bluuebunny/crossref_metadata_2025 huggingface dataset:
Multimodal analysis of learners’ communications in CSCL of a mathematical proof
Authors: KANEKO Masataka , EGI Hironori , NODA Takeo
Published: January 2025

In this study, we explore the CSCL of a mathematical proof using HTML- based dynamic geometry content. In addition to the learners’ transcribed communication, multimodal log data of their manipulations of the content and utterances are analyzed. First, we use multimodal data to segment the whole learning process into stages and identify the characteristics of those stages. This segmentation is then aligned with the transcribed communication. Our finding is that the participants’ choice of words varies according to each stage and is compatible with the characteristics derived from multimodal data. Resultingly, when and how the convergent conceptual change occurred is inferred from the commognitive perspective.
ChatGPT’s Performance in Spreadsheets Modeling Assessments based on Revised Bloom’s Taxonomy
Authors: CHEONG Michelle
Published: January 2025

ChatGPT has taken the education scene by storm and caused uneasiness among educators. Mixed reactions were observed with some institutions banning it, while others embracing it with caution. This paper evaluates the performance of ChatGPT on solving spreadsheets modeling assessment questions with multiple test items categorized according to the revised Bloom’s taxonomy, to discover the accuracy of the answers provided at each cognitive learning level. The insights obtained may be useful for educators to design future assessment questions which focus more on testing critical thinking skills to assess the students accordingly to achieve the intended learning outcomes, and we propose recommended actions on how to do so. Our proposed methodology can be applied to other course modules to achieve their respective insights for future assessment designs and actions.
Promoting Middle School Students' Achievement and Attitude toward Science Learning through Sphere Recognition- Based AR Application
Authors: LIU Ruixue , LIANG Lijun , WEI Xiaodong
Published: January 2025

With the advancement of Augmented Reality (AR) technology, considerable studies have explored AR’s application in various educational fields, especially in the field of science. This paper used a sphere recognition-based identifier to develop an AR application that supports middle school students learning of science. A quasi- experimental method was adopted, using a pretest and posttest of science knowledge to measure academic performance. A questionnaire was conducted to measure students’ attitudes toward the use of AR in science lessons. The research sample included 80 middle school students and was divided into experimental and control groups. Students in the experimental group learned science lessons by using a sphere recognition-based AR application, while the control group learned the same material by using a traditional method. Results showed that students who learned science lessons in a sphere recognition-based AR application performed better in academic achievement than that in the control group. In addition, the experimental group showed a positive attitude toward the use of AR in science classes. This study provides empirical evidence to explore the use of sphere recognition-based AR in science education.
Measuring Self-regulated Learning Processes in Computer Science Education
Authors: CLOUDE Elizabeth B. , BAKER Ryan S. , PANKIEWICZ Maciej
Published: January 2025

Self-regulated learning (SRL) is important for computer science education. Yet, students often do not have SRL skills to benefit their learning. In this study, we examined 187 (n=187) students’ SRL behaviors while they built programs with an automated feedback tool. Anchored in Winne and Hadwin’s (1998) COPES model of SRL, our results showed that novices used more operators to debug compiler errors, while more experienced programmers used more operators to debug non-compiler errors. Finally, a random forest classifier showed that prior knowledge was the most important COPES feature predicting learning gain, followed closely by the student’s perceived programming ability, use of evaluations with the automated feedback tool, and operators used to debug non-compiler errors on failed programs.
Construction of a Japanese Language Learning Support System for Learning Semantic Negotiation
Authors: Kogure Satoru , YOSHIDA Akira , NOGUCHI Yashihiro , YAMASHITA Koichi , KONISHI Tatsuhiro , KONDO Makoto
Published: January 2025

Semantic negotiation techniques are important for beginners of Japanese learner. In this study, we investigated how semantic negotiation is handled in a learning environment and then reclassified it. We developed a Japanese language learning support system that can handle semantic negotiation using text input. We report the results of a questionnaire survey administered to three Japanese language teachers and an experimental evaluation of a foreign student.
Predicting and Analyzing Students’ Higher-Order Questions in Collaborative Problem-Solving
Authors: ZHANG Shan , EARLE-RANDELL Toni V. , SHEN Qian , BOTELHO Anthony F. , ISRAEL Maya , BOYER Kristy Elizabeth , LYNCH Collin F. , WIEBE Eric
Published: January 2025

