bluuebunny/crossref_metadata_2025 huggingface dataset:
Technology Considerations in Building Virtual Educational Avatars
Authors: DROBNJAK Antun , BOTICKI Ivica
Published: January 2025

This paper examines the area of technology development for virtual educational avatars. Since such avatars can be real-like and closely resemble real or fictional persons, the paper examines practical aspects of such designs, linking technology designs to pedagogy requirements. Following these, technology development considerations for realistic voice and video generation and the corresponding architecture which enables realistic virtual avatar for use in education are discussed. Additionally, using powerful CPUs and GPUs shows how current technology allows for efficient and sophisticated video and audio generation, emphasizing the need for optimized resource management to balance processing speed and output quality.
A Robot-Assisted Scenario Training for Students with ASD
Authors: FUNG Ka Yan , FUNG Kwong Chiu , LUI Tze-Leung Rick , PANG Feifan , QU Huamin , SONG Shenghui , SIN Kuen Fung
Published: January 2025

Students with autism spectrum disorders (ASD) often feel insecure in new environments due to social challenges, unfamiliarity, and a lack of support or understanding. Despite considerable efforts dedicated to assisting students in adapting to new environments and understanding appropriate behaviours in public settings, there remains a lack of interactive and personalized learning systems. In this work, we developed a robot-assisted scenario training (RAST) system to facilitate inclusive learning and arouse students' learning interests. With the RAST system, we seek to identify effective interactions that can improve students' engagement. To this end, we invited 13 students with ASD to participate in an evaluation study. In the study, self- determination theory (SDT) measures students' learning engagement. Learning engagement and effectiveness are evaluated using variance analysis (ANOVA). Students also participated in interviews to report their user experience regarding the system. The results reveal that learning with the RAST system can significantly arouse students' intrinsic motivation and improve their behavioural, emotional, and cognitive engagement. Additionally, students with ASD increased their learning performance by 8.33%. Furthermore, students exhibited a high level of engagement in scenario training with certain types of interactions, including personalized functions, visual cues and sound quality. Overall, the RAST system demonstrates promising capabilities in enhancing students' learning engagement and proficiency with ASD.
Comparing Effects of Adaptive Gamification and One-Size-Fits-All Gamification on Students' Task Completion Process and Learning Performance
Authors: BAI Shurui , LIU Yingxue
Published: January 2025

Gamification applies game elements, such as points, badges, and leaderboards, to influence people's motivation to complete certain tasks. One-size-fits-all gamification (OG) uses the same game elements for all users, while adaptive gamification (AG) customizes game elements to align with individual users' motivations in gamified systems. This study compares the effects of AG (n 36) and OG (n 37) on students' task completion process and learning performance via a quasi-experiment design. The results showed that AG could significantly enhance students' task engagement and learning performance by applying different game elements based on player types. The connections of "pre-task reading" to "post-task review" and 'just-in-time learning" to "post-task review" are the two most common task completion processes in the adaptive gamification group. The connection of "post-task review" to "pre-task reading" is the most common task completion process in the one-size-fits-all gamification group. This study contributes empirical evidence to the adaptive gamified learning and indicates the effectiveness of the use of adaptive gamification to cater to diverse motivation needs.
Dialogue Game-Based Learning for AI Ethics Education
Authors: SO Hyo-Jeong , KIM Sung-Eun
Published: January 2025

This study aims to develop a dialogue game for exploring ethical issues in artificial intelligence (Al) and to investigate the dialogic learning process in gameplay. The research suggests that effective Al ethics education goes beyond traditional dogmatic instruction, advocating for the integration of dialogue game-based learning as a promising pedagogical approach. Through the card game Al Ethics Dilemmas, participants articulate their ethical perspectives via moral reasoning discourse. The designed game incorporates three components—situations, roles, and questions—to facilitate players' dialogic learning and ethical deliberations. The study involved 28 Korean learners grouped into 4-6 members each, actively engaging in playing the designed game. Gameplay discourse was recorded and transcribed using Alexander's (2020) framework of learning talk. The analysis revealed that learners' in-game discourse predominantly focused on transactional and expressive aspects. Moreover, participants' discussions indicated the ethical reasoning process, reflecting the core values of Al ethics and the conflict structures surrounding diverse stakeholders. This study underscores the potential of dialogue game-based learning in fostering learners' ethical deliberations and enhancing their understanding of complex Al-related dilemmas.
Detecting Off-Task Behavior of Learners in Minecraft Using Exploration and Personalized Features
Authors: ESCLAMADO Maricel A. , RODRIGO Maria Mercedes T.
Published: January 2025

