International Journal of Mobile Learning and Organisation (18 papers in press)

Regular Issues

• Teachers’ generative AI literacy on their perceptions of generative AI in education: self-efficacy as a mediator  
  by Yuchen Chen 
  Abstract: As generative artificial intelligence (GAI) has exerted profound impacts on education, GAI in education (GAIED) has garnered widespread attention. Teachers are the practitioners and facilitators of GAIED. As teachers’ perceptions have attached great significance to GAIED research, exploring the factors that may affect teachers’ perceptions of GAI in education (PGAIED) becomes an important research issue. Considering the literature, teachers’ GAI literacy (GAIL) and self-efficacy (SE) are the factors that may influence their PGAIED. Hence, the present study employed PLS-SEM to explore the relationship among teachers’ GAIL, SE, and PGAIED. One hundred ninety-five teachers engaged in the present research. The results revealed that: (1) Teachers’ GAIL had a significantly direct impact on their SE and PGAIED; (2) Teachers’ SE had a significantly direct impact on their PGAIED; (3) Teachers’ SE played a mediator between their GAIL and PGAIED. In light of the current findings, this study provided advice for the follow-up research. The present study is expected to provide valuable implications for professional development and propel the implementation of GAIED.
  Keywords: generative artificial intelligence (GAI); GAI literacy; self-efficacy; perceptions of GAI in education; teacher.
  DOI: 10.1504/IJMLO.2025.10069198
   
  
• A mobile story mapping-based learning approach to enhancing Japanese as a foreign language learners' oral and communication performances  
  by Bow-Ju Ferng, Gwo-Jen Hwang 
  Abstract: Speaking is a significant challenge for foreign language learners due to limited practice opportunities, which can lead to low motivation. This study proposed a mobile story mapping-based learning approach to engage students in organising and connecting learning content to real-life contexts using mobile technology for presentations in a foreign language. A quasi-experimental lesson was conducted in a Japanese as a foreign language (JFL) conversation course at a university in Taiwan. Two classes of first-year students participated: one using the mobile story-mapping-based learning (MSML) approach and the other using the conventional mobile learning (CML) approach. Results showed that the MSML group performed significantly better in accuracy, fluency, comprehension, and Japanese oral performance, but not in pronunciation. This study provides a reference for integrating technology in second foreign language education through MSML approach.
  Keywords: mobile learning; computer-assisted language learning; Japanese as a foreign language; JFL; oral performance; communication performance.
  DOI: 10.1504/IJMLO.2025.10069420
   
  
• Learning style-oriented GPT assistants: an exploratory study of personalised learning in virtual environments  
  by Po-Han Wu, Cheng-Hung Wang, Li-Wen Lu, Guan-Ting Ye 
  Abstract: In the contemporary educational environment, the rapid development of technology has subverted the traditional teaching mode. In particular, although virtual reality (VR) technology can stimulate students' learning motivation and improve learning efficiency, its application still faces the challenge of satisfying students' diverse learning styles. This study investigates the effects of integrating learning style-oriented GPT teaching supplements in VR environment on elementary school students' history learning effectiveness, cognitive load, and behavior. A five-week experiment was conducted with 67 fifth and sixth grade students in Tainan City, Taiwan. The results showed that matching learning styles with VR materials significantly improved learning effectiveness and promoted more self-directed and exploratory behaviors. No significant differences were found for cognitive load. Behavioral analyses showed that students using GPT-assisted VR materials showed greater interactivity and exploration, especially when learning styles were matched, which provide implications for future AI-assisted VR learning designs.
  Keywords: generative pre-training transformers; GPTs; learning styles; cognitive load; virtual reality; learning behaviours; personalised learning.
  DOI: 10.1504/IJMLO.2025.10069535
   
  
• An evaluation of student response systems in secondary mathematics classrooms  
  by Risma Nurul Auliya, Jirarat Sitthiworachart, Mike Joy 
  Abstract: This study aimed to determine the effects of Kahoot! and Plickers for secondary school students to improve mathematics performance and learning engagement, while also analyzing students’ perceptions. This research was designed as a pretest-posttest quasi-experimental study. 71 seventh-grade students who participated were divided into three groups: two experimental groups where Kahoot! (n=25) and Plickers (n=22) were deployed, and a control group (n=24) where conventional learning was delivered. A mathematics performance test, learning engagement, and perception scale were used to collect the data. The findings showed the posttest mean scores of the mathematics performance and learning engagement were increased significantly in the three groups (p<0.05) and the Kahoot! groups had a greater impact. Furthermore, most students had positive opinions of both Plickers and Kahoot!, noting their simplicity, creating enjoyable learning, encouraging participation, building self-confidence, keeping focus, and increasing competitiveness, although some students found them challenging, time-consuming, and presenting technical problems.
  Keywords: Kahoot!; Plickers; mathematics performance; learning engagement; perception.
  DOI: 10.1504/IJMLO.2026.10069947
   