Question-asking is a crucial learning and teaching approach. It reveals different levels of students' understanding, application, and potential misconceptions. Previous studies have categorized question types into higher and lower orders, finding positive and significant associations between higher-order questions and students' critical thinking ability and their learning outcomes in different learning contexts. However, the diversity of higher-order questions, especially in collaborative learning environments. has left open the question of how they may be different from other types of dialogue that emerge from students' conversations, To address these questions, our study utilized natural language processing techniques to build a model and investigate the characteristics of students' higher-order questions. We interpreted these questions using Bloom's taxonomy, and our results reveal three types of higher-order questions during collaborative problem-solving. Students often use "Why", "How" and "What If' questions to I) understand the reason and thought process behind their partners' actions: 2) explore and analyze the project by pinpointing the problem: and 3) propose and evaluate ideas or alternative solutions. In addition. we found dialogue labeled 'Social'. 'Question - other', 'Directed at Agent', and 'Confusion/Help Seeking' shows similar underlying patterns to higher-order questions, Our findings provide insight into the different scenarios driving students' higher-order questions and inform the design of adaptive systems to deliver personalized feedback based on students' questions.
Is Internal State Feedback in an E-Learning Environment Acceptable to People?
Authors: ASHIDA Atsushi , KAWAMURA Ryosuke , SHIRAI Shizuka , TAKEMURA Noriko , ALIZADEH Mehrasa , HAYASHI Hideaki , NAGAHARA Hajime
Published: January 2025

In on-demand e-learning environments, the lack of direct intervention can lead to a decline in learners' engagement. To address this issue, systems that estimate the learners' attitudes and provide feedback have been proposed. However, the acceptability of such systems has not been sufficiently researched. In this study, we investigated the acceptability by people to an e-learning system with internal state feedback, for future personalized learning support. To this end, we developed a system that estimates and visualizes the learner's internal state in real-time. The system was exhibited in a public space for free use, and users' impressions were analyzed. To estimate the learners' internal state, we developed a machine-learning model that recognizes learners' alertness from facial videos. The system was deployed in an exhibition space, and 131 responses were collected. These responses were coded and analyzed using a co-occurrence network. The result indicated that learners tend to dislike the system due to feelings of being observed by supervisors. In contrast, instructors expressed favorable options toward the introduction of the system.
The Effect of Feature Reliability on the Generalization of Machine Learning Models in Educational Data
Authors: ZHANG Yingbin
Published: January 2025

Reliability quantifies the extent of measurement errors in the observed feature scores and is an important quality indicator of measurements in educational research. However, the effect of feature reliability is underexplored in educational studies that use machine learning techniques. Understanding this effect is critical because the most of common features in education are contaminated by measurement errors. Recent research has revealed that the low reliability of features damages the prediction accuracy of machine learning models. The current study proposes that feature reliability also influences the generalization of machine learning models. This paper provides mathematical proof for the notion and further supports it via analyses on two empirical educational datasets. The results of data analyses also indicated that the effect of feature reliability on model generalization was moderated by the model complexity but not related to the model accuracy. Approaches to mitigate the impact of feature reliability are discussed.
Scaffolding Students' Ill-Structured Problem Solving via LLM — Multi-Armed Bandit Problem as a Case
Authors: LIU Jiayi , JIANG Bo
Published: January 2025

In this work, we explore the ability of LLMs to automatically generate hints for learners, taking the multi-armed bandit problem as a case. The ill-structured problem-solving process is divided into four stages: problem representation, solution generation, solution evaluation and adjustment, and final solution decision. We propose a prompt framework to fine-tune LLM based on four problem-solving stages and offer cognitive and metacognitive scaffolds at each stage. A preliminary study is conducted to analyze students' questioning tendencies and the quality of LLM-generated scaffolds. The results found that scaffolds generated by LLM were generally satisfactory, and effectively assisted learners in task analysis, domain knowledge supplementation, and solution iterations.
MESHing Minds: Bridging the Gap Between Creativity and IoT Programming Through Collaborative Mixed Reality
Authors: SAKABE Yusuke , AYEDOUN Emmanuel , TOKUMARU Masataka
Published: January 2025

Fostering creativity in programming tasks is a challenging endeavor, especially when working alone. Traditional programming environments often lack support for stimulating creative thinking and idea generation. This paper presents an interactive augmented reality (AR) system that aims to enhance creativity in Internet of Things (IoT) programming tasks. The proposed system leverages Interactive Evolutionary Computation (IEC) and AR technologies to facilitate the collaborative exploration and evolution of IoT device programs (MESH programs). Users can create, evaluate, and iteratively refine MESH programs through an immersive AR interface, while being inspired by the system's suggestions and other users' creations. The system employs a genetic algorithm to evolve MESH programs based on user evaluations, and utilizes natural language processing to generate program descriptions that can trigger new ideas. A user study (n=16) was conducted to evaluate the system's effectiveness in stimulating creativity and promoting collaboration. Quantitative analysis revealed a significant increase in idea generation over time and a greater impact on inspiration for novice programmers. Qualitative findings highlighted the system's ability to foster a creative and collaborative environment. The insights gained from this study inform the design of future tools and experiences that support creative thinking and collaboration in the IoT domain.
Online Making-Based Learning at Scale: Towards Equity in STEM Learning
Authors: GAUTAM Deeksha , KOTHIYAL Aditi , SHEORAN Rashmi , GARG Neha , IYER Adithi , BHAKUNI Ashutosh , THAKKAR Jay , KRISHNAN Jyothi , JAIN Manish
Published: January 2025

