bluuebunny/crossref_metadata_2025 huggingface dataset:
Review of the Literature on Question- Posing-based Self-Directed Learning
Authors: SADHUKHAN Sumitra , MISHRA Shitanshu , IYER Sridhar
Published: January 2025

Self-directed learning presents a promising approach to enable students to achieve self-reliance and cultivate greater ownership over their learning pursuits. In the current teaching-learning scenarios, the implementation of classroom-oriented self-directed learning (SDL) strategies does not achieve their desired goal. The primary reason may be that the teachers are not trained to implement these strategies. According to the literature, learners face difficulties in following different SDL strategies. Question posing (QP) serves as a tool that can help learners understand the concept, clear misconceptions, and collaborate with peers to construct their knowledge. We have analyzed existing papers on question-posing-based classroom- oriented self-directed learning strategies to find how question-posing may help students overcome their difficulties and find ownership in their learning. We find that QP-based teaching-learning approaches require well-designed activities that can help students elicit questions and with which students can navigate in achieving ownership of their learning. The paper concludes with the identification of a QP-based strategy that conforms to the essential set of requirements of self-directed learning.
A Preliminary Study on Knowledge Reconstruction Activity for Fostering Cognitive Presence in Online Discussion
Authors: HASANI Lintang Matahari , JUNUS Kasiyah , SADITA Lia , HIRASHIMA Tsukasa , HAYASHI Yusuke
Published: January 2025

Asynchronous online discussion activity has become a popular form of online collaborative learning (OCL) and has been widely adopted in higher education. In the discussion, learners are expected to effectively co-construct knowledge together through engaging in problem solving discourse. Such an ability to construct and confirm understanding while working together to solve a problem is defined as cognitive presence, which plays a central role in the success of OCL. However, despite various facilitation strategies suggested in prior studies, it is challenging to ensure that learners show sufficient cognitive presence. Providing a preparatory activity that increases engagement with learning materials before participating in the discussion is another strategy that could foster cognitive presence. This study aims to investigate the effectiveness of providing two kinds of knowledge reconstruction activities, namely kit- build concept mapping (KBCM) and summary writing, as a discussion preparatory activity. The results show that using KBCM for reconstructing basic knowledge related to discussion topic has a potential to be better for fostering cognitive presence compared to summary writing. The KBCM activity provides opportunities to engage more with basic knowledge related to the discussion topic, to confirm understanding, and to familiarize themselves with common terms or keywords used in the discussion through reconstructing a teacher-created map. Some directions for future studies are discussed.
Adding Interactive Mode to Active Video Watching
Authors: BOJNORDI Ehsan , MITROVIC Antonija , GALSTER Matthias , MALINEN Sanna , HOLLAND Jay
Published: January 2025

Presentation skills are crucial for tertiary students and graduates but are difficult to teach. We augmented active video watching (AVW) approach with the possibility of interactions among students, and conducted an experiment with AVW- Space, an online platform which supports video-based learning. The participants watched and commented on videos first. In the second phase, the participants reviewed, rated, and responded to their peers’ comments. We found that students who interacted with other students and responded to their comments increased their conceptual understanding of presentation skills.
Interaction Patterns between Learners and AI Tools for English Writing
Authors: XIE Yun Shu , JANG Jin Ho , KIM Su Yeon , CHO Young Hoan
Published: January 2025

The advancement of artificial intelligence (AI) has drawn educators' attention to its educational potential. However, the efficacy of AI depends on learners' effective interaction, avoiding either neglect or excessive dependence. Despite the significance of learner-AI interaction, research on interaction patterns remains limited. This study investigates how EFL (English as a foreign language) learners interact with an AI tool for English writing and explores the effects of different interaction patterns on their writing performance. Through an experiment involving 29 EFL undergraduates, three distinct interaction patterns emerged, exhibiting significant differences in their engagement with the AI tool. The comparisons of the three clusters indicate that different AI interaction patterns lead to varied interaction approaches, and not all learners equally benefit from AI's potential. In order to promote productive learner-AI interaction in educational environments, instructors should provide personalized support and feedback.
Embracing Synchronicity in Distance Education: Unraveling the Paradox
Authors: AOKI Kumiko
Published: January 2025

In this paper, I describe the challenges of introducing synchronicity in distance education in which the flexibility for students to learn anywhere and anytime has been most valued. With the wide diffusion of web conferencing systems such as Zoom, Microsoft Teams and Google Meet during the COVID-19 pandemic, it has become natural not only for traditional on-campus institutions, but also for distance education institutions to utilize synchronous communication tools for instructional delivery. There are advantages to utilize such tools while there are certain disadvantages especially for distance education institutions. This paper presents the results of synchronous web class trials at the Open University of Japan.
Influence of Robot Roles on Self-Review
Authors: SADA Shunsuke , KASHIHARA Akihiro
Published: January 2025

