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Teacher development in robot and IoT knowledge, skills, and attitudes with the use of the TPACK-based Support-Stimulate-Seek approach

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Interactive learning environments 2023年第9期31卷 5811-5830页

作者： Hu, Chih-Chien Yeh, Hui-Chin Chen, Nian-Shing Department of Information Management Tatung University Taipei City Taiwan Department of Applied Foreign Languages National Yunlin University of Science and Technology Yunlin Douliou Taiwan Institute for Research Excellence in Learning Sciences Program of Learning Sciences National Taiwan Normal University Taipei City Taiwan

In-service teachers’ professional development regarding technology adoption in education is often focused on only one specific technology. To maximize the utilization of technologies, teachers need to be able to leverage different technologies seamlessly. Technological Pedagogical Content Knowledge (TPACK) is one of the most important frameworks depicting teachers’ competences for effectively teaching with technology. The TPACK Support-Stimulate-Seek model (3S-TPACK) was used to design training programs with learning activities using robots, IoT-based sensors, actuators, tablets, and computer programming tools. The results show that the training programs designed by adapting the 3S-TPACK model not only can improve the teachers’ learning outcomes but also can support positive attitudes toward adopting robots and IoT technologies in the teaching and learning process. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： 21st century abilities interdisciplinary projects Teacher education teacher professional development technological pedagogical content knowledge technology in education

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The effect of real-time pose recognition on badminton learning performance

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Interactive learning environments 2023年第8期31卷 4772-4786页

作者： Lin, Kuo-Chin Ko, Cheng-Wen Hung, Hui-Chun Chen, Nian-Shing Center for Physical and Health Education National Sun Yat-sen University Kaohsiung Taiwan Department of Computer Science and Engineering National Sun Yat-sen University Kaohsiung Taiwan Graduate Institute of Network Learning Technology National Central University Chung-Li Taiwan Institute for Research Excellence in Learning Sciences and Program of Learning Sciences National Taiwan Normal University Taipei Taiwan

Badminton is a very popular subject in Physical education (Pe). Many students enroll badminton courses in every semester which pose a tremendous teaching load to the instructors. The one-on-one guiding/feedback time provided by the instructor to each student is also greatly reduced. To overcome this challenge, some studies have tried to adopt pose recognition technique in teaching badminton. However, the lack of mobility and recognition accuracy problems hinder its applicability. To address this issue, a new pose recognition technique, OpenPose, was employed to develop a real-time pose recognition badminton teaching APP in this study. The APP was then installed on a mobile device to enhance badminton smash skill learning performance. The scores distribution of the experimental group shows majority of students achieved satisfactory performance, this implies the badminton teaching APP is helpful to all students no matter what their initial skill levels are. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

关键词： badminton teaching motor skill learning physical education Pose recognition real-time feedback

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Applying Smart Glasses in Situated exploration for learning english in a national science Museum

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Ieee Transactions on learning Technologies 2023年第5期16卷 820-830页

作者： Chen, Hong-Ren Lin, Wen-Shan Hsu, Tien-Yu Lin, Tzu-Chun Chen, Nian-Shing National Taichung University of Education Department of Digital Content and Technology Taichung City40306 Taiwan National Cheng Kung University Institute of International Management Tainan City701 Taiwan National Museum of Nature Science Department of Science Education Taichung City404023 Taiwan Graduate Institute of Library and Information Science National Chung Hsing University Taichung City40306 Taiwan National Taiwan Normal University Program of Learning Sciences Taipei City106 Taiwan

Research on the use of augmented reality technology in museums is mostly limited to scientific knowledge. The use of wearable device technology learning materials to benefit students in the process of english learning has been somewhat explored, along with differences in students' learning styles and their influence on students' learning motivation, but there remains much to be done in this field. This study explored the learning effect of smart glasses integration into the english language dinosaur exhibition at the Museum of Natural science and investigated their impact on motivation. The experimental group used smart glasses learning strategy to facilitate their learning experience, whereas the control group used a tablet learning strategy. The research results show that: 1) learning effectiveness and motivation were significantly superior when using smart glasses learning strategy, as compared to using a tablet learning strategy when learning through the english language situated exploration game. 2) The interaction between different learning strategies and learning styles had a significant impact on learning effectiveness. In the smart glasses learning strategy group and the tablet learning strategy group, the learning effectiveness of the kinesthetic students was significantly higher than those of the auditory students. The learning effectiveness of the visual students using the tablet learning strategy was higher than auditory students. 3) The interaction between different learning strategies and learning styles had no significant effect on learning motivation. In terms of learning motivation, visual students were more affected than auditory and kinesthetic students. © 2008-2011 Ieee.