Making, grounded in theories of constructionism, offers learners the opportunity to construct their own knowledge through constructing personally meaningful artifacts, thus making them interested and committed to the process of their own learning. However, making-based learning is challenging to implement owing to the limitations of materials and well-qualified teachers. Online learning is a way for marginalized learners, who often do not have access to quality educational resources such as well-qualified teachers and learning materials, to access well-qualified teachers. With the growth of synchronous e-learning, learners now have opportunities to interact with their teachers and obtain immediate feedback, a process known to be productive for learning. In this paper, we report on a large-scale making-based online intervention whose design leverages the potential of online learning and cheap, easily accessible materials to create a science, technology, engineering and math (STEM) learning pathway for girls from marginalized communities by engaging them in STEM practices. Using evidence from observations and interviews we evaluate the effectiveness of the intervention in creating these learning pathways. We find that while the intervention increases learner interest in STEM practices, thus initiating a pathway to deepening participation, the language used in the intervention, technology, material and teacher factors can become barriers that have the potential to constrain this pathway and further marginalize the students. We discuss implications and potential solutions to these challenges.
Combining Multimodal Analyses of Students' Emotional and Cognitive States to Understand Their Learning Behaviors
Authors: S Ashwin T , SNYDER Caitlin , AKPANOKO Celestine E. , P Srigowri M , BISWAS Gautam
Published: January 2025

The incorporation of technology into primary and secondary education has facilitated the creation of curricula that utilize computational tools for problem-solving. In Open-Ended Learning Environments (OELEs), students participate in learning-by- modeling activities that enhance their understanding of (Science, technology, engineering, and mathematics) STEM and computational concepts. This research presents an innovative multimodal emotion recognition approach that analyzes facial expressions and speech data to identify pertinent learning-centered emotions, such as engagement, delight, confusion, frustration, and boredom. Utilizing sophisticated machine learning algorithms, including High-Speed Face Emotion Recognition (HSEmotion) model for visual data and wav2vec 2.0 for auditory data, our method is refined with a modality verification step and a fusion layer for accurate emotion classification. The multimodal technique significantly increases emotion detection accuracy, with an overall accuracy of 87%, and an Fl -score of 84%. The study also correlates these emotions with model building strategies in collaborative settings, with statistical analyses indicating distinct emotional patterns associated with effective and ineffective strategy use for tasks model construction and debugging tasks. These findings underscore the role of adaptive learning environments in fostering students' emotional and cognitive development.
Progressive Behavior Patterns of Online Discussion at Different Circle of Self-Regulated Learning
Authors: HUANG Shih-Hua , SHIAU De-Yu , FANG Yung-Sian , HSU Ting-Chia
Published: January 2025

This study examines the progressive behavior patterns of learners in online asynchronous discussions during different phases of self-regulated learning, using the Bookroll platform. Learners engaged in self-regulated activities, such as previewing videos at home and participating in online discussions, over a three-month period. The activity logs were divided into three phases, with roles of speakers and respondents coded for analysis. The cyclic behavior analysis revealed significant correlations and differences in discussion behaviors. In the first two phases, responders played a key role in guiding discussions, providing analyses, and asking questions, which promoted critical thinking. In the third phase, positive reinforcement and additional explanations helped redirect discussions when topics deviated. The study highlights the importance of questions and positive reinforcement from instructors to motivate learners, maintain discussion depth, and enhance engagement, thereby promoting effective learning.
Empowering Educational Researchers with a Privacy-Centric Data Platform: Design, Implementation, and Implications
Authors: WIJERATHNE Isanka , FLANAGAN Brendan , OGATA Hiroaki
Published: January 2025

The Educational Research Data Platform (EREDA) developed at Kyoto University addresses the challenges of managing and analyzing educational data while prioritizing privacy and security. EREDA seamlessly integrates with the existing Learning and Evidence Analytics Framework (LEAF) and offers advanced data management and analysis capabilities, including a robust Data Integrity Checker (DIC) tool and backfilling. By employing real-time data streaming, robust anonymization techniques, and a multi-tenancy design, EREDA empowers researchers to conduct secure and efficient educational research. The platform also features collaborative tools that enhance knowledge sharing and accelerate insight generation. As EREDA continues to evolve, its potential to drive data-driven decision-making in educational institutions and influence educational policies is significant. Future developments will focus on scaling the platform to reach a broader user base and enhancing its functionality to better support researchers.
Linking Real-World Experiences with Course Contents: A Text Mining Approach Toward Effective “There and Back Again”
Authors: ISHIHARA Manabu , HORIKOSHI Izumi , OGATA Hiroaki
Published: January 2025

