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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
Mohamed Zine; Fouzi Harrou; Mohammed Terbeche; Ying Sun – Education and Information Technologies, 2025
E-learning readiness (ELR) is critical for implementing digital education strategies, particularly in developing countries where online learning faces unique challenges. This study aims to provide a concise and actionable framework for assessing and predicting ELR in Algerian universities by combining the ADKAR model with advanced machine learning…
Descriptors: Electronic Learning, Learning Readiness, Artificial Intelligence, Organizational Change
Daniel Kangwa; Mgambi Msambwa Msafiri; Antony Fute – Journal of Computer Assisted Learning, 2025
Background: This study explored the factors that influence the balance between academic integrity and the effective use of GenAI tools in higher education. It focused on the role of institutional guidelines in enhancing the responsible use of GenAI technologies to enhance academic integrity. Objectives: The study was theoretically grounded in the…
Descriptors: Integrity, Artificial Intelligence, Technology Uses in Education, Higher Education
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
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
Ahmed Alkaabi; Asma Abdallah; Shamma Alblooshi; Fatima Alomari; Sara Alneaimi – Journal of Education and e-Learning Research, 2025
This study examines the opportunities and challenges of employing ChatGPT in higher education, identifies essential user competencies, and evaluates its impact in the absence of formal policy guidelines. A qualitative case study design involved interviews with 10 faculty members and 10 students at a federal university in the United Arab Emirates.…
Descriptors: Artificial Intelligence, Teaching Methods, Computer Software, Higher Education
David B. Nelson; Anaelle Emma Gackiere; Samantha Elizabeth LeGrand; Daniel A. Guberman – Thresholds in Education, 2025
In response to the significant disruption posed by emergent AI technology, we propose a four part framework for teaching and learning practice and development. Rather than focus on the specific technologies of the moment, this framework provides actionable suggestions for individuals with varying views of AI and its positive and negative…
Descriptors: Teaching Methods, Learning Processes, Algorithms, Artificial Intelligence
Peer reviewedHodgson, Ted – Educational Studies in Mathematics, 1996
Analysis of (n=92) university students' construction of visual representations (Venn diagrams) of eight set expressions found competent and error-prone students constructed and used procedures to complete set translation tasks, and two-thirds of observed errors arose from consistent implementation of ill-formed procedures. (Author/MKR)
Descriptors: Algorithms, College Students, Higher Education, Mathematics Skills
Carlsen, William S.; Single, Peg Boyle – 2000
This paper reports findings from a comprehensive evaluation of the first national electronic mentoring program that matches female engineering students with mentors working in industry. The program being evaluated--MentorNet--uses a combination of on-line tools, computer databases, mentoring specialists, and campus and industrial contacts to…
Descriptors: Algorithms, College Students, Electronic Mail, Engineering Education
Peer reviewedNaveh-Benjamin, Moshe; And Others – Journal of Educational Psychology, 1986
This article presents a new method of inferring students' cognitive structures and their development. A modification of Reitman and Rueter's "ordered tree technique," the method generates a structure that displays important relationships assumed to be in a student's memory about concepts taken from a specific field of study. (Author/LMO)
Descriptors: Algorithms, Analysis of Variance, Cognitive Development, Cognitive Structures
Gallagher, Ann; Mandinach, Ellen – 1992
Twenty-four students who scored 650 or more on the Scholastic Aptitude Test Mathematics test (SAT-M) were asked to think aloud while solving 13 mathematics items in either multiple-choice or free-response format. Strategies students used to solve the items were classified as either algorithmic or insightful. Data analyses indicated that items in…
Descriptors: Algorithms, College Students, Higher Education, Mathematics Tests
Peer reviewedBockenholt, Ulf; Bockenholt, Ingo – Psychometrika, 1991
A reparameterization of a latent class model is presented to classify and scale nomial and ordered categorical choice data simultaneously. The model extension represents a nonhomogeneous population as a mixture of homogeneous subpopulations. Simulated data and data from a magazine preference survey of 347 college students illustrate the model.…
Descriptors: Algorithms, Classification, College Students, Computer Simulation
Roddick, Cheryl Stitt – 1995
This study investigated students' conceptual and procedural understanding of calculus within the context of an engineering mechanics course. Four traditional calculus students were compared with three students from one of the calculus reform projects, Calculus & Mathematica. Task-based interviews were conducted with each participant throughout…
Descriptors: Algorithms, Calculus, Cognitive Style, College Students
Peer reviewedBurston, Jack; Monville-Burston, Monique – CALICO Journal, 1995
Describes the academic context in which the "French CAT" was created and trialed and gives a detailed consideration of the test presentation platform and operating algorithms. Finally, the article evaluates the first administration of the test and discusses its reliability and validity as a placement instrument for first-year Australian…
Descriptors: Achievement Tests, Algorithms, College Students, Computer Assisted Testing
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