bluuebunny/crossref_metadata_2025 huggingface dataset:
Relations between Instructional Factors and Student Acceptance of Flipped Learning in Chinese Language Learning
Authors: LAU Kit Ling , QIAN Quan
Published: January 2025

This study investigated the relations between instructional factors and students’ acceptance and use of flipped learning (FL) in the context of L1 Chinese language learning. A total of 2160 students from ten secondary schools in Hong Kong filled out two questionnaires measuring their perception of the instructional design and implementation of FL in their Chinese language classes and their acceptance of and actual participation in FL activities. Findings of the descriptive analysis indicated that from the perception of students, the design and implementation of FL in Chinese language classes generally adhered to the instructional principles of FL. Students also showed a moderately high level of acceptance of FL and a moderate level of participation in FL activities. The results of structural equation modeling indicated that both the quality of in-class and out-of-class eLearning activities had significant and positive effects on students’ perceived usefulness, ease of use, and enjoyment of FL and, in turn, indirectly affected their actual participation of FL activities. The connection between in-class and out-of-class eLearning activities also had a significant direct effect on student participation. These findings highlight the important role of instructional factors in promoting students’ willingness to accept FL as a new learning approach in a traditional teacher-centered school subject.
Informatics Education for University Students based on Text Input Time
Authors: MURAKAMI Yuko , INAGAKI Tomohiro
Published: January 2025

Japan is rapidly changing the ICT environment for students due to the Global and Innovation Gateway for All (GIGA School) since 2019. Students educated in various ICT environments will soon enter universities, and higher education will need to be optimized in these environments. For current university students in the transitional stage of ICT education, we measured the time required to input text using multiple methods, including laptops and smartphones, and the age when they started using the devices. For university students, smartphone input time is shorter than laptop input time, and individual differences are insignificant, suggesting that smartphone use may be effective in higher education. We also observed that the students who use devices such as smartphones and laptops from earlier educational stages have better typing skills. It will be necessary to design classes assuming a variety of students.
Development and Usability Evaluation of an Intelligent Personalized Erhu Pitch and Rhythm Learning System
Authors: HWANG Gwo-Haur , TSAI Ping-Tsung , LAIN Jenn-Kaie , HUANG Shiuan-Han
Published: January 2025

Pitch accuracy and rhythm errors are the most common problems encountered by erhu beginners. The traditional way of learning the erhu involves using a tuner and a metronome to improve these two issues. However, for erhu beginners, without the assistance of a teacher, it is often difficult to address these problems effectively. Therefore, this study has developed an "Intelligent Personalized Erhu Pitch and Rhythm Learning System" to help erhu learners learn to pitch and rhythm anytime and anywhere without the presence of a teacher while providing professional feedback. This system included pitch and rhythm training features. In addition to automatically generating sheet music in the MML (Music Macro Language) format, it allows the erhu learners to play along with the sheet music. After each performance, the system provides learners with expert-like comments on pitch and rhythm, respectively. The system also keeps a record of learners' practice sessions and provides appropriate encouragement and guidance based on their learning progress by creating an intelligent and personalized learning scaffold. After the development of the system, this study conducted a usability evaluation and investigated the relationship between usability and erhu playing experience. The results showed that the average for all usability dimensions was above 4.6, indicating that the system is acceptable for erhu learners. Moreover, learners with more erhu playing experience showed higher acceptance of the system compared to those with less experience in erhu.
The Impact of Preschool Teacher Training on STEAM Education: Professional Preparedness and Confidence
Authors: CHANG Wan-Chen
Published: January 2025

This study aims to explore the impact of teacher training in the field of STEAM education on preschool teachers' preparedness and confidence. The participants of this study were nine education and childcare professionals from a public preschool in northern Taiwan. A small-scale workshop was conducted to train the teachers, covering topics such as an overview of STEAM education, STEAM learning for preschoolers, teaching methods, and curriculum design. The results revealed that prior to the training, the teachers had a high awareness of the importance and expected outcomes of STEAM education. However, they scored relatively low in terms of teaching experience and self-efficacy. After the training, the teachers showed significant improvement in their knowledge of STEAM teaching methods and environmental support. Nevertheless, their ratings for confidence and teaching efficacy remained relatively low. These findings highlight the need for further professional development and support for teachers in the field of STEAM education. The results of this study provide valuable insights and recommendations for teacher training and instructional practices in preschool settings.
A Study of Versatile Tutor Training Programs for Universities in Japan
Authors: ISHIGE Yumi , KABEYA Kazuhiro , NAGAO Kayoko , TANIGAWA Hirotoshi
Published: January 2025