  
• From data to decisions: leveraging learning analytics for predictive insights in university admissions  
  by Kam Cheong Li, Billy Tak-Ming Wong, Mengjin Liu 
  Abstract: This paper surveys the application of learning analytics to support prediction in university admissions, summarising the patterns and trends in relevant learning analytics practices and highlighting the potential of data-driven approaches to enhance decision-making processes within higher education institutions. It covers 79 publications published from 2005 to 2024 collected from Web of Science and Scopus. The analysis focused on the types of data collected, the target variables measured, the methods used for data analysis, and the identified users of these analytics. The findings indicate that academic performance, educational background, and demographic information were the main criteria for candidate selection for admissions. Most of the studies utilised multiple data types in admissions analytics. Nearly half of the predictive models focused on binary classification of admission outcomes. The study also identifies limitations in the existing literature, particularly regarding insufficient details of data and evaluation methods. More research into the interconnections among data, variables, analytics techniques, and user profiles is recommended to further optimise predictive learning analytics in university admissions.
  Keywords: learning analytics; predictive analytics; machine learning; educational data mining; university admissions; student enrolment.
  DOI: 10.1504/IJMLO.2026.10070131
   
  
• A study on the integration of distanced simulated games with CLIL teaching method on elementary school students’ English motivation, effectiveness, and altruistic behaviour  
  by Po Han Wu, Wei Ting Wu , Yang Jung Ku 
  Abstract: This study investigates the effectiveness of integrating Content and Language Integrated Learning (CLIL) with distance-simulated games in enhancing English learning among elementary students in Taiwan. Addressing the challenges of CLIL implementation, including speaking anxiety and resistance to cooperative learning, this research focuses on learning outcomes, motivation, and altruistic behaviour. Sixth-grade students from Tainan City were divided into experimental and control groups, with the former engaging in game-based learning using the Gather. Town virtual environment and the latter participating in traditional classroom activities. Pre- and post-tests measured prior knowledge, learning motivation, and CLIL concept understanding. The results were inspiring, with the experimental group significantly outperforming the control group in learning outcomes and exhibiting deeper motivation. Notably, students in the virtual environment demonstrated higher frequencies of altruistic behaviours, enhancing cooperative learning and social interaction. This study underscores the potential of integrating CLIL with digital games to foster effective English learning, increase engagement, and promote positive social behaviours among elementary students, thereby contributing to Taiwan's bilingual education goals.
  Keywords: content and language integrated learning; CLIL; gamified situated learning; learning achievement; learning motivation; altruistic behaviour.
  DOI: 10.1504/IJMLO.2026.10070132
   
  
• Trends of generative AI applications in educational settings  
  by Yun-Fang Tu, Yi-Chun Lu 
  Abstract: With the development and widespread adoption of Generative Artificial Intelligence (GenAI), educational institutions and scholars worldwide have begun exploring the potential contributions and applications of GenAI in education. This study aimed to identify the primary research directions of Generative Artificial Intelligence (GenAI) in education using keyword co-occurrence analysis, revealed the commonly used keywords for GenAI application in educational research as well as the correlations between different research topics. The results indicate that current research on GenAI in education primarily focuses on “learners’ perceptions of using GenAI” and “literature reviews of GenAI in education research.” Over time, studies on the “evaluation of the learning effectiveness of GenAI” have increased; however, there are still fewer studies on the “testing and development of GenAI as a teaching support tool” and the “application of GenAI as an evaluation and feedback tool.” Moreover, there is a notable lack of “analysis of the cognitive and behavioral characteristics of learners during the learning process of GenAI.” Based on the analysis results, this study provides recommendations for future research within each research category.
  Keywords: generative artificial intelligence; research trends; literature review; bibliometric analysis.
  DOI: 10.1504/IJMLO.2025.10070631
   