Off-task behavior refers to any action by a learner that is unrelated to the learning task, and it can have a negative effect on learning outcomes. Determining when a behavior is off task is challenging because these behaviors vary across different learning environments and goals. Off-task behavior in Minecraft might be more difficult to detect because of the open-ended nature of the game, which allows learners to explore the environment and complete learning tasks in various ways. This study aims to model off-task behavior of learners using the What-If Hypothetical Implementations using Minecraft (WHIMC). Detector of off-task behavior was developed using features from the interaction logs of the learners in WHIMC. Initially, the detector was constructed using the basic feature set as the baseline, that includes the time-based features, frequency-based features, and sequence features. The feature set was further expanded to include exploration features and personalized features, and the performance of the models using different sets of features were compared. This study found that the detector built with the addition of exploration features to the baseline feature set showed slightly higher performance compared to the detector built using the baseline feature set. Then, the detector built using the feature set that also included personalized features had better performance compared to the detector using the feature set with the exploration features. Some selected exploration and personalized features were also found to be more predictive of off-task behavior compared to some features in the baseline feature set.
Exploring the Effects of Leaderboards on an Online Professional Development Course for Teachers
Authors: LAZARO Aime Michelle , DE LEON Marlene
Published: January 2025

This study investigates the effects of leaderboards on an online teacher professional development (TPD) course and examines: (1) module completion of the game and the non-game groups in terms of section views/visits, time spent and overall completion including optional activities; and (2) the learning gains for each individual participant and for the whole group based on pre- and post-test scores. An experimental research method was used for this study. The mediating process of Richard N. Landers' theory of gamified learning was used as a framework for the experiment while the self-paced online TPD course was structured in keeping with the four-stage model of David Kolb's experiential learning cycle. The results of this study support the mediation effect of leaderboards on learning gains by increasing section views/visits (↑ 9.6%), time spent (↑ 23.8%), and completion of optional activities (↑ 137.5%) in the game group compared with the non-game group. Further, the game group posted higher average of gains (↑ 20.5%) and gain of averages (↑ 26.1%). The game group's higher output count for completion of optional activities also points that the leaderboard functioned as an extrinsic incentive and promoted performance quantity, without impairing intrinsic motivation.
Game-Based College English Translation Instructional Design Based on Representational Redescription Model: Implicit Knowledge Transformed into Explicit Knowledge
Authors: JIANG Xinyu , CHEN Mengya , HUANG Lu
Published: January 2025

Translation is a process of semantic and semiotic transformation between original language and target language. It is an implicit learning process that can be made explicit through game-based study, facilitating the advancement of students' translation abilities. This paper reveals four phases in game-based translation instruction: context construction, game experience, verbal report and written representation, based on the "four levels" and "three-phase cycle" of representational redescription model. It elaborates on the impact of games on Chinese non-English major students' implicit learning of translation in terms of materials, time, context and attention. Finally, an instructional design for game-based college English translation instruction, integrating the games Gone Home and Lost CC to create contexts for students to gain knowledge of cultural, situational and linguistic context of target text, is proposed. This design aims to improve Chinese non-English major students' translation ability by combining various representations, including images, verbal language and written text.
TAMMY: Supporting EFL Translation Practice with an LLM-Powered Chatbot
Authors: WOOLLASTON Steve , FLANAGAN Brendan , OCHEJA Patrick , DAI Yiling , OGATA Hiroaki
Published: January 2025

Learning EFL through translation tasks is an effective language learning technique, but requires consistent practice and scaffolding. This study evaluates TAMMY, a prototype EFL chatbot designed for Japanese learners to practise English translation tasks. Using the extended Technology Acceptance Model, the study examines Tammy's usability, usefulness, and enjoyment. Response appropriateness and task success are also explored. Findings from a pilot study with Japanese university students indicate high usability and positive attitudes towards the chatbot. Tammy effectively provided accurate feedback in most tasks successfully guiding learners to an accurate translation, though improvements are needed in feedback clarity and conversational adaptability. Despite limitations, Tammy shows promise as a support tool for language learning, offering an engaging and non-judgmental platform for practising translation and enhancing English proficiency.
Exploring Graph Slopes Through a Series of Embodied Learning Experiences
Authors: ELANGAIVENDAN Priyadharshni , ALBUQUERQUE Melwina , DARA Shizuka , CHANDRASEKHARAN Sanjay
Published: January 2025

This study presents a sequence of embodied learning designed to help students understand the concepts of rate of change and slope. The sequence with an embodied exploration of proportion using the Mathematics Imagery Trainer. Building on this experience, two other learning systems were developed These generate graphs when learners walk in proportions. Through the second task learners are expected to get a sense of rate of change, by blending the walking experience with the graphs. In the third task, learners generate movements corresponding to given graphs. This sequence of embodied experiences is designed to help learners integrate and qualitative understandings of rate of change with the formal notion of slope, through the process of conceptual blending.
A Preliminary Investigation of the Definition and Components of Computational Thinking in the Malaysian Education Landscape: From Educational Technology Experts' Perspective
Authors: HAMED Ahmad Sarji Abdul , WONG Su Luan , RANI Mohd Zariat Abdul , KHAMBARI Mas Nida Md , RAHIM Nur Aira Abd , KHALID Fariza , MOSES Priscilla
Published: January 2025