In recent years, a considerable number of studies have been made on learning with social robots as partner for learners. In these studies, robots are often assigned their roles in advance such as tutor, peer, or learners themselves. On the other hand, the roles assigned to the robots could give learners a cognitive bias to their own thoughts, emotions, attitudes, interaction ways, etc., related to learning. However, such role influence has not been sufficiently explored so far. In this work, we investigate this in the context where learners self-review their own presentation with a social robot. We have conducted a case study with the presentation robot we developed in our previous work. The robot reproduced learners’ presentation with two roles that were their peer and themselves. The results suggest that the role of robot as peer brings about more effective self-review in regard to reducing uncomfortableness in self-review and promoting awareness of points to be improved in presentation than the role as learners themselves.
Posthumanizing Creativity and Material Histories
Authors: V Alekh , DASGUPTA Chandan
Published: January 2025

With this article, we attempt to shift the conceptualization of creativity from a human centered perspective to a wider perspective of posthumanism. We use the scenario of collaborative making context, and illustrate how material history evolved rooting on the posthumanist standpoint. We see that the humans and nonhuman entities are enmeshed in creative acts where agency is spread across the various actors leading to learning opportunities and innovative outcomes.
ICCE 2023 Learning Outcomes of Computer Programming and Information Technology - Integrated Courses for Non-Computer Science Majors: Case Study of a Public Research University in Taiwan
Authors: HSU Che-Yu , HWANG Feng-Nan , CHEN Tseng-Yi , CHANG Chia-Hui
Published: January 2025

This study investigates non-CS major students' performance in computer programming and Information Technology-integrated (IT I) courses at a Taiwanese research university. Non-CS students struggle in introductory programming due to syntax and logical thinking limitations, resulting in lower grades compared to advanced programming. Similarly, ITI course grades are lower due to subject-specific demands. Gender and entry channels impact outcomes, with females excelling in informal learning. Favorable results are seen in individual applications and Multi-star Projects. Challenges include different learning paces and cultural adjustments. Regression analysis shows Introduction to Computer Programming (ICP), Advanced Computer Programming (ACP) and gender significantly affect ITI performance, explaining 24% of its variance. Recommendations include diverse teaching methods, problem-solving guidance, practical programming, collaboration, and project participation to enhance skills.
What's Going on Behind the Scenes? Peer Assessment as a Strategy for Enhancing Students' Commitment and Learning Motivation in Working Collaboratively
Authors: ABD RAHIM Nur Aira , GHAZALI Norliza , PONRAHONO Zakiah , SYED ABDULLAH Sharifah Intan Sharina , MOHAMAD Fadzilah , MOHD HAJARAIH Syahidatul Khafizah
Published: January 2025

Peer assessment (PA) refers to any arrangement in which learners consider the amount, level, value, worth, quality or success of the learning outcomes of their peers. In simpler words, peer assessment is a form of assessment which allows the learners to provide grades/marks and/or feedback to their peers by assessing their peers' work and contribution. This paper conceptually explains about peer assessment as a strategy to increase students' commitment and motivation when working collaboratively. The first part of this paper discusses about the nature of collaborative in higher education setting. Essentially, peer assessment can be the key to uncovering what happened behind the scenes during the collaborative learning process, i.e. during group assignment or group project. In this research, an exploratory case study design was conducted among higher education instructors at a public university in Malaysia. This research seeks to explore the strategies and tools used by higher education instructors to conduct peer assessment in their teaching, with a focus on innovative approaches and digital tools used by these instructors in multidisciplinary educational contexts.
Front Matter: The 31st International Conference on Computers in Education
Authors: SHIH Ju-Ling , KASHIHARA Akihiro , CHEN Weiqin , OGATA Hiroaki
Published: January 2025

This PDF file contains the front matter associated with ICCE Proceedings including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.
Method for Estimating Learning Strategies from Tools Using Bayesian Network
Authors: KUWAJIMA Kento , ASHIDA Atsushi , KOJIRI Tomoko
Published: January 2025

With the recent development of the robot technology, teacher robots will be introduced into educational settings to instruct learners. Such teacher robots, like human teachers, will be required not only to teach knowledge to learners, but also to monitor their learning process and motivate them. Positive learning attitudes can be ascertained by changing the learning strategy. The fact that learners change their learning strategies may indicate that they are making efforts to find an appropriate strategy. The learning strategies used by learners can be inferred from the tools they use to learn. Therefore, we propose a method to estimate learning strategies using Bayesian networks when learners change them.
Learning Support System to Understand Others Through Dramatic Script Reading and Its Evaluation
Authors: OKAMOTO Hanano , HAYASHI Yuki , SETA Kazuhisa
Published: January 2025

