Persistent inequities in access to high-quality science instruction continue to limit students' learning opportunities in rural and underserved communities worldwide. Digital inquiry-based learning environments offer a promising pathway for addressing such disparities. However, limited research has examined how learners in marginalized contexts perceive and adopt these systems, particularly regarding the role of design affordances, technology acceptance processes, and their influence on learning outcomes. This study investigates the factors shaping middle school students' acceptance and use of a Web-enhanced Inquiry Learning Common for Science Literacy (WILC-SL), a platform particularly designed to support guided science inquiry in rural Thai schools. Drawing on technological, pedagogical, and content affordances and extending the Technology Acceptance Model (TAM), we employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze survey data from 170 seventh-grade students. The PLS-SEM results indicate that technological affordance strongly predicts perceived ease of use. In contrast, content and pedagogical affordances do not significantly influence students' perceived usefulness or usability of the WILC-SL system. Although these affordances had limited power to predict outcomes, students’ attitudes toward the system became a key factor influencing their behavioral intention, which then significantly improved their science literacy outcomes. These findings highlight a motivational pathway, rather than a purely functional one, through which inquiry-oriented digital platforms can support equitable science learning in resource-constrained settings. The study contributes to research on digital learning adoption by demonstrating how usability, affective engagement, and contextualized design intersect to influence learning performance in rural environments. Implications for designing inclusive systems, such as an extended TAM and inquiry-rich digital learning systems, are discussed.

Personalized learning has been widely recognized as an effective approach to address individual student needs; however, many systems face challenges in supporting students to explore content while maintaining motivation and enjoyment systematically. To address these limitations, the Augmented Reality, Inquiry-Based Personalized Gaming (ARIPG) framework integrates the strengths of Augmented Reality (AR), inquiry-based learning, and personalized learning to compensate for the limitations inherent in each approach, resulting in a more coherent and balanced learning model. While AR enhances the visualization and contextualization of abstract concepts, inquiry-based learning promotes active knowledge construction and scientific inquiring, and personalized learning addresses individual differences among learners. By synergistically combining these approaches, ARIPG creates a holistic learning environment that leverages its complementary advantages to support both cognitive and affective learning outcomes. An experiment was conducted in a biochemical university course to evaluate students’ learning achievement and the role of emotional engagement. The results indicated that students who learned with the ARIPG approach significantly outperformed those in a conventional personalized gaming environment. Moreover, the findings revealed no significant differences in achievement between students with low and high levels of affection, suggesting that the proposed approach can effectively support diverse learners’ emotional engagement.

Recently, scholars have suggested artificial intelligence to enhance digital game-based learning by considering applications of the decision tree-based method. However, the technology acceptance model still needs to be determined to reveal findings from active and inactive students. With a validated questionnaire, the stepwise multiple regression technique was used to analyse the data collected from 434 samples in secondary school settings. It was found that active students thought an effective mobile game would include particular situations or tasks and the materials and methods influencing the adjustment of their behaviours. It is interesting to note that active students' attitudes toward the decision tree-based contextual mobile gaming system are largely influenced by how easy they perceive the use of the system to be. Regarding the findings, this study discusses further implementation by properly developing and implementing the decision tree-based contextual mobile gaming approach to cultivate students' digital citizenship competencies.

The declining interest of young people in farming careers poses a significant challenge to sustainable agriculture and global food security. This study presents the design and preliminary evaluation of a digital game aimed at fostering positive attitudes toward farming and sustainability. Grounded in game-based learning theories, the game integrates scenario-driven missions, decision-based gameplay, and roleplaying narratives to immerse students in real-world agricultural challenges. A pilot study with undergraduate agriculture students assessed the game's usability and perceived effectiveness using the Technology Acceptance Model (TAM). Survey results indicated high ratings in Perceived Usefulness, Perceived Ease of Use, Attitude Toward Technology, and Behavioral Intention, suggesting that the game effectively enhances problem-solving skills, engagement, and motivation. Furthermore, sustainability indicators and resource management tasks reinforced environmental responsibility, demonstrating the link between farming decisions and ecological outcomes. These findings suggest that interactive and well-structured learning environments have the potential to influence perceptions of farming careers while promoting awareness of sustainable agricultural practices.

