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Stacey von Winckelmann – ProQuest LLC, 2023
The research problem addressed in this study is that racial bias programmed into predictive algorithm recommendations negatively impacts students in historically underrepresented groups. The purpose of this qualitative descriptive study was to explore the perception of algorithm accuracy among data professionals in higher education and explore the…
Descriptors: Prediction, Algorithms, Racism, Accuracy
Stacey Lynn von Winckelmann – Information and Learning Sciences, 2023
Purpose: This study aims to explore the perception of algorithm accuracy among data professionals in higher education. Design/methodology/approach: Social justice theory guided the qualitative descriptive study and emphasized four principles: access, participation, equity and human rights. Data collection included eight online open-ended…
Descriptors: Prediction, Algorithms, Racism, Accuracy
Michael Wade Ashby – ProQuest LLC, 2024
Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…
Descriptors: Artificial Intelligence, Algorithms, Prediction, Learning Management Systems
Ke Ting Chong; Noraini Ibrahim; Sharin Hazlin Huspi; Wan Mohd Nasir Wan Kadir; Mohd Adham Isa – Journal of Information Technology Education: Research, 2025
Aim/Purpose: The purpose of this study is to review and categorize current trends in student engagement and performance prediction using machine learning techniques during online learning in higher education. The goal is to gain a better understanding of student engagement prediction research that is important for current educational planning and…
Descriptors: Literature Reviews, Meta Analysis, Artificial Intelligence, Higher Education
Binbin Zhao; Rim Razzouk – International Journal of Web-Based Learning and Teaching Technologies, 2024
In order to promote the growth of contemporary music and the reform of music, this article designs an improved collaborative filtering (CF) algorithm to solve the problem of sparse matrix in traditional recommendation algorithms. The data matrix is dimensionally reduced to find the nearest neighbor, so as to realize personalized recommendation of…
Descriptors: Music Education, Higher Education, Teaching Methods, Matrices
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
Tanjea Ane; Tabatshum Nepa – Research on Education and Media, 2024
Precision education derives teaching and learning opportunities by customizing predictive rules in educational methods. Innovative educational research faces new challenges and affords state-of-the-art methods to trace knowledge between the teaching and learning ecosystem. Individual intelligence can only be captured through knowledge level…
Descriptors: Artificial Intelligence, Prediction, Models, Teaching Methods
Murad, Dina Fitria; Murad, Silvia Ayunda; Irsan, Muhamad – Journal of Educators Online, 2023
This study discusses the use of an online learning recommendation system as a smart solution related to changing the face-to-face learning process to online. This study uses user-based collaborative filtering, item-based collaborative filtering, and hybrid collaborative filtering. This research was conducted in two stages using the KNN machine…
Descriptors: Online Courses, Grades (Scholastic), Prediction, Context Effect
Kukkar, Ashima; Mohana, Rajni; Sharma, Aman; Nayyar, Anand – Education and Information Technologies, 2023
Predicting student performance is crucial in higher education, as it facilitates course selection and the development of appropriate future study plans. The process of supporting the instructors and supervisors in monitoring students in order to upkeep them and combine training programs to get the best outcomes. It decreases the official warning…
Descriptors: Academic Achievement, Mental Health, Well Being, Interaction
Kamdjou, Herve D. Teguim – Open Education Studies, 2023
This article revisits the Mincer earnings function and presents comparable estimates of the average monetary returns associated with an additional year of education across different regions worldwide. In contrast to the traditional Ordinary Least Squares (OLS) method commonly employed in the literature, this study applied a cutting-edge approach…
Descriptors: Outcomes of Education, Artificial Intelligence, Human Capital, Regression (Statistics)

Gray, John S. – Journal of Computing in Higher Education, 1994
A detailed analysis and computer-based solution to a puzzle addressing the arrangement of dominoes on a grid is presented. The problem is one used in a college-level data structures or algorithms course. The solution uses backtracking to generate all possible answers. Details of the use of backtracking and techniques for mapping abstract problems…
Descriptors: Algorithms, Computer Assisted Instruction, Computer Science Education, Computer Software

Wileman, Stanley; And Others – Journal of Educational Research, 1981
Eight factors were studied to determine their relationship to success in a beginning computer science course. Significant correlations were found between the final exam score and reading comprehension, sequence completion, logical reasoning, and algorithmic execution. (Authors/JN)
Descriptors: Academic Achievement, Academic Aptitude, Algorithms, Computer Science Education