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Showing 1 to 15 of 26 results Save | Export
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Carey Bernini Dowling; C. Veronica Smith; Yue Yin; Jeffrey M. Williams – Journal of the Scholarship of Teaching and Learning, 2025
People view many attributes, including intelligence, through implicit theories (or mindsets). Entity mindsets position the attribute as unchangeable or static, whereas incremental mindsets see the attribute as malleable or capable of being changed/improved (Dweck & Leggett, 1988). The present studies examined a new questionnaire designed to…
Descriptors: Grade Point Average, Undergraduate Students, Study Habits, Intelligence
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Xu Du; Lizhao Zhang; Jui-Long Hung; Hao Li; Hengtao Tang; Miao Dai – Journal of Computing in Higher Education, 2024
This study aims to track college students' on-task rate during the teaching process and to analyze the influence of instructional strategies on on-task rate through the aspects of observable and internal engagement indicators. Thirty-six undergraduate students at a higher education institution in China participated in the study. Students'…
Descriptors: Teaching Methods, Attention Control, Brain Hemisphere Functions, Diagnostic Tests
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Winchell, Adam; Lan, Andrew; Mozer, Michael – Cognitive Science, 2020
When engaging with a textbook, students are inclined to highlight key content. Although students believe that highlighting and subsequent review of the highlights will further their educational goals, the psychological literature provides little evidence of benefits. Nonetheless, a student's choice of text for highlighting may serve as a window…
Descriptors: Predictor Variables, Reading Comprehension, Student Interests, Reader Text Relationship
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Ives, Bob; Giukin, Lenuta – Journal of Academic Ethics, 2020
A total of 1390 university students from five public Moldovan universities completed a survey reporting their experiences and beliefs with respect to 22 types of academic misconduct. An interpretable five-factor solution to the frequencies of these behaviors accounted for more than half of the total variance. The two most reliable predictors were…
Descriptors: Foreign Countries, Behavior Patterns, Predictor Variables, Public Colleges
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Chen, Changsheng; Meng, Xiangzeng – International Journal of Distance Education Technologies, 2021
As a supplement to face-to-face teaching, small private online courses (SPOCs) have become increasingly popular in higher education. Nevertheless, there is a lack of research on behavioral patterns in the university SPOC. This empirical study investigates the behavioral patterns of 306 undergraduate students taking a degree course partially taught…
Descriptors: Student Behavior, Behavior Patterns, Outcomes of Education, Online Courses
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Chen, Yu; Hu, Xiaodan – Research in Higher Education, 2021
Community college near-completion students are community college starters who have accumulated a considerable number of credits but left college without any postsecondary educational credential. This quantitative study examined a nationally representative sample and intended to reveal significant predictors of becoming a community college…
Descriptors: Community Colleges, Two Year College Students, College Credits, Dropout Characteristics
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Lechuga Sancho, María Paula; Martín-Navarro, Alicia; Ramos-Rodríguez, Antonio Rafael – Studies in Higher Education, 2020
When studying entrepreneur's intentions, researchers have mainly relied on the theory of planned behaviour model developed by Ajzen (1991. "The Theory of Planned Behavior." "Organizational Behavior and Human Decision Processes" 50 (2): 179-211) which includes personal variables such as subjective norms, attitude and perception…
Descriptors: Structural Equation Models, Intention, Predictor Variables, College Seniors
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Bailie, Jeffrey L. – Journal of Instructional Pedagogies, 2020
For close to three decades. the positive effects of online learner engagement in asynchronous discussions have been reported. Given the many positive effects of asynchronous discussion that have been conveyed in the literature, a preponderance of today's online courses include the activity as a part of the learning experience. It seems only…
Descriptors: Learning Analytics, Asynchronous Communication, Predictor Variables, Grades (Scholastic)
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Sinclair, Arabella J.; Schneider, Bertrand – International Educational Data Mining Society, 2021
Collaborative dialogue is rich in conscious and subconscious coordination behaviours between participants. This work explores collaborative learner dialogue through theories of alignment, analysing inter-partner movement and language use with respect to our hypotheses: that they interrelate, and that they form predictors of collaboration quality…
Descriptors: Dialogs (Language), Cooperative Learning, Correlation, Predictor Variables
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Nieuwoudt, Johanna Elizabeth – Australasian Journal of Educational Technology, 2020
Learning is facilitated by participation and interaction and can be synchronously or asynchronously in online education. This study investigated the relationship between students' academic success and online interaction and participation and explored their class attendance (synchronous virtual classes and/or watching the recorded virtual classes)…
Descriptors: Asynchronous Communication, Synchronous Communication, Predictor Variables, Online Courses
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Mandalapu, Varun; Chen, Lujie Karen; Chen, Zhiyuan; Gong, Jiaqi – International Educational Data Mining Society, 2021
With the increasing adoption of Learning Management Systems (LMS) in colleges and universities, research in exploring the interaction data captured by these systems is promising in developing a better learning environment and improving teaching practice. Most of these research efforts focused on course-level variables to predict student…
Descriptors: Integrated Learning Systems, Interaction, Undergraduate Students, Minority Group Students
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Akpinar, Nil-Jana; Ramdas, Aaditya; Acar, Umut – International Educational Data Mining Society, 2020
Educational software data promises unique insights into students' study behaviors and drivers of success. While much work has been dedicated to performance prediction in massive open online courses, it is unclear if the same methods can be applied to blended courses and a deeper understanding of student strategies is often missing. We use pattern…
Descriptors: Learning Strategies, Blended Learning, Learning Analytics, Student Behavior
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Chen, Yu; Upah, Sylvester – Journal of College Student Retention: Research, Theory & Practice, 2020
Science, Technology, Engineering, and Mathematics student success is an important topic in higher education research. Recently, the use of data analytics in higher education administration has gain popularity. However, very few studies have examined how data analytics may influence Science, Technology, Engineering, and Mathematics student success.…
Descriptors: STEM Education, Academic Advising, Data Analysis, Majors (Students)
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Foung, Dennis; Chen, Julia – Electronic Journal of e-Learning, 2019
In recent years, research using learning analytics to predict learning outcomes has begun to increase. This emerging field of research advocates the use of readily-available data to inform teaching and learning. The current case study adopts a learning analytics approach to evaluate the online learning package of an academic English course in a…
Descriptors: Foreign Countries, Blended Learning, Electronic Learning, English for Academic Purposes
Brown, Sarah A.; Menendez, David; Alibali, Martha W. – Grantee Submission, 2019
Why do people change their strategies for solving problems? In this research, we tested whether negative feedback and the context in which learners encounter a strategy influence their likelihood of adopting that strategy. In particular, we examined whether strategy adoption varied when learners were exposed to a target strategy in isolation, in…
Descriptors: Student Characteristics, Learning Strategies, Problem Solving, Feedback (Response)
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