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Mengjiao Yin; Hengshan Cao; Zuhong Yu; Xianyu Pan – International Journal of Web-Based Learning and Teaching Technologies, 2024
This study presents the Academic Investment Model (AIM) as a novel approach to predicting student academic performance by incorporating learning styles as a predictive feature. Utilizing data from 138 Marketing students across China, the research employs a combination of machine learning clustering methods and manual feature engineering through a…
Descriptors: Predictor Variables, Artificial Intelligence, Performance, Cluster Grouping
Bin Meng; Fan Yang – International Journal of Web-Based Learning and Teaching Technologies, 2025
This paper proposes a computer-aided teaching model using knowledge graph construction and learning path recommendation. It first creates a multimodal knowledge graph to illustrate complex relationships among knowledge. Learning elements and sequences are then used to form time sequences stored as directed graphs, supporting flexible path…
Descriptors: Students, Teachers, Computer Assisted Instruction, Knowledge Representation
Baidada, Mohammed – International Journal of Web-Based Learning and Teaching Technologies, 2022
In education, the needs of learners are different in the majority of the time, as each has specificities in terms of preferences, performance and goals. Recommendation systems have proven to be an effective way to ensure this learning personalization. Already used and tested in other areas such as e-commerce, their adaptation to the educational…
Descriptors: Foreign Countries, Higher Education, Automation, Online Systems
Hongyu Xie; He Xiao; Yu Hao – International Journal of Web-Based Learning and Teaching Technologies, 2024
Modern e-learning system is a representative service form in innovative service industry. This paper designs a personalized service domain system, optimizes various parameters and can be applied to different education quality evaluation, and proposes a decision tree recommendation algorithm. Information gain is carried out through many existing…
Descriptors: Artificial Intelligence, Electronic Learning, Individualized Instruction, Models
Wenqiang Dai; Qiongyao Liu; Yuemin Gao; Wenjing Liu; Shaojuan Ouyang – International Journal of Web-Based Learning and Teaching Technologies, 2025
The traditional curriculum design methods suffer from issues like outdated content and limited instructional approaches. To address these, this article proposes an optimized curriculum design system that integrates CAD and neural network models. This system enables intelligent curriculum content generation, introduces CAD-assisted instructional…
Descriptors: Curriculum Design, Computer Assisted Design, Artificial Intelligence, Computer Uses in Education
Makhambetova, Aliya; Zhiyenbayeva, Nadezhda; Ergesheva, Elena – International Journal of Web-Based Learning and Teaching Technologies, 2021
The purpose of the research is to study and scientifically substantiate personalized strategies as the basis for personalized learning aimed at improving academic performance and student motivation. The study involved 65 teachers and 700 students of various specialties from three Russian and Kazakhstan universities. The survey analysis showed that…
Descriptors: Individualized Instruction, Learning Strategies, Academic Achievement, Student Motivation
El-Attar, Noha Ezzat; El-Ela, Niveen Abo; Awad, Wael A. – International Journal of Web-Based Learning and Teaching Technologies, 2019
Improving the performance of e-learning services to provide a scalable and effective e-learning system is a big challenge for the educational organizations. The e-learning system faces many challenges in pedagogical services (e.g. learning design and learning content problems), and technical services (e.g. resource provisioning and financial…
Descriptors: Electronic Learning, Individualized Instruction, Virtual Classrooms, Computer System Design
Nadira, Benmedakhene; Makhlouf, Derdour; Amroune, Mohamed – International Journal of Web-Based Learning and Teaching Technologies, 2021
The success of MOOC (massive open online courses) is rapidly increasing. Most educational institutions are highly interested in these online platforms, which embrace intellectual and educational objectives and provide various opportunities for lifelong learning. However, many limitations, such as learners' diversity, lack of motivation, affected…
Descriptors: Individualized Instruction, Computer Assisted Instruction, Online Courses, Open Education
Yang Chen – International Journal of Web-Based Learning and Teaching Technologies, 2025
With the rapid advancement of information technology, the Intelligent Teaching System (ITS) has emerged as a pivotal tool in mathematics education. This paper aims to evaluate the effectiveness of ITS by exploring its impact on personalized learning, increased student interaction and participation, intelligent assessment and feedback, teacher…
Descriptors: Learning Management Systems, Mathematics Education, Technology Uses in Education, Student Participation
Ni Li – International Journal of Web-Based Learning and Teaching Technologies, 2025
In depth exploration of how the pandemic has reshaped the education ecosystem over the past three years, especially in the context of the surge in demand for online education courses and learning platforms, this article focuses on the field of student ideological and political education, and innovatively constructs a moral and political education…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Algorithms
Singh, Ninni; Ahuja, Neelu Jyothi – International Journal of Web-Based Learning and Teaching Technologies, 2019
Face-to-face human tutoring in classroom environments amply facilitates human tutor-learner interactions wherein the tutor gets opportunity to exercise his cognitive intelligence to understand learner's pre-knowledge level, learning pattern, specific learning difficulties, and be able to offer course content well-aligned to the learner's…
Descriptors: Intelligent Tutoring Systems, Sequential Learning, Student Centered Learning, Curriculum Design
Oduwobi, Olukunle; Ojokoh, Bolanle Adefowoke – International Journal of Web-Based Learning and Teaching Technologies, 2015
Instructors recommend learning materials to a class of students not minding the learning ability and reading habit of each student. Learners are finding it problematic to make a decision about which available learning materials best meet their situation and will be beneficial to their course of study. In order to address this challenge, a new…
Descriptors: Electronic Learning, Individualized Instruction, Instructional Materials, Electronic Libraries
Mohamed, Hafidi; Lamia, Mahnane – International Journal of Web-Based Learning and Teaching Technologies, 2015
Learners usually meet cognitive overload and disorientation problems when using e-learning system. At present, most of the studies in e-learning either concentrate on the technological aspect or focus on adapting learner's interests or browsing behaviors, while, learner's skill level and learners' success rate is usually neglected. In this paper,…
Descriptors: Intelligent Tutoring Systems, Electronic Learning, Online Courses, Difficulty Level