Mastering medical principles, laboratory methods, and interpreting test results poses a significant challenge for medical technology students, particularly when traditional instructional methods limit opportunities for flexible and selfpaced learning. To address this issue, this study aimed to enhance teaching time efficiency and improve learning outcomes by transforming traditional instruction into an onlinebased flipped-ubiquitous learning environment. This innovative approach provided students with flexible, repeated access to key immunology topics anytime and anywhere. The study evaluated the impact of this learning environment on the performance and perceptions of 66 medical technology students enrolled in a fundamental immunology course at a university. An experimental research design was implemented, incorporating pre- and post-test assessments, laboratory evaluations, and a learning perception questionnaire. Repeated measures analysis revealed that the flipped-ubiquitous learning environment significantly improved students’ performance. Moreover, students with higher levels of self-engagement exhibited greater performance improvements compared to their lowerengagement peers. Questionnaire responses further indicated positive student perceptions of the learning approach, suggesting that favorable attitudes may contribute to enhanced learning outcomes. The findings highlight the importance of fostering self-engagement and optimizing online learning strategies to support medical technology students in mastering essential knowledge and skills. Recommendations are provided to guide the effective implementation of similar learning models in medical education.

As digital citizenship becomes an essential educational priority in the digital age, there is a growing need for sustainable and engaging instructional designs that foster students' ethical and responsible use of technology. Addressing this gap, this study modeled the sustainability perspectives underlying personalized digital game-based learning through a partial least squares structural equation modeling (PLS-SEM) approach. A longitudinal repeated-measures design was conducted with 372 lower secondary students in Thailand, using fuzzy logic and decision tree algorithms to personalize ethical digital scenarios. The proposed model examined how pedagogical design, content quality, usability, behavioral decisions, and motivation shape students' perceptions of sustainability. Results indicated that sustained motivation at later learning stages was the strongest predictor of perceived sustainability, while pedagogical and experiential factors exerted significant indirect effects through motivational engagement. The analysis also confirmed the longitudinal influence of early motivational experiences on later engagement, emphasizing the importance of adaptive feedback and reflective learning processes. These findings advance understanding of how AI-driven personalization can promote sustainable digital citizenship learning by integrating adaptive pathways, culturally relevant content, and motivational scaffolds to support long-term behavioral change. Implications for educational design, pedagogy, and policy are discussed to guide the development of scalable AI-supported learning environments.

This study explores how immersive, inquiry-based STEM education, supported by virtual reality (VR), can enhance primary students’ learning experiences, behaviors, and interdisciplinary understanding. Thirty-six students (Grades 1–5) participated in 31 curriculum-aligned STEM activities designed around real-world problems, integrating science, technology, engineering, and mathematics through hands-on and VR-enhanced tasks. Using a qualitative case study design, data were collected through classroom observations, student work samples, interviews, and reflective feedback. The findings reveal strong student engagement, a deepening understanding of STEM integration, and the emergence of an eight-step learning cycle characterized by iterative problem-solving and collaboration. This study makes a theoretical contribution to inquiry-based and self-regulated learning models, providing practical guidance for educators and policymakers seeking to implement scalable, immersive STEM learning environments. Future directions highlight the potential of personalized learning systems to support adaptive and reflective STEM engagement.

