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Changpetch, Pannapa; Reid, Moya – Journal of Education for Business, 2021
Based on a statistical analysis, undergraduate business students are shown to prefer classification tree over six other standard data mining techniques. Data were collected over a 4-year period from students taking a data mining course offered at a business university in the US. The principal reason given by students for this preference is that…
Descriptors: Data Analysis, Models, Statistical Analysis, Undergraduate Students
Demir, Seda; Doguyurt, Mehmet Fatih – African Educational Research Journal, 2022
The purpose of this research was to compare the performances of the Fixed Effect Model (FEM) and the Random Effects Model (REM) in the meta-analysis studies conducted through 5, 10, 20 and 40 studies with an outlier and 4, 9, 19 and 39 studies without an outlier in terms of estimated common effect size, confidence interval coverage rate and…
Descriptors: Meta Analysis, Comparative Analysis, Research Reports, Effect Size
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
Czyzewska, Marta; Mroczek, Teresa – Education Sciences, 2020
The aim of the paper is to diagnose the entrepreneurship competency levels among students to identify differences in competencies and their levels regarding gender, material status, and professional situation. In addition, the goal of the analysis is to indicate the competencies that need to be strengthened among individual groups of students. The…
Descriptors: Data Analysis, Entrepreneurship, Competence, Foreign Countries
Hung, Jui-Long; Shelton, Brett E.; Yang, Juan; Du, Xu – IEEE Transactions on Learning Technologies, 2019
Performance prediction is a leading topic in learning analytics research due to its potential to impact all tiers of education. This study proposes a novel predictive modeling method to address the research gaps in existing performance prediction research. The gaps addressed include: the lack of existing research focus on performance prediction…
Descriptors: Prediction, Models, At Risk Students, Identification
Evale, Digna S. – Journal of Information Technology Education: Research, 2017
Aim/Purpose: This study is an attempt to enhance the existing learning management systems today through the integration of technology, particularly with educational data mining and recommendation systems. Background: It utilized five-year historical data to find patterns for predicting student performance in Java Programming to generate…
Descriptors: Integrated Learning Systems, Technology Integration, Educational Technology, Technology Uses in Education
Izadi, Dina; Ley, César Eduardo Mora; Díaz, Mario Humberto Ramírez – Physics Education, 2017
Succeeding theories and empirical investigations have often been built over conceptual understanding to develop talent education. Opportunities provided by society are crucial at every point in the talent-development process. Abilities differ and can vary among boys and girls. Although they have some responsibility for their own growth and…
Descriptors: Foreign Countries, Science Education, Student Motivation, Student Attitudes
Anderson, Ariana; Locke, Jill; Kretzmann, Mark; Kasari, Connie – Autism: The International Journal of Research and Practice, 2016
Although children with autism spectrum disorder are frequently included in mainstream classrooms, it is not known how their social networks change compared to typically developing children and whether the factors predictive of this change may be unique. This study identified and compared predictors of social connectivity of children with and…
Descriptors: Social Networks, Network Analysis, Elementary School Students, Autism
Gray, Geraldine; McGuinness, Colm; Owende, Philip; Hofmann, Markus – Journal of Learning Analytics, 2016
This paper reports on a study to predict students at risk of failing based on data available prior to commencement of first year. The study was conducted over three years, 2010 to 2012, on a student population from a range of academic disciplines, n=1,207. Data was gathered from both student enrollment data and an online, self-reporting,…
Descriptors: Prediction, At Risk Students, Academic Failure, College Freshmen
Chen, Chih-Ming; Wang, Jung-Ying; Chen, Yong-Ting; Wu, Jhih-Hao – Interactive Learning Environments, 2016
To reduce effectively the reading anxiety of learners while reading English articles, a C4.5 decision tree, a widely used data mining technique, was used to develop a personalized reading anxiety prediction model (PRAPM) based on individual learners' reading annotation behavior in a collaborative digital reading annotation system (CDRAS). In…
Descriptors: Reading Strategies, Prediction, Models, Quasiexperimental Design
Edgerton, Jason; Peter, Tracey; Roberts, Lance – Alberta Journal of Educational Research, 2014
Bourdieu's theory of cultural and social reproduction posits that students' habitus--learned behavioural and perceptual dispositions rooted in family upbringing--is a formative influence on how they react to their educational environments, affecting academic practices and academic achievement. Although originally conceived as a "class"…
Descriptors: Gender Differences, Academic Achievement, Investigations, Models
Frantz, Kyle J.; Demetrikopoulos, Melissa K.; Britner, Shari L.; Carruth, Laura L.; Williams, Brian A.; Pecore, John L.; DeHaan, Robert L.; Goode, Christopher T. – CBE - Life Sciences Education, 2017
Undergraduate research experiences confer benefits on students bound for science, technology, engineering, and mathematics (STEM) careers, but the low number of research professionals available to serve as mentors often limits access to research. Within the context of our summer research program (BRAIN), we tested the hypothesis that a team-based…
Descriptors: Undergraduate Students, Student Characteristics, Personality Traits, Career Development
Brooks-Russell, Ashley; Foshee, Vangie A.; Ennett, Susan T. – Journal of Youth and Adolescence, 2013
This study identified classes of developmental trajectories of physical dating violence victimization from grades 8 to 12 and examined theoretically-based risk factors that distinguished among trajectory classes. Data were from a multi-wave longitudinal study spanning 8th through 12th grade (n = 2,566; 51.9 % female). Growth mixture models were…
Descriptors: Risk, Drinking, Gender Differences, Victims
Conner, Laura D. Carsten; Danielson, Jennifer – International Journal of Science Education, 2016
Gender-matched role models are often proposed as a mechanism to increase identification with science among girls, with the ultimate aim of broadening participation in science. While there is a great deal of evidence suggesting that role models can be effective, there is mixed support in the literature for the importance of gender matching. We used…
Descriptors: Science Education, Scientists, Role Models, Females
Ormel, Johan; Oldehinkel, Albertine J.; Sijtsema, Jelle; van Oort, Floor; Raven, Dennis; Veenstra, Rene; Vollebergh, Wilma A. M.; Verhulst, Frank C. – Journal of the American Academy of Child & Adolescent Psychiatry, 2012
Objectives: The objectives of this study were as follows: to present a concise overview of the sample, outcomes, determinants, non-response and attrition of the ongoing TRacking Adolescents' Individual Lives Survey (TRAILS), which started in 2001; to summarize a selection of recent findings on continuity, discontinuity, risk, and protective…
Descriptors: Psychopathology, Mental Health, Adolescents, Anxiety