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Jamal Kay B. Rogers; Tamara Cher R. Mercado; Ronald S. Decano – Journal of Education and Learning (EduLearn), 2025
Poor academic performance remains among the most concerning educational issues, especially in higher education and online learning. To address the concern, institutions like the University of Southeastern Philippines (USeP) leverage educational data mining (EDM) techniques to generate relevant information from learning management systems (LMS)…
Descriptors: Foreign Countries, Learning Management Systems, Academic Achievement, Data Analysis
Duran, Antonio; Okello, Wilson Kwamogi; Pérez, David, II – International Journal of Qualitative Studies in Education (QSE), 2023
Using Jackson and Mazzei's thinking with theory, this paper centers the stories of three researchers who practiced critical self-reflection while engaging in secondary analysis of data from The Pedagogy of Student Success Project, a study intended to learn about graduate students' evolving conceptualizations of student success. In particular, the…
Descriptors: Graduate Students, Educational Theories, Academic Achievement, Data Analysis
M. Nazir; A. Noraziah; M. Rahmah – International Journal of Virtual and Personal Learning Environments, 2023
An effective educational program warrants the inclusion of an innovative construction that enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational decision support system has currently been a hot topic in educational systems, facilitating the pupil…
Descriptors: Data Analysis, Academic Achievement, Artificial Intelligence, Prediction
Hussain, Asif; Khan, Muzammil; Ullah, Kifayat – Education and Information Technologies, 2022
Educational institutions are creating a considerable amount of data regarding students, faculty and related organs. This data is an essential asset for academic institutions as it has valuable insights, knowledge and intelligence for the policymakers. Students are the fundamental entities and primary source of data creation in any educational…
Descriptors: Data Analysis, Artificial Intelligence, Prediction, Academic Achievement
Achmad Bisri; Supardi; Yayu Heryatun; Hunainah; Annisa Navira – Journal of Education and Learning (EduLearn), 2025
In the educational landscape, educational data mining has emerged as an indispensable tool for institutions seeking to deliver exceptional and high-quality education. However, education data revealed suboptimal academic performance among a significant portion of the student population, which consequently resulted in delayed graduation. This…
Descriptors: Data Analysis, Models, Academic Achievement, Evaluation Methods
Cullinan, John; Flannery, Darragh; Palcic, Donal – Education Economics, 2022
There is increasing attention on study abroad programmes in higher education. However, there is little evidence on how participation might impact students' academic performance on return. Using administrative data from Ireland and a range of regression models and matching estimators, we find no independent association between study abroad and…
Descriptors: Study Abroad, Student Participation, Academic Achievement, Data Analysis
Alaa Althubaiti; Suha M. Althubaiti – SAGE Open, 2024
The flipped classroom (FC) is a pedagogical model with an active learning concept and a hybrid course design that reverses the typical lecture process. Given the widespread use of online delivery methods, there is a need to explore the FC in delivering statistics courses. This study employs a prospective quasi-experimental study design to evaluate…
Descriptors: Flipped Classroom, Statistics Education, Data Analysis, Computer Software
Mohd Elmagzoub Eltahir; Najeh Rajeh Alsalhi – Contemporary Educational Technology, 2025
As we examine the pandemic's impact on higher education, we can see that many previously traditional teaching and learning frameworks have been invalidated, and the need for new teaching and learning approaches has increased. This indicates that the traditional frameworks for higher education may no longer be effective. Consequently, there is a…
Descriptors: Foreign Countries, Academic Achievement, Flipped Classroom, Higher Education
Wen-shuang Fu; Jia-hua Zhang; Di Zhang; Tian-tian Li; Min Lan; Na-na Liu – Journal of Educational Computing Research, 2025
Cognitive ability is closely associated with the acquisition of programming skills, and enhancing learners' cognitive ability is a crucial factor in improving the efficacy of programming education. Adaptive feedback strategies can provide learners with personalized support based on their learning context, which helps to stimulate their interest…
Descriptors: Feedback (Response), Cognitive Ability, Programming, Computer Science Education
Robert J. Mills; Emily R. Fyfe; Tanya Beaulieu; Maddy Mills – Instructional Science: An International Journal of the Learning Sciences, 2024
Teachers form expectations that can influence their students' performance, and there are a variety of ways these expectations can be communicated. In the current study, we tested a novel method for communicating expectations via examples of student work--examples that contain basic, entry-level work and communicate low, but manageable expectations…
Descriptors: Teacher Expectations of Students, Academic Achievement, Teaching Methods, Communication (Thought Transfer)
Selma Tosun; Dilara Bakan Kalaycioglu – Journal of Educational Technology and Online Learning, 2024
Predicting and improving the academic achievement of university students is a multifactorial problem. Considering the low success rates and high dropout rates, particularly in open education programs characterized by mass enrollment, academic success is an important research area with its causes and consequences. This study aimed to solve a…
Descriptors: Academic Achievement, Open Education, Distance Education, Foreign Countries
Ge Bai – International Journal of Web-Based Learning and Teaching Technologies, 2025
This study focuses on the construction of the learner-centered teaching college English teaching mode under big data technology. Traditional college English teaching has issues, such as standardized teaching ignoring individual differences and lagging feedback. However, the development of big data technology offers opportunities for teaching…
Descriptors: Student Centered Learning, English Instruction, College Instruction, College Students
Bessadok, Adel; Abouzinadah, Ehab; Rabie, Osama – Interactive Technology and Smart Education, 2023
Purpose: This paper aims to investigate the relationship between the students' digital activities and their academic performance through two stages. In the first stage, students' digital activities were studied and clustered based on the attributes of their activity log of learning management system (LMS) data set. In the second stage, the…
Descriptors: Learning Activities, Academic Achievement, Learning Management Systems, Data Analysis
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
J. Bryan Osborne; Andrew S. I. D. Lang – Journal of Postsecondary Student Success, 2023
This paper describes a neural network model that can be used to detect at- risk students failing a particular course using only grade book data from a learning management system. By analyzing data extracted from the learning management system at the end of week 5, the model can predict with an accuracy of 88% whether the student will pass or fail…
Descriptors: Identification, At Risk Students, Learning Management Systems, Prediction