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Shabnam Ara S. J.; Tanuja Ramachandriah; Manjula S. Haladappa – Online Learning, 2025
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…
Descriptors: Learning Analytics, Privacy, Artificial Intelligence, Regression (Statistics)
MOOC Performance Prediction and Analysis via Bayesian Network and Maslow's Hierarchical Needs Theory
Luyu Zhu; Jia Hao; Jianhou Gan – Interactive Learning Environments, 2024
Nowadays, Massive Open Online Courses (MOOC) has been gradually accepted by the public as a new type of education and teaching method. However, due to the lack of timely intervention and guidance from educators, learners' performance is not as effective as it could be. To address this problem, predicting MOOC learners' performance and providing…
Descriptors: MOOCs, Academic Achievement, Prediction, Bayesian Statistics
Giselle Larissa Allsopp; Sarah Elizabeth Wooding; Jan Maree West; Anne Isabella Turner – Advances in Physiology Education, 2025
Optimizing the workload of university students is important for their academic performance and student experience. Large perceived workloads are associated with poorer academic performance and lower student satisfaction in university students. In response to student feedback in 2021, we redesigned a second-year undergraduate physiology subject to…
Descriptors: Time on Task, Student Experience, Undergraduate Students, Physiology
Zhaofeng Zeng; Siew Wei Tho; Zhengfang Gao; Nur Hamiza Adenan; Sue Ting Ng – International Journal of Education in Mathematics, Science and Technology, 2024
This study aims to review the STEM education intervention on the undergraduate level by applying CiteSpace software, an innovative tool for bibliometric analysis and visualization. The Web of Science (WOS) database was used and covers the period from January 2008 to August 2023. Based on keyword search, seven clusters with the largest research…
Descriptors: STEM Education, Undergraduate Students, Databases, Information Retrieval
Yao, Jing; Yao, Jijun; Li, Peixuan; Xu, Yifan; Wei, Lai – Science Insights Education Frontiers, 2023
The after-school program is a crucial initiative for implementing the Double Reduction policy; however, prior research has not provided conclusive evidence on whether extended school hours contribute to students' cognitive and non-cognitive development or on which types of after-school services are more beneficial for student development. This…
Descriptors: After School Programs, Students, Cognitive Ability, Ability
Erica Harbatkin; Jason Burns; Samantha Cullum – Education Policy Innovation Collaborative, 2023
School climate is critical to school effectiveness, but there is limited large-scale data available to examine the magnitude and nature of the relationship between school climate and school improvement. Drawing on statewide administrative data linked with unique teacher survey data in Michigan, we examine whether school climate appeared to play a…
Descriptors: Educational Environment, School Turnaround, Trust (Psychology), Leadership Role
Corin D. Mathews – South African Journal of Childhood Education, 2025
Background: Base-ten thinking (BTT) -- children's ability to reason in tens and ones is a crucial measure of Foundation Phase learners' mathematical performance in South Africa. Aim: The study looks at the six learners using BTT to solve additive tasks through two different assessments. Setting: Six purposely selected Grade 3 learners in…
Descriptors: Evaluation Methods, Task Analysis, High Achievement, Low Achievement
Cohausz, Lea – Journal of Educational Data Mining, 2022
Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…
Descriptors: Guidelines, Academic Achievement, Dropouts, Prediction
Gumaelius, Lena; Hartell, Eva; Svärdh, Joakim; Skogh, Inga-Britt; Buckley, Jeffrey – International Journal of Technology and Design Education, 2019
In Sweden, there have been multiple large scale interventions to support compulsory school teachers generally and within specific subjects. Due to the costs associated with such interventions it is critical that interim evaluation measures exist which can indicate potential success. Additionally, evaluation measures which can measure the actual…
Descriptors: Foreign Countries, Intervention, Technology Education, Evaluation Methods
What Works Clearinghouse, 2023
The What Works Clearinghouse (WWC) Study Review Protocol accompanies the "WWC Procedures and Standards Handbook, Version 5.0," and guides reviews of studies by the WWC. The WWC uses this protocol to review all studies, including those cited as evidence for U.S. Department of Education grant competitions, studies that were funded by the…
Descriptors: Educational Research, Evaluation Methods, Eligibility, Selection Criteria
Lundine, Jennifer P. – Topics in Language Disorders, 2020
For academic success, it is increasingly important that students of all ages can produce and comprehend expository discourse. This article provides guidance to clinicians and educators on using language sample analysis (LSA) to assess the expository language abilities of students across grades. Focusing on microstructural and macrostructural…
Descriptors: Elementary School Students, Middle School Students, High School Students, Academic Achievement
Agley, Jon; Tidd, David; Jun, Mikyoung; Eldridge, Lori; Xiao, Yunyu; Sussman, Steve; Jayawardene, Wasantha; Agley, Daniel; Gassman, Ruth; Dickinson, Stephanie L. – Educational and Psychological Measurement, 2021
Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…
Descriptors: Data Analysis, Longitudinal Studies, Data Collection, Intervention
Barkat, Shaheen – British Educational Research Journal, 2019
Evaluating the impact of widening participation interventions can be challenging. This article discusses some of the difficulties in "attributing" change to complex widening participation interventions and suggests that the Theory of Change (ToC) approach can address some of these challenges by evidencing the "contribution"…
Descriptors: Selective Admission, Universities, Access to Education, Enrichment Activities
Fulya Y. Ersoy – Annenberg Institute for School Reform at Brown University, 2021
How does the perceived relationship between effort and achievement affect effort? To answer this question, I conduct a field experiment with a popular online learning platform. I exogenously manipulate students' beliefs about returns to effort by assigning them to different information treatments, each of which provides factual information.…
Descriptors: Productivity, Electronic Learning, Beliefs, Student Attitudes
McComb, Bruce E.; Lyddon, Jan W. – New Directions for Community Colleges, 2016
This chapter discusses the importance and common challenges of evaluating community college student success efforts; it includes a broad-based framework for carrying out effective evaluations.
Descriptors: Academic Achievement, Intervention, Community Colleges, Two Year College Students