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Jamiu Adekunle Idowu – International Journal of Artificial Intelligence in Education, 2024
This systematic literature review investigates the fairness of machine learning algorithms in educational settings, focusing on recent studies and their proposed solutions to address biases. Applications analyzed include student dropout prediction, performance prediction, forum post classification, and recommender systems. We identify common…
Descriptors: Algorithms, Dropouts, Prediction, Academic Achievement
Brendan Bartanen; Andrew Kwok; Andrew Avitabile; Brian Heseung Kim – Grantee Submission, 2025
Heightened concerns about the health of the teaching profession highlight the importance of studying the early teacher pipeline. This exploratory, descriptive article examines preservice teachers' expressed motivation for pursuing a teaching career. Using data from a large teacher education program in Texas, we use a natural language processing…
Descriptors: Career Choice, Teaching (Occupation), Teacher Education Programs, Preservice Teachers
Masihay-Akbar, Hasti; Amiri, Parisa; Rezaei, Marjan; Jalali-Farahani, Sara; Cheraghi, Leila; Momenan, Amir Abbas; Azizi, Fereidoun – Journal of School Health, 2022
Background: This study assesses the long-term effectiveness of a lifestyle intervention on cigarette, passive, and hookah smoking in adolescent boys and girls. Methods: One thousand one hundred and fifty-nine adolescent participants of Tehran Lipid and Glucose Study (TLGS) (2001-2004) were followed for 12 years. Participants in the intervention…
Descriptors: Life Style, Intervention, Gender Differences, Health Behavior
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
Yanagiura, Takeshi – Community College Review, 2023
Objective: This study examines how accurately a small set of short-term academic indicators can approximate long-term outcomes of community college students so that decision-makers can take informed actions based on those indicators to evaluate the current progress of large-scale reform efforts on long-term outcomes, which in practice will not be…
Descriptors: Community Colleges, Community College Students, Educational Indicators, Outcomes of Education
Dolezel, Diane; Shanmugam, Ram; Morrison, Eileen E. – Journal of American College Health, 2020
Objective: To examine the health literacy of college students. Participants: A convenience sample of 245 graduate and undergraduate college students. Methods: During February-April of 2018 participants completed the Short Test of Functional Health Literacy which assessed literacy on two passages describing a thyroid scan, and basic healthcare…
Descriptors: Classification, Health, Literacy, Health Behavior
Light, Audrey; Rama, Apoorva – Education Economics, 2019
Using a sample of college graduates from the NLSY97, we introduce a new approach to assessing wage benefits of STEM training, STEM jobs, and the match between the two: rather than classify individuals dichotomously as STEM or non-STEM, we measure the STEM-intensities of both their college coursework and their occupational requirements. While the…
Descriptors: STEM Education, Gender Differences, Prediction, College Graduates
Yang, Jie; DeVore, Seth; Hewagallage, Dona; Miller, Paul; Ryan, Qing X.; Stewart, John – Physical Review Physics Education Research, 2020
Machine learning algorithms have recently been used to predict students' performance in an introductory physics class. The prediction model classified students as those likely to receive an A or B or students likely to receive a grade of C, D, F or withdraw from the class. Early prediction could better allow the direction of educational…
Descriptors: Artificial Intelligence, Man Machine Systems, Identification, At Risk Students
Lucas, Lyrica; Helikar, Tomáš; Dauer, Joseph – International Journal of Science Education, 2022
Comprehensive understanding of complex biological systems necessitates the use of computational models because they facilitate visualisation and interrogation of system dynamics and data-driven analysis. Computational model-based (CMB) activities have demonstrated effectiveness in improving students' understanding and their ability to use and…
Descriptors: Cytology, Science Instruction, Teaching Methods, Biology
Michel, George F.; Babik, Iryna; Sheu, Ching-Fan; Campbell, Julie M. – Developmental Psychology, 2014
Handedness for acquiring objects was assessed monthly from 6 to 14 months in 328 infants (182 males). A group based trajectory model identified 3 latent groups with different developmental trajectories: those with an identifiable right preference (38%) or left preference (14%) and those without an identifiable preference (48%) but with a…
Descriptors: Infants, Handedness, Child Development, Lateral Dominance
Cen, Ling; Ruta, Dymitr; Powell, Leigh; Hirsch, Benjamin; Ng, Jason – International Journal of Computer-Supported Collaborative Learning, 2016
The benefits of collaborative learning, although widely reported, lack the quantitative rigor and detailed insight into the dynamics of interactions within the group, while individual contributions and their impacts on group members and their collaborative work remain hidden behind joint group assessment. To bridge this gap we intend to address…
Descriptors: Cooperative Learning, Statistical Analysis, Group Dynamics, Group Activities
Saint-Maurice, Pedro F.; Welk, Gregory J.; Finn, Kevin J.; Kaj, Mónika – Research Quarterly for Exercise and Sport, 2015
Purpose: The purpose of this article was to evaluate the validity of the Progressive Aerobic Cardiovascular and Endurance Run (PACER) test in a sample of Hungarian youth. Method: Approximately 500 participants (aged 10-18 years old) were randomly selected across Hungary to complete both laboratory (maximal treadmill protocol) and field assessments…
Descriptors: Prediction, Foreign Countries, Physical Fitness, Physical Activities
Allen, Caitlan E. – ProQuest LLC, 2018
Background and Objective: Research has repeatedly found that students who have not developed sufficient reading skills by the third grade have lower rates of high school graduation and post high school outcomes. A growing body of literature has examined how the use of curriculum-based measurements (CBMs) can be used to identify these struggling…
Descriptors: Grade 1, Elementary School Students, Screening Tests, Reading Skills
Marcotte, Amanda M.; Clemens, Nathan H.; Parker, Christopher; Whitcomb, Sara A. – Assessment for Effective Intervention, 2016
This study investigated the classification accuracy of the "Dynamic Indicators of Vocabulary Skills" (DIVS) as a preschool vocabulary screening measure. With a sample of 240 preschoolers, fall and winter DIVS scores were used to predict year-end vocabulary risk using the 25th percentile on the "Peabody Picture Vocabulary Test--Third…
Descriptors: Classification, Preschool Children, Vocabulary, Screening Tests
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
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