Real-world applications can be potent tools in chemistry teaching, fostering highly beneficial learning for students. By involving students in real-world phenomena, we not only alter their perceptions of chemistry but also cultivate crucial chemistry competencies, preparing them for the future as scientists and citizens. In this report, we introduce the "Plastic Detective," a citizen inquiry mobile app specifically designed to promote chemistry learning about the circular plastic economy. This app, developed using a user-centered design approach, focuses on engaging young people in environmental science through active inquiry-based chemistry learning. The app allows users to participate in the investigation and monitoring of plastic waste, offering interactive features for data collection, organizing, and sharing. The case studies included in this report detail how students at elementary, secondary, and tertiary levels engaged with the app, demonstrating its ability to enhance their understanding of chemistry concepts and foster environmental stewardship. The findings reveal that students responded positively to the app, as observed through researchers' interactions with participants and informal feedback, indicating noticeable improvements in their attitudes toward chemistry. This highlights the need for accessible technologies that facilitate practical, real-life chemistry learning experiences and a deeper understanding of circular plastic economy concepts.

A personalized online learning system incorporating a self-regulated learning approach was developed to deliver the factorization in quadratic polynomials topic on mathematics learning. This system created four learning materials for learning a certain topic in mathematics, corresponding to the students’ characteristics. This study followed the education design research approach to develop a self-regulated-based personalized online learning system and evaluate the system from a technology acceptance perspective. The Pearson correlation was computed and revealed the best fit of the collected data for further stepwise multiple regression analysis through students’ acceptance of learning mathematics before and after using the developed system. Furthermore, the Chi-square test was performed to determine the acceptance change and frequency rated by items to ensure an in-depth understanding of how acceptance changed before and after. Although the findings revealed that students’ perceived ease of use was primarily a predictor of their attitude about the system, they showed an increment in perceived usefulness after participating in the developed system. The students’ perceptions of ease and attitude toward the self-regulated-based personalized online learning system for mathematics learning should be mainly considered in further development, including the different learning approaches for supporting mathematics learning.

The COVID-19 pandemic forced schools to move instruction online and learning from home, laying on learning anywhere and anytime at the students' own pace. This study designed and implemented ubiquitous learning with the digital board game in response to government-issued learn-at-home and work-from-home orders. The present paper also shows how the multimedia debriefing method supports a digital board game for ubiquitous learning in the course of cyberbullying behaviour. A repeated measure experiment with 56 middle school students showed that students' conceptions and perceptions of cyberbullying behaviours improved significantly after gaming with multimedia debriefing sessions compared to gaming without multimedia debriefing sessions. Additionally, the students were asked to respond to a self-reported questionnaire and were interviewed. The results revealed that they had a positive experience with the multimedia debriefing method and perceived the ubiquitous game-based learning as an effective environment that helped improve their learning regarding cyberbullying conceptions.

Educators have recognized the importance of providing a realistic learning environment which helps learners to not only comprehend learning content, but also to link the content to practical problems. Such an environment can hence foster problem-solving skills in nursing training. However, when learners interact in a virtual environment with rich learning resources, they might encounter difficulties if there is a lack of proper guidance, clinical sense, or a well thought-out instructional design process. Hence, this work developed a maternity VR-based situated learning system (MVR-SLS) based on the experiential learning theory to support professional courses in obstetrics. A quasi-experiment was conducted to verify the impacts of this method on learners' learning achievement, OSCE (Objective Structured Clinical Examination) competency, problem solving skills, learning engagement, and teaching effectiveness. The experimental results indicate that the new method improved learners' learning achievement, OSCE competency, problem-solving ability, and recognition of learning engagement. Moreover, the learners who learned with the new method showed more active learning behaviors compared to the learners in the control group. Findings of the present study offer concrete suggestions for implementing effective virtual reality (VR)-based learning strategies for medical and nursing textbooks.

