (PV) solar systems, has led to the development of numerous simulation software tools to simplify system design, analysis, and optimization. This study evaluates five widely used PV simulation software packages—SAM, PVsyst, HOMER, PV∗SOL, and RETScreen—by analyzing their features and performance across ten critical criteria, including cost, solar database accessibility, modeling capabilities, and ease of use. Using the Analytic Hierarchy Process (AHP), the criteria are ranked by importance, with the working platform identified as the most influential factor in software selection, followed by economic modeling capabilities and software cost. Additionally, the flexibility of simulation data requirements, reporting and analysis options, and user friendliness and ease of use are identified as important criteria, albeit ranking lower in importance. Performance analysis using simulation and real data further validates the evaluation process, providing insights into the accuracy and reliability of the simulation results generated by each software. Our findings indicate that SAM delivers superior accuracy when compared to real-world data, making it the most reliable tool for PV system analysis. PV∗SOL also ranks highly for its robust reporting and modeling capabilities. These results provide valuable insights for professionals and researchers in selecting the most suitable software for PV system design and optimization, emphasizing the balance between functionality, cost-effectiveness, and user-friendliness.

The emergence of generative AI tools like ChatGPT has sparked investigations into their applications in teaching and learning. In computer programming education, efforts are underway to explore how this tool can enhance instructional practices. Despite the growing literature, there is a lack of synthesis on its use in this field. This rapid review addresses this gap by examining the current literature to outline research trends, assess how it supports teaching and learning processes, and discern the issues that emerge from its application in programming instruction. A total of 107 documents disseminated across 81 distinct sources and authored by 394 contributors were identified. The review adopted a broad and inclusive approach, selecting literature based on relevance to ChatGPT's application in programming education and encompassing studies from diverse settings and methodologies. Results highlight applications such as personalized tutoring, knowledge reinforcement, instructional material creation, source code generation, immediate feedback, and assessment support. However, its use also introduces challenges such as academic dishonesty, ethical dilemmas, diminished critical thinking, overdependence on ChatGPT, and various technical limitations. Considering these findings, a balanced approach to the utilization of ChatGPT in programming education is essential. Implications and recommendations have been provided to guide policymakers, curriculum designers, teachers, and students in harnessing the benefits of this technology while mitigating potential challenges.

This study examined factors driving the adoption of generative artificial intelligence tools like ChatGPT for research writing through an integrated framework combining the Technology Acceptance Model, Task Technology Fit, and Trust in Specific Technology. Responses from 564 researchers in 12 countries were analyzed using a structural equation modeling approach. Intriguingly, perceived usefulness and ease of use were insignificant despite being considered the strongest predictors of behavioral intention in countless studies. Instead, researchers prioritize trusting beliefs and the compatibility between a technology and a task when considering its use. It was also found that trust in the technology has greater explanatory power than task-technology compatibility, and this trust is influenced by beliefs that ChatGPT is a socially and academically accepted tool for manuscript writing. Overall, this study contributes new insights for researchers, funding bodies, publishers, policymakers, and the academic community as they navigate the evolving role of AI in scholarly writing.

Teaching in the metaverse presents a dynamic frontier for educational innovation. Avatars, serving as digital representations of teachers, play a pivotal role in shaping virtual learning experiences. This study explores the impact of avatar design and behavioral realism on student perceptions of credibility and teaching effectiveness in avatar-mediated environments. True experimental research with a 2 × 2 factorial design was conducted involving students from three campuses. Across all experimental conditions, students consistently favored realistic avatars over cartoonish ones. A crisscross pattern emerged in relation to behavioral realism. Cartoonish avatars exhibiting realistic behaviors received higher ratings for instructor credibility but not for teaching effectiveness, whereas realistic avatars with the same gestures received higher ratings for teaching effectiveness but not for instructor credibility. From an educational standpoint, leveraging realistic avatars with authentic behaviors holds great promise for enhancing the teaching and learning experiences in the metaverse. Overall, this study contributes to the growing body of literature on educational metaverse and avatar-mediated teaching and learning by shedding light on the importance of avatar design and behavioral realism in shaping student perceptions and experiences.