This research reports on the creation of online tutor training programs for learning support centers in Japanese universities. As this topic is relatively new in Japanese higher education institutions, there is a lack of practical training programs that can serve as references. To address the issue, we have opted to develop programs based on a framework established in the United States. The programs were planned in accordance with two core concepts: “usable by any university” and “to be self- learning materials.” The primary objective was to create training programs that can be universally used in Japanese universities, allowing tutors to learn independently even without a lecturer. In conclusion, it can be affirmed that the programs serve as versatile tutor training resources. While some cultural differences may have emerged due to the adoption of a US-based framework, it is believed that these variances can be partially resolved by making adjustments during on-site programs.
The Impact of Development-questioning Activities on Students' Pre-writing Ideas
Authors: HONG Jia Ling , LIAO Chang-Yen , Chan Tak-Wai , Chang Jui-Fen
Published: January 2025

Studies suggest that questioning is a potent cognitive tool that can guide students toward a more profound engagement with their learning and comprehension, mainly driven by their innate curiosity. In conventional teaching methods, instructors often assign writing topics directly, causing a lack of enthusiasm and hindering students' ability to generate original ideas. This circumstance can gradually breed an aversion to writing. In response to this challenge, our research aims to introduce a question-oriented activity that provides students with a participatory platform for idea generation and organization. By engaging in group collaboration and brainstorming, questioning elements are presented to stimulate students' curiosity. Participation in this activity allows students to compile a broad range of ideas for future writing tasks. The intended outcome is to aid students in developing coherent ideas, bolster their motivation for writing, and refine their skills in questioning.
Exploring Student Engagement and Teacher-Student Interaction Patterns in Collaborative STEM PBL courses through Epistemic Network Analysis
Authors: KUO Ting-Yen , CHEN Ssu-Kuang , LIN Sunny
Published: January 2025

To assess junior high school students' engagement in collaborative STEM project-based learning courses, this study employed a web-based observation protocol called COPIE-STEM to collect classroom observation data. This protocol coded data based on the ICAP theory and teacher instructional approaches. Over the course of six weeks, data on student engagement behaviors and teacher behaviors were gathered. In addition to using coding and counting methods, Epistemic Network Analysis (ENA) was employed to explore the trajectory of the STEM-PBL course during these six weeks. The results revealed that passive student engagement behaviors and teacher- centered behaviors clustered on the left side, while active student engagement behaviors and student-centered teacher behaviors clustered on the right side. Furthermore, examining the network graphs for each week's courses showed that as the course progressed, instruction shifted from teacher-centered to student-centered, and students exhibited higher levels of engagement. These findings provided insights into the dynamics of STEM-PBL classrooms.
Learning Analysis infrastructure to support optimal learning based on IRT and Video Enrollment Data
Authors: SAKAMOTO Masahiro , MATSUBARA Yukihiro , MOURI Kousuke
Published: January 2025

Currently, local governments in Japan need DX (=Digital Transformation) promotion personnel. However, even today, Japan's civil service system still employs mainly legal and human personnel, resulting in a need for more necessary human resources. Therefore, the demand for DX human resource development for local government officials is rapidly increasing. In response to this, we have been engaged in human resource development using e-learning materials based on Moodle for three years since 2020, targeting approximately 9,500 employees of the Hiroshima City Office, where I work, and through formative evaluation of the materials, we have succeeded in creating materials at a level where all employees who took the course expressed a desire to promote DX. The company succeeded in developing educational materials so that all staff members who took the course were willing to promote DX. However, only about 5% of all staff members completed the course, reaching the limit of the improvement method in formative evaluation from those who completed the course. During the three-year effort, we also identified a wide gap in the IT skills of local officials and that we cannot provide optimal educational materials for 95% of the staff. In this study, we created multiple-choice questions corresponding to the DX literacy standard set by the Ministry of Economy, Trade and Industry (METI) in December 2022, which we regarded as a complete mastery map, and optimized them using IRT. The objective was to develop a model for measuring the DX literacy of local government officials and an e-learning course that provides individualized and optimal learning based on the measurement results. Through these efforts, we would like to establish a method of correlating skill surveys using IRT (=Item Response Theory) with e-learning course attendance data to overcome the limitations of the technique of creating e-learning courses and improving them through formative evaluation and to present a method to overcome the limitations of formative assessment in the ID (=Instructional Design) field. We hope to offer a strategy to overcome the limitations of formative evaluation in ID.
Exploring the Benefits of Chatbots Game-based Learning in Science Learning Outcomes and Motivation
Authors: CHEN Ching-Huei
Published: January 2025