关键词： Glass

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Uncovering emotion sequence patterns in different interaction groups using deep learning and sequential pattern mining

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Journal of Computer Assisted learning 2024年第4期40卷 1777-1790页

作者： Huang, Changqin Yu, Jianhui Wu, Fei Wang, Yi Chen, Nian-Shing Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Zhejiang Normal University Jinhua China School of Education Zhejiang International Studies University Hangzhou China College of Computer Science and Technology Zhejiang University Hangzhou China Institute for Research Excellence in Learning Sciences Program of Learning Sciences National Taiwan Normal University Taipei Taiwan

Background: Investigating emotion sequence patterns in the posts of discussion forums in massive open online courses (MOOCs) holds a vital role in shaping online interactions and impacting learning achievement. While the majority of research focuses on the relationship between emotions and interactions in MOOC forum discussions, research on identifying the crucial difference in emotion sequence patterns among different interaction groups remains in its infancy. Objectives: This research utilizes deep learning and sequential pattern mining to investigate whether there are differences in emotion sequence patterns across different groups of learners who exhibit various types of interactions in online discussion forums. Methods: Data from a comprehensive array of sources, including log files, discussion texts and scores from 498 learners in online discussion forums, were collected for this study. The agglomerative hierarchical algorithm is used to classify learners into groups with different levels of interactions. Additionally, we implement and evaluate multiple deep learning models for detecting different emotions from online discussions. Relevant emotion sequence patterns were identified using sequence pattern analysis and the identified emotion sequence patterns were compared across different groups with different levels of interactions. Results and Conclusions: Using an agglomerative hierarchical algorithm, we classified learners into three distinct groups characterized by different levels of interactions: high, average and low level. Leveraging the bi-directional long short-term memory model for emotion detection yielded the highest predictive performance, with an impressive F-measure of 94.01%, a recall rate of 93.83% and an accuracy score of 95.01%. The results also revealed that learners in the low-level interaction group experienced more emotion transition from boredom to frustration than the other two groups. Therefore, the aggregation of students into groups

关键词： deep learning emotion sequence patterns learning analytics learning behaviour sequential pattern mining

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exploring Preschool Teachers’ Conceptions of Teaching and learning, and Their Self-efficacy of Classroom Management and Pedagogical Content Knowledge

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Asia-Pacific education Researcher 2023年第2期32卷 263-273页

作者： Shen, Kuan-Ming Cheng, Yi-Wen Lee, Min-Hsien Institute of Education National Sun Yat-sen University Kaohsiung City Taiwan Master of Science in Computer Science Westcliff University Irvine United States Program of Learning Sciences National Taiwan Normal University 162 Section 1 Heping E. Rd. Taipei City 106 Taiwan Institute for Research Excellence in Learning Sciences National Taiwan Normal University Taipei City Taiwan

This study aimed to understand the relationship among conceptions of teaching and learning (COLT), classroom management self-efficacy (CMSe), and pedagogical content knowledge self-efficacy (PCKSe). A total of 485 in-service taiwanese preschool teachers participating in this study completed three questionnaires, viz. the Conceptions of Teaching and learning, the Classroom Management Self-efficacy, and the Pedagogical Content Knowledge Self-efficacy. The research findings indicated that, while teachers regarded conceptions of teaching and learning from a constructivist perspective, they tended to possess higher classroom management self-efficacy and in turn expressed higher PCK self-efficacy. On the contrary, teachers with traditional conceptions of teaching and learning tended to have lower classroom management self-efficacy and accordingly displayed lower PCK self-efficacy. According to the research findings, the present study encouraged teachers to develop constructivist COTL in order to foster better management and PCK. Besides, it is suggested that future studies explore other factors affecting teachers’ self-efficacy. © 2022, De La Salle University.