Previous studies have designed educational methods to cultivate digital citizenship behavior and support the construction of knowledge. However, these methods have not well incorporated personalized feedback mechanisms for enhancing digital citizenship knowledge. Therefore, this study proposed an algorithm that combines concept-effect propagation, fuzzy logic, and decision tree methods to address this drawback and create a personalized, contextual gaming experience. This personalization ensures an engaging and contextually relevant learning experience, addressing learning challenges related to digital citizenship scales. The game was tailored to individual learning experiences and decision-making patterns, with fuzzy logic interpreting nuanced student responses and decision trees guiding learning paths. A digital citizenship knowledge test and an affection questionnaire measured the game's impact. Moreover, eye tracking was used to ensure attention in the experimental group. Therefore, a quasi-experimental design was conducted to evaluate the influence of a digital citizenship game on 110 students. ANCOVA and the Chi-square tests were performed to analyze students' knowledge of digital citizenship. Moreover, eye-tracking metrics were used to gain deeper insights into students' visual attention and engagement. The experimental results reveal that the proposed game enhanced the students' digital citizenship achievement and promoted their perceptions. Additionally, eye-tracking data showed that the proposed gaming environment positively influenced students' engagement. Findings indicate that using fuzzy logic and decision trees in educational games significantly promotes affection and alters attention in learning digital citizenship. This study contributes to educational technology by showcasing the potential benefits of personalized educational experiences. The insights gained are valuable for educators and educational game developers focused on digital citizenship education.

In response to the evolving demands of the digital era, the significance of programming skills has led to a reevaluation of traditional classroom instruction. This study introduced a collaborative inquiry-based online system to enhance individual and peer-supported coding practice. Through a quasi-experimental design, 346 Thai undergraduates were divided into a control group, which continued with conventional classroom teaching, and an experimental group that utilized the collaborative inquiry-based online approach. The research assessed conceptual learning performance via a pre- and post-test consisting of 15 questions. In addition, perceptions of the learning environment and motivation were assessed through 19-item and pre-post questionnaires with 20 items, respectively. The results indicated that the experimental group outperformed the control group in understanding programming, problem-solving abilities, and coding proficiency. Furthermore, the students in the experimental group demonstrated higher engagement and motivation, alongside improved teamwork and communication skills, which are essential in the modern online learning environment. This study suggests collaborative inquiry-based online learning can effectively complement or replace traditional instruction, offering valuable insights for educators, instructional designers, and policymakers. It advocates for a shift towards a more student-centered, interactive, and engaging learning experience in computer science education.

Digital citizenship has become an essential aspect of modern education. As technology becomes increasingly ubiquitous daily, there is a growing need to cultivate digital citizenship skills among students worldwide. Few studies have explored the potential of game-based learning using ubiquitous technologies to enhance digital citizenship education. Game-based learning has emerged as a promising approach to engage learners and promote the development of these crucial competencies. Moreover, ubiquitous learning approaches can provide seamless educational experiences across various contexts and devices. This paper proposes a comprehensive framework for designing and implementing a ubiquitous game-based learning system to foster digital citizenship in the Thai educational context. Drawing on existing research, this study analyzed the challenges and opportunities associated with this endeavor, addressing considerations around technology integration, pedagogical design, and implementation strategies. The study revealed that a ubiquitous game- based learning system could leverage AI-powered personalization to tailor learning experiences and provide real-time feedback to cultivate digital citizenship among Thai K-12 students. The findings also provide valuable insights for researchers, educators, and policymakers interested in leveraging innovative learning approaches to nurture digitally literate and responsible citizens in Thailand.

The growing demand for artificial intelligence (AI) skills across various sectors has enhanced AI-focused careers and shaped academic exploration in educational institutions. These institutions have been actively developing teaching methods that enhance practical AI applications, particularly through integrating AI with the Internet of Things (IoT), leading to the emergence of the Artificial Intelligence of Things (AIoT). This convergence promises significant advancements in AI education, addressing gaps in structured learning methods for AIoT. This study explored AIoT’s application in Smart Farming (SF) and its potential to enrich AI education and sectoral advancements. The AIoT platform was designed for SF simulations, integrating environmental sensing, AI processing, and user-friendly outputs. This platform was implemented with 40 first-year computer science university students in Thailand using a one-group pre-posttest design. This approach transformed theoretical AI concepts into experiential learning through interactive activities, demonstrating AIoT’s capability to increase AI conceptual understanding, trigger AI competencies, and promote positive learning perceptions. Therefore, this study presented the results as indicative of the AIoT platform’s potential benefits, emphasizing the need for further robust experimental research. This study contributes to educational technology discussions by suggesting improvements in AIoT platform effectiveness and highlighting areas for future investigation.