In this study, we aimed to assess the effectiveness of using Chatbot-assisted game-based learning to enhance science learning outcomes and motivation. A total of 202 seventh-grade students participated in the study and were randomly assigned to three groups: (1) Game only, (2) ChatbotGame, and (3) ChatbotGame with examples. The experimental groups received game-based learning with the assistance of Chatbot, either with or without examples, while the control group only received game- based learning without any Chatbot support. The results indicated that students in the ChatbotGame with examples group achieved significantly better learning outcomes compared to those in the Game only group. Moreover, students in both the ChatbotGame and ChatbotGame with examples groups reported significantly higher levels of perceived competence compared to the Game only group. Additionally, the data collected from learning analytics and interviews suggested that Chatbot-assisted game-based learning can effectively enhance students' intrinsic motivation and promote positive learning behaviors in the context of science education. These findings hold important implications for the design and implementation of Chatbots in game- based learning environments, as they have the potential to significantly improve students' learning outcomes and motivation.
Proposing a Training Model on Energy Management of Compressed Air Systems with Artificial Intelligence of Things
Authors: MONOK Noppadon , HOWIMANPORN Suppachai , CHOOKAEW Sasithorn
Published: January 2025

Technology 4.0 in the industry focuses on effective energy saving. There is an increase in the need for industrial worker training, especially in compressed air systems, air kept under more significant pressure than atmospheric pressure. It is an important medium for the transfer of energy in industrial processes. However, the new technology of energy management systems to enhance performance has yet to be widespread. Owing to the learning material for training is expensive. It is also not possible to simulate the operation of a comprehensive system. The employees lack an understanding of the big picture, causing problems in learning and lacking practical skills. Especially new employees may need more knowledge and experience and have operation errors or problem-solving skills. In this study, we proposed a training model consisting of a compressed air systems training kit based on the Artificial Intelligence of Things (AIoT), and the energy-saving scenarios consist of 1) controlling the compressed air pressure fed to the air cylinder while being subjected to loads of different sizes. 2) controlling the compressed air pressure supplied to the air cylinder while operating the air cylinder without load. 3) controlling the compressed air supplied to the machine while it is stopped. In addition, we use an outcome-based approach to drive training activities. The results show that the training model can simulate the process of energy management systems of compressed air systems and show it on the dashboard. It can be implemented in employee or engineer practical training in the future.
Promoting STEM Interest through Empathy and Creative Thinking in a STEM-based Community Service Program
Authors: NALIPAY Ma. Jenina , HUANG Biyun , JONG Morris Siu-Yung , CHAI Ching Sing , LUK Eric Tsun-Hin
Published: January 2025

Students’ interest in science, technology, engineering, and mathematics (STEM) tends to decline as they reach high school. Among the factors to which this decline is attributed are the perceptions about the lack of communality and creativity in STEM. To address this problem, we implemented an 8-week STEM-based community service program where high school students learned about STEM and community service. The students were asked to design possible solutions to problems faced by people from disadvantaged groups (e.g., visually impaired people). Using the post-test data from 275 high school students who participated in the program, we examined a model of empathy predicting STEM interest via creative thinking. Results of mediation analysis showed that empathy predicted STEM interest through creative thinking. The findings provided support for the important roles of empathy and creative thinking in the promotion of STEM interest. This information can be used as a basis for designing STEM-based community service programs for the enhancement of students’ interest in learning STEM.
Designing a Training Tool for an Industrial Robot Operating with a Programmable Logic Controller
Authors: WATANAKUL Porramut , HOWIMANPORN Suppachai , CHOOKAEW Sasithorn
Published: January 2025

The industry sector has a complex manufacturing process and technology, mainly utilizing robots and automation, which are necessary for factory operation. Many vocational colleges try to use methods to promote the students' experience of learning automation technology to control robots with a programmable logic controller (PLC). Preparing students who will use technology in Industry 4.0 with robot arm operation is essential. However, the learning tools used to practice based are high-cost, and the technology is constantly changing and evolving. Hence, this research aims to design a training tool for an industrial robot operating using a programmable logic controller (IRO- PLC). The proposal shows that the design training model can simulate steps of the learning activity to control the robot with PLC and then display it on the dashboard with an IoT device. It can increase the student's performance in practical vocational education training in future studies.
Effectiveness of Learning Seminar Course to Promoting Research Skills : Observe- Plan-Organize-Present in Science Project
Authors: YACHULAWETKUNAKORN Chitphon , SUPANDEE Witsanu , PHATTHALUNGc RATTHAKARN NA
Published: January 2025