In higher education, teachers sometimes urge students to apply what they have learned during class to real-life situations. However, interweaving real-world events with class activities, or the There and Back Again process, entails difficulty in relating dynamic experiences to the course contents. This study attempted to link both sides using text mining techniques on course data from a Japanese university. We extracted key phrases from four weekly assignments featuring students' real-world explorations. Then we measured the semantic similarity between each key phrase and each course content and linked the pairs with high similarity. For the linked pairs, we conducted data analyses. We also held a semi-structured interview with a course teacher regarding the interpretability of visualized data and its practical use. Consequently, we confirmed: 1) the links between the course contents and students' key phrases appeared differently in the weekly assignments, 2) notable links between specific course contents and key phrases were identified, and 3) the visualized data contained valuable insights for the teacher, but more fine-grained linking and integrated presentations were required. Despite several limitations, the results support the potential utilization of this approach for effective data-enhanced experiential learning.
Using Educational VR Systems to Promote Inquiry-Based Learning in Natural Science
Authors: TSAI Shu-Ying , CHEN Zhi-Hong , WENG Min-Hsuan
Published: January 2025

The study aims to investigate whether educational VR can enhance inquiry- based learning (IBL) in natural science for primary students. Researchers integrated VR to a marine education curriculum with IBL theory in a quasi-experimental study to analyze students' learning outcomes and motivation. The results demonstrated that educational VR significantly improved students' learning outcomes, enhanced their motivation, and effectively developed their critical thinking and problem-solving skills. This study underscored the value and impact of educational VR in inquiry-based learning.
Data-Driven Peer Recommendation and Its Applications in Extracurricular Learning
Authors: JIANG Peixuan , LIANG Changhao , OGATA Hiroaki
Published: January 2025

This paper introduces a system designed to enhance extracurricular learning by recommending suitable peer helpers. The system integrates educational big data of knowledge and learner models to optimize peer learning opportunities with learning analytics. Utilizing a graph-based recommendation algorithm, it incorporates three distinct indicators to dynamically match learners with suitable peers based on specific learning contexts and needs. A significant feature of the system is its capability to visualize the knowledge and proficiency levels of potential helpers, thereby empowering learners to make well-informed decisions with less bias. The system's adaptability also permits educators to tailor it to meet diverse educational goals. We are conducting an experiment with this system during a university's paper reading course to test its usability. The system aims to reduce the burden on teachers and minimize the time students spend seeking help outside of class.
Designing Interactive Mathematical Teaching Tools for Tablet-Based Learning: Enhancing Student Engagement and Tactile Exploration
Authors: LEE Loong-Chuan , LIN Chia-Ying , TAN Yu-Han , LIU Kuo-Yu
Published: January 2025

The rapid advancement of digital technology has transformed mathematicseducation. This paper explores tablet-based tools using constructivist theory toenhance engagement and tactile exploration. A primary school case study confirmedtheir effectiveness in improving learning outcomes. The integration of Unity'sGeometric Drawing Application with Moodle LMS offers a comprehensive educationalexperience. The paper emphasizes the need for further research, technologicalimprovements, and cost-effective solutions to make education technology moreaccessible.
FLOU: Evaluating the Intrinsic Motivation of Learners in Gamifying Academic Programs Through a Gamified Mobile Application
Authors: AGRAVANTE Marl Vincent , FERNANDEZ Jeru Kian , PEREZ Ma. Louisa , MARTINEZ Joshua
Published: January 2025

Learning is deeply influenced by motivational factors, and gamification has emerged as a tool to enhance student engagement by incorporating game elements into educational settings. Despite initial positive responses, sustaining long-term intrinsic motivation remains a challenge. This research investigates the relationship between intrinsic motivation and gamified learning, employing Self-Determination Theory to guide the analysis and design construct. It aims to balance intrinsic and extrinsic motivators in designing gamified educational platforms. The study evaluates the intrinsic motivation of students using a gamified platform called Flou. Findings show that user motivation did not necessarily lead to higher levels of intrinsic motivation or engagement compared to those who did not use the application. Moreover, the implored user-centric gamified design on Intrinsic Motivators had little to no interactions among the user—with which only elements from Competence have found to have most engagements from the user, mainly attaining badges. Recommendations are made for designing balanced gamified educational experiences. The study offers insights into designing gamified platforms that enhance students' intrinsic motivation and engagement while promoting meaningful educational outcomes. The findings of the study are used to formulate recommendations towards the design of a balanced gamification to be used in an educational context. This study aims to contribute to the evolving field of gamification in education by addressing the challenge of sustaining students' motivation and promoting self-directed learning within gamified platforms.
Designing an Educational Game for Facilitating Development of Media and Information Literacy
Authors: XIE Jun , LI Xiang , HASEGAWA Kotomi , LIU Zhichun , REICHERT Frank
Published: January 2025