关键词： Classroom management Conceptions of teaching and learning Pedagogical content knowledge Preschool teachers Self-efficacy

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How humor styles affect humor comprehension and appreciation: A typological approach

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Current Psychology 2023年第19期42卷 16392-16400页

作者： Wu, Ching-Lin Yen, Ying-Fan Chen, Hsueh-Chih Program of Learning Sciences National Taiwan Normal University Taipei Taiwan Institute for Research Excellence in Learning Sciences National Taiwan Normal University Taipei Taiwan Department of Educational Psychology and Counseling National Taiwan Normal University Education College Building Room 612 No. 162 Sec. 1 Heping E. Rd. Da-an District Taipei City 10610 Taiwan Chinese Language and Technology Center National Taiwan Normal University Taipei Taiwan

There have been many empirical studies on humor styles and humor comprehension and appreciation, but relatively few have directly addressed the relationship between these two topics of humor research, especially studies using a typological approach for humor styles. Therefore, the present study aimed to examine how humor styles are associated with humor comprehension and appreciation using a typological approach. The present study collected the responses of humor styles questionnaires that included ratings of comprehension and funniness of humorous pictures for 962 high school students in taiwan. The cluster analysis result indicated that there were four humor types of participants: general humor endorsers, humor deniers, positive humor endorsers, and negative humor endorsers. The positive humor endorsers could understand the content of humor pictures better than other types of participants. The general humor endorsers found the humor pictures much funnier than the humor deniers. These findings indicate that humor styles have different associations with humor comprehension and humor appreciation. © 2021, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Humor appreciation Humor comprehension Humor style Pictorial humor

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Influence of Junior High School Students’ humor styles and perceptions of their class Teachers’ humor Styles on Teacher-Student Interaction

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Current Psychology 2023年第19期42卷 16442-16450页

作者： Wu, Ching-Lin Huang, Hsiang-Ju Chen, Pei-Zhen Chen, Hsueh-Chih Program of Learning Sciences National Taiwan Normal University Taipei Taiwan Institute for Research Excellence in Learning Sciences National Taiwan Normal University Taipei Taiwan Department of Educational Psychology and Counseling National Taiwan Normal University Education College Building Room 612 No. 162 Sec. 1 Heping E. Rd. Da-an District Taipei 10610 Taiwan Chinese Language and Technology Center National Taiwan Normal University Taipei Taiwan

A sense of humor constitutes a core factor that influences teacher-student interactions. The humor that teachers utilize in class may influence teacher-student relationships, either positively or negatively. Moreover, teachers’ humor style influences students’ humor style, and vice versa. This study aimed to construct patterns of humor styles based on typology and explore how these patterns influence their interactions. Data were collected from 990 taiwanese students regarding their self-reported humor styles and perceptions of class teachers as well as the interaction between the two. Subsequently, k-means clustering was conducted by dividing participants into four clusters based on the collected data: positive humor endorsers, negative humor endorsers, humor deniers, and contradictory humor endorsers. Among these, the grouping of contradictory humor endorsers differed from previous findings. Among the four clusters, the teachers of positive humor endorsers were perceived to have a significantly higher influence and proximity to students, whereas contradictory humor endorsers were perceived to have the lowest influence and proximity to students. The research findings revealed that different patterns of teachers’ and students’ humor styles have a distinct influence on their interactions, which deepens our understanding of the extent to which their humor styles consistently impact their interactions. © 2022, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Humor style Influence Proximity Teacher-Student Interaction

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Using LSTM and Regression Analysis for Railway Passenger Traffic Volume Prediction 11

Using LSTM and Regression Analysis for Railway Passenger Tra...

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11th Ieee Global Conference on Consumer electronics, GCCe 2022

作者： Tey, Fu Jie Tuan, Chih-Chi Cai, Cheng-en Wu, Ming-Xuan Wu, Yun-Sheng Wu, Tin-Yu National Taiwan University of Science and Technology Department of Electrical Engineering Taipei Taiwan National Ilan University Master Program of E-Learning for Multimedia and Network Communications Yilan Taiwan National Pingtung University of Science and Technology Department of Management Information Systems Pingtung County Taiwan

ISBN: (纸本)9781665492324

The purpose of this paper is to investigate the factors affecting the passenger traffic volume on the high-capacity MRT, to analyze the traffic volume trends, and to make traffic volume predictions more accurately. This paper uses the LSTM (Long Short-term Memory) model and regression analysis for Taipei MRT passenger traffic volume prediction. The training data, including dates, temperatures and number of passengers, were collected, and a regression analysis was performed to find trends in the data. © 2022 Ieee.