  
• Effects of a self-regulated personalised ubiquitous learning system on students mathematics learning achievement and behavioural patterns  
  by Thanyaluck Ingkavara, Patcharin Panjaburee, Wararat Wongkia, Pratchayapong Yasri 
  Abstract: Innovative methods exist to enhance engagement and understanding of mathematics. However, these methods often fall short of addressing students’ diverse conceptual knowledge and learning preferences. Therefore, for the benefits of ubiquitous learning, this study proposed a self-regulated-based personalised learning system to help students manage their learning goals, including learning sequences, time management, and achievement tracking. A quasi-experimental research design was conducted in a Thai secondary school to examine the proposed system’s effectiveness, including those who used the self-regulated-based-personalised learning system and those who followed a conventional personalised learning system in ubiquitous learning. The findings highlight the efficacy of self-regulated-based-personalised learning systems in enhancing learning achievement and self-regulation abilities in mathematics. Moreover, lag sequence analysis revealed learning transitions occurring more frequently among students with high and low achievement levels. This research contributes to the growing evidence supporting integrating personalised learning technologies to accommodate learning needs and improve overall mathematics learning outcomes.
  Keywords: AI-based approach; personalisation; learning systems; self regulation; mathematic education.
  DOI: 10.1504/IJMLO.2026.10070733
   
  
• Augmented reality enhanced board games in educational research: a systematic review  
  by Poramate Tarasak, Narisra Komalawardhana 
  Abstract: Augmented reality (AR) is increasingly applied in areas like gaming, medical fields, and education. Educational board games, which combine entertainment with learning, enhance cognitive skills and collaboration. The integration of AR in board games is a recent area of research. This paper presents a systematic review of 29 studies on AR-enhanced board games in education. The review identifies trends in modes of play, AR types, learning topics, research methods, and the effects on learning. AR-enhanced board games cover various subjects, effectively deliver content, and provide novel learning experiences. Despite clear benefits in knowledge acquisition, other learning measures still need exploration. A new framework categorising AR roles in board games is introduced, including virtual object display, referee, assistance, and assessment. These roles complement traditional teaching by offering 3D visuals, instant feedback, and personalised learning. In conclusion, AR-enhanced board games can be an effective educational tool when applied in the right context.
  Keywords: augmented reality; board game; educational research; learning environment; education; immersive learning; game-based learning; scaffolding.
  DOI: 10.1504/IJMLO.2026.10070795
   
  
• Integrating problem-based learning and augmented reality for enhancing problem-solving and computational thinking skills  
  by Risma Nurul Auliya, Jirarat Sitthiworachart, Mike Joy, Thanin Ratanaolarn 
  Abstract: The study investigated the effect of problem-based learning (PBL) with augmented reality (AR) on problem-solving and computational thinking (CT) skills, along with students’ satisfaction with AR in mathematics learning. Ninety eighth-grade students participated in a quasi-experiment with three groups: experimental (PBL with AR and standard PBL) and control (conventional learning) groups, each with thirty students. The geometry learning using augmented reality experience (GLARE) application covered 3D geometry, including cubes, cuboids, prisms, pyramids, cones, cylinders, and spheres. MANOVA was used to examine the problem-solving and CT, while the satisfaction was evaluated as percentages. The findings demonstrated all groups improved significantly in CT and problem-solving (p<0.05), with the PBL+AR group achieving the highest improvement. Most students found AR engaging, motivating, and effective for understanding complex geometry concepts. They also appreciated its ease of use and support for independent learning. However, some encountered technical problems, such as device incompatibility and poor internet connectivity.
  Keywords: augmented reality; computational thinking; problem-based learning; PBL; problem-solving; satisfaction.
  DOI: 10.1504/IJMLO.2026.10071079
   
  
• Promoting self-regulated learning in computational games: prediction model for learners with difficulty adjustment level using gradient boosting and synthetic minority oversampling technique  
  by Ratchanon Nobnop, Nacha Chondamrongkul, Punnarumol Temdee 
  Abstract: Determining Dynamic Difficulty Adjustment (DDA) in computational games involves fine-tuning the game environment to keep players engaged, motivated, and challenged while fostering self-regulation for better learning outcomes and sustained motivation. This study proposed a gradient boosting (GB)-based model for predicting learners’ difficulty adjustment levels in a computational game-based learning environment. The key contribution is the development of a novel method that integrates the planning stage with common game features to build a prediction model. Data from 347 learners were collected for model construction. The GB model was selected for its capability to handle complex data and Synthetic Minority Oversampling Technique (SMOTE) was used to handle imbalanced data. Comparative analysis against other machine learning (ML) methods revealed that the proposed model, GB with SMOTE, outperformed other models in terms of accuracy, precision, recall, F1-score, and Area Under the Receiver Operating Characteristic Curve (AUC-ROC).
  Keywords: game-based learning; computational thinking; difficulty adjustment; DA; self-regulated learning; SRL; gradient boosting; GB.
  DOI: 10.1504/IJMLO.2026.10071104
   