This paper attempted to study the effectiveness of learning approaches between Seminars Course, and Science Project Course in the context of research skill development; Observation, Planning, Organizing, and Presentation skills. Besides, each process of learning could increase the essential research skills, This process required learner’s effort to work in group within two semester. The learners received and continued to this CRSS approach the high level of learning achievement in the context of research skills; Observation, Planning, Organizing, and Presentation. Furthermore, the finding of this study could be expressed to the correlative soft skills could be used more than one course, which can be designed others curriculum involved.
Ethical Implications of Utilizing Artificial Intelligence in Education for Assessment
Authors: PATKI Mihir , SANADI Saira , JADHAV Shraddha , MUSALE Ashish , KADAM Kapil
Published: January 2025

The growing integration of Artificial Intelligence (AI) in education has brought forth ethical quandaries, particularly concerning its role in assessment methodologies. This research paper delves into the intricate ethical implications linked to the use of AI-driven technologies for educational evaluation. Through an extensive literature review, this study explores the potential merits and drawbacks of AI application in educational assessments, addressing concerns encompassing fairness, transparency, privacy and the inherent biases embedded in algorithmic decision-making. This article critically assesses the ethical aspects of AI incorporation in formative and summative evaluations, examining its repercussions on student learning encounters and academic outcomes. By scrutinizing the viewpoints of educators, students, policymakers and technologists, this paper provides insights into the complex ethical predicaments arising when AI assumes the role of evaluating human aptitudes and understanding. The findings underscore the essentiality of a well-balanced approach that upholds ethical principles, human discernment and the responsible advancement of AI technologies to ensure equitable and impartial educational assessment practices during the AI-driven epoch.
The Impact of an Educational Board Game on Students' Learning Achievement and Flow State in Media and Information Literacy
Authors: HSU Ting-Chia , ZHANG Ya-Xuan
Published: January 2025

Given the increasing international emphasis on the importance of identifying and critiquing media content and the proper use of information and communication software, it is imperative to enhance students’ media and information literacy education. In this study, an educational board game for media and information literacy was developed to cultivate the basic knowledge of media and information literacy among university school students in Taiwan. A quasi-experimental study was conducted to investigate the effects of the educational board game on students' learning achievement and flow state. Results showed that the educational board game increased students' learning achievement and flow state, but no difference was found between the collaborative-team gaming group and the competitive-multiplayer gaming group in terms of learning achievement and flow state.
Explainable AI in the Real World: Challenges and Opportunities
Authors: BOTICKI Ivica , HORVAT Dora , SEOW Peter , DROBNJAK Antun
Published: January 2025

This paper presents the results of a systematic review of the research papers on the use of explainable AI in the real world. The present body of research indicates there is a huge drive from the academic society in pushing and exploring explainable AI across disciplines from a research perspective, and there is inherent need to design prototypes with increased complexity to tackle the numerous scientific and methodological issues in the process. The main conclusions of the review are that there exist serious methodological issues with the use of XAI in complex systems which reside on vast or layered information systems spanning across multiple organizational units with important data sometimes missing, potentially limiting the validity of the XAI approach used in practice. For XAI to work in the real-world context of education, the approaches to presenting explanations to the stakeholders such as teachers and students should be understandable by them to take appropriate actions or decisions. This would highlight the need to study of human-computer interaction between AI and users that would lead to better transparency, trust and personalization.
Role of Seamless Learning in Enhancing Interest-Driven Creator Theory
Authors: WONG Su , KHAMBARI Mas , TANG Sai
Published: January 2025

This paper discusses the concept of seamless learning and its alignment with Interest-Driven Creator (IDC) Theory in response to Tak-Wai Chan’s keynote at the 1st MetaACES 2023. He introduced the Seamless Interest-Driven Co-Creator (SIDC) learning framework — an integration of seamless learning and IDC learning. This paper also explores the educational implications of SIDC learning framework.
Web-based VR Education Contents Supporting VR-goggles and User Study
Authors: OKADA Yoshihiro , KANEKO Kosuke , SHI Wei
Published: January 2025

This paper treats the user study for web-based VR education contents supporting VR-goggles. Educational materials using multimedia have ability to enhance the education efficiency rather than text books. Similarly, educational materials using new technologies like VR have ability to attract much interests of students. Based on Interest-Driven Creator Theory (IDC Theory), this means educational materials using VR may have high educational efficiency. For experiment subjects and exercise subjects, the most efficient learning environments should be the same as the real ones as possible. Educational materials using VR can provide virtually students with high immersive learning environments. Therefore, educational VR materials supporting VR-goggles may have higher education efficiency rather than the others. This may justify Seamless Interest-Driven Creator Theory (SIDC Theory). So, this paper introduces several web-based VR education contents, and also show simple user study results especially for the comparison between their web-browser mode and VR goggle mode.
Pupils’ perceived immersion, attitudes, and learning effectiveness in virtual field trips: A comparison between immersive and projective environments
Authors: CHENG Kun-Hung
Published: January 2025