This qualitative study explores the definition and essential components of computational thinking (CT) within the Malaysian educational context. Through semi- structured interviews with educational technology experts, the research delves into the nuanced understanding of CT, considering its adaptation to the local educational landscape and its broader applicability beyond technical skills. The findings reveal that CT in Malaysia is defined as a problem-solving methodology emphasizing inclusivity and thinking, as guided by the Malaysian Ministry of Education (MOE). Essential of CT identified by experts align with MOE's framework and encompass abstraction, decomposition, pattern recognition, algorithms, logical reasoning, and evaluation. This approach equips students with skills for a computational world and strengthens their critical thinking. The study concludes that integrating CT by focusing on these key skills can enhance students' problem-solving abilities and support national progress. Limitations include the study's focus on educational technology experts. potentially excluding broader educator perspectives, and variations in CT adaptation across regions. Future research should include diverse educator viewpoints and longitudinal studies to assess CT instruction's long-term impact and effectiveness.
Exploring Learning Analytics: A Case Study of Tertiary Educators' Utilization and Integration of AnimoSpace LMS in the Online Learning Environment
Authors: FLORES Rozanne Tuesday G. , ONG Ethel C.
Published: January 2025

Abstract: This research study employs learning analytics to analyze data and explore the utilization patterns of AnimoSpace, an online learning environment, and its integration by faculty before and during the pandemic. The study provides valuable insights into optimizing learning outcomes and enhancing pedagogical strategies by examining access frequency, application diversity, and technology integration among tertiary educators across eight terms. A significant increase in AnimoSpace usage during the pandemic, particularly from the second term of the Academic Year 2019- 2020 to the third term of the Academic Year 2020-2021 , indicates its effectiveness in supporting online learning and facilitating technology integration among educators. The study also identifies the most frequently used features of AnimoSpace, offering insights for developers and administrators for platform enhancements to improve the online learning experience and support faculty teaching practices. The study's focus on ethical considerations and transparency in learning analytics reassures the audience about the responsible use of technology in education, ensuring that these technologies promote ethical practices and literacy. This research highlights the pivotal role of platforms like AnimoSpace in advancing educational technology, reinforcing the importance of continued research in this area.
PERS: A Personalized Recommender System for Student-Generated Questions in Programming Courses
Authors: THO Pham-Duc
Published: January 2025

This study introduces PERS (Personalized Exercise Recommender System), integrating Student-Generated Questions (SGQ) with a recommender system for programming courses. Implemented in a 10-week introductory programming course with 395 undergraduates (200 using PERS, 195 as control), PERS uses collaborative filtering to suggest personalized exercises. This study addresses the impact of PERS on student engagement and learning outcomes, the effectiveness of its recommender system, and students' perceptions of the system. Results show significant improvements in exercise completion rates, assignment scores, and final exam performance for PERS users compared to the control group. The system demonstrated high recommendation relevance and user satisfaction, suggesting its potential to enhance personalized learning in programming education.
An Implementation of Augmented Reality in Guided Inquiry-Based Learning for Enhancing Primary Students' Mental Models in Science
Authors: PREMTHAISONG Sasivimol , CHAIPIDECH Pawat , PONDEE Phattaraporn , SRISAWASDI Niwat
Published: January 2025

Augmented reality (AR) is increasingly recognized as an essential tool in science education by providing interactive and immersive experiences that make complex concepts more concrete and tangible. This is particularly important for primary students, who must establish precise mental models in order to understand science concepts including the states of matter. To accomplish meaningful learning, this is essential to understand both the macroscopic properties and the microscopic structures. Consequently, this study examines the effect of AR in guided inquiry-based learning on the conceptual understanding and mental models of primary school students who are studying the states of matter. The study was conducted with 46 fourth-grade students, utilizing AR to facilitate interactive learning in science classroom settings. A paired samples t-test was performed to analyze students' conceptual understanding. In addition, mental models of states of matter were analyzed by inter-rater reliability techniques. The findings suggested that when effectively integrated AR into inquiry-based learning frameworks, this learning can play a crucial role in enhancing students' conceptual understanding and their mental models, bridging the gap between observable and molecular level in the state of matter concept. Lastly, this study provided suggestions for future research and implementation of AR in guided inquiry-based learning science education.
Cognicraft: Smart Exam Question Generation with AI and Bloom's Taxonomy
Authors: SAGADRACA Christian , SANTOS Zainal , SIMON Jr. Danilo , TOLENTINO Marianne Jessica , VENTURA Reymar
Published: January 2025

