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Frydenlund, Jonas Højgaard – Scandinavian Journal of Educational Research, 2023
In this ethnographic study, I present a single school's practice of registering and analysing absence from school. I show that teachers use various "dirty," interpretational contexts for understanding absence and make it classifiable in "clean" attendance categories -- a move that decontextualises the meaning of absence. When…
Descriptors: Ethnography, Attendance, Truancy, Classification
Majdi Beseiso – TechTrends: Linking Research and Practice to Improve Learning, 2025
Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…
Descriptors: Prediction, Success, Academic Achievement, Artificial Intelligence
Joanna Clifton-Sprigg; Jonathan James – British Educational Research Journal, 2025
Using newly released detailed data on absence from school, we find a 'Friday effect'--children are much less likely to attend schools in England on Fridays. We use daily level data across the whole of England and find that this pattern holds for different schools and for different types of absence, including illness-related authorised and…
Descriptors: Foreign Countries, Attendance Patterns, Student Behavior, Attendance
Kearney, Christopher A.; Childs, Joshua – Improving Schools, 2023
School attendance and absenteeism are critical targets of educational policies and practices that often depend heavily on aggregated attendance/absenteeism data. School attendance/absenteeism data in aggregated form, in addition to having suspect quality and utility, minimizes individual student variation, distorts detailed and multilevel…
Descriptors: Data Analysis, Attendance, Educational Policy, Causal Models
Nathan Jones; Lindsey Kaler; Jessica Markham; Josefina Senese; Marcus A. Winters – Educational Researcher, 2025
Students with and without disabilities may be educated across various service delivery models (SDMs): general education, cotaught, pull-out, and self-contained. Still, evidence for their relative effectiveness at scale remains limited. Using longitudinal administrative data from Indiana, we measured the effect of different SDMs on test scores,…
Descriptors: Students with Disabilities, Teaching Methods, Students, Instructional Effectiveness
Tonya Stewart-Magee – ProQuest LLC, 2024
This quantitative, causal-comparative study aims to examine the academic performance of all third-grade students who participated in after-school tutoring from English Language Arts (ELA) in comparison to those who did not, using the results from the 2022-2023 Mississippi Academic Assessment Program English Language Arts (MAAP ELA) assessment. The…
Descriptors: Grade 3, Elementary School Students, Tutoring, Language Arts
Kearney, Christopher A.; Childs, Joshua – Preventing School Failure, 2023
School attendance/absenteeism (SA/A) is a crucial indicator of health and development in youth but educational policies and health-based practices in this area rely heavily on a simple metric of physical presence or absence in a school setting. SA/A data suffer from problems of quality (reliability, construct validity, data integrity) and utility…
Descriptors: Attendance, Educational Policy, Health, Improvement
Shilpa Bhaskar Mujumdar; Haridas Acharya; Shailaja Shirwaikar; Prafulla Bharat Bafna – Journal of Applied Research in Higher Education, 2024
Purpose: This paper defines and assesses student learning patterns under the influence of problem-based learning (PBL) and their classification into a reasonable minimum number of classes. Study utilizes PBL implemented in an undergraduate Statistics and Operations Research course for techno-management students at a private university in India.…
Descriptors: Problem Based Learning, Information Retrieval, Data Analysis, Pattern Recognition
Selwyn, Neil; Pangrazio, Luci; Cumbo, Bronwyn – Research in Education, 2021
Contemporary schooling is seen to be altering significantly in light of a combined 'digitisation' and 'datafication' of key processes. This paper examines the nature and conditions of the datafied school by exploring how a relatively prosaic and longstanding school metric (student attendance data) is being produced and used in digital form.…
Descriptors: Data Analysis, Data Use, Attendance, School Personnel
Hideo Akabayashi; Ryuichi Tanaka – Education Economics, 2024
We present new estimates of the internal rate of return to early childhood education. Utilizing the nationwide expansion of preschool education in Japan between 1960 and 1980, we initially assess the impact of preschool attendance on high school graduation and college enrollment for men. Subsequently, we compute the social rate of return to…
Descriptors: Outcomes of Education, Early Childhood Education, Foreign Countries, School Expansion
Nancy Montes; Fernanda Luna – UNESCO International Institute for Educational Planning, 2024
This article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…
Descriptors: Data Collection, Data Use, At Risk Students, Foreign Countries
Yu, L. C.; Lee, C. W.; Pan, H. I.; Chou, C. Y.; Chao, P. Y.; Chen, Z. H.; Tseng, S. F.; Chan, C. L.; Lai, K. R. – Journal of Computer Assisted Learning, 2018
This study presents a model for the early identification of students who are likely to fail in an academic course. To enhance predictive accuracy, sentiment analysis is used to identify affective information from text-based self-evaluated comments written by students. Experimental results demonstrated that adding extracted sentiment information…
Descriptors: Prediction, Academic Failure, Models, Identification
Karnik, Ajit; Kishore, Pallavi; Meraj, Mohammad – Research in Comparative and International Education, 2020
The relationship between class attendance and academic performance has been an important area of research, with a positive association being posited between the two. The setting for our study is an International Branch Campus (IBC) of a British university that needs to demonstrate the quality of its service delivery both to the parent institution…
Descriptors: Correlation, Attendance, Academic Achievement, International Cooperation
Aydogdu, Seyhmus – Education and Information Technologies, 2020
Prediction of student performance is one of the most important subjects of educational data mining. Artificial neural networks are seen to be an effective tool in predicting student performance in e-learning environments. In the studies carried out with artificial neural networks, performance predictions based on student scores are generally made,…
Descriptors: Prediction, Academic Achievement, Electronic Learning, Artificial Intelligence
Paul T. von Hippel – Annenberg Institute for School Reform at Brown University, 2021
In an effort to reduce viral transmission, many schools are planning to reduce class size if they have not reduced it already. Yet the effect of class size on transmission is unknown. To determine whether smaller classes reduce school absence, especially when community disease prevalence is high, we merge data from the Project STAR randomized…
Descriptors: Attendance, Communicable Diseases, Class Size, Small Classes