Focusing on the implementation of virtual field trips in elementary school classroom, this study aimed to explore pupils’ affective perceptions and cognitive performance in either immersive environments (using VR headsets, n=26) or projective environments (using traditional projection screen, n=26) through a quasi-experimental design. The results showed that the pupils exhibited stronger perceived immersion and positive attitudes toward virtual learning and achieved better learning effectiveness in the immersive setting than in the projective setting. We are continuing to expand this work for more understandings of immersive virtual field trips in elementary classrooms.
A Preliminary Evaluation of Using Realistic Virtual Space in Designing Gamification Training Activities for Museum Interpreters
Authors: HOU Huei-Tse , NIab Shen-Yang , LIU Shu-Wei
Published: January 2025

In the digital age, the job roles and skills required of modern museum professionals have changed significantly, and many museums have begun to apply digital technology to the training of museum professionals. In this study, we sought to address the shortcomings of traditional training methods by designing a museum gamification training activity to enable learners to develop their museum skills in a highly simulated virtual space. Preliminary results indicate that the gamification of the interpreter training was able to provide learners with flow and learning motivation and that the learners were highly receptive to the training activities and highly appreciated the use of the simulated virtual space to help them learn museum interpretation.
Experimental study for a computational model in ITS to predict the learners’ state
Authors: TAWATSUJI Yoshimasa , MURAMATSU Keiichi , MATSUI Tatsunori
Published: January 2025

Cognitive architecture plays essential role in Intelligent Tutoring System (ITS). For effective learning support, dynamic model subserving the function of the prediction of learners’ states should be incorporated. In this paper, we proposed a neural network-based architecture in progress that can incorporate the dynamic model to generate the prediction of leaners’ perceptual states when categorical ambiguous stimulus and the instruction of category were given.
Optimization of Personalized Content Providing Function for Adult Learners with Diverse Backgrounds
Authors: NAGAOKA Chikako , FURUKAWA Masako , SUN Yuan , YAMAJI Kazutsuna
Published: January 2025

The skills required in relation to the same topic can differ depending on learner’s attributes such as job and preference. For example, when training on research data management for staffs in universities and research institutes, the skills needed differ depending on the learner’s jobs, such as researchers, research administrators, and IT technologists. In the past research, we developed a Moodle plug-in that provides learning contents and quizzes optimized for each learner’s job and preference dynamically. In this research, we further enhance this plug-in to register skills retrieved from the skill repository and support learners selecting learning contents based on their preference.
Promotion of ERD Design Comprehension Using Recomposing Method
Authors: ARHANDI Putra , ANDOKO Banni , Hirashima Tsukasa
Published: January 2025

Conceptual modelling is a critical ability for a computer science student, enabling them to create a variety of conceptual models such as Entity Relationship Diagrams (ERDs). However, learning to create an ERD is a challenging task especially for novices because it involves various cognitive processes and actions. This research proposes a recomposing approach using kit-build exercise for ERD design learning. In a kit-build exercise, a student is provided a set of components of a structure and asked to recompose the structure using these components. The kit-build exercise has advantages as (1) reducing student’s cognitive load by providing available components and (2) realization of automatic assessment by comparing recomposed structure with the original structure. This exercise has been already implemented for concept maps and the learning effect has also been confirmed both experimentally and practically. Considering the structural similarities between ERDs and concept maps, we have applied the kit-build exercise approach to ERDs. In this paper, we describe the kit- build exercise for ERD with automatic assessment and feedback.
Timorese University Students’ Perception on E-learning: A Case Study
Authors: GONÇALVES Agostinho , PEREIRA Sebastião , ULFA Saida
Published: January 2025

For the sake of maintaining academic continuity during the Covid19 pandemic that struck the world, particularly in East Timor, all students were required to adopt the distance learning format. Online learning, which allows flexibility in learning, is one of these formats. This study aims to describe how Timorese University students perceive online learning. 190 college students from Instituto Superior Cristal (ISC), East Timor, participated in this study. According to the study's findings, students generally have a favorable perception of online learning.
Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
Authors: DUDA Ewa , ANACKA Helena , KOWAL Jolanta , NOWAKOWSKA Iwona , OBRACHT-PRONDZYŃSKA Hanna
Published: January 2025