To form and maintain smooth interpersonal relationships in various situations in social life, the ability to appropriately understand the mental states of others, such as their intentions and feelings, is required. However, it is difficult to infer the unobservable mental states of others, and it is also difficult to learn from others how to perform inferring activities that are not externalized. In this study, we focus on “dramatic scripts” as a learning material that contributes to the training of the ability to understand others and propose a learning support system that aims to improve the ability to understand others and to cultivate an attitude of understanding others through inference activities about the emotions and conflicts of characters.
Reflection Support System with Audience Robots for Presentation Practice
Authors: KISHIMOTO Yuya , KOJIRI Tomoko
Published: January 2025

During a presentation, an effective presenter will modify his/her own presentation style by observing the audience's reaction. To hone this skill, we have developed an audience robot that reacts according to the presenter's presentation style. The objective of this study is to propose a system that supports self-reflection after presentation practice with an audience robot, To modify the presentation style, the presenter needs to understand how the audience's psychological state corresponds to each reaction and what presentation style the presenter should adopt to modify the audience's psychological state. In addition. he/she needs to utilize this knowledge at the appropriate time, Therefore. during reflection, the presenter should evaluate whether he/she has such knowledge and whether he/she can utilize it. This study constructs a system that visualizes the presentation data graphically to represent each evaluation item clearly for effective consideration.
UniSpLLM: An Integrated Approach for Enhancing Reasoning and Education with Large Language Models
Authors: ZHAO Hanyu , WU Yuzhuo , YU Yang , YU Xiaohua , CHEN Liangyu
Published: January 2025

Large Language Models (LLMs) show constrained performance when confronted with a set of mathematical problems spanning various knowledge concepts. Unlike natural language tasks, the understanding and solution strategies for math problems significantly vary, presenting a great challenge for LLMs to consistently generate precise solutions for different problem types. To address this limitation, we propose UniSpLLM(A Universal Template integrated with Specific methods using Large Language Models), a strategy devised to bolster LLMs' efficiency in solving problems enriched with varied knowledge concepts. UniSpLLM innovates by crafting a Universal Template, versatile enough to accommodate any problem type. Specifically, we design six Specific Methods that can be adapted to different problem types. UniSpLLM distinguishes itself from other prompt-based approaches, which typically cater to a singular problem type. By achieving an improvement of nearly 15% on the latest dataset TAL_SAQ6K_EN from AAA12024 and surpassing the GPT-4 baseline by almost 17% on the MMLU-Math dataset, UniSpLLM significantly elevates the utility of LLMs within educational fields. Our approach and results hold significant educational value, as they aid students in acquiring diverse thinking skills tailored to various problem types.
Enhancing Diversity in Difficulty-Controllable Question Generation for Reading Comprehension via Extended T5
Authors: GOTO Teruyoshi , TOMIKAWA Yuto , UTO Masaki
Published: January 2025

Recently, automatic generation of reading comprehension questions with controllable difficulty levels has attracted growing interest for educational purposes. The latest method for difficulty-controllable question generation employs a two-stage mechanism utilizing two independent large language models. Specifically, given a reading passage and a difficulty level as inputs, it first produces a reference answer using BERT and then generates a corresponding question using GPT-2. However, this two-stage approach has the limitation that the questions generated depend strongly on the reference answers produced beforehand, restricting the diversity of questions. To overcome this limitation, we propose an end-to-end method that enables the simultaneous generation of questions and reference answers by extending T5, a large language model with an encoder mechanism equivalent to BERT and a decoder mechanism equivalent to GPT-2. In our method, T5 is extended to generate answers from its encoder and questions from its decoder, with the encoder's output vector passed to the decoder. Experiments using a benchmark dataset demonstrate that our method significantly improves the diversity of both questions and answers compared with the conventional method while maintaining difficulty controllability.
Student Perceptions of Using Generative AI Chatbot in Learning Programming
Authors: KHOR Ean Teng , CHAN Leta , KOH Elizabeth , SEOW Peter
Published: January 2025

Interest in Generative Al (GenAl) chatbots has exploded across the education industry, subsequently expanding in sophistication and usage. However, students' perceptions on utilizing this technology ultimately determines how well these chatbots promote learning. Hence, this study examines the factors influencing how Singapore secondary school-aged computing students perceive using MyBotBuddy (MBB), a GenAl chatbot, to assist them with programming tasks. A thematic analysis determined that students' perceptions were influenced by reliability, utility, cognitive effort needed, satisfaction, and enjoyment. The study contributes to the literature on GenAl chatbots supporting secondary school programming students and may guide the development of such tools in secondary school classrooms more effectively.
Exploring Explainable Artificial Intelligence in Active Video Watching
Authors: LUMAPAS Raul Vincent , MITROVIC Antonija , GALSTER Matthias , MALINEN Sanna
Published: January 2025