Conventional approaches of exam question creation are often characterized by time-consuming manual methods and challenges in aligning questions with specific educational objectives. This study addresses these challenges by developing an innovative AI-powered exam question generation tool designed to streamline and improve the exam composition process. Cognicraft uses the Feature Driven Development-Agile Methodology and Bloom's Taxonomy to automatically generate exam questions that are academically acceptable. Iterative design cycles were used in the development process to identify, implement, and revise important features in response to continuous user feedback. The methodology included gathering requirements from educators, designing and implementing system features, and conducting User Acceptability Testing (UAT) to evaluate performance across four key dimensions: functionality, reliability, efficiency, and acceptability. The results from the UAT , involving 50 participants, demonstrated high ratings across all criteria. Cognicraft also achieved strong scores in generating relevant and varied exam questions, maintaining consistency and accuracy, and providing a user-friendly experience. The findings indicate that Cognicraft successfully addresses the limitations of traditional exam creation methods by significantly reducing the time and effort required for question generation while ensuring alignment with educational objectives. The system's ability to generate questions that adhere to Taxonomy enhances the quality and diversity of assessments, offering a valuable for educators seeking to improve their exam creation processes. represents a significant advancement in educational technology, providing a practical and efficient solution to longstanding challenges in exam question development.
Design and Implementation of an Educational Escape Rooms Class
Authors: PATO Jesus Alvaro C. , GO Gerick Jeremiah Niño N. , CAOILE Paolo Santino P. , REYES Gio Gabriel C. , SINJIAN Joaquin Enrique B. , AQUINO Jerold Luther P. , RODRIGO Maria Mercedes T.
Published: January 2025

An escape room is a game in which a player or team of players is locked in a room or series of rooms. To exit the room successfully, they must solve puzzles or search for clues within a set amount of time. While commercial escape rooms are typically designed for entertainment, an escape room format can be used as an educational experience as well. A well-designed escape room can heighten engagement, provide immediate feedback, and help practice and cooperation. This paper describes the design and implementation of an educational escape rooms class at a major university in the Philippines. It describes the class's goals and objectives, and the major elements of an escape room's design. The class was offered during the second semester (January to May) of 2024 and the summer session (June to July) of 2024. The paper discusses two of the rooms that were designed by the members of the class, and some feedback from the games' alpha testers.
A User Acceptance Testing Tool for Mobile Game-based Learning Application
Authors: GUILLEN Christian Jade D. , NISPEROS Saturnina F.
Published: January 2025

This study developed a user acceptance testing tool designed to guide the creation of mobile game-based learning applications. Topics involving mobile game-based learning applications, mobile learning, game-based learning, user acceptance test tool and technology acceptance model were analyzed to come up with the different assessment constructs for evaluating a mobile game-based learning application. After identifying these constructs, the researcher had the constructs validated by selected panels of experts from the academe and industries to see if it is relevant in assessing a mobile game-based learning application.
Overall, results revealed that the User Acceptability Test tool for Mobile Game-Based Learning application constructs and measurement items were assessed to be very highly relevant in terms of Learning Content, Game Personalization, Learning, Experience, Learning Objective, and Game Design. Hence, the findings indicate that the user acceptability test tool can be utilized to evaluate a mobile game-based learning application.
This study could be expanded to include people from different countries and cultures, which would make the instrument more encompassing.
Mapping Morphological Patterns: A Framework for Rinconada Bikol Language Morphological Analysis and Stemming
Authors: PANDES Tiffany Lyn , MARTINEZ Joshua
Published: January 2025

Natural Language Processing (NLP), a subfield of Artificial Intelligence (Al), has gained traction in management research, particularly linguistics. However, only High-resource language is being established in NLP. This paper aims to analyze morphological patterns of Low-resource languages with limited linguistic data and resources available for NLP tasks such as Rinconada Bikol Language (RBL). This paper proposed a framework suited for RBL as the approach to developing the RBL Morphological Analyzer. This paper utilized the framework and evaluated it using Morphological Accuracy, revealing an impressive 90% accuracy in identifying correct analysis and stemming. The system's precision stands at 0.90, with a perfect recall of 1.00, resulting in an Fl score of 0.95. This high level of performance indicates the system's strong ability to recognize morphological features and patterns within the dataset effectively. The findings also reveal that the framework could also accurately analyze the morphological structure of RBL sentences.
Development of a Chatbot and Evaluation of Its Effects on Learning and Intrinsic Motivation of a Public Secondary School's Spanish Language Learners
Authors: JANUBAS Julian Eymard , DEYSOLONG Josiah Jose , ESTOPIA Hanz Lucas , TABBAY Karl Mykell , OBISPO Jun Rangie
Published: January 2025

