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Junfeng Man; Rongke Zeng; Xiangyang He; Hua Jiang – Knowledge Management & E-Learning, 2024
At present, the widespread use of online education platforms has attracted the attention of more and more people. The application of AI technology in online education platform makes multidimensional evaluation of students' ability become the trend of intelligent education in the future. Currently, most existing studies are based on traditional…
Descriptors: Cognitive Ability, Student Evaluation, Algorithms, Learning Processes
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
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
Anagha Ani; Ean Teng Khor – Education and Information Technologies, 2024
Predictive modelling in the education domain can be utilised to significantly improve teaching and learning experiences. Massive Open Online Courses (MOOCs) generate a large volume of data that can be exploited to predict and evaluate student performance based on various factors. This paper has two broad aims. Firstly, to develop and tune several…
Descriptors: MOOCs, Classification, Artificial Intelligence, Prediction
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
Senay Kocakoyun Aydogan; Turgut Pura; Fatih Bingül – Malaysian Online Journal of Educational Technology, 2024
In every culture and era, education is considered the most fundamental reality and rule that societies prioritize and deem essential. Throughout the process spanning thousands of years, from the emergence of writing to the present day, education has undergone various forms and formats of change. Education has been a continuous guide for shaping,…
Descriptors: Prediction, Academic Achievement, Artificial Intelligence, Algorithms
Meriem Zerkouk; Miloud Mihoubi; Belkacem Chikhaoui; Shengrui Wang – Education and Information Technologies, 2024
School dropout is a significant issue in distance learning, and early detection is crucial for addressing the problem. Our study aims to create a binary classification model that anticipates students' activity levels based on their current achievements and engagement on a Canadian Distance learning Platform. Predicting student dropout, a common…
Descriptors: Artificial Intelligence, Dropouts, Prediction, Distance Education
Nayak, Padmalaya; Vaheed, Sk.; Gupta, Surbhi; Mohan, Neeraj – Education and Information Technologies, 2023
Students' academic performance prediction is one of the most important applications of Educational Data Mining (EDM) that helps to improve the quality of the education process. The attainment of student outcomes in an Outcome-based Education (OBE) system adds invaluable rewards to facilitate corrective measures to the learning processes.…
Descriptors: Predictor Variables, Academic Achievement, Data Collection, Information Retrieval
Kenneth David Strang; Narasimha Rao Vajjhala – Industry and Higher Education, 2024
This study explores integrating industry-crowdsourced projects within capstone courses of a 4-year Bachelor of Science program at an accredited American university. A unique business consulting model was developed for the final year course, aligning students with 16-weeks industry projects that reflected their academic goals and the program's…
Descriptors: Industry, Universities, Higher Education, Capstone Experiences
Monique Crummie – ProQuest LLC, 2024
The purpose of this quantitative, correlational-predictive study was to assess if and to what extent second-grade student race (operationalized as minority status) and student socioeconomic status (operationalized as eligibility for Free and Reduced Lunch) predict second-grade student classification as gifted under two scenarios: using the current…
Descriptors: Predictor Variables, Classification, Academically Gifted, Minority Group Students
Yagci, Mustafa – Smart Learning Environments, 2022
Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic achievements. This study proposes a new model based on machine learning algorithms to predict the final exam grades of undergraduate students, taking their midterm exam grades as the source data. The…
Descriptors: Data Analysis, Academic Achievement, Prediction, Undergraduate Students
Xiaoxiao Liu; Jiahua Liu; Carrie Demmans Epp; Ying Cui – Educational Technology Research and Development, 2025
Parental involvement is essential to children's learning engagement activities and academic performance. Much research revolves around the impact of parental involvement on students' academic performance or the relationship between student engagement and grades. However, few studies have used process data to examine the relationship between…
Descriptors: Parent Participation, Parent Child Relationship, Learner Engagement, Academic Achievement
Seif Hashem Al-Azzam; Mohammad Al-Oudat – Educational Process: International Journal, 2025
Background/purpose: University students in Jordan face numerous challenges that affect their lifestyle on campus and academic performance. The most common challenges can be summarized into two important categories: psychological and academic factors. Psychological factors, such as anxiety levels and daily sleep duration, and academic factors such…
Descriptors: Artificial Intelligence, Technology Uses in Education, Classification, Prediction
Yan, Lixiang; Martinez-Maldonado, Roberto; Gallo Cordoba, Beatriz; Deppeler, Joanne; Corrigan, Deborah; Gaševic, Dragan – British Journal of Educational Technology, 2022
Identifying students facing difficulties and providing them with timely support is one of the educator's key responsibilities. Yet, this task is becoming increasingly challenging as the complexity of physical learning spaces grows, along with the emergence of novel educational technologies and classroom designs. There has been substantial research…
Descriptors: Student Behavior, Social Behavior, Elementary School Students, At Risk Students
Mourdi, Youssef; Sadgal, Mohammed; Berrada Fathi, Wafa; El Kabtane, Hamada – Turkish Online Journal of Distance Education, 2020
At the beginning of the 2010 decade, the world of education and more specifically e-learning was revolutionized by the emergence of Massive Open Online Courses, better known by their acronym MOOC. Proposed more and more by universities and training centers around the world, MOOCs have become an undeniable asset for any student or person seeking to…
Descriptors: Online Courses, Classification, Artificial Intelligence, Distance Education

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