  
• Approaches to identifying personalised learning needs: an analysis of evidence  
  by Billy Tak-Ming Wong  
  Abstract: Personalised learning prioritises the creation of an environment tailored to learners’ interests, abilities, and needs. The first step in achieving personalised learning is understanding students’ needs. To address this, various approaches have been developed to identify and address these needs. This paper analyses the approaches to identifying personalised learning needs, focusing on the types of learning needs examined, the data collected, and the approaches used. A comprehensive review of 458 journal articles published between 2012 and 2023 sourced from Scopus was conducted. The findings highlighted various personalised learning needs, with learning content, learning experience and tutoring being the most common. Personalised learning needs are often identified through learning platforms, learner profiles and learner assessments. Data on learner characteristics, performance and behaviours are frequently collected to identify these needs. These findings serve as a foundation for offering appropriate support tailored to cope with learners’ diverse needs and enhance their learning experience.
  Keywords: learning needs; personalised learning; personalised education; personalisation; individualisation.
  DOI: 10.1504/IJMLO.2026.10071209
   
  
• How does technology support from teacher, parent, school, and learning affect students' learning motivation and overall performance? Evidence from developing countries  
  by Muhammad Aizri Fadillah, Mhd Rafi'i Ma'arif Tarigan, Febry Azmiana Siregar, Lisa Amalia, Usmeldi  
  Abstract: The present study explores the impact of support from teachers, parents, schools, and learning environments on students' motivation and overall performance. Data were collected from 283 high school students in Indonesia. The analysis employed PLS-SEM to test the correlational model and machine learning powered by SHAP, Boruta, and Ranger for predictive modelling. Technology support from teachers, parents, and learning environments significantly improved students' learning motivation and overall performance, but school technology support did not. The predictive model identified digital information-gathering activities, teacher explanations of technology use, and parental support for learning to use technology as the main predictors of student motivation and performance. While school support did not directly affect motivation and performance, providing access to information and creating a conducive learning environment remains important. These insights contribute to the technology-based education literature and significantly affect educational policies and instructional strategies, especially in developing countries.
  Keywords: technology support; learning motivation; student performance; PLS-SEM; machine learning.
  DOI: 10.1504/IJMLO.2026.10071371
   
  

Special Issue on: Pedagogical Innovations with Mobile and Intelligent Technologies

• How does HMD VR aid in creating a flexible language learning environment? A preliminary study  
  by Yoko Hirata, Yoshihiro Hirata 
  Abstract: The implementation of virtual reality (VR) using head mounted displays (HMDs) in education has recently emerged to provide students with more flexible and creative ways of learning. However, little is known about how such newly adopted technology leads to better interactive language learning outcomes, in comparison to conventional in-person learning environments. Guided by self-determination theory, this intervention study aims to explore how Japanese university students assess their interactive language learning experiences in a HMD avatar-enhanced immersive VR environment, as opposed to those in a conventional in-person classroom. The findings suggest that the language learning environment provided by the HMD avatar-enhanced VR offers students more engaging and flexible educational experiences compared to the conventional in-person mode. Qualitative and quantitative data also indicated that such VR mode plays an important role as a ubiquitous tool to mitigate students' negative emotional reactions to language learning, therefore foster more inclusive and equitable learning environments.
  Keywords: virtual reality; head mounted display; HMD; interactive language learning; inclusive learning environments; flexible education experiences: in-person classroom.
  DOI: 10.1504/IJMLO.2025.10065109
   