This study describes the development and formative evaluation of a board game intended to facilitate players' development of awareness, knowledge and strategies related to media and information literacy in the post-truth era. Preliminary data were obtained from one gameplay session with nine players, and we analyzed how they understood and interacted with news issues in a simulated post-truth context. The results of qualitative analysis reveal the strengths and weaknesses of current design in terms of whether expected game experience and learning experience were achieved. The findings contribute to further revision on game design and unlock the educational potentials for adopting a game-based approach to promote media and information literacy.
Exploring Cognitive Engagement in AI-Driven Adaptive Psychomotor Sport Training
Authors: PORTAZ Miguel , MAJUMDAR Rwitajit , SANTOS Olga
Published: January 2025

This paper explores the dynamics of learning interactions between practitioners (those learning skills for real-world activities, sports trainee), and facilitators (those guiding the learning process, sports coach), with a focus on cognitive engagement in adaptive psychomotor learning contexts. Furthermore, this paper examines how to establish an appropriate environment for replicating tangible activities, such as creating optimal conditions for learning how to move in sport scenarios. In particular, we explore how to personalize psychomotor learning approaches through Learning Management Systems (LMS) where the personalization of the learning of motor skills is driven by the Sensing, Modeling, Design and Delivery (SMDD) process model that is based on Artificial Intelligence (A1) support, and the optimization of the learning workflow is managed by the Learning Analytics' enhanced Reflective Task (LA-ReflecT) platform integrated in Moodle LMS.
Design and Assessment of a Mobile Cloud Learning Platform for the Classroom: Examining the Efficiency of Blended Learning in Post-COVID Science Education
Authors: VILLANUEVA Joselito Christian Paulus , VILLAMIN John Lorence , TUMOLVA Joshua
Published: January 2025

The COVID-19 pandemic has brought forth numerous educational obstacles but has also created opportunities for progress and innovation. In the aftermath of the pandemic, education is expected to place greater emphasis on technology, and one promising solution in this regard is the utilization of mobile cloud learning technologies. These technologies offer various advantages, including flexibility, customization, and cost-effectiveness, revolutionizing the leaming process. This paper details the creation and advancement of a self-contained mobile learning platform designed for teaching science by integrating mobile cloud learning technology. The objective was to assess the effectiveness of this blended approach, which combines traditional teaching methods with technology. The evaluation encompassed lesson delivery, organization, classroom atmosphere, enrichment, and accessibility. The results demonstrated that the blended approach complemented conventional teaching techniques. The instant feedback provided by the proved beneficial in monitoring students' progress in real-time and intervening promptly when necessary. However, the study highlights the importance of addressing limitations and challenges in implementing this approach to fully maximize its Valuable insights are provided regarding the key factors to consider when designing and implementing blended learning in the contributing to the ongoing discourse surrounding the future of education in a post-COVID world.
Design and Development of a Stepwise Learning Environment for Problem Posing of Arithmetic Word Problem
Authors: HAYASHI Yusuke , YAMAMOTO Nagito , SHIMAKAWA Susumu , HIRASHIMA Tsukasa
Published: January 2025

In this paper, we focus on learning through problem-posing in arithmetic word problems and propose an environment for stepwise learning of problem-posing. As a foundation for stepwise learning, we have summarized the relationship between problem-posing tasks as a problem-posing task graph by setting difficulty levels based on the of conditions that must be considered during problem-posing. This is based on a domain that summarizes the structural conditions necessary for arithmetic word problems to be valid. Based on this, we designed and developed a stepwise learning environment called Monsakun Step. To verify its effectiveness, we conducted an experiment with university students. The results suggest that using Monsakun Step may be particularly effective for learners with a low structural understanding of arithmetic word problems.
Driving Informed EdTech Quality Decisionmaking: A Research-Practice Partnership-Based Solution for Diverse Stakeholders' Needs
Authors: ISHIKA Ishika , PHILIP Angelina Susan , VASUDEVAN Sheeja , MURTHY Sahana
Published: January 2025