Active Video Watching supports engagement through scalable interventions, such as notetaking in the form of comments. Machine Learning is used to categorize comments based on their quality to provide personalized feedback to students. In previous work on AVW-Space, an online portal for active video watching, a machine learning model was trained using data from several studies on presentation skills. In this paper, we explore the effectiveness in assessing the comment quality of this model in Face-to-Face Meeting Communication skills in comparison to a model trained specifically for this soft skill. We used Explainable Artificial Intelligence to identify and compare the important features of the models. Results show the need for comment quality assessment models to be specific to the soft skill in question and show major differences between their important features, highlighting the necessity to create a model specific to a particular soft skill.
Unveiling the Interplay of Students’ Epistemic Emotions and Knowledge Building Activities in Design Studios
Authors: LEE Alwyn Vwen Yen , TEO Chew Lee , ONG Aloysius , YUAN Katherine
Published: January 2025

Educational research may have established intricate connections between student achievements and emotions, but there remains a need to conduct more research on the crucial role of students' epistemic emotions during learning. The emergence of global knowledge societies has nudged researchers to delve deeper into the understanding of students' epistemic emotions within evolving learning environments, such as knowledge building environments that encourage complex learning and knowledge creation. This study addresses this gap via a naturalistic study of students' epistemic emotions in a student Knowledge Building Design Studio (sKBDS). We aim to illuminate the intersections between epistemic emotions and knowledge building activities, with findings to inform the design of more rigorous studies and designs to advance knowledge building practices. An Epistemic Emotion Survey (EES) was adapted for gathering students' epistemic emotions and to align with knowledge building activities in the sKBDS. A total of 11022 sets of epistemic emotion data from 73 primary and secondary school students were collected from two runs of the sKBDS, compiled into a single repository for descriptive analysis. Findings show that students experienced heightened curiosity, interest, excitement, and were generally happy to participate in activities at the sKBDS, while demonstrating relatively less anxiety, frustration, and confusion when undergoing knowledge building activities. Throughout the sKBDS, students also exhibited surprise at planned activities and what they have discovered and worked on. In addition, knowledge building activities also had varying effects on students' emotions, ranging from tiredness and hunger to occasional positive feelings. Overall, the findings from this study will be used for improving knowledge building practices and designs in future design studios, with implications for educators, students, and researchers.
Enhancing Social Learning in Active Video Watching
Authors: BOJNORDI Ehsan , MITROVIC Antonija , GALSTER Matthias , MALINEN Sanna , HOLLAND Jay , MOHAMMADHASSAN Negar
Published: January 2025

To learn effectively by watching videos, learners need to engage actively with video content. Writing comments on videos (also known as video annotation) is a common way of engagement in Active Video Watching (AVW). Reviewing comments on videos written by peers, as a form of social learning, has also been shown to increase learning. In this paper, we extended social learning in AVW by enabling learners to respond to comments written by their peers (rather than just reviewing peer comments) and replacing a categorical comment rating design with a numerable binary one. We investigated the impact of using such a form of comment reviewing on learning, engagement, and students' perceptions. The findings show that our intervention results in increased learning, engagement and student satisfaction compared to the situation when students could not respond to comments.
Rethinking Trust in Human-AI Collaboration in the Generative AI Era
Authors: LU Yijie , JIANG Bo
Published: January 2025

Trust has been thoroughly investigated in human-human collaboration. As large language models advance, human-Al collaboration is becoming the future trend. Generative Al can act as a collaborator. However, limited research dedicated to exploring trust in human-Al collaboration. The degree of trust is intricately connected to both the user's reliance on the system and the system's perceived usefulness. Based on a human- Al collaborative writing dataset, this work employed cluster analysis to explore collaborative patterns in the process of human-Al collaboration. The results show that trust is dynamic, two-sided, and vague element. Meanwhile, based on the changes in trust, human-Al collaboration can be categorized into three types: increasing, curvilinear, and decreasing.
Review of Different Assessment Methods Used by Online Inquiry-Based Learning Systems That Support Argumentation
Authors: JHA Nitesh Kumar , BHOWMIK Plaban Kumar , BHAGAT Kaushal Kumar
Published: January 2025

The study aims to provide a current synthesis of assessment methods in Online Inquiry-Based Learning (OIBL) systems that use argumentation as a pedagogy. Three databases were used, namely, Scopus, Web of Science, and ERIC, for data collection. The present review analyzed 73 studies from 2010 to 2023. A qualitative content analysis examined the assessment methods used in inquiry-based systems. Results showed that most studies used direct methods of assessment followed by indirect methods. Among the direct method, more studies used the analysis of artefacts as an assessment method compared to the Multiple Choice Questions (MCQ)/short answer test. Among analysis of artefacts, most studies analyzed log files/chat/multimedia posts as artefacts followed by written arguments and video/audio recordings of interactions. Also, regarding MCQ/short answer tests, a majority of studies used achievement and conceptual understanding tests to assess student performance. Future studies need to use embedded assessment tools in their platform to increase learning opportunities for students. Also, future studies should enable synchronous and asynchronous access for teachers to student activities for proper assessment.
BioAnalogica: SBF-Based Analogical Stories to Enhance Understanding of Complex Biological Processes
Authors: PAWAR Meera , VASUDEVAN Sheeja , MURTHY Sahana
Published: January 2025

