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Jose Silva-Lugo; Heather Maness – Sage Research Methods Cases, 2025
The study provides a detailed methodological approach, cross-industry standard process for data mining, for predicting at-risk students with an imbalanced class. The objective was to identify the best machine learning model for predicting students at risk of failing the course during weeks 2-8 of the semester. We encountered issues in the dataset,…
Descriptors: Prediction, Predictor Variables, At Risk Students, Information Retrieval
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Sheng Lun; Hsin Ning Jessie Ho; Meilun Shih; Yeng-Horng Perng; Lucky Tsaih; Jyh-Chong Liang – International Journal of Technology and Design Education, 2025
Extensive research has highlighted the significant impact of students' approaches to learning and self-efficacy on academic achievement. It has been suggested that deep learning approaches, high self-efficacy, and strong academic performance are crucial for developing undergraduates' intentions to engage in sustainable lifelong learning after…
Descriptors: Self Efficacy, Academic Achievement, Learning Strategies, Design
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Sebastian Bergold; Ricarda Steinmayr – Child Development, 2024
Based on investment theories and guided by Mussel's (2013) intellect model, the present study investigated reciprocal relations over 1 year (2021-2022) between investment traits (need for cognition, achievement motives, epistemic curiosity) and fluid and crystallized cognitive abilities in 565 German elementary school children (298 girls;…
Descriptors: Personality Traits, Cognitive Ability, Elementary School Students, Student Motivation
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Meyers, Coby V.; Wronowski, Meredith L.; VanGronigen, Bryan A. – Educational Assessment, Evaluation and Accountability, 2021
School improvement research has insufficiently considered the importance of intervening in schools with declining academic performance. Fields such as engineering and medicine have prioritized predicting decline to save structures or patients before they are in peril. Unfortunately, in education, school improvement policies and interventions are…
Descriptors: Identification, Educational Improvement, Academic Achievement, Predictor Variables
Perkins, Ayanna – ProQuest LLC, 2023
Nationally, teacher candidates struggle to pass the Praxis examination, which they need to be licensed. Little research has been done to examine the characteristics and learning strategies of teacher candidates who pass and who do not pass the Praxis examination. Studies have shown benefits in the use of self-regulation and achievement in courses…
Descriptors: Preservice Teachers, Licensing Examinations (Professions), Teacher Certification, Learning Strategies
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Silvia Di Battista – British Journal of Educational Psychology, 2025
Background: According to gender-differentiated attributions of failure in the STEM field, errors tend to be attributed to internal factors more to girls than to boys. Aims: This experimental study explored factors influencing gender-differentiated teachers' internal attributions of girls' and boys' errors and the consequent likelihood of teachers'…
Descriptors: Gender Differences, Failure, Attribution Theory, STEM Education
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Montano, Renz Louis T. – Educational and Developmental Psychologist, 2023
Objective: The present study aimed to: (1) to determine how the two dimensions of perfectionism -- perfectionistic strivings (PS) and evaluative concerns (EC) are associated with academic engagement; and (2) to determine if failure mindset mediates the relationship between perfectionism and academic engagement. Method: Four hundred and forty-eight…
Descriptors: Undergraduate Students, Foreign Countries, Learner Engagement, Failure
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Jackie V. Calhoun – Quest, 2024
Athletic buoyancy is the ability to handle everyday challenges in sports, though little research has been conducted. Therefore, the purpose of this study was to examine intrapersonal and interpersonal factors related to athletic buoyancy, as well as a potential outcome variable. Collegiate club sport athletes (N = 239) completed a questionnaire…
Descriptors: Student Athletes, College Students, Predictor Variables, Anxiety
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Lydia Paulin Schidelko; Hannes Rakoczy – Cognitive Science, 2025
The standard view on Theory of Mind (ToM) is that the mastery of the false belief (FB) task around age 4 marks the ontogenetic emergence of full-fledged meta-representational ToM. Recently, a puzzling finding has emerged: Once children master the FB task, they begin to fail true belief (TB) control tasks. This finding threatens the validity of FB…
Descriptors: Childrens Attitudes, Theory of Mind, Beliefs, Young Children
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José M. Ortiz-Lozano; Pilar Aparicio-Chueca; Xavier M. Triadó-Ivern; Jose Luis Arroyo-Barrigüete – Studies in Higher Education, 2024
Student dropout is a major concern in studies investigating retention strategies in higher education. This study identifies which variables are important to predict student dropout, using academic data from 3583 first-year students on the Business Administration (BA) degree at the University of Barcelona (Spain). The results indicate that two…
Descriptors: Dropouts, Predictor Variables, Social Sciences, Law Students
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Wang, Qiang; Song, Xin; Hong, Jon-Chao; Li, Shuang; Zhang, Mengmeng; Yang, Xiantong – Education and Information Technologies, 2023
In response to the wide-ranging concern of online academic futility, the current study aimed to explore the independent variables and mediating variable from a novel perspective of parents during COVID-19. Based on the social comparison theory and the control-value theory of achievement emotions, social comparison and tutoring anxiety were…
Descriptors: Self Concept, Tutoring, Anxiety, Parent Attitudes
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Hui Shi; Nuodi Zhang; Secil Caskurlu; Hunhui Na – Journal of Computer Assisted Learning, 2025
Background: The growth of online education has provided flexibility and access to a wide range of courses. However, the self-paced and often isolated nature of these courses has been associated with increased dropout and failure rates. Researchers employed machine learning approaches to identify at-risk students, but multiple issues have not been…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, At Risk Students
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Eileen du Plooy; Daleen Casteleijn; Denise Franzsen; Gopika Ramkilawon – Journal of Occupational Therapy Education, 2025
Significant disparities in academic performance that may be associated with specific demographics can be utilized for supporting diverse student cohorts. Strategies can be developed for students to enhance equity and inclusivity in undergraduate occupational therapy education to ensure student success. This study aimed to determine the predictive…
Descriptors: Occupational Therapy, Allied Health Occupations Education, Academic Achievement, Predictor Variables
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Lucia Uguina-Gadella; Iria Estevez-Ayres; Jesus Arias Fisteus; Carlos Alario-Hoyos; Carlos Delgado Kloos – IEEE Transactions on Learning Technologies, 2024
Students learn not only directly from their teachers and books, but also by using their computers, tablets, and phones. Monitoring these learning environments creates new opportunities for teachers to track students' progress. In particular, this article is based on gathering real-time events as students interact with learning tools and materials…
Descriptors: Predictor Variables, Academic Achievement, Computer Assisted Instruction, Electronic Learning
Elaine M. Allensworth; Marisa de la Torre; Kaitlyn Franklin; Jinqing Xu – University of Chicago Consortium on School Research, 2025
This study explores how predictive different indicators are for high school graduation, college enrollment, and degree completion for different groups of English Learners. Using these indicators can improve schools' ability to understand the needs of English Learners, enabling them to provide better support and increase students' educational…
Descriptors: English Learners, Grades (Scholastic), High School Students, Grade Point Average
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