In the educational technology (EdTech) ecosystem, stakeholders such as government decision-makers, entrepreneurs, parents and teachers face challenges in making informed decisions about the quality of EdTech products that meet their varied needs. While numerous frameworks exist that address diverse stakeholders, there is a lack of customizable frameworks that cater to each of the stakeholders' requirements, especially in lower-middle-income countries. This paper presents the EdTech Tulna initiative, a Research-Practice Partnership (RPP) aimed at building a shared understanding of what constitutes 'good' quality EdTech. This partnership between the research group, non-profit organization and diverse stakeholders presents a unique solution for varied needs and purposes. An analysis of the EdTech Tulna initiative's key offering is provided, which is the robust Tulna framework that supports stakeholders in making informed decisions about the quality of EdTech. The paper examines the design of the Tulna framework and presents case studies on how the framework has been customized to support diverse stakeholders' EdTech quality decision-making. This paper contributes to understanding an RPP's dynamics. It also promotes the discourse on the usefulness of research-based frameworks to drive EdTech Quality decision-making for diverse stakeholders' needs.
Integrating Virtual Environment in Teaching Courses
Authors: CHEN Chiu-Jung , LIU Pei-Lin
Published: January 2025

In recent years, the integration of virtual reality (VR) technology into educational environments has gained significant attention, particularly within natural science courses. This paper explores the implementation of VR interactive experiments as a means to enhance inquiry-based learning and foster critical thinking skills among students. By immersing students in realistic and interactive scientific scenarios, VR provides a dynamic platform for exploring complex concepts and phenomena that are often challenging to demonstrate in traditional classroom settings. The study underscores the pedagogical benefits of VR, particularly its role in fostering critical thinking skills, increasing student engagement, and improving understanding Of abstract concepts. Additionally, it discusses practical considerations for incorporating VR into natural science curricula and textbooks, addressing potential challenges such as cost, accessibility and teacher training. Through a comprehensive review of existing literature and case studies, this paper aims to provide educators with insights and strategies for effectively integrating VR technology to create an enriched and interactive learning experience in natural science education.
Investigating the Impact of Cooperative Group Learning on Blended Teaching and Learning Outcomes: A Case Study of Sixth-Grade Students in an Elementary School
Authors: MO De Jun , TANG Joni Tzuchen
Published: January 2025

Taiwan's education landscape has undergone profound changes in the aftermath of the COVID-19 pandemic. Educators, students, and campus environments have all adapted to digital learning, facilitating a smoother transition to blended learning in the post-pandemic era. This study utilizes spatial production theory, blended teaching methodologies, and cooperative learning approaches to investigate the impact of collaborative learning on the efficacy of blended teaching. Findings indicate that elementary school students encounter challenges transforming digital materials into topic discussions, hindering peer discussion and interaction in cooperative learning settings. Consequently, the learning outcomes slightly lag those of the control group engaged in individual learning. However, the overall performance tends to concentration and improvement, as evidenced by the standard deviation.
Investigating Students' Online Learning Perception Through the Lens of Constructivism
Authors: TALANDRON-FELIPE May Marie P. , BONIFACIO Kent Levi A. , AYUNAR Gladys S.
Published: January 2025

This paper explores students' perception and experience with an online Learning Management System (LMS) and its relationship to the areas that are crucial for a constructivist learning environment. We surveyed 526 college students from a public university in the Philippines to look at their extent, confidence, and satisfaction of using LMS. We also used the Constructivist On-Line Learning Environment Survey (COLLES) to measure the students' preferred and actual experience in terms of the LMS' role in professional relevance, reflective thinking, interactivity, cognitive demand, affective support, and interpretation of meaning. Majority of the students have experience with various LMS and have been using online learning platforms for more than two years. Results showed that students' satisfaction and confidence in using the LMS have a large significant positive relationship. However, a significant difference was found when their preferred experience and actual experience were compared for all the statements of the six COLLES dimensions. This indication that the students' expectations on these aspects were not met during their actual experience is a call to action to both administrators and teachers to ensure that the use of online learning platforms do not hinder the students to actively construct their own knowledge and understanding through experiences and interactions.
Investigation of Skills Training System Using TF-IDF for the Plasterer's Skeletal Data
Authors: TANAKA Ryota , GOTODA Naka , SAERON Lee , KANDA Ryo , HUNABIKI Ayaka , KANISAWA Hirotake , KANDA Kanae , TAKAI Yuka , HAYASHI Toshihiro
Published: January 2025

Artisans and athletes have the tacit knowledge, such as skills and tips that their bodies have learnt. These skills usually require a long apprenticeship. We thought the TF-IDF could be used to visualize tendency and frequency of mistakes made by beginners and investigated whether the TF-IDF could be used from data on past Sakan work.
How AI Supports Returning Adult Learners in a Developing Economy: Enhancing Academic Writing Through Self-Determination Theory
Authors: MARTINEZ Mary Rose , EBARDO Ryan
Published: January 2025