  
• Developing Hi Nano mobile apps as integrated education instrument on nanotechnology and cancer treatment learning  
  by Erti Hamimi, Ibrohim Ibrohim, Irma Kartika Kusumaningrum, Wira Eka Putra, Ahmad Kamal Sudrajat, Wachidah Hayuana, Maisuna Kundariati, Maya Umi Hajar, Nik Ahmad Nizam Nik Malek 
  Abstract: Due to the explosion of nanotechnology, there is a necessity to update school science curricula by integrating nanotechnology-related concepts to students. This research aims to develop the Hi Nano application as an Education Kit or learning tool to increase knowledge about nanotechnology and cancer treatment. This research was a mix-method design and lead by the three research aims. First, we asked teachers to complete a questionnaire related to the nanotechnology. This initial analysis shows that technology as a learning media is greatly needed to increase student nanotechnology knowledge. Second, the Hi Nano mobile app validation tests were carried out with the experts. Third, the evaluation of this research has resulted in Hi Nano application being developed in the effective category. The results of this research can be used by teachers to increase students' understanding about nanotechnology as a more effective optimal learning process.
  Keywords: nanotechnology; Hi Nano mobile apps; cancer treatment learning.
  DOI: 10.1504/IJMLO.2025.10064220
   
  
• Research on learning experience influencing factors of information-based teaching MOOCs  
  by Xin Zhang 
  Abstract: The growing importance of information technology in education reform has highlighted the need for more adaptable teaching methods. Traditional offline training, limited by varied resources and knowledge backgrounds, often fails to address the diverse needs of teachers. To address this, education departments are now advocating for online education, notably massive open online courses (MOOCs), which are renowned for their unique features and benefits. This study integrates latent Dirichlet allocation (LDA), BERTopic topic mining analysis, sentiment analysis, salience-valence analysis (SVA) analysis, and cluster analysis based on course reviews and reviewers' homepages in iCourse, a Chinese MOOC platform, to explore key factors driving positive learning experiences for distinct learner types. The findings offer insights into digital training mode and promotional strategies of teachers' information-based teaching ability, focusing on course organisation, content design, customisation for diverse learner profiles and utilising key opinion leaders (KOLs) for course promotion.
  Keywords: learning experience; massive open online courses; MOOC; latent Dirichlet allocation; LDA; BERTopic; topic mining; sentiment analysis; salience-valence analysis; SVA; cluster; information-based teaching; text mining.
  DOI: 10.1504/IJMLO.2025.10064364
   
  
• Effects of adaptive difficulty adjustment-based gamification on young children's cognitive development and enjoyment experience  
  by Fu-Ning Guo, Chen-Chen Liu, Youmei Wang, Hai-Jie Wang 
  Abstract: Early childhood is an important stage of cognitive development. Based on the theory of embodied cognition, touchscreen devices have become increasingly prevalent in boosting the cognitive abilities of young children in the context of technological development. However, due to inadequate instructional design, traditional touchscreen devices may also struggle to ensure interaction and engagement in early childhood education. Therefore, this study proposed a gamification approach to maintain students' learning interest and introduced an adaptive difficulty adjustment mechanism to conform to students' cognitive development. To explore the effectiveness of the adaptive difficulty adjustment-based gamification approach, a quasi-experimental study was conducted with 25 young children in two groups. The results showed that the current approach had a positive effect on children's cognitive skills but failed to increase enjoyment of the experience, complemented by teachers' and parents' feelings about and experiences of the two different approaches by analysing interview data.
  Keywords: touch screen; adaptive difficulty adjustment; early childhood education; cognitive development.
  DOI: 10.1504/IJMLO.2025.10065251
   
  
• Enhancing higher education through student-staff collaboration: case studies from a Sino-foreign institution  
  by Boon Giin Lee, Amarpreet Gill, Matthew Pike, Linjing Sun, Joseph Thenara, Dave Towey 
  Abstract: University of Nottingham Ningbo China (UNNC) was the first Sino-foreign higher education institution (SfHEI). It has a history of innovation, including through collaborations with students in research and application projects. This paper reports on three student-staff collaborations to design and create technology-enhanced teaching or training interventions. Case studies are presented for each of the three collaborations. The first case study examines the development of a mobile application to support human-centred design (HCD) education. The second case study focuses on an augmented reality (AR) educational game for teaching Design for Manufacturing and Assembly (DfMA). The third case study investigates the use of mixed reality (MR) for firefighting equipment training. The findings highlight the effectiveness of these digital pedagogies in fostering strong student-staff partnerships, and for enhancing collaborative learning experiences. The paper concludes with pedagogical implications and recommendations for future research in technology-enhanced education.
  Keywords: immersive mixed reality; iMR; students as partners; SaP; students as change agents; SACA; engineering education; digital pedagogy; educational technology.
  DOI: 10.1504/IJMLO.2025.10067033