关键词： Long short-term memory

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Undergraduate Students’ Profiles of Cognitive Load in Augmented Reality–Assisted science learning and Their Relation to science learning Self-efficacy and Behavior Patterns

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International Journal of science and Mathematics education 2024年第2期22卷 419-445页

作者： Lin, Xiao-Fan Wong, Seng Yue Zhou, Wei Shen, Weipeng Li, Wenyi Tsai, Chin-Chung School of Education Information Technology Office 214 GuangDong Engineering Technology Research Center of Smart Learning South China Normal University 55 Zhongshan Dadao Xi Guangzhou 510631 China Guangdong Provincial Institute of Elementary Education and Information Technology Guangzhou China Guangdong Provincial Philosophy and Social Sciences Key Laboratory of Artificial Intelligence and Smart Education Institute for Artificial Intelligence Education Guangzhou China Centre for Internship Training and Academic enrichment (CITrA) University of Malaya Kuala Lumpur Malaysia Program of Learning Sciences National Taiwan Normal University Taipei Taiwan Institute for Research Excellence in Learning Sciences National Taiwan Normal University Taipei Taiwan

Research evidence indicated that a specific type of augmented reality–assisted (AR-assisted) science learning design or support might not suit or be effective for all students because students’ cognitive load might differ according to their experiences and individual characteristics. Thus, this study aimed to identify undergraduate students’ profiles of cognitive load in AR-assisted science learning and to examine the role of their distinct profiles in self-efficacy together with associated behavior patterns in science learning. After ensuring the validity and reliability of each measure, a latent profile analysis confirmed that 365 Chinese undergraduates carried diverse dimensions of cognitive load simultaneously. The latent profile analysis findings revealed four fundamental profiles: Low engagement, Immersive, Dabbling, and Organized, characterized as carrying various respective cognitive loads. The multivariate analysis of variance findings revealed different levels of the six AR science learning self-efficacy dimensions across profiles. Low engagement students displayed the lowest self-efficacy among all dimensions. Organized students recorded better conceptual understanding and higher-order cognitive skills than Dabbling ones. Students with the Immersive profile had the highest science learning self-efficacy. The lag sequential analysis results showed significant differences in behavior patterns among profiles. Among them, profiles with social interaction, test, and reviewing feedback behavior had a significantly higher score for self-efficacy than those patterns mainly based on test learning and resource visits. This finding provides a unified consideration of students’ diverse profiles and can inform interventions for effective design of AR-assisted science learning to match appropriate strategies to facilitate the science learning effect. © 2023, national science and technology Council, taiwan.

关键词： Augmented reality Behavior Cognitive load science learning Self-efficacy

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A Genetic Algorithm to Optimize Cargo Stability in Container Transportation 11

A Genetic Algorithm to Optimize Cargo Stability in Container...

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11th Ieee Global Conference on Consumer electronics, GCCe 2022

作者： Hsieh, Chi-Jung Wu, Kuang-Sung Wu, Tin-Yu Tey, Fu Jie Chen, Yi-Kai Ho, Jye Yi National Ilan University Department of Computer Science and Information Engineering Ilan County Taiwan National Ilan University Master Program of E-Learning for Multimedia and Network Communications Yilan Taiwan National Pingtung University of Science and Technology Department of Management Information Systems Pingtung County Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei Taiwan

ISBN: (纸本)9781665492324

In the era of the global village, frequent cross-border trade in goods has made container transportation a significant part in delivery of cargo. However, rollover accidents of container trucks often occur because of tall truck height, improper cargo stowage or crooked roads. Therefore, how to find the optimal center of gravity (CG) of the packed cargo remains an issue that the transportation industry should not neglect. To optimize cargo stability and reduce the incidence of rollovers, this paper proposes a genetic algorithm that scores the cargo stacking process to find the best CG of the cargo based on the CG of the vehicle. According to the deviation angle and the point closest to the best CG, we can Figure out the optimal cargo stacking method. © 2022 Ieee.

关键词： Genetic algorithms

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