The process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between transport and learning, men focused mainly on transport. This study contributes to the growing field of the use of educational mobile applications for the promotion of environmentally friendly behavior. The study results can support the design and development of future applications that encourage sustainable practices, benefit society, and contribute to a more sustainable future.
Exploring the Potential of Mobile Assisted Language Learning in Rural Area of Indonesian
Authors: HADI Fais
Published: January 2025

This study aims to explore the potential of Mobile Assisted Language Learning (MALL) in Indonesian rural areas. Rural communities often face challenges to access a good education. Therefore, an innovative approach is needed that can overcome these obstacles. MALL is emerging as a potential solution that harnesses the power of mobile technology to enhance the language learning experience, providing flexibility and learning opportunities according to the needs of learners. This research uses a systematic approach in the literature review to explore the benefits of MALL in improving language learning outcomes in Indonesian rural communities. By exploring the potential of MALL in language learning in rural Indonesian communities, this research is expected to contribute to improving the practice of language education in rural areas, as well as providing equal educational opportunities for students throughout Indonesia.
Exploring a Supportive Ecosystem for Creative Teaching in Higher Education
Authors: Han Weijing , Abdrahim Nur
Published: January 2025

This study aims to explore the construction of a supportive ecosystem in the development of teacher creativity within the education domain. The research primarily focuses on the emergence and development of teachers' individual creativity within the organizational context and their interaction with the organizational environment, in support of the teacher’s professional development. As a result, the mechanisms underlying the occurrence of individual creativity within the organizational context are summarized, and supportive policies to foster teacher creativity development are proposed. This research has significant implications for the development of individual teacher creativity, professional development, and organizational creativity management.
Supporting Interactive Learning in Active Video Watching
Authors: BOJNORDI Ehsan
Published: January 2025

The potential of Active Video Watching (AVW) to train soft skills is evident. Despite considerable achievements in learning via AVW, the capacity of interactive learning has yet to be explored. This PhD research aims to investigate and support interactive learning in AVW via (a) interaction among learners, and (b) intelligent and adaptive interaction between the system and learners (comment recommendations). To this end, I initially provided learners with the possibility of responding to other learners’ comments on videos and calling attention to them by Like/Dislike rating mechanism. In the second phase, a comment recommendation engine will be developed, based on the learner model and a specific-domain ontology with respect to the target soft skill. I will also augment comment recommendations with verbal and visual explanations to increase transparency of the recommendations in hope of enhancing learners’ engagement, interactions, and learning.
Using meaningful gamification to redesign simulation-labs for engaging learners in science inquiry practices
Authors: RANE Archana
Published: January 2025

Practical labs in science are expected to foster disciplinary practices of “doing science” in learners. Simulation-based labs which provide the convenience of conducting practical lab experiments online offer several technological affordances, however, come with their own set of challenges such as steep learning curves, working in isolation, lack of personalization which may adversely affect learner engagement and motivation. OLabs is a set of simulation-based labs for schools widely used in India. The main goal of this work is to re-design simulation-based labs like OLabs to engage learners in science practices and to motivate learners to engage in science practices using gamification. Gamification is known to have a positive impact on learner engagement and motivation. Meaningful gamification, a type of gamification approach focuses on intrinsically motivating learners to find meaning in the given learning context. We have designed a framework GaMINLab, which is the proposed redesign of OLabs and the preliminary design is informed by exploratory study findings and literature recommendations of disciplinary practices and simulation-based labs. Currently GaMINLab framework is built around 2 labs and study is planned to validate the design of GaMINLab.
Learner Perceptions on Gamifying Active Video Watching Platforms
Authors: PEIRIS Pasan , GALSTER Matthias , MITROVIC Antonija , MALINEN Sanna , LUMAPAS Raul
Published: January 2025

Video-based learning (VBL) provides self-paced and flexible learning. However, VBL is often a passive learning method. Active video watching (AVW) has been proposed as an approach to increase learner engagement. We investigate the motivation and perception of learners towards gamification to further increase engagement in AVW. Results from a survey in New Zealand and the Philippines show a positive perception towards integrating gamification into AVW, with learners preferring a combination of game elements rather than individual elements. Our findings provide foundations for a gamification intervention in AVW.
A holistic visualisation solution to understanding multimodal data in an educational metaverse platform – Learningverse
Authors: SONG Yanjie , CAO Jiaxin , TAO Lei , Gašević Dragan
Published: January 2025

