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Interactive effects of scaffolding digital game-based learning and cognitive style on adult learners’ emotion, cognitive load and learning performance

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International Journal of Educational technology in Higher Education 2023年第1期20卷 1-25页

作者： Chang, Chi-Cheng Yang, Szu-Ting Department of Technology Application and Human Resource Development National Taiwan Normal University Taipei Taiwan ROC

There has been a little research on emotion, cognitive load, or learning performance for digital game-based learning (DGBL). However, there is still a dearth of research on investigating the interactive effects of scaffolding DGBL and cognitive style on the above three outcomes. Participants were 97 middle-aged and elder adults from a community college and randomly assigned into three groups. Taking prior knowledge as the covariate, 3 × 2 two-way MANCOVA was adopted to verify the interactive effects of scaffolding DGBL (hard scaffolding DGBL, soft scaffolding DGBL, and non-scaffolding DGBL) and cognitive style (Serialist and Holist). The findings presented that there exited significantly interactive effects of scaffolding DGBL and cognitive style on learning emotion, cognitive load, and learning performance. In hard scaffolding DGBL, learning emotion, cognitive load, and learning performance of Serialist learners were significantly better than those of Holist learners. Conversely, in soft scaffolding DGBL, learning emotion, cognitive load, and learning performance of Holist learners were significantly better than those of Serialist learners. Learning emotion, cognitive load, and learning performance of Serialist learners using hard scaffolding DGBL and Holist learners using soft scaffolding DGBL were significantly better than those of learners using non-scaffolding DGBL. The findings demonstrated concrete contributions and implications on practical promotion and theoretical development. This study ensures sufficiency of applying the cognitive-affective theory of learning with media (CATLM), cognitive load theory and cognitive style theory on DGBL, suggesting to extend the application of these theories to scaffolding.

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Explainable AI for Trustworthy Clinical Decision Support: A Case-Based Reasoning System for Nursing Assistants

Explainable AI for Trustworthy Clinical Decision Support: A ...

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IEEE International Conference on Big Data

作者： Yen-Ku Liu Yun-Cheng Tsai Department of Technology Application and Human Resource Development National Taiwan Normal University Taipei Taiwan

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

The increasing complexity of patient data and the need for reliable, transparent decision-making in healthcare drive the demand for advanced AI systems. This paper introduces a Clinical Decision Support System (CDSS) integrating Explainable AI (XAI) with Retrieval-Augmented Generation (RAG), designed to offer transparent, real-time, and evidence-based recommendations. HIPAA-compliant and grounded in historical case studies, the system facilitates trustworthy decision-making in high-pressure environments for nursing assistants. Although preliminary, simulations indicate the system’s potential to reduce cognitive load and enhance decision accuracy, with future clinical trials planned for comprehensive validation. It ensures HIPAA compliance while utilizing real-time patient data and historical case studies to support transparent and reliable clinical decisions. The system provides real-time, mobile-friendly recommendations based on predictive analytics and case-based reasoning, ensuring that nursing assistants can make informed, transparent decisions even in high-pressure scenarios. Future work will validate the system through simulations and clinical trials to assess its impact on decision accuracy and cognitive load reduction. Designed specifically for nursing assistants, the system provides real-time, explainable recommendations and retrieves relevant historical cases and clinical guidelines to support decision-making. While this work is preliminary and has not been deployed in clinical settings, theoretical analysis suggests that the system has the potential to improve decision accuracy and reduce cognitive load. A roadmap for future validation and clinical trials is outlined to demonstrate how the proposed system can be integrated into healthcare workflows.

