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Agus Santoso; Heri Retnawati; Kartianom; Ezi Apino; Ibnu Rafi; Munaya Nikma Rosyada – Open Education Studies, 2024
The world's move to a global economy has an impact on the high rate of student academic failure. Higher education, as the affected party, is considered crucial in reducing student academic failure. This study aims to construct a prediction (predictive model) that can forecast students' time to graduation in developing countries such as Indonesia,…
Descriptors: Time to Degree, Open Universities, Foreign Countries, Predictive Measurement
Jialun Pan; Zhanzhan Zhao; Dongkun Han – IEEE Transactions on Learning Technologies, 2025
Properly predicting students' academic performance is crucial for elevating educational outcomes in various disciplines. Through precise performance prediction, schools can quickly pinpoint students facing challenges and provide customized educational materials suited to their specific learning needs. The reliance on teachers' experience to…
Descriptors: Prediction, Academic Achievement, At Risk Students, Artificial Intelligence
Khue N. Tran – ProQuest LLC, 2022
The main objective of this dissertation was to investigate factors that affect decision-makers' trust in and reliance on algorithmic predictions as decision aids in the context of college admission prediction tasks. College admission officers often made predictions about the applicants' future success based on multiple pieces of available…
Descriptors: Algorithms, College Admission, Prediction, Academic Achievement
John Pace; John Hansen; John Stewart – Physical Review Physics Education Research, 2024
Machine learning models were constructed to predict student performance in an introductory mechanics class at a large land-grant university in the United States using data from 2061 students. Students were classified as either being at risk of failing the course (earning a D or F) or not at risk (earning an A, B, or C). The models focused on…
Descriptors: Artificial Intelligence, Identification, At Risk Students, Physics
Fatima, Saba – ProQuest LLC, 2023
Predicting students' performance to identify which students are at risk of receiving a D/Fail/Withdraw (DFW) grade and ensuring their timely graduation is not just desirable but also necessary in most educational entities. In the US, not only is the Science, Technology, Engineering, and Mathematics (STEM) major becoming less popular among…
Descriptors: Artificial Intelligence, Prediction, Outcomes of Education, At Risk Students
Parhizkar, Amirmohammad; Tejeddin, Golnaz; Khatibi, Toktam – Education and Information Technologies, 2023
Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…
Descriptors: Algorithms, Grade Point Average, Interdisciplinary Approach, Prediction
William Parker Morgan IV – ProQuest LLC, 2020
Accurate placement into an initial college mathematics course is a key step toward the successful completion of college mathematics and, eventually, a college degree. Conversely, misplacement in mathematics may lead to a reduced likelihood of course completion and degree attainment. This study investigated the ability of two placement models to…
Descriptors: College Mathematics, College Students, Student Placement, Mathematics Achievement
Kalelioglu, Filiz; Dogan, Dilek; Gulbahar, Yasemin – Informatics in Education, 2022
This study aims to provide a deeper understanding about the Bebras tasks, which is one of the computational thinking (CT) unplugged activities, in terms of age level, task category, and CT skills. Explanatory sequential mixed method was adopted in the study in order to collect data according to the research questions. The participants of the study…
Descriptors: Foreign Countries, Computation, Thinking Skills, Problem Solving