Traditional digital learning environments faced challenges in obtaining comprehensive user interaction data, often yielding fragmented insights without a cohesive visual representation. The emergence of metaverse platforms has enriched this landscape, enabling detailed user activity representation with multimodal data through avatars. However, how to understand the multimodal data related to teaching, social and cognitive presences underpinned by the 'Community of Inquiry' theoretical framework in the metaverse is a big challenge for educators. This study introduces a holistic visualisation solution to bridge this gap, ensuring a better understanding of avatars’ behaviours in an educational metaverse platform – Learningverse developed by our research team. The solution captures a range of multimodal data in Learningverse, such as avatar location, behaviours, emotions, and conversation. Key visualisation elements include heatmaps, points, and arrows, each with distinct informational value. In the future, integrating the solution with multimodal learning analytics is our next step work to understand teaching, social and cognitive presences.
Task-based Robot-assisted learning to support L2 Speaking Practice
Authors: JAO Cheng-Yueh , YEH Hui-Chin , YANG Shih-Hsien , WU Ming-Chang , WANG Chen-Fu
Published: January 2025

This study examined the impact of task-based robot-assisted interactive presentation creation on the students’ speaking skills. The study used a paired-sample t-test to compare students’ English speaking scores before and after the intervention, with robot-assisted interactive presentation creation as the independent variable and English speaking skills as the dependent variable. The results of the study showed a significant improvement in students’ English speaking skills after the intervention. The study’s results provide evidence for the effectiveness of robot-assisted instruction in enhancing English speaking skills among students. The interactive nature of the presentations created with the help of robots may have contributed to the significant improvements observed in this study. By engaging students in the creation of their own presentations, the intervention may have increased their motivation to improve their English speaking skills.
An Efficient and Generic Method for Interpreting Deep Learning based Knowledge Tracing Models
Authors: WANG Deliang , Lu Yu , ZHANG Zhi , CHEN Penghe
Published: January 2025

Deep learning-based knowledge tracing (DLKT) models have been regarded as the promising solution to estimate learners’ knowledge states and predict their future performance based on historical exercise records. However, the increasing complexity and diversity make DLKT models still difficult for users, typically including both learners and teachers, to understand models’ estimation results, directly hindering the model’s deployment and application. Previous studies have explored using methods from explainable artificial intelligence (xAI) to interpret DLKT models, but the methods have been limited in their generalizing capability and inefficient interpreting procedures. To address these limitations, we proposed a simple but efficient model-agnostic interpreting method, called Gradient*Input, to explain the predictions made by these models in two datasets. Comprehensive experiments have been conducted on the existing five DLKT models with representative neural network architectures. The experiment results showed that the method was effective in explaining the predictions of DLKT models. Further analysis of the interpreting results revealed that all five DLKT models share a similar rule in predicting learners’ item responses, and the role of skill and temporal information was found and discussed. We also suggested potential avenues for investigating the interpretability of DLKT models.
Recommending Learning Actions Using Neural Network
Authors: Kohama Hirokazu , Ban Yuki , Hirakawa Tsubasa , Yamashita Takayoshi , Fujiyoshi Hironobu , Itai Akitoshi , Usami Hiroyasu
Published: January 2025

Many studies applying neural networks to the field of education have focused on student performance prediction and explainability of their decisions. While those studies introduced neural networks into educational settings, such networks cannot directly support student learnings in place of teachers. Therefore, we present a method that uses a general Transformer encoder to recommend appropriate learning actions for improving student performance. By considering the attention weight of a low-performing student to be close to that of a high-performing student, our method recommends the learning materials and actions for learning the materials. To evaluate the effectiveness of our method, we trained a deep neural network (DNN) on a private dataset of student operations (e.g., NEXT, PREV, OPEN) on digital learning materials obtained from a Japanese university. The number of operations divided by each learning material and by type of operation are input to the DNN, and the DNN outputs the student’s grade on 5-point scale. We applied our method with this trained DNN to samples that successfully predicted grades, and the number of operations increased on the basis of the recommended learning materials and actions. By re-inputting modified sample into the DNN, we then observe how the student performance changes. The results of this simple experiment indicate that more students improved their performance with both the material-based and operation-based recommendations than with random recommendations. The percentage of students whose grades improved tended to be larger for those with low grades. Specifically, the improvement ratio for students with the two lowest grades was over 90% by operation-based recommendation. This is consistent with our intuition that low-performing students are more likely to improve.
Exploring Students' Adoption of ChatGPT as a Mentor for Undergraduate Computing Projects: PLS-SEM Analysis
Authors: GOTTIPATI Swapna , SHIM Kyong Jin , SHANKARARAMAN Venky
Published: January 2025