关键词： Decision support systems Accuracy Explainable AI Scalability Retrieval augmented generation Medical services Clinical trials Cognitive load Real-time systems Load modeling

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Effects of caring climate on career commitment for preschool teachers: the mediating roles of interpersonal trust and cooperative learning

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Early Years 2024年第1期45卷 103-118页

作者： Chang, I-Hsiung Hsu, Pi-Chun Chen, Ru-Si Department of Technology Application and Human Resource Development National Taiwan Normal University Taipei Taiwan Department of Childhood Care and Education MacKay Junior College of Medicine Nursing and Management Taipei Taiwan Department of Early Childhood Education and Care Minghsin University of Science and Technology Hsinchu Taiwan

Preschool teachers in Taiwan face pedagogical and emotionalchallenges that shape their job satisfaction, commitment, and socialidentity. Understanding their views on professional developmentand organizational commitment in early childhood education is critical. This study aims to examine the relationship between caring climate and career commitment and test the multiple mediating effects of interpersonal trust and cooperative learning in this relationship. A survey was conducted in Taiwan to test preschool teachers’ attitudes toward career commitment and other related factors. The questionnaire consisted of four latent factors: caring climate, career commitment, interpersonal trust and cooperative learning. We used partial least squares to analyze the sample data and examine the reliability and validity in the multiple mediation model. The results of the multiple mediating analysis indicated that interpersonal trust and cooperative learning fully positively mediated the association between caring climate and career commitment. Preschool teachers’ career commitment is influenced by their perceptions of caring climate in workplaces. Their positive attitudes toward kind interactions and teamwork with colleagues in preschools actively support sustainable development of their career paths. © 2024 TACTYC.

关键词： Career commitment caring climate cooperative learning interpersonal trust preschool teachers

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A Study on the Effects of Using the 6E Model and a Robot Teaching Assistant on Junior High School Students’ STEM Knowledge, Learning Motivation, and Hands-on Performance

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Journal of Science Education and technology 2024年第5期33卷 759-778页

作者： Hsiao, Hsien-Sheng Chen, Jhen-Han Chang, Tze-ling Li, Po-Hsun Chung, Guang-Han Department of Technology Application and Human Resource Development National Taiwan Normal University Taipei City Taiwan (R.O.C.)

The integration of education and robotics has emerged as a crucial development in the technological landscape. This study focuses on the use of a robot teaching assistant to enhance the learning efficiency of 8th-grade students in hands-on STEM activities centered around the theme of “Smart City.” It explores the impact of educational robots on students' learning outcomes and their development of hands-on skills through diverse learning methods. Conducted over 12 weeks with 103 participants, the study employed a quasi-experimental design. Students were split into two groups: The Experimental Group (EG), using the 6E model with robot teaching assistants, and the Control Group (CG), using only the 6E model. The analysis of covariance revealed that the EG exhibited superior performance in STEM knowledge, motivation, and hands-on skills compared to the CG. Further analysis indicated that learning motivation significantly influenced hands-on performance in the EG, particularly in high-scoring subgroups. The findings suggest that combining the 6E model with educational robots effectively enhances STEM learning and student engagement. Educational robots as teaching assistants not only aid in knowledge acquisition but also significantly boost students' motivation and hands-on skill development. This implies a promising direction for integrating advanced technology in educational practices to foster more effective learning environments.

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development and preliminary validation of the middle school students’ attitudes toward STEM learning scale

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Research in Science and Technological Education 2023年第1期43卷 86-106页

作者： Tsai, Shin-Ping Ting, Yu-Liang Chu, Lin Department of Special Education National Taipei University of Education Taipei Taiwan Department of Technology Application and Human Resource Development National Taiwan Normal University Taipei Taiwan Department of Instructional Systems Technology Indiana University Bloomington Bloomington IN United States

The purpose of this study was to develop and validate an instrument to measure attitudes of middle school students toward STEM learning, including integrative STEM learning. The participants were 274 middle school students (grades 7–9) in Taiwan. Results from the expert review, exploratory factor analysis, correlational analysis, and group difference analysis provided different sources of validity evidence. Five factors were identified, including students’ interest/expectancies in math, perceptions of importance/utility of math, attitudes toward science, attitudes toward technology/engineering, and attitudes toward integrative STEM learning. Moderate correlations among the factors and STEM career interests and statistically significant group differences in terms of gender and participation in math remedial instruction were found. Multiple regression analysis results also showed that the five factors statistically significantly predicted STEM career interests. Internal consistency indicated an appropriate to excellent level. These results provided preliminary support for the psychometric properties to measure middle school students’ attitudes toward STEM learning. Finally, this study points out the critical role of integrative STEM learning in the construct and suggests further research on the mechanisms among expectancies for success, subjective task value, and persistence in learning STEM. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Attitudes toward STEM expectancy-value model instrument development integrative STEM learning

