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Tyler Milburn; Meagan E. Ita; Krista M. Kecskemety – Discover Education, 2025
A better understanding of how to improve student retention in engineering is required to support students in completing engineering degrees and entering the workforce. Application processes to engineering majors are one barrier to retention in some engineering programs. This study evaluates demographic, grades, application process, and engineering…
Descriptors: College Students, Majors (Students), Engineering Education, Predictor Variables
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Jonathan Steinberg; Carol Forsyth; Jessica Andrews-Todd – ETS Research Report Series, 2024
In a study of 370 postsecondary students in electronics, engineering, and other science classes, we investigated collaborative problem-solving (CPS) skills that best predict performance at individual levels in an online electronics environment. The results showed that while monitoring was a consistent predictor across levels, other skills such as…
Descriptors: Problem Solving, Predictor Variables, Performance, Task Analysis
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Phan, Nga Thi Tuyet – Knowledge Management & E-Learning, 2023
Most previous studies have focused on learners' self-efficacy in face-to-face learning environments, while few have delved into that of MOOC learners. No research has touched upon the MOOC self-efficacy of engineering students in developed and developing countries. This research compared the self-efficacy levels of engineering students in Taiwan…
Descriptors: Self Efficacy, MOOCs, Comparative Analysis, Foreign Countries
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Harun Cigdem; Semiral Oncu – TechTrends: Linking Research and Practice to Improve Learning, 2025
Despite efforts to implement innovative approaches such as flipped learning leveraging computer technology, the challenge of student failure persists. Understanding the factors that contribute to student success in flipped engineering courses remains a critical issue. This study addresses this issue by investigating the impact of student…
Descriptors: Gamification, Flipped Classroom, Learner Engagement, Learning Readiness
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Yanyao Deng; Chao Shi – Journal of Applied Research in Higher Education, 2024
Purpose: This study aims to evaluate student motivation before and after the summer internship, in other words, to evaluate whether the summer internship affects male and female motivations differently. Design/methodology/approach: Investigating whether the motivation score predicts grade point average was included by adopting a quantitative…
Descriptors: Student Motivation, Engineering Education, Military Training, Active Learning
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Van Wyk, Barend; Mason, Henry D. – Cogent Education, 2021
This article reports on a study investigating the relationship between university students' self-reported use and application of learning and study strategies and student success indicators (timeframe and student type, namely low-performing, average-performing, or high-performing). Participants were 1,439 engineering students enrolled for academic…
Descriptors: Learning Strategies, Engineering Education, College Students, Foreign Countries
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Sahoo, Swagatika; Panda, Rajeev Kumar – Education & Training, 2019
Purpose: The purpose of this paper is to empirically investigate the impact of the contextual antecedents on the individual entrepreneurial orientation (IEO) of university graduates, which, in turn, affects their entrepreneurial intentions (EIs). Design/methodology/approach: Primary data were collected in the form of 510 valid responses from…
Descriptors: Entrepreneurship, Intention, College Students, Engineering Education
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Alalouch, Chaham – Education Sciences, 2021
Cognitive styles affect the learning process positively if tasks are matched to the cognitive style of learners. This effect becomes more pronounced in complex education, such as in engineering. We attempted to critically assess the effect of cognitive styles and gender on students' academic performance in eight engineering majors to understand…
Descriptors: Cognitive Style, Gender Differences, Academic Achievement, Engineering Education
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Abdelfattah, Faisal A.; Obeidat, Omar S.; Salahat, Yousef A.; BinBakr, Maha B.; Al Sultan, Adam A. – Journal of Applied Research in Higher Education, 2022
Purpose: This study examined predictors of cumulative grade point average (GPA) from entrance scores and successive performance during students' academic work in university engineering programs. Design/methodology/approach: Scores from high school coursework, the General Ability Test and the Achievement Test were examined to determine if these…
Descriptors: Prediction, Validity, Scores, Grade Point Average
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Olanrewaju P. Olaogun; Nathaniel J. Hunsu – European Journal of Psychology of Education, 2025
Students have misconceptions about many scientific topics they encounter in the classroom--such misconceptions are especially rife in subjects with counterintuitive concepts. Several studies have copiously documented students' misconceptions in different science domains. Research shows that students' misconceptions can be resistant to change and…
Descriptors: College Students, College Faculty, Engineering Education, Misconceptions
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Yuksel, Dogan; Soruç, Adem; Horzum, Baris; McKinley, Jim – Studies in Second Language Learning and Teaching, 2023
This study focuses on the predictive power of linguistic (i.e., general English proficiency; identified simply as "proficiency" in this paper) and non-linguistic (i.e., language learning anxiety and self-regulation) factors on the academic success of English medium instruction (EMI) students studying in engineering and social sciences…
Descriptors: Language Proficiency, English (Second Language), Second Language Learning, Anxiety
Munroe Bignall, Seliene Elessia – ProQuest LLC, 2020
The purpose of this study was to examine the relationship between the qualifying cumulative grade point average (C-GPA) and grit in engineering students compared with African American female engineering students, who qualify to take upper-level courses in engineering at a Historically Black Colleges and Universities (HBCU) in a Southern state.…
Descriptors: Grade Point Average, Engineering Education, College Students, Academic Persistence
Saira Anwar; Muhsin Menekse – Grantee Submission, 2020
Prior literature in engineering education has focused on student-centered learning by utilizing active, constructive, and interactive instructional strategies. However, most research focused on evaluating the effectiveness of these instructional strategies by comparing them with traditional approaches, which typically placed students in passive…
Descriptors: Reflection, Teamwork, Engineering Education, College Students
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Cannistrà, Marta; Masci, Chiara; Ieva, Francesca; Agasisti, Tommaso; Paganoni, Anna Maria – Studies in Higher Education, 2022
This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…
Descriptors: Dropouts, Potential Dropouts, Dropout Prevention, Dropout Characteristics
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Bowen, Bradley D.; Wilkins, Jesse L. M.; Ernst, Jeremy V. – Journal of STEM Education: Innovations and Research, 2019
The problematic persistence rates that many colleges and schools of engineering encounter has resulted in ongoing conversations about academic readiness, retention, and degree completion within engineering programs. Although a large research base exists about student preparedness in engineering, many studies report a wide variety of factors that…
Descriptors: At Risk Students, Engineering Education, Graduation Rate, College Students
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