This study developed and evaluated a Messenger-based chatbot designed to enhance learning and intrinsic motivation among Spanish language learners at a public secondary school. Using the pretest-posttest design, the study involved 28 students who were assessed on their Spanish language skills and motivational levels before and after interacting with the chatbot. Descriptive and inferential statistics revealed a statistically significant improvement in academic performance, affirming the chatbot's effectiveness as an educational tool. While the paired samples t-test did not show a statistically significant increase in intrinsic motivation, the Repeated Measures ANOVA did reveal a significant effect, suggesting that the chatbot had a meaningful impact on motivation when considering changes over time. Spearman's rho correlation analyses indicated no strong relationship between post-intervention intrinsic motivation and learning outcomes. Additionally, linear regression analysis showed that pretest grades were a strong predictor of posttest grades, whereas pre-intervention intrinsic motivation did not significantly predict posttest grades. These findings suggest that while chatbots can effectively enhance language proficiency, their influence on intrinsic motivation is more complex and requires further investigation.
Sociotechnical Challenges of Older Educators in Delivering Medical Education Online
Authors: EBARDO Ryan , TUAZON John Byron , FERMIN Miriam Louella
Published: January 2025

This study explores the sociotechnical challenges faced by silver teachers in teaching medicine, focusing on integrating technology in educational settings from the perspective of older educators in the field of medicine. Utilizing the Sociotechnical System (STS) theory, the research highlights the interplay between social and technical elements in education, emphasizing the need for solutions beyond technology to equip older educators with the necessary skillset in teaching medicine online. Key challenges identified include the fluidity of achieving a digital social presence, and siloed training, particularly pronounced in low-resource settings. The study utilized thematic analysis based on the results of interviews with twelve older adult educators in the Philippines who teach medicine. The findings underscore the barriers to adopting LMS, e-learning, and other technological methods of delivering medical education due to unfamiliarity with emerging technologies and resistance to changing traditional teaching
Factors Influencing ChatGPT Use Behaviour Among Trainee Teachers
Authors: VALAIDUM Sarala , MAHAT Jazihan
Published: January 2025

The integration of ChatGPT in educational settings has the potential to enhance teaching and learning experiences- This study explores the factors influencing the use behaviour of ChatGPT among trainee teachers at Universiti Putra Malaysia (UPM). Drawing on established Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of (UTAUT) models, and risk perception theory, the research focuses on perceived usefulness, ease of use, perceived risk, anxiety, social influence, attitude, and use behaviour for learning purposes. A total of 224 trainee teachers were selected using simple random sampling. The findings highlight that perceived usefulness, social influence, and attitude significantly influence the use of ChatGPT among trainee teachers. Additionally, the study reveals no significant effect of perceived ease of use, perceived risk, and anxiety on ChatGPT use behaviour among trainee teachers. The result showed that all factors contributed 50% (R2 = 0.50) in impacting ChatGPT use behaviour among trainee teachers. These insights provide valuable guidance for educators and policymakers aiming to integrate ChatGPT into teacher training programs, emphasizing the need to create environments that minimize anxiety and perceived risks while promoting the benefits and ease of use of ChatGPT.
Implementation and an Evaluation of a Search Function Allowing Misspelling for a Japanese Learning System
Authors: KUNICHIKA Hidenobu , VILLALOBOS ZUNIGA Miguel Antonio
Published: January 2025

Search functions are useful in foreign language learning. Learners may sometimes make spelling mistakes. This makes it difficult to find the information they need using a search function. The target of this research is to implement and evaluate a grammar search function allowing misspelling for a Japanese learning system. As the result of an evaluation, we found that our search function is superior to a simple search function in terms of accuracy.
Learning Effectiveness and Reflections on AI Literacy in Junior High School Students with Game-Based Learning and Problem-Based Learning
Authors: HUANG Shih-Hua , HSU Ting-Chia
Published: January 2025

This research attempts to cultivate the AI literacy of junior high sci-ml students and aims to evaluate the learning effectiveness of integrating game-based learning with problem-based learning to improve their A1 literacy. using a self- developed board game on Naive Bayes Classifier and Generative AI applications as teaching material, students engage in a problem-based learning approach through group The results of the research show a significant improvement in students' AI literacy, particularly in their understanding of AI, and a significant increase in their behavioral intentions and engagement. The results confirm the effectiveness of this pedagogical approach for promoting AI literacy at the high level.
Do Academic Stress and Risk Propensity Affect Behavioral Intention to Use ChatGPT among University Students?
Authors: SAMSON Brylle , LURIAGA Ronnie , EBARDO Ryan
Published: January 2025