This study examines the integration of artificial intelligence (AI), specifically ChatGPT, in enhancing the educational experiences of returning adult learners in a developing economy through the lens of Self-Determination Theory (SDT). The research aims to understand how AI tools can support the unique needs of non- traditional students by fostering autonomy, competence, and relatedness, critical components of SDT. Utilizing a qualitative inquiry approach, the study involved in-depth, semi-structured interviews with 11 returning adult learners who have adopted ChatGPT for academic writing. The participants, non-traditional students typically over 25, provided insights into their experiences with AI in their learning processes. The thematic analysis of the data revealed three key themes: Learning Partner, Writing Proficiency, and Academic Collaboration. As a Learning Partner, ChatGPT was found to facilitate idea generation, enhance writing tasks, and support independent learning, promoting learner autonomy. Regarding Writing Proficiency, AI tools contributed to expanding vocabulary, improving writing clarity, and boosting confidence, aligning with the competence component of SDT. The theme of Academic Collaboration highlighted the role of peer influence and academic support in adopting AI tools, fostering a collaborative and supportive learning environment, which addresses the relatedness component of SDT. The findings suggest that AI tools like ChatGPT have significant potential to improve the educational experiences of returning adult learners by addressing their diverse needs and motivations. The study recommends the integration of AI into academic curricula, supported by policies and training, to maximize its benefits for non-traditional students.
Predicting Emotional Impact on Peer Review, Peer Assessment, and Self Assessments Using Deep Learning and NLP in STEM Education
Authors: MAH Pascal Muam
Published: January 2025

Digitalization has transformed academic environments with an increased volume of scientific articles, projects, reports, and workplace events overload. Applications like NLP, ML, DL, AI, and Cloud computing have ushered in more tools for researchers to automate scientific tasks which has led to a skyrocket in duty overlord and pressure on peer review. Due to huge task overloads, emotional expressions on academic assessments, have outweighed factual justifications consistency. This study highlights the present and future changes associated with academic assessment work overload and how this impacts future scientific lifecycles. Aim: The study investigated the impact of the increasing pressure and burden on academic assessment overload, academic assessment feedback, and increased emotional sentiments on peer reviews. The study applied DL and NLP to investigate the impact of emotional sentiments on academic assessments. A total of 90 reviews and feedback from conferences, journals, and patent comments were utilized to predict 4 years' future sentiment level in academic evaluation. Based on the selected reviewers' comments, our model with an accuracy of 72% predicts a fall in reviewers' emotional sentiments throughout the next four years. The study concluded that Peer Review, Peer Assessment, and Self-Assessment as integral parts of AI-driven sustainable education, are fast integrating with technological evolution to better serve the interest of scientific communities.
Exploring the Impact of Digital Divide on the Academic Performance of STEM Students in Hybrid Modality
Authors: TALANDRON-FELIPE May Marie P. , INTAO Jundy V.
Published: January 2025

This paper investigates the digital divide among undergraduate students enrolled in STEM programs at a satellite campus of a public university. A survey was conducted to collect data on access to technology, internet connectivity, socioeconomic status, and the use of digital educational materials. The results show that more than half of the respondents are from households classified as 'poor,' reflecting disparities in technology ownership and access. While most students own a smartphone, less than half have their own tablet or computer, and the majority rely on mobile data for internet connection. Using k-means clustering, three distinct student groups were identified, primarily distinguished by device ownership, frequency of computer use outside school, and proficiency in using digital tools such as email, social media, and office productivity software. The study found a slight but significant difference in academic performance (measured by general weighted average) between two clusters, corresponding to differences in access and digital proficiency. The findings highlight the need for targeted support programs, improved internet accessibility, and enhanced digital literacy training to address the digital divide and promote equitable educational outcomes in a hybrid learning environment.
Does Interactive Augmented Reality Enhance Primary Students' Geometric Understanding and Visual-Spatial Skills in Mathematics Learning?
Authors: ASSAWAPHUM Atcharaporn , PREMTHAISONG Sasivimol , CHAIPIDECH Pawat
Published: January 2025

Augmented reality (AR) in education has gained much attention as an innovation that promotes tangible visualization and can therefore be applied in various fields of education, especially in enhancing students' conceptual understanding and visual and spatial abilities in mathematics. Geometry often poses challenges due to its abstract nature, but AR offers interactive visualizations that make learning more engaging and accessible. This study used a quasi-experimental design on second grade forty-six students' understanding of geometric shapes. The experimental group had twenty-three students engaged in AR-enhanced learning activities, while the control group had twenty-three students who followed traditional teaching methods. Results showed that the AR group significantly improved in both geometric understanding and visual-spatial skills. These findings highlight the potential of AR to make early mathematics education more effective and engaging.
Exploring the Use of Short Video Social Media for Learning ESL in Indonesia
Authors: SAPUTRA Riska , JALILIY Tsaqufal , SETIANI Intan
Published: January 2025