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Effects of voice assistant creation using different learning approaches on performance of computational thinking

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Computers and Education 2023年 192卷

作者： Hsu, Ting-Chia Chang, Ching Lin, Yi-Wei Department of Technology Application and Human Resource Development National Taiwan Normal University Taiwan

Designing artificial intelligence (AI) artefact learning has gone beyond command-line-based instruction, to include a low-barrier threshold with block-based programming. Such instructional design must not solely emphasise AI workings. Rather, it must offer students computational thinking (CT) practice to support their AI-related artefact creation while reducing their AI anxiety about future job replacement or sociotechnical blindness. In this study, this research explored an experiential learning approach to improve CT along with AI application capabilities when engaging undergraduate students in creating a voice assistant application (VA app). A total of 56 students participated in the study. The control group (CG) of 26 students used a conventional subject-based learning method, while the experimental group (EG) of 30 students adopted an experiential learning method. This study aimed to examine the differences in the learning achievement of CT and AI concept, as well as the perspectives of AI anxiety, and CT;in the meanwhile, this study analysed the students' learning behaviours using sequential behavioural analysis to discuss the learning process. Results showed that the CT ability of the EG was better than that of the CG, although no significant difference was found between the two groups’ AI concepts and anxiety. The behaviour analysis also revealed that the EG students were willing to ask more questions, and conducted their VA evaluation, whereas the CG students were inclined to focus on the input and output of knowledge, and replicated what the teacher presented. Suggestions and implications are given for future research. © 2022 Elsevier Ltd

关键词： Artificial intelligence

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Do attitudes matter? An investigation into students’ attitudes toward engineering and learning performances through engineering-focused STEM curricula

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International Journal of technology and Design Education 2025年第1期35卷 123-150页

作者： Tzeng, Sy-Yi Yu, Kuang-Chao Wu, Pai-Hsing Fan, Szu-Chun Department of Graphic Communications and Digital Publishing Shih-Hsin University Taipei City Taiwan Department of Technology Application and Human Resource Development National Taiwan Normal University Taipei City Taiwan Center for Textbook Research National Academy for Educational Research New Taipei City Taiwan Department of Industrial Technology Education National Kaohsiung Normal University No. 62 Shenzhong Rd. Yanchao Dist Kaohsiung City824 Taiwan

Many studies have investigated students’ attitudes toward engineering (ATE), but few have examined the changes in attitudes after attending an engineering design curriculum. This study analyzes these attitudinal changes in students attending an engineering-focused science, technology, engineering, and mathematics (EF-STEM) curriculum and investigates the influence and correlation between attitudes and learning performance. The participants included 364 tenth-grade students (ages 16–18 years). An 18-week experimental intervention design (2 h per week) was adopted. The Attitudes Towards Engineering Scale—Taiwan was applied before and after attending the EF-STEM course;remaining assessments were conducted post-course. The results showed that the ATE statistically decreased after attending the course, shifting from a positive attitude to a neutral-leaning attitude. Although most students appreciated the importance of engineering design, they exhibited a high degree of anxiety toward it. Moreover, their pre-ATE was significantly correlated with their perception of engineering design and learning performance. These results indicate that engineering design curricula do not necessarily have a positive effect on student ATE. © The Author(s), under exclusive licence to Springer Nature B.V. 2024.

关键词： Curricula

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Effects of virtual reality on creativity performance and perceived immersion: A study of brain waves

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British Journal of Educational technology 2023年第2期54卷 581-602页

作者： Wang, Yen-Yin Weng, Tz-Han Tsai, I-Fan Kao, Jing-Yueh Chang, Yu-Shan Department of Technology Application and Human Resource Development National Taiwan Normal University Taipei Taiwan