The widespread adoption of support tools, such as artificial intelligence, is evident across various fields, including the academic community. Students' attitudes towards using Al tools like ChatGPT significantly impact their utilization. The research employs the Theory of Reasoned Action (TRA) framework, incorporating academic stress and risk propensity as additional constructs to examine students' attitudes toward ChatGPT. The study focuses on college students using Al tools for academic purposes. A survey was conducted across educational institutions, yielding 413 responses. Analysis using the Partial Least Squares — Structural Equation Model revealed that academic stress and peer influence do not positively affect the intention to use ChatGPT. However, academic stress and risk propensity positively impact students' attitudes toward ChatGPT, influencing the intention to use the tool. The study recommends expanding research to include teachers and other professionals, considering diverse cultural settings and employing various research methods. The findings also provide insights for academia to enhance the adoption and integration of Al tools.
Representing Learning Progression of Unguided Exercise Solving: A Generalization of Wheel-Spinning Detection
Authors: YAMAUCHI Taisei , HOPPE H. Ulrich , DAI Yiling , FLANAGAN Brendan , OGATA Hiroaki
Published: January 2025

This study aims at modeling and visualizing students' behavior in a self- regulated and unguided learning environment with a focus on learning progression. Since the modeling approach is process-oriented and does not depend on specific mastery learning criteria, this paper provides a novel way to identify wheel-spinning in self-regulated learning solely based on activity monitoring. The study investigates the free and unsupervised engagement of junior high school students in solving mathematics exercises during summer vacation. During this period, a pool of exercises was provided on the LEAF online learning platform. Additionally, the students receive adaptive exercise recommendations as an add-on. Guided by the basic idea of wheel- spinning as persistent engagement without learning progression, we have designed a mathematical model and a graphical representation to capture and gauge the individual learning progression. Based on an expert questionnaire survey, we considered how this novel representation can serve as a basis to analytically characterize learning progression and specifically to identify wheel-spinning.
The Impact of Using an Online Collaborative Platform in Blended Learning on Postsecondary Vocational School Year One Students' Self-Regulated Learning Abilities: A Quasi-Experimental Research
Authors: WU Siyou , TSE Alex Wing Cheung
Published: January 2025

Self-regulated learning (SRL) abilities refer to learners' abilities to achieve their individual learning goals in the continuous learning process. While previous research has demonstrated the positive impact of SRL abilities on learning outcomes, there is a lack of exploration regarding the use of online collaborative whiteboards as regulating scaffolds (e.g., organizational structure for learning or tasks, tools for communication and knowledge co-construction, and timely feedback) for affecting students' SRL abilities in blended learning contexts. Therefore, 141 students participated in this quasi-experimental study to evaluate the influence of blended learning through BoardMix, an online collaborative whiteboard platform, on the SRL abilities of year one students in a Chinese postsecondary vocational school. During a four-week learning, with the pedagogical approach based on Zimmerman's cyclical model of SRL, students in the experimental group used the BoardMix platform to collaborate with each other. The Online Self-Regulated Learning Questionnaire (OLSQ) (Barnard et al., 2009) was used to collect quantitative data in pre-tests and post-tests for both experimental and control groups, and ANCOVA was adopted to analyze the data. The ANCOVA results revealed significant improvements in SRL abilities and significant differences between the experimental and control groups. Collaborating through the online platform BoardMix significantly enhanced the SRL abilities of the experimental group. In the second phase of this research project, qualitative research was adopted to provide deeper insights into the influence of online whiteboards on learners' SRL abilities, and future applications of collaborative learning can be explored based on these findings which will be presented in another paper.
Investigating the Impact of Kahoot! on EFL Grammar Learning
Authors: CHIN Jonathan Y. , CHANG Ben
Published: January 2025

English grammar can be viewed as a tiresome subject for English as a foreign language learning; therefore to spark the engagement of the learners, this study proposes to integrate game-based platform (Kahoot!) into the classroom. 287 students from 7 different grammar class taught by the same instructor were involved in the study for 18 weeks. The class was organized into groups of 6 students and in the groups the students were then paired up. The pairs took turns being the group leader to enrich grammar learning by creating game-based activities. The quantitative result confirms, game-based learning can increase students' grammar proficiently and students whom experience beyond medium joyfulness had more significant increase in grammar understanding compared to students with less joyfulness.
Developing an LLM-Empowered Agent to Enhance Student Collaborative Learning Through Group Discussion
Authors: AN Sixu , LI Yicong , MA Yunsi , CHENG Gary , XU Guandong
Published: January 2025