In response to industry demands, universities offer diverse digital technology majors, some focusing purely on technology while others integrate with domains like arts, business, or science. These interdisciplinary programs aim to equip students with the skills necessary to thrive in a digitally driven world. However, matching students with the right major can be challenging, especially given the diverse learning preferences among students. The VARK framework categorizes students into visual, aural, reading/writing, and kinesthetic learners, while the Kolb model classifies learners based on their experiences as diverger, assimilators, converger, or accommodators. These frameworks offer insights into how students prefer to acquire and retain information. The resulting predictive models will recommend the most suitable majors for students based on their learning styles. These recommendations will consider the compatibility between students' preferred learning methods with digital major. Moreover, leveraging machine learning models can predict students' suitability for digital majors based on learning styles. Analyzing student profiles and outcomes facilitates informed decisions, benefiting both students and universities in shaping educational pathways and career trajectories. Through the application of Support Vector Classifier, this study seeks to provide personalized academic guidance to students, helping them make informed decisions about their educational pathways. By considering students' individual learning styles, universities can enhance the effectiveness of their digital maj or offerings, ultimately addressing the shortage of skilled digital professionals in the workforce. The study findings showcase the proposed approach as highly promising, achieving outstanding classification accuracy. Specifically, the Area Under the Curve (AUC) accuracy values are notable: Animation and Visual Effects with an AUC of 0.89, Business Computer with an AUC of 0.97, and Computer Engineering with an AUC of 0.96.

Aside from the necessary learning skills of logical thinking, problem-solving, and creativity, undergraduate students in the programming discipline must also be self-motivated because these abilities enable them to overcome obstacles and achieve success. In the digital learning era, a pedagogical approach emphasizing inquiry and collaborative approaches can enhance students' programming skills anywhere and anytime. As a result, this research aims to investigate the effects of collaborative learning on academic achievement and motivation by managing ubiquitous learning in computer courses at three universities in northern Thailand using a collaborative inquiry-based approach. The learning environment allowed students to practice independently using the instructor-provided content and exercises. Then, as part of group learning, students gave advice and shared knowledge until they found the best solution. Following class, the instructor discussed the merits of each group's responses with all students. Students were then asked to repeat the questions to ensure they completely understood the logical reasoning and problem-solving process. According to the findings, ubiquitous learning management based on collaborative inquiry-based approaches could help them learn more effectively, with higher learning achievement and motivation. The study's findings inspire further research into creating a collaborative digital learning environment in computer education, particularly from the standpoint of ubiquitous learning.

Developing a self-regulated based personalized online learning system (SPOLS) for learning factorization aimed to provide appropriate learning materials that allow students to learn factorization and control themselves to accomplish their target. The study aimed to investigate the impact of using SPOLS on students' learning achievement and their perception of online self-regulated ability. The participants consisted of a single group comprising seventy-two eighth-grade students. They were administered pre- and post-tests before and after completing a lesson on factorization. Additionally, they were required to rate their scores on an online self-regulated questionnaire before and after utilizing SPOLS. The results showed that incorporating SPOLS led to a statistically significant increase in the average students' achievement on the post-test for the numerical factorization compared to their performance on the pre-test. However, using SPOLS for learning polynomial factorization did not elicit a statistically significant change in achievement scores. Moreover, in part of the self- regulated ability, after using SPOLS participants' scoring on pre- and post-self- regulated questionnaires, Chi-square implies discovering the relationship between two categorical variables. The result showed that seventeen questionnaire items were statistically significant after using SPOLS.