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Nargiza Mikhridinova; Carsten Wolff; Wim Van Petegem – Education and Information Technologies, 2024
An individual competence is one of the main human resources, which enables a person to operate in everyday life. A competence profile, formally captured and described as a structured model, may enable various operations, e.g., a more precise evaluation and closure of a training gap. Such application scenarios supported by information systems are…
Descriptors: Taxonomy, Competence, Models, Profiles
Nabila Khodeir; Fatma Elghannam – Education and Information Technologies, 2025
MOOC platforms provide a means of communication through forums, allowing learners to express their difficulties and challenges while studying various courses. Within these forums, some posts require urgent attention from instructors. Failing to respond promptly to these posts can contribute to higher dropout rates and lower course completion…
Descriptors: MOOCs, Computer Mediated Communication, Conferences (Gatherings), Models
Caihong Feng; Jingyu Liu; Jianhua Wang; Yunhong Ding; Weidong Ji – Education and Information Technologies, 2025
Student academic performance prediction is a significant area of study in the realm of education that has drawn the interest and investigation of numerous scholars. The current approaches for student academic performance prediction mainly rely on the educational information provided by educational system, ignoring the information on students'…
Descriptors: Academic Achievement, Prediction, Models, Student Behavior
Kajal Mahawar; Punam Rattan – Education and Information Technologies, 2025
Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…
Descriptors: Electronic Learning, Artificial Intelligence, Academic Achievement, Prediction
Yan Yang; Yoon Fah Lay – Education and Information Technologies, 2025
The global impact of COVID in 2020 is forcing higher education institutions in many countries to adopt a hybrid model of education. The shift to blended education has been trending globally. However, the change in pedagogy has reduced the quality of students' learning experience and prevented them from deep learning. Therefore, the current study…
Descriptors: Blended Learning, Higher Education, Resilience (Psychology), Teacher Role
Monsalve-Pulido, Julian; Aguilar, Jose; Montoya, Edwin – Education and Information Technologies, 2023
The adaptation of traditional systems to service-oriented architectures is very frequent, due to the increase in technologies for this type of architecture. This has led to the construction of frameworks or methodologies for adapting computational projects to service-oriented architecture (SOA) technology. In this work, a framework for adaptation…
Descriptors: Artificial Intelligence, Information Technology, Design, Governance
Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
Ahmed A. Alsayer; Jonathan Templin; Chris Niileksela; Bruce B. Frey – Education and Information Technologies, 2025
Prior research on the "Community of Inquiry" (CoI) framework has a limited amount of work which uses structural techniques to confirm the factorial structure of the CoI. The current study investigates the structural relationships among the three elements of the CoI framework (cognitive presence, teaching presence, and social presence),…
Descriptors: Communities of Practice, Inquiry, Online Courses, Educational Experience
Adil Boughida; Mohamed Nadjib Kouahla; Yacine Lafifi – Education and Information Technologies, 2024
In e-learning environments, most adaptive systems do not consider the learner's emotional state when recommending activities for learning difficulties, blockages, or demotivation. In this paper, we propose a new approach of emotion-based adaptation in e-learning environments. The system will allow recommendation resources/activities to motivate…
Descriptors: Psychological Patterns, Electronic Learning, Educational Environment, Models
Fu Chen; Chang Lu; Ying Cui – Education and Information Technologies, 2024
Successful computer-based assessments for learning greatly rely on an effective learner modeling approach to analyze learner data and evaluate learner behaviors. In addition to explicit learning performance (i.e., product data), the process data logged by computer-based assessments provide a treasure trove of information about how learners solve…
Descriptors: Computer Assisted Testing, Problem Solving, Learning Analytics, Learning Processes
Linyan Li; Xiao Bai; Hongshan Xia – Education and Information Technologies, 2024
The higher the level of development of higher education, the larger its contribution to socioeconomic development. In order to predict the trend of higher education development in a country more accurately, a new methodology is employed in this study. A weakening buffer operator-based GM (1, 1) model is constructed using Kazakhstan's gross…
Descriptors: Prediction, Educational Trends, Higher Education, Models
Hayat Sahlaoui; El Arbi Abdellaoui Alaoui; Said Agoujil; Anand Nayyar – Education and Information Technologies, 2024
Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…
Descriptors: Sampling, Classification, Algorithms, Prediction
Yuan Liu; Yongquan Dong; Chan Yin; Cheng Chen; Rui Jia – Education and Information Technologies, 2024
The open online course (MOOC) platform has seen an increase in usage, and there are a growing number of courses accessible for people to select. An effective method is urgently needed to recommend personalized courses for users. Although the existing course recommendation models consider that users' interests change over time, they often model…
Descriptors: MOOCs, Online Courses, Models, Course Selection (Students)
A Method for Generating Course Test Questions Based on Natural Language Processing and Deep Learning
Hei-Chia Wang; Yu-Hung Chiang; I-Fan Chen – Education and Information Technologies, 2024
Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…
Descriptors: Natural Language Processing, Test Construction, Test Items, Models
Liang, Zibo; Mu, Lan; Chen, Jie; Xie, Qing – Education and Information Technologies, 2023
In recent years, online learning methods have gradually been accepted by more and more people. A large number of online teaching courses and other resources (MOOCs) have also followed. To attract students' interest in learning, many scholars have built recommendation systems for MOOCs. However, students need a variety of different learning…
Descriptors: MOOCs, Artificial Intelligence, Graphs, Educational Resources