This study investigates the use of TikTok as a social media platform for supporting English as a Second Language (ESL) learning in Indonesia, with a focus on IELTS exam preparation. Grounded in social learning theory and media literacy, the research highlights TikTok's potential to enhance learner engagement and motivation through its interactive features like duets and challenges. Utilizing a mixed-methods approach, the study captures the motivations, experiences, and outcomes of both learners and content creators. Findings suggest that while TikTok shows promise in improving listening, speaking, and vocabulary acquisition, its effectiveness in comprehensive exam preparation, particularly for writing and grammar, is limited. The study recommends the development of more structured educational content on TikTok and emphasizes the importance of media literacy in helping learners navigate the platform effectively. This research contributes to the understanding of how social learning and media literacy frameworks apply to informal language learning in digital environments.
Theory-Driven Design for the Development of a Student-Centered Error-Correction Online Learning System
Authors: YU Fu-Yun
Published: January 2025

Many benefits are associated with error-correction, but currently, the task is mostly done by teachers. Although student self-correction should help activate generative behavior and promote learning, most students are not accustomed to self-correction nor equipped with the needed knowledge and skills. Hence, the main goal of this work is to create a theory-driven student-centered error-correction learning system. In this paper, literature on error-correction to serve as the basis for the development of a generic error-correction framework is briefly reviewed. Additionally, four design principles to guide its development are described.
Understanding Collaborative Teacher Growth from the Lens of Digital Learning Agility: A Pathway to Educational Excellence
Authors: ABDULLAH Kamilah , MD KHAMBARI Mas Nida , WONG Su Luan , ZAKARIA Noor Syamilah , ABD RAHIM Nur Aira , MOSES Priscilla , MOHD ROSLI Nur Dania
Published: January 2025

This study explores collaborative teacher growth through the lens of Digital Learning Agility (DLA) and its impact on teaching practices and professional development. Using qualitative methods and thematic analysis, the research highlights how fostering collaboration among educators can enhance instructional approaches and student outcomes, ultimately creating a supportive and innovative educational environment.
Proposal for Simulation Environment to Support Understanding of Tactical Positioning
Authors: OHTSUKA Yuki , KOJIRI Tomko
Published: January 2025

To lead tactics to success in team sports, the player needs to judge whether they should apply the tactics based on the positional relationships of their allies, opponents, and other relevant factors. Players build up successful positional relationships based on the experience, i.e. to satisfy the positions of the allies and opponents of the success experience and exclude those of the failure experiences. However, novice players, due to lack of experience, do not have appropriate successful positional relationships. In order to acquire the successful positional relationships, two steps are necessary: to experience tactics with various positional relationships and to acquire the successful positional relationships from the experiential results. This paper focuses on supporting the first step and proposes a tactic simulation system for the given tactics and positional relationships.
Microlearning Strategy in ICT Education
Authors: TORII Kotaro
Published: January 2025

The purpose of this paper is to clarify how young people in developing countries can achieve their ICT (Information and Communication Technology) skills and get a job. This study focused on the system that covers from their ICT skill learning to job matching. In many countries and regions, there is still a noticeable lack of ICT educators as well as little demand for ICT engineers. Additionally, e-learning often requires significant tuition fees. Studying a one-off course will not lead directly to a job. On the other hand, when taking a comprehensive courseware course, the content is too overwhelming to start a career. Given this background, the following are desirable environments in ICT education. First, it is effective to break down the skills into smaller parts that match the needs of companies thusly supporting microlearning for both companies and young people. The next step is to map the skills that have been already achieved by layering the smaller parts, and then match applicants with job openings. The accuracy of skill improvement records will be ensured by blockchain. This will enable a system that allows for anonymous verification and search of each. Based on this strategy, it is expected that young people in developing countries will be able to acquire skills efficiently and quickly and be able to participate in the global software development sector.
Instructors' Perceptions and Use of Feedback Dashboard
Authors: LIN Feng , LIM Rebekah Wei Ying
Published: January 2025

Enhancing teaching quality has always been one of the core objectives of higher education institutions as it has a profound influence on students’ learning experiences. Feedback dashboard, utilizing data visualization and analytics, has emerged as a powerful tool to facilitate this process. It could provide instructors with insights into students’ learning experiences, empowering them to make data-driven decisions regarding their pedagogical practices. Despite the increasing interests in developing feedback dashboards, little is known about how they can be effectively used by instructors. This paper presents an ongoing research project that aims to understand how instructors perceive and use feedback dashboards.