The purpose of this study was to explore the effects of virtual reality (VR) application on creative performance and immersion, evaluated through electroencephalography brain wave data to achieve accurate and robust results. In this study, 72 middle school teachers were recruited as participants, and a non-randomized control-group pre-test–post-test design was employed. The experimental group received VR-based design instruction, and the control group received lecture-based design training. Our results revealed that VR significantly affects immersion, especially with regard to attention. Additionally, VR had a positive effect on the feasibility of the creative process, although its effects on variety and novelty were inconclusive. VR was significantly correlated with theta, beta, and gamma brain wave activity. VR also increased attention-related and meditation-related brain wave activity and desynchronized alpha waves. Practitioner notes: What is already known about this topic VR is used in many areas. VR in education is getting more important day after day. What this paper adds VR significantly affects immersion, especially with regard to attention. VR had a positive effect on the feasibility of the creative process, although its effects on variety and novelty were inconclusive. VR was significantly correlated with theta, beta, and gamma brain wave activity. VR also increased attention-related and meditation-related brain wave activity and desynchronized alpha waves. Implications for practice and/or policy User lack of familiarity with VR may also have influenced the results;more VR learning materials should be provided for learners. In addition to using a larger sample, future studies should focus on creative novelty when developing VR content to improve creative processes and outcomes. Familiarizing learners with the use of VR could effectively reduce the cognitive load, as well as contribute to the stimulation of creative brain waves. © 2022 British Educational

关键词： Virtual reality

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Enhanced engineering design behaviour using chatbots with user experience

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Behaviour and Information technology 2023年第12期42卷 2030-2041页

作者： Chien, Yu-Hung Yao, Chun-Kai Department of Technology Application and Human Resource Development National Taiwan Normal University Taipei Taiwan

In recent years, both industrialists and scholars have come to believe that involving users in the design process is the basis for ensuring design innovation and successful product development. However, practical restrictions of time, budget, and location may inhibit users’ long-term participation at teaching sites. With the development of emergent chatbot technology, the aim of this study is to investigate the feasibility that students practice interacting with chatbots who incorporate multiple real-life users’ experiences with products and product-specific knowledge in the classroom for exempting from time and accessibility constraints. We conducted an experiment using a design workshop to compare the student groups with respect to their interactions with chatbots, with target customers, and with no users while they generated design concepts. The quality of the three student groups’ design concepts and the differences of their design behaviours were compared. The outcomes of this study indicate that the chatbot group exhibited more significant transitions of engineering design behaviours and better design concept score than that the target-user and no-user group did. Chatbots incorporate user experience may provide students with opportunities to practice extracting information from users with the aim of promoting the success of the design process. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Students

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The Artificial Intelligence Learning Anxiety and Self-Efficacy of In-Service Teachers Taking AI Training Courses

The Artificial Intelligence Learning Anxiety and Self-Effica...

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International Conference on Artificial Intelligence and Education (ICAIE)

作者： Ting-Chia Hsu Tai-Ping Hsu Yi-Ting Lin Department of Technology Application and Human Resource Development National Taiwan Normal University Taipei Taiwan

This research explored the degree of learning self-efficacy of machine learning experience (MLSE) and artificial intelligence learning anxiety (AILA) of elementary and junior high school teachers. The participants were in-service teachers in the technology domain. This research applied the AI2 Robot City, which is a computational thinking board game, to in-service teacher education. The learning content was image classification for AI application. Elementary and junior high school teachers operated the MIT App Inventor(MAI) and Personal Image Classifier(PIC) platform, and trained the model for practicing AI to implement supervised machine learning on the PIC platform. The learners then inserted the model they had trained into the block-based programming environment of MAI. They completed the smart phone app and used the app to recognize the board game cards so as to control the movement of the smart cars on the table map to meet the requirements of the task in the AI2 Robot City board game. In order to understand affective factors such as the self-efficacy and learning anxiety of the elementary and middle school teachers participating in the AI teacher training workshop, the MLSE and AILA scales were administered before and after the classes. A total of 28 samples were collected. The results showed that there was no significant difference between the MLSE of the elementary and junior high school teachers. However, the average AILA degree of the junior high school teachers was significantly higher than that of the elementary school teachers. It was found that AILA was significantly negatively correlated with MLSE. The elementary and junior high school teachers were confident that they could study AI-related courses. However, the AILA of the junior high school teachers was higher than that of the elementary school teachers. Therefore, more teacher training workshops on AI application can be conducted for junior high school teachers to generally improve their familiari

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