·This sub-conference focuses on the paradigms, principles, design, practice, and application of learning analytics and learning assessment. The aim of this sub-conference is to analyze the process learning data to discover the law of learners’ behavior, predict learning performance, promote the design and development of technology-supported learning tools, and better understand and upgrade the learning process. The learning process and learning assessment are born of the convergence of disciplines that span learning technologies, educational research and practice, cognitive and learning sciences, computer science, data science, psychology, and linguistics, as well as other related areas. The challenges facing the application of learning analytics and learning technologies arise from their transdisciplinary nature, multivariate analysis, and methods, which require cross-disciplinary systematic research and data-driven solutions. The sub-conference is expected to provide an open platform for scholars to share knowledge, experience, ideas, and strategies to generate new theoretical and practical insights that will further advance the field. Researchers are encouraged to consider the following topics as a reference for selecting relevant issues for discussion…It is important to note, however, that the scope of research topics extends beyond these suggestions.

1. Tools and Methodology for Learning Analytics

This theme covers approaches, tools, and methodologies in learning analytics. We explore various methods and approaches in the study of learning analytics, as well as investigate the tools and techniques employed in the field of learning analytics. The focus is on examining paradigms in learning analytics research, specifically, theoretical frameworks and methodologies adopted in educational research. Emphasis is placed on optimizing teaching and learning experiences to provide more effective support for learners. The following are some examples of research areas:

2. Decision-Making and Evaluation in Learning Analytics:

This theme concentrates on utilizing data for precise diagnosis of learners and providing timely and effective feedback. We address assessment methods for tracking changes throughout the learning process and evaluating final outcomes, enabling educators to comprehensively understand students' learning situations. Additionally, the sub-conference encourages the integration of innovative technologies to enhance the efficiency and accuracy of assessments. The following are examples of research areas:

3. Learner Characteristics and Learning Analytics:

Learner characteristics and learning analytics focus on various aspects of individual differences among learners. Through the analysis of diverse traits such as emotions and behaviors, we propose corresponding assessment methods to gain a more comprehensive understanding of students' academic performance and potential. The aim is to delve into learners' personalized needs and behavioral patterns, achieving a more personalized, flexible, and efficient learning experience. The following are examples of research areas:

4. Human-Computer Interaction and Learning Analytics

With the rise of generative AI across industries, this sub-conference seeks to explore learning analytics research in the context of the human-computer interaction process. The theme focuses on understanding how learning analytics technologies can comprehend and enhance interactions between individuals and intelligent partners. Exploring the ethical and moral norms to be followed in learning analytics and AIED, and investigating the construction of learning theories and their manifestations in interactions. "By leveraging the understanding of learning analytics technology and adapting to interactions between individuals and intelligent companions, personalized learning support is provided, fostering more effective teaching and learning interactions. The following are examples of research areas:

Notes on Paper submission:

Full manuscripts (including Long, Short, and Poster papers) shall be submitted to the conference for review. Abstract submissions will NOTbe accepted. This conference uses a double-blind review, which means that both the reviewer’s and author’s identities are concealed from the reviewers. Therefore, please kindly note that when authors submit papers for review, the authors’ information has to be blinded in the title, the contents, and the reference part. After the paper is accepted, the authors’ information will be displayed in the final version of the submitted paper.

Since 2020, the nine sub-conferences of GCCCE will have called for papers only in Chinese. Therefore, the papers submitted to this chapter must be written in Chinese (Long papers: 8 pages; Short pages: 4 pages; Poster: 2 pages). Submissions written in Chinese should include the title, abstract and keywords both in Chinese and English. The authors should upload the papers in PDF format to the conference website:https://easychair.org/conferences/?conf=gccce2024. Please make use of the paper template(Chinese) for preparing submissions. Please note that all papers in English, regardless of topics, should be submitted to the "English Paper Track". Once the paper is accepted, at least one author must be registered and present to publish the paper.

Sub-Conference Executive Chair:

Jiun-yu, Wu             National Yang Ming Chiao Tung University

Sub-Conference Vice Executive Chairs:（listed in alphabetic order of surnames）:

Shi-hui, Feng          The University of Hong Kong

Xian-min, Yang       Jiangsu Normal University

Yiz-hou, Fan           Peking University

Agenda Committee Members (Listed in alphabetical order):

Cheng-Huan, Chen  Asia University

Chih-Ming, Chen  Chengchi University

Ching-Lin, Wu  National Taiwan Normal University

Chung Kwan, Lo  The Education University of Hong Kong

Fan, Ouyang             Zhejiang University

Gaowei, Chen       The University of Hong Kong

Hong-Liang, Ma  Shaanxi Normal University

Hou-Chiang, Tseng  National Science and Technology University

Hsi-Hsun, Yang  National Yunlin University of Science and Technology

Hsiang-Yu, Chien  University of Kansas

Hsiao-Chi, Juan  National Taichung University of Education

Huei-Chuan, Wei  National Yang Ming Chiao Tung University

Hui-Chun, Hung  National Central University

Oi-Man, Kwok   Texas A&M University

Jianwen, Sun  Central China Normal University

Jr-Hung, Lin             National Taiwan Normal University

Kangkang, Li             Jiangsu Normal University

Liang-Yi, Li                National Taiwan Normal University

Liru, Hu             The University of Hong Kong

Meng-Ting, Lo  National Yang Ming Chiao Tung University

Ming-Chi, Liu             Feng Chia University

Morris, Jong             The Chinese University of Hong Kong

Sheng-Kai, Yin  Cheng Shiu University

Tzu-Chi, Yang  National Yang Ming Chiao Tung University

Xiaopeng, Ni             Franklin University

Xin, Li                        Jiangsu Normal University

Xiuhan, Li             Central China Normal University

Yuan-Hsuan, Lee  National Tsing Hua University

Yuyao, Tong             The University of Hong Kong

Zheng-yu, Zhong  National Yang Ming Chiao Tung University

Zhichun, Liu             The University of Hong Kong

Zhijia, Mou             Jiangnan University

Zhiqiang, Ma             Jiangnan University