Understanding complex systems is crucial, making it vital to strengthen high school students' grasp of complex biological processes. This study explores the design, development, and implementation of BioAnalogica, a Technology Enhanced Learning Environment comprising animated stories based on the Structure-Behaviour-Function (SBF) framework that use real-life analogies, like roof repair, to illustrate the human immune system's wound healing process. BioAnalogica was implemented with high school students as participants. Their understanding of wound healing was assessed through pre- and post-tests, interviews, and surveys. Findings show that students made improvements in understanding the mechanisms of wound healing, though their grasp of structures and functions did not change significantly. They responded positively to BioAnalogica, praising its clarity, connection to concepts, and engaging approach.
Analyzing Student Behavior in Viat-map: Steps and Time as Performance Indicators
Authors: ANDOKO Banni Satria , LESTARI Vivin Ayu , PRAMUDHITA Agung Nugroho , NURAINI Amalia , NISAK Inda Khoirun , HIRASHIMA Tsukasa
Published: January 2025

Number of steps and time duration needed while solving the problem can be considered as a representative of student's learning behavior and their effort of understanding. Learning Analytics is a process for monitoring students' thinking process and can become strong evidence to support teachers' objectives in class. Viat-map is an application that implements the Toulmin Argument method and reconstruction approach. It will assist students to think logically by following the teacher's logic, and it shows a positive contribution in the learning process. The reconstruction process used in Viat-map also offers immediate evaluation of student's mistakes. However, a challenge arises in the Viat-map's evaluation of the student's learning process, as the reconstruction process requires students to have the correct answer to complete the learning process. Having this way, new approaches in using student's behavior as learning process score (Viat-map score) are offered. This study involved 105 Students divided into 58 students from the previous research (2023) and 47 students to confirm the Viat-map score (2024). K-Means clustering was chosen for its ability to perform unsupervised clustering, ANOVA was used for comparing more than two groups, and Pearson Correlation was used to examine the relationship between two sets of data. The results suggest that the number of steps taken and the time spent in the learning process can be considered positive indicators of student behavior in the learning process.
An Embodied Projection Recognition System for Situated Learning to Enhance Learning Effectiveness and Self-Reflection Ability
Authors: LIU Hui-Ting , DING Zi-Ting , YANG Su-Hang , WU Jian-Yu , WANG Jen-Hang , CHAO Po-Yao , ZHUANG Yung-Yu , CHEN Gwo-Dong
Published: January 2025

In service-oriented disciplines such as Hospitality Management Education and Nursing Education, multimodal elements such as bodily movements and facial expressions play crucial roles in addition to learning through oral instruction and written materials. Current digital reality learning systems provide excellent spaces for situated learning and real-time assessment. However, they often lack an environment that simultaneously considers real-time assessments of physical actions and spatial awareness. This omission can prevent students from effectively applying their learned knowledge in real professional settings, thereby reducing the practicality and effectiveness of their learning. To address this issue, our study has developed a teaching assistance system aimed at enhancing learners' experiences through readily available technologies. We established a new learning environment and model that can be used in the classroom, incorporating the concepts of personas and spatial computation proposed by Apple Vision Pro to facilitate real-time assessment and scaffolded guidance in service-oriented learning. This model, which complements traditional learning methods, supports embodied cognition and situated learning, allowing users to interact simultaneously with the physical environment and digital reality. Students can engage in both language and embodied action exercises within this environment. Through the system's real-time evaluation and feedback, students can immediately reflect and adjust their behavior in a nearly real interaction setting, enhancing their practical experience and thus improving their ability to absorb and apply learned skills. Moreover, students' performances in the digital reality are displayed on a large screen in the classroom, allowing peers in the audience area to simultaneously observe each other's acts, thereby creating a theater-style learning environment. This transformation not only allows students to see their own and others' real-time performances but also shifts their role from mere participants to performers. This shift helps build a sense of responsibility and enhances their motivation to learn. This method was tested in the 'Hospitality Practices and Japanese' course at a university of technology, with results showing significant improvements in learning outcomes in practical courses that require physical and verbal interactions compared to traditional digital realities.
Designing Interaction Scenario for Alleviating Persistence in Learning Strategies
Authors: SASAKI So , KASHIHARA Akihiro
Published: January 2025