Aiming at improving collaborative learning, the current study builds and tests an LLM-empowered agent to enhance student engagement in group discussion. We introduce a four-module conversational system, providing a user-friendly chat website integrated with an LLM agent, where students can discuss on and learn a specific topic in an online classroom. The LLM agent can continuously monitor the dialogue process and give constructive and reflective responses as a knowledgeable learning peer to engage students in the computer-supported collaborative learning (CSCL) environment. To evaluate the pedagogical performance of the system, three LLMs were tested by prompting. The results showed that LLMs with only prompting were unable to accurately process multi-user dialogue information and lacked pedagogical strategies in their responses.
Designing an LLM-Based Dialogue Tutoring System for Novice Programming
Authors: PEREZ Julieto , ONG Ethel
Published: January 2025

In this paper, we present the design of a dialogue-based tutoring system called DT4-Coding to help novice programmers understand their misconceptions about programming concepts and work towards correcting them. The error or misconception detection and correction are based on Ohlsson's Theory of Learning from Performance Error, which suggests that a mentor (in this case, a software tutor) is necessary to help learners detect these errors and provide feedback to repair faulty knowledge. We utilized the constraint-based model (CBM) for domain and knowledge modeling, which allows human experts to represent knowledge as a constraint. These constraints were used to assess student answers and to generate LLM-based feedback via a question- answer form of dialogue. By incorporating human-written domain knowledge, the system could potentially reduce the problem of LLMs in generating solutions that may be factually incorrect.
Addressing Public Speaking Anxiety with an AI Speech Coach
Authors: GARCIA Jr. Frederick Voltair , PASCUAL Nicanor Froilan , SYBINGCO Miguel Elijah , ONG Ethel
Published: January 2025

Public speaking anxiety (PSA) can hinder academic performance when students face challenges engaging in class discussions, delivering fluent presentations, and undertaking oral examinations. A primary reason for the prevalence of PSA is students' perceived lack of speaking skills. Speech coaching has been found to be an effective way of enhancing public speaking skills but its effects on PSA reduction need further investigation. In this paper, we report our experiments to evaluate the impact of utilizing an AI speech coach in reducing students' anxiety, improving their self-perceived competence, and increasing performance in public speaking tasks. A mixed-method approach combining qualitative analysis of participants' experiences with the AI speech coach and quantitative measures of anxiety levels and speaking performance improvements was utilized. Results from participants' pre- and post- public speaking anxiety scores showed an average of 25.2% reduction in the anxiety levels and 60.5% increase in speaker speech competency. Statistical metrics and personalized feedback given by the speech coach allow participants to monitor their speech and identify areas for improvement which are essential for self-improvement efforts. These findings can inform educators and students on the potential use of digital speech coaches to address PSA while providing the latter with a personalized platform for practicing their speech delivery.
A Case Study for Educators with ChatGPT and Plato's Allegory of the Cave
Authors: HUANG Anna Y.Q. , TZENG Jain-Wei , HUANG Chi-Sheng , LIU Zhi-Qi , TANUJAYA Bryan Carl , LU Owen H.Q.
Published: January 2025

Generative AI (GenAl) has demonstrated its benefits for student learning outcomes in various educational settings. Due to its diverse applications, it has become a trend for many researchers to explore its usage. In this study, we applied GenAl, specifically ChatGPT, in a workshop designed for 43 university teachers to understand the importance of Plato's Allegory of the Cave in the context of education. The Allegory was chosen because the university teachers came from diverse disciplines, and we needed a subject area that they were not already familiar with. The workshop utilized GenAl in four main aspects: question creation, topic breakdown, problem-solving, and post-class summaries. After the workshop, we used statistical and natural language processing techniques to analyze the teachers' learning outcomes regarding the Allegory of the Cave and the potential of post-class summaries for assessment. The experimental results showed a significant improvement in the teachers' understanding of Plato's Allegory of the Cave. It also confirmed that post-class summaries, as the highest form of knowledge expression, were significantly related to their learning outcomes.
Factors Contributing to the Negative Online Learning Academic Self-Concept of College Students
Authors: BRINGULA Rex , BAET Roman Paulo , GARCIA Ralph Lawrence , MORALES Franchesca Mari , RAMOS Jan Carlo , SARMIENTO Hanna Sophia , TORRES Edmon
Published: January 2025

This study attempted to determine the factors that contributed to the negative online learning academic self-concept of college students who took pure online learning classes. Toward this goal, 501 randomly selected college students answered an open-ended survey form. It was shown that all aspects of online ASC were negative. The results of thematic analysis disclosed that the negatively perceived ability to understand online course content was mainly attributed to domestic, interaction, personal, pedagogical, and technological factors. Students perceived that they exerted more effort in pure online learning classes because of assessment, pedagogical, consultation, technological, learning approach, and personal factors. The lack of interest in the new learning environment was attributed to interaction, technological, personal, personal physical learning space, pedagogical, assessment, and learning effectiveness issues relating to pure online learning classes. Of the three aspects of online learning self-concept (i.e., ability, effort, interest), interest had the most number of barriers. Recommendations and future research directions are offered.
Supporting Students' Post-Exam Reflection Needs in College Automation Engineering Course Using LLM
Authors: ANOLIEFO Edward , OCHEJA Patrick , OCHONU Regina , FLANAGAN Brendan , OGATA Hiroaki
Published: January 2025

