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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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Iustina Alexandra Groza; Marius Ciprian Ceobanu; Cristina Maria Tofan – European Journal of Psychology of Education, 2024
Academic procrastination has been a subject of particular interest in research due to its frequent association with heightened levels of anxiety, stress, and the long-term risk of emotional and behavioural vulnerability (Hoge et al., 2013). Our study tests the correlation between motivational persistence as a trait and academic procrastination, as…
Descriptors: Study Habits, Females, Foreign Countries, Student Motivation
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Feifei Han – OTESSA Conference Proceedings, 2021
This study investigates to what extent there is an association between students' self-reported perceptions of online learning and observed online learning behaviors recorded by the learning analytic data. The participants were 319 undergraduates studying an engineering course in an Australian university. Data analyses were conducted using cluster…
Descriptors: Online Courses, Behavior Patterns, Correlation, Learning Processes
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Li, Yuhao; Chang, Mengyi; Zhao, Hanxuan; Jiang, Caihong; Xu, Sihua – Journal of Computer Assisted Learning, 2023
Background: Mobile devices facilitate learning activities in a self-paced way. However, the current understanding of learning participation and its consequence are minimal when learners take advantage of opportunities provided by mobile technologies worldwide. Aims: The primary purpose of this study is to examine the effectiveness of environmental…
Descriptors: Anxiety, Computer Software, Computer Assisted Instruction, Learning Processes
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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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Hoppenfeld, Jared; Graves, Stephanie J.; Sewell, Robin R.; Halling, T. Derek – Public Services Quarterly, 2019
Sedentary behavior has increased over the last several decades, and this has led to major life-threatening health issues. Texas A&M University Libraries has introduced an innovative idea in three of their buildings. This case study highlights the implementation of Bike Desks at an academic library while offering strategies for other libraries…
Descriptors: Physical Activities, Academic Achievement, Academic Libraries, Furniture
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Lin, Jian-Wei – Journal of Computer Assisted Learning, 2019
Team-based learning (TBL) stresses applying knowledge rather than absorbing knowledge in class; studies have investigated the use of TBL and its merits in different teaching courses (e.g., medical science and business). TBL is most effective when students learn autonomously before class. However, the ability of autonomous learning is highly…
Descriptors: Teamwork, Metacognition, Learning Strategies, Knowledge Level
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Du, Xin; Duivesteijn, Wouter; Klabbers, Martijn; Pechenizkiy, Mykola – International Educational Data Mining Society, 2018
Behavioral records collected through course assessments, peer assignments, and programming assignments in Massive Open Online Courses (MOOCs) provide multiple views about a student's study style. Study behavior is correlated with whether or not the student can get a certificate or drop out from a course. It is of predominant importance to identify…
Descriptors: Student Behavior, Assignments, Large Group Instruction, Online Courses
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Gitinabard, Niki; Barnes, Tiffany; Heckman, Sarah; Lynch, Collin F. – International Educational Data Mining Society, 2019
Students' interactions with online tools can provide us with insights into their study and work habits. Prior research has shown that these habits, even as simple as the number of actions or the time spent on online platforms can distinguish between the higher performing students and low-performers. These habits are also often used to predict…
Descriptors: Blended Learning, Student Adjustment, Online Courses, Study Habits
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Lindblom-Ylänne, Sari; Saariaho, Emmi; Inkinen, Mikko; Haarala-Muhonen, Anne; Hailikari, Telle – Frontline Learning Research, 2015
The study explored university undergraduates' dilatory behaviour, more precisely, procrastination and strategic delaying. Using qualitative interview data, we applied a theory-driven and person-oriented approach to test the theoretical model of Klingsieck (2013). The sample consisted of 28 Bachelor students whose study pace had been slow during…
Descriptors: Time Management, Undergraduate Students, Interviews, Student Behavior
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Xu, Jianzhong; Fan, Xitao; Du, Jianxia – Psychology in the Schools, 2015
This study presents a psychometric evaluation of the Homework Management Scale (HMS) for mathematics, consisting of five subscales for measuring homework management strategies. Confirmatory factor analyses were conducted with a sample of middle school students (N = 796). Results indicated that the factor structure of the Chinese version of the HMS…
Descriptors: Homework, Psychometrics, Measures (Individuals), Middle School Students
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Reichle, Erik D.; Drieghe, Denis – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2013
The question of why readers sometimes skip words has important theoretical implications for our understanding of perception, cognition