It is necessary for learners to properly use learning strategies according to learning phases/objectives, which improves the effectiveness and efficiency of learning. However, there are learners who persist in the use of a particular strategy even when they are taught a new appropriate strategy. In addition, they are not likely to emotionally apply the new strategy. To resolve this problem, it is necessary to alleviate their persistence. In this work, we have proposed a model of empathy, in which learners are expected to change the use of learning strategy through empathy for a peer learner who has the same experiences in persisting in the same strategy, overcoming the persistence, and making a success in the change of strategy. In this paper, we follow the model to design an interaction scenario with a social robot to alleviate learners' persistence, and demonstrate the robot interaction system that conducts the scenario. The results of the case study with the system suggest that the designed scenario allows learners to positively change their learning strategies.
Construction of a Japanese Language Learning Support System that Enables Word Accent Learning
Authors: KOGURE Satoru , TOMITA Kazuki , NOGUCHI Yasuhiro , YAMASHITA Koichi , KONISHI Tatsuhiro , KONDO Makoto
Published: January 2025

In second language learning, learners learn four skills: reading, writing, listening, and speaking. However, compared with the other three skills, speaking skills have rarely been studied in environments wherein they can be learned. Therefore, we proposed a method for recognizing Japanese word accents using the pitch average of the whole word and that of each mora as part of speaking skill learning. We demonstrated that this method outperforms the pitch drop detection method. Using the proposed accent recognition method, we embedded a function that enabled learners to learn the accents of target words into the feedback phase of an existing Japanese language learning support system. This allowed learners to speak the target words and receive feedback on whether their accents were correct.
Developing a Feedback Analytic Tool to Support Instructor Reflection
Authors: LIN Feng , LI Chenchen , LIM Rebekah Wei Ying , LEE Yew Haur
Published: January 2025

Gathering student feedback on teaching is an important way for instructors to learn about students' experiences and engage in reflective practices to improve their teaching. Such feedback usually includes numerical ratings and qualitative comments. While numerical patterns can be quickly discerned, analyzing and interpreting qualitative feedback can be time-consuming and challenging, especially in situations involving large classes or multiple courses. To help instructors effectively reflect on the qualitative feedback, we have developed an analytical tool to visualize this feedback. This paper outlines the methodologies and approaches we developed for creating the feedback analytics tool.
Peer Feedback Feature Analysis with Large Language Models: An Exploratory Study
Authors: LYU Qianru , LIN Zirou , CHEN Wenli
Published: January 2025

Abstract: Peer feedback is a pedagogical strategy for peer learning. Despite recent indications of Large Language Models (LLMs) ' potential for content analysis, there is limited empirical exploration of their application in supporting the peer feedback process. This study enhances the analytical approach to peer feedback activities by employing state-of-the-art LLMs for automated peer feedback feature detection. This research critically compares three models—GPT-3.5 Turbo, Gemini 1.0 Pro, and Claude 3 Sonnet— to evaluate their effectiveness in automated peer feedback feature detection. The study involved 69 engineering students from a Singapore university participating in peer feedback activities on the online platform Miro. A total of 535 peer feedback instances were collected and human-coded for eleven features, resulting in a dataset of 5,885 labeled samples. These features included various cognitive and affective dimensions, elaboration, and specificity. The results indicate that GPT-3.5 Turbo is the most effective model, offering the best combination of performance and cost-effectiveness. Gemini 1.0 Pro also presents a viable option with its higher throughput and larger context window, making it particularly suitable for educational contexts with smaller sample sizes. Conversely, Claude 3 Sonnet, despite its larger context window, is less competitive due to higher costs and lower performance, and its lack of support for training and fine-tuning with researchers' data weakens its learning capabilities. This research contributes to the fields of Al in education and peer feedback by exploring the use of LLMs for automated analysis. It highlights the feasibility of employing and fine-tuning existing LLMs to support pedagogical design and evaluations from a process-oriented perspective.
Development of Metacognitive Reflection Support System on Creative Discussion
Authors: SHIMIZU Toshimasa , HAYASHI Yuki , SETA Kazuhisa
Published: January 2025

Research meetings are critical forums for sharing and evolving ideas, where the depth of the discussion can significantly enhance the research content. Effective meetings require not just a recapitulation of the discussions but a thorough examination of the thoughts and decisions preceding the meeting. In this paper, we propose a support system that promotes metacognitive reflection by aligning pre-meeting preparations with post-discussion feedback, thus enhancing the overall research process and outcomes.
Program Learning Support System with Visualization Reflecting Teacher's Intent for Learner’s Code
Authors: KOBAYASHI Kenzo , KOGURE Satoru , NOGUCHI Yasuhiro , YAMAMOTO Raiya , YAMASHITA Koichi , KONISHI Tatsuhiro , ITOH Yukihiro
Published: January 2025