Post-exam reflection is critical in helping students consolidate knowledge acquired during a course, enabling them to apply this understanding in future professional contexts. This study investigates the effectiveness of Mirai, a large language model-based (LLM) chatbot, in supporting students' post-exam reflection needs in an Automation Engineering course. Through a controlled experiment, we explored how context-tuned and non-context-tuned versions of Mirai impacted students' reflection habits, help-seeking behaviors, and perceptions of the tool. Students interact with the chatbot to clarify exam questions and receive personalized explanations. A a surveys based on the extended technology acceptance model (exTAM) was conducted and the resulting data was analyzed. We assessed the efficacy of Mirai in facilitating a deeper understanding of exam-related material, improving students' knowledge, engagement and performance. The findings from this study provide insights into the immediate educational benefits of LLM-based tools, their acceptance among students, and their role in enhancing learning outcomes in engineering education.
Research on the Dual-Pathway Impact of Artificial Intelligence Technology on Teachers' Human-Machine Collaboration
Authors: XU Yujie , HU Yiling
Published: January 2025

Based on the Job Demands-Resources (JD-R) theory and the Unified Theory of Acceptance and Use of Technology (U TAUT) model, the study proposed and tested the dual-pathway impact of artificial intelligence (Al) technology on teachers' human-machine collaboration. The results indicated that Al had both negative and positive effects on teachers' human-machine collaboration. Specifically, perceived risk, through the partial mediating effect Of Al anxiety, negatively influenced the collaboration between teachers and Al. Conversely, technology acceptance had a positive influence on teachers' human-machine collaboration through the partial mediation of human- machine compatibility.
Determinants of ChatGPT Adoption in Academe & Other Fields – A Review on Theoretical Perspective
Authors: ELINZANO Gerand Boy O. , CHING Michelle Renee
Published: January 2025

ChatGPT has been showing promising advantages including its capability to optimize work and converse like human being. In the academe, ChatGPT was seen to have the capability to answer formative assessments, aid in research, and act as virtual tutor. However, ChatGPT is also being criticized for its misleading and inaccurate responses. This led the scientific community to further study its adoption factors. This review discussed and analyzed 53 empirical studies that aimed to determine the factors influencing ChatGPT adoption and use in the academe and other fields. Performance expectancy, personal innovativeness, trust, attitude, and self-efficacy were identified as common determinants of ChatGPT adoption in various fields. To add, experience and presence of Generative Al policy also determine ChatGPT adoption. Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT/UTUAT2) are the most widely used frameworks found in this review. Practically, this review recommends that ChatGPT adoption and use be further studied in educational sector focusing on the contrasting results of significant factors found. Policy on how academic institutions will adopt and use ChatGPT is also highly recommended. With respect to other areas, studies on ChatGPT adoption and use in other economic institutions (healthcare, business, law, software development, dentistry, etc.) are recommended. Theoretically, this review recommends use of TAM and UTUAT/UTUAT2 in future studies of ChatGPT adoption considering personal innovativeness, trust, and self-efficacy as extension constructs and focusing on experience and policy as moderating constructs.
Exploring Cross-Disciplinary Education: Enhancing Science Learning with Digital Picture Books
Authors: JAU Yan-Yu , TANG Joni Tzuchen
Published: January 2025

The research developed a digital picture book titled "My Helpful Friend: Hydrogen" on hydrogen energy. Collaborative efforts across disciplines led to the successful creation of the picture book, which was then tested with the participation of 11 first-year college students. The findings indicate that incorporating digital picture books into science education improves student learning outcomes and encourages a positive attitude toward learning. In addition to offering empirical evidence, the study presents practical tools and techniques for cross-disciplinary learning. Future research endeavors could explore diverse themes and subjects to further enhance students' learning experiences and promote the development of creativity and collaborative skills for addressing real-world challenges.
Math Learning Application on Mobile Devices Following the STEAM Educational Model
Authors: THANG Nguyen-Manh , THO Pham-Duc
Published: January 2025

Building a math learning application on mobile devices following the STEAM educational model is a solution to help students see and grasp the role of mathematics in all aspects of their lives, have the mathematical skills to execute ideas correctly, be able to apply mathematical theories and skills to everyday life; create interest, curiosity, eagerness for learning in students. In addition, the application helps parents stay closer to their children and helps parents conveniently accompany their children in learning. This article summarizes the overview studies on applying the STEAM educational model in building math learning applications on mobile devices for grade 1 students.