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Ziyan Yang; Jia Hu; Shaochun Zhong; Lan Yang; Geyong Min – Education and Information Technologies, 2025
Intelligent technology plays a pivotal role in revolutionizing learning assessments, overcoming the constraints of traditional assessment methods and driving educational innovation. Knowledge tracing (KT) emerges as a critical component for assessing students' learning states and forecasting their future performance. However, existing graph-based…
Descriptors: Learning Processes, Artificial Intelligence, Graphs, Concept Mapping
Chiara Alzetta; Ilaria Torre; Frosina Koceva – Technology, Knowledge and Learning, 2024
Extracting and formally representing the knowledge embedded in textbooks, such as the concepts explained and the relations between them, can support the provision of advanced knowledge-based services for learning environments and digital libraries. In this paper, we consider a specific type of relation in textbooks referred to as…
Descriptors: Textbooks, Information Retrieval, Documentation, Graphs
Leonie Disch; Angela Fessl; Simone Franza; Joachim Kimmerle; Viktoria Pammer-Schindler – Discover Education, 2025
Reading and understanding scientific texts is useful and necessary in many informal collaboration settings, including research or innovation collaborations, or when discussing public science in lay peer groups. In this work, we investigate whether an interactive predefined concept map that builds up gradually while reading a scientific research…
Descriptors: Reading Comprehension, Graphs, Concept Mapping, Cooperative Learning
Li Chen; Gen Li; Boxuan Ma; Cheng Tang; Masanori Yamada – International Association for Development of the Information Society, 2024
This paper proposes a three-step approach to develop knowledge graphs that integrate textbook-based target knowledge graph with student dialogue-based knowledge graphs. The study was conducted in seventh-grade STEM classes, following a collaborative problem solving process. First, the proposed approach generates a comprehensive target knowledge…
Descriptors: Concept Mapping, Graphs, Cooperative Learning, Problem Solving
Ye Jia; Xiangzhi Eric Wang; Zackary P. T. Sin; Chen Li; Peter H. F. Ng; Xiao Huang; George Baciu; Jiannong Cao; Qing Li – IEEE Transactions on Learning Technologies, 2024
One of the promises of edu-metaverse is its ability to provide a virtual environment that enables us to engage in learning activities that are similar to or on par with reality. The digital enhancements introduced in a virtual environment contribute to our increased expectations of novel learning experiences. However, despite its promising…
Descriptors: Computer Simulation, Educational Technology, Learning Processes, Socialization
Qian Wang; Shiwang Hou; Sixian Wan; Xin Feng; Hao Feng – European Journal of Education, 2025
To prepare undergraduates for complex careers, interdisciplinary higher education is gaining popularity. However, implementing interdisciplinary learning in engineering management is challenging due to the complex and intertwined knowledge structures. While smart education platforms provide access to extensive knowledge bases, the intricate web of…
Descriptors: Undergraduate Students, Higher Education, Interdisciplinary Approach, Engineering Education
Wenlong Yi; Xuan Huang; Sergey Kuzmin; Igor Gerasimov; Yun Luo – Education and Information Technologies, 2025
This study proposes a knowledge graph-based big data analysis model for course quality evaluation, aiming to address issues in online education course evaluations such as semantic bias, grammatical deficiencies, vocabulary limitations, false evaluations, information distortion, and imbalanced evaluation categories. The model incorporates three…
Descriptors: Electronic Learning, Online Courses, Course Evaluation, Concept Mapping
Thomas, Jay – Journal of Applied Testing Technology, 2022
A model of cognition and a construct, such as a concept map (Wilson, 2009), is critical in designing assessments of that construct. The Knowledge, Skills and Abilities (KSAs) in the construct must be put to use in order to assess what test takers know and can do (National Research Council, 2001). In order to validate a construct map for graphic…
Descriptors: Eye Movements, Concept Mapping, Cognitive Processes, Graphs
Liu, Chunhong; Zhang, Haoyang; Zhang, Jieyu; Zhang, Zhengling; Yuan, Peiyan – International Journal of Information and Communication Technology Education, 2023
Current learning platforms generally have problems such as fragmented knowledge, redundant information, and chaotic learning routes, which cannot meet learners' autonomous learning requirements. This paper designs a learning path recommendation system based on knowledge graphs by using the characteristics of knowledge graphs to structurally…
Descriptors: Educational Technology, Artificial Intelligence, Electronic Learning, Concept Mapping
Dragos Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2023
Reading comprehension is essential for both knowledge acquisition and memory reinforcement. Automated modeling of the comprehension process provides insights into the efficacy of specific texts as learning tools. This paper introduces an improved version of the Automated Model of Comprehension, version 3.0 (AMoC v3.0). AMoC v3.0 is based on two…
Descriptors: Reading Comprehension, Models, Concept Mapping, Graphs
Xia Xiao; Ziqi Fang; Shuaiyi Zou; Chengde Zhang; Xinzhong Chen – Interactive Learning Environments, 2024
Online learning has been greatly widespread since the explosion of COVID-19. However, due to the lack of interaction between teachers and students in online courses, it is very difficult for students to focus on course content and complete the learning. Therefore, we developed a novel intelligent multilevel knowledge graph to help students quickly…
Descriptors: Cues, Graphs, Visual Aids, Electronic Learning
Zheng, Lanqin; Kinshuk; Fan, Yunchao; Long, Miaolang – Education and Information Technologies, 2023
Online collaborative learning has been an effective pedagogy in the field of education. However, productive collaborative learning cannot occur spontaneously. Learners often have difficulties in collaborative knowledge building, group performance, coregulated behaviors, learning engagement, and social interaction. To promote productive…
Descriptors: Learning Analytics, Performance, Electronic Learning, Cooperative Learning
Joshua R. Polanin; Qi Zhang; Joseph Taylor; Ryan T. Williams; Megha Joshi; Lauren Burr – Grantee Submission, 2022
Systematic reviews and meta-analyses are important techniques because they synthesize results from multiple primary studies on a similar topic. To influence policy, practice, and research, however, synthesis researchers must translate the results for various audiences. Ideally, the translation drives future research agendas, informs policymaking,…
Descriptors: Evidence, Educational Research, Meta Analysis, Concept Mapping
Chansanam, Wirapong; Jaroenruen, Yuttana; Kaewboonma, Nattapong; Tuamsuk, Kulthida – Education for Information, 2022
This article describes the development process of the Thai cultural knowledge graph, which facilitates a more precise and rapid comprehension of the culture and customs of Thailand. The construction process is as follows: First, data collection technologies and techniques were used to obtain text data from the Wikipedia encyclopedia about cultural…
Descriptors: Foreign Countries, Graphs, Data Collection, Semantics
Zheng, Lanqin; Long, Miaolang; Chen, Bodong; Fan, Yunchao – International Journal of Educational Technology in Higher Education, 2023
Online collaborative learning is implemented extensively in higher education. Nevertheless, it remains challenging to help learners achieve high-level group performance, knowledge elaboration, and socially shared regulation in online collaborative learning. To cope with these challenges, this study proposes and evaluates a novel automated…
Descriptors: Learning Analytics, Computer Assisted Testing, Cooperative Learning, Graphs

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