Understanding program behavior is challenging for novice learners. To address this problem, various program visualization systems such as TEDViT have been developed. TEDViT allows teachers to establish drawing rules, ensuring that their intentions are reflected in the visualization results. However, visualizing programs edited by learners using TEDViT has been hindered by its rule notation. In this study, we propose a novel rule designed to accommodate learner-edited programs. Furthermore, we develop a new system based on this rule.
Exploring the Impact of Incorporating Digital Escape Room on Learners’ Performance and Motivation in Environmental Sustainability Education
Authors: LAI Yu-Chao , YANG Jie-Chi
Published: January 2025

Environmental education has been conducted to equip learners with relevant environmental conservation knowledge for many years. However, learners seldom put the knowledge into practice and even have few ideas about how to protect the earth. Accordingly, continuous attention to this issue is necessary to enhance the effectiveness of environmental education. One of the strategies is gamification through technological application, which could enhance learning interaction and motivation with learners. The current study developed an online environment with the concept of escape room in the experimental group on the basis of a gamification strategy. With the immersion of the escape room, learners were encouraged to protect nature in a playful and challenging way. This empirical study was implemented to examine whether the online environment could promote learners' understanding and motivation. Our findings showed that the learners' performance in experimental group was significantly higher than that in the control group, highlighting the effectiveness of the digital escape room in enhancing learning performance. Nevertheless, there were no statistically significant differences in motivation between the groups, although the experimental group exhibited consistently higher mean motivation scores, suggesting a positive trend that warrants further research.
Middle School Students' Ability to Detect Lies When Interacting with an Educational AI Robot
Authors: SALEM Ahmed , SUMI Kaoru
Published: January 2025

Educational robots are becoming increasingly incorporated into classrooms to teach many subjects including language, science, and also substitute teachers. In recent years, ChatGPT has become easy to use for education but there are problems if students take it literally and believe it. We investigate the effectiveness of different deception techniques through robot teaching. We conduct an experiment in a Japanese Junior High School with 14 students where we investigate the learning and deception effectiveness, and believability using the social robot "Furhat". Moreover, we vary the social agency of the robot by using two different faces, a human (social identity theory) and an anime face (Japanese anime culture). A robot with an anime face achieved a significantly higher learning effectiveness compared to a robot with a human face. However, the human robot face was found to be excellent at deceiving when the paltering deception technique was utilized.
Unpacking Interaction Markers of Critical Thinking
Authors: KOTHIYAL Aditi , MAJUMDAR Rwitajit , MISHRA Shitanshu , WARRIEM Jayakrishnan Madathil , PANDE Prajakt
Published: January 2025

Abstract: In this we focus on critical thinking activities conducted in an online environment and interaction markers based on the data collected from those activities. The work is based on the ENACT framework. We conducted an empirical study to understand the clusters of critical thinkers based on Performance and interactional marker values of the participants (n=37). The highlights the definitions of the interaction markers and conducts an clustering analysis of the of Critical Thinking patterns that emerged. The results show two clusters with similar critical thinking outcome performance but different action patterns. We discuss the need of further empirical evidence relating learning effect on the actions and Critical Thinking.
Examining Augmented Reality's Influence on Pronunciation Training: Insights from PinyinGuo's Application and Comparative Avatar Testing
Authors: SINYAGOVSKAYA Daria
Published: January 2025

This study introduces PinyinGuo, an immersive language learning application developed in Unity, leveraging LipSync plugin integration from RogoDigital for accurate articulation of facial sounds in AR avatar. MongoDB integration enhances user data processing and personalization. An online experiment evaluates the impact of AR technology by comparing 3D and AR avatars on mobile phones for speech training and language learning, with preliminary results indicating promising outcomes for AR on mobile platforms. Through rigorous usability testing, PinyinGuo demonstrates the transformative potential of AR in language education and speech training, highlighting the role of AR technology in reshaping speech training applications.
Difficulty-Controllable Reading Comprehension Question Generation Considering the Difficulty of Reading Passages
Authors: TOMIKAWA Yuto , UTO Masaki
Published: January 2025

In recent years, various question generation (QG) methods for reading comprehension have been that automatically generate questions related to given reading passages. Specifically, QG methods based on deep neural networks have succeeded in generating high-quality questions. To apply such QG methods in educational systems, such as intelligent tutoring systems and adaptive learning systems, it is crucial to generate questions with difficulty levels that are appropriate for each learner's reading ability. To meet this need, several difficulty-controllable QG have been proposed recently. However, a limitation of existing difficulty- controllable methods is that they overlook the difficulty of the reading passages, which are given as the input context for QG. Since the difficulty of reading passages can affect the difficulty of the generated questions, selecting reading passages with appropriate difficulty is crucial. Therefore, in this study, we develop a difficulty-controllable QG that includes a mechanism for selecting reading passages with appropriate difficulty for each learner. Our approach begins with the of a new item response theory (IRT) model capable of simultaneously estimating the difficulty of both questions and reading passages. Using the developed IRT model and the latest IRT- based difficulty-controllable QG method, we propose a framework to select reading passages and generate questions that are appropriate for each learner's reading ability.
Does Experience of Feedback Generation Promote Student Novel Problem Posing? An Empirical Study in a Database Course
Authors: KOJIMA Kazuaki
Published: January 2025

The use of problem posing to assess students' understanding and transfer of knowledge has been discussed. The author's previous study proposed a for learning assessment where students created problems that could be solved with solutions of given problems by changing the contextual settings in texts (situations). However, some of the students' problems did not feature new situations. To promote novel idea generation in the transfer of solutions into novel situations, this study adopted the generation of feedback to problems that students learned in a course to involve them more deeply in the problems. It then empirically investigated the effects of feedback generation on the students' problem-posing performance.
Extraction of Important Characteristics for Data-Informed Guidance and Counseling from Daily Usage Log Data
Authors: ATAKE Junya , HSU Chia-Yu , HORIKOSHI Izumi , OGATA Hiroaki
Published: January 2025

In many schools, teachers ensure that learners acquire academic knowledge and competences and promote their comprehensive psychological and social development through a process known as Guidance and Counseling (G&C). However, this process often involves dealing with difficult tasks and requires considerable effort from teachers. In recent years, as ICT tools have become more common, log data on daily use and learning log data have accumulated. These data have enabled teachers to understand leamer processes. Utilizing data across contexts is expected to deepen learners understanding, which is the basis of G&C. However, despite these needs and potential, the use of data for G&C has not yet been fully explored. Therefore, this study examines how the log data accumulated in the Goal-Oriented Active Learner (GOAL) system can be used by teachers to understand learners. Specifically, we extracted the characteristics of each learner's situation for various contexts from the log data, which can capture learning and daily routines. We then interviewed two teachers to determine how the visualized characteristics might be useful for G&C. The results suggest that the visualized characteristics are valuable for understanding learners' conditions both inside and outside of school, and these characteristics could support teachers' G&C activities, transcending specific subjects and activities.
The Trends in Computer-Supported Virtual Reality Collaborative Learning
Authors: CHANG Ching-Yi , CHEN Cheng-Huan
Published: January 2025

The integration of computer-supported virtual reality (VR) in collaborative learning environments is rapidly evolving, presenting new opportunities and challenges for educators and learners. This paper examines the current trends and developments in VR-enhanced collaborative learning, focusing on the technological advancements. pedagogical strategies, and educational outcomes. Through a comprehensive review of recent studies and practical applications, we identify key factors that influence the effectiveness of VR in fostering interactive and immersive learning experiences. The findings highlight the potential of VR to enhance student engagement, improve spatial understanding, and facilitate experiential learning. Additionally, the paper discusses the implications of VR for future educational practices and suggests areas for further research to address the existing limitations and optimize the use of VR in collaborative learning settings.
Exploring the Effect of Collaborative Programming Learning Environment on Student's Computer Programming Competencies and Cognitive Learning
Authors: CHANG Chia-Jung , HUANG Wen-Lung
Published: January 2025

The aims to develop a synchronous collaborative programming learning environment to facilitate students' computer programming and to explore its impact on programming competencies, problem-solving behaviors, and cognitive learning, The results showed that the environment not only improved students' programming competencies, but also enhanced their high-level cognitive learning. Additionally, students in collaborative programming demonstrated a higher percentage of problem-solving behaviors in exploring and understanding, and planning and executing. Meanwhile, the study identified the differences between individual and collaborative activities on problem-solving behaviors.
Analyzing Teacher-Student Dialogues in Online One-on-One Primary Mathematics Tutoring: A Lag Sequential Analysis of Group Differences
Authors: CHENG Gary , JIANG Bo , SUN Daner , GAO Ming , SONG Zhixuan
Published: January 2025

This study aimed to identify effective teacher-student dialogues in online one-on-one tutoring sessions for primary mathematics. A total of 35 online videos of one-on-one tutoring sessions focused on the topic of fractions were collected and transcribed into textual data. Two key methods were employed to analyze the data. First, a hybrid coding scheme combining the Initiation-Response-Feedback (IRF) model with scaffolding techniques was used to code teacher-student dialogues from each tutoring session to categorize the session into one of two groups: the more effective tutoring and the less effective tutoring group, based on the presence of indicators suggested by the literature. Second, lag sequential analysis (LSA) was applied to compare dialogue patterns between the more and less effective tutoring groups at a more fine-grained level. Our results indicate that tutors who employed a variety of strategies, including modeling and diverse scaffolding techniques, were more effective in engaging students and addressing their learning needs. This study suggests that adaptive tutoring strategies are crucial for enhancing student understanding in primary mathematics. Future research could further refine these approaches with inputs from human experts and explore their application in different educational contexts, such as developing AI-powered chatbots capable of providing adaptive scaffolding to students beyond the classroom.