As computing projects increasingly become a core component of undergraduate courses, effective mentorship is crucial for supporting students' learning and development. Our study examines the adoption of ChatGPT as a mentor for undergraduate computing projects. It explores the impact of ChatGPT mentorship, specifically, skills development, and mentor responsiveness, i.e., ChatGPT’s responsiveness to students' needs and requests. We utilize PLS-SEM to investigate the interrelationships between different factors and develop a model that captures their contribution to the effectiveness of ChatGPT as a mentor. The findings suggest that mentor responsiveness and technical/design support are key factors for the adoption of AI tools like ChatGPT. The study provides practical implications for educators seeking to incorporate AI as a mentor to support students doing computing projects and contributes to the broader understanding of the use of AI in education.
Large Language Models (GPT) for automating feedback on programming assignments
Authors: PANKIEWICZ Maciej , BAKER Ryan S.
Published: January 2025

Addressing the challenge of generating personalized feedback for programming assignments is demanding due to several factors, like the complexity of code syntax or different ways to correctly solve a task. In this experimental study, we automated the process of feedback generation by employing OpenAI’s GPT-3.5 model to generate personalized hints for students solving programming assignments on an automated assessment platform. Students rated the usefulness of GPT-generated hints positively. The experimental group (with GPT hints enabled) relied less on the platform's regular feedback but performed better in terms of percentage of successful submissions across consecutive attempts for tasks, where GPT hints were enabled. For tasks where the GPT feedback was made unavailable, the experimental group needed significantly less time to solve assignments. Furthermore, when GPT hints were unavailable, students in the experimental condition were initially less likely to solve the assignment correctly. This suggests potential over-reliance on GPT- generated feedback. However, students in the experimental condition were able to correct reasonably rapidly, reaching the same percentage correct after seven submission attempts. The availability of GPT hints did not significantly impact students' affective state.
Overcoming Barriers to Sustainable Dissemination of L2 Learning Resources: An Integrated Framework for Creating and Distributing Dialogue Scenarios
Authors: AYEDOUN Emmanuel , HAYASHI Yuki , SETA Kazuhisa
Published: January 2025

Language learning resources, such as dialogue scenarios, are important for supporting second language (L2) learning by engaging learners in simulated conversations or role-plays. However, there are often barriers to the wider dissemination of these resources, including the lack of a standard format for distributing them, the difficulties of maintaining and updating them over time, and the need for effective means of tracking their use and impact. This paper presents an integrated framework for fostering the wider dissemination of L2 learning resources, with a focus on dialogue scenarios. The framework is designed to address the above challenges by providing a novel approach for creating and distributing dialogue scenarios, as well as a set of guidelines to ensure that they are pedagogically sound and compatible with learning management systems (LMS). The paper also discusses the potential benefits of the framework for L2 learners and educators and outlines future directions for the project.
An Adaptive Learning Support System based on Ontology of Multiple Programming Languages
Authors: NA NONGKHAI Lalita , WANG Jingyun , MENDORI Takahiko
Published: January 2025

This research proposes to develop an adaptive ontology-based learning support system for computer programming learning. Firstly, the system adopts a previously developed ontology called CONTINUOUS, which represents programming concepts and their relation in a graph and makes use of its content to serve as hints within programming questions. Secondly, we design an adaptive strategy for recommending suitable exercises to learners, which uses CONTINUOUS as metadata of exercises and the Elo rating system to estimate learners' skills. This work aims to design a system to provide personalized exercise path for the learner and evaluate its effectiveness.
Future City: A Simulation for Making SDGs Action Decisions
Authors: CHEN Pin-Chen , LU Yu-Hao , SHIH Ju-Ling
Published: January 2025

The Sustainable Development Goals (SDGs) deliver a concept aimed at addressing social, economic, and environmental challenges that require collaborative efforts from everyone. The actions often involve conflicts of interest between businesses, governments, social organizations, and citizens. This study develops an inquiry-based learning system  aiming to illustrate SDGs issues. Students play different roles and simulate future social scenarios based on their positions and action decisions. This assists students in understanding the concepts of sustainability.
A Thematic Analysis Exploring Flexibility in Programming-based Mathematical Problem Solving
Authors: YE Huiyan , NG Oi-Lam , CUI Zhihao
Published: January 2025

Research on computational thinking (CT) have received significant attention in recent years, but how CT and mathematical thinking (MT) work together to influence problem solver’s computational strategies and competency has not been illuminated. Taking the method of thematic analysis combined with a conceptual framework of flexibility in programming-based mathematical problem solving, this study aims to shed light on the interplay between CT and MT. We identify two kinds of flexibility when a problem solver engages in programming-based mathematical problem-solving: translation flexibility and integrated flexibility. We hope that this research will contribute to a deeper understanding of the interplay of CT and MT as a basis for conceptualizing an interdisciplinary form of STEM education and thinking on task design, pedagogy, and assessment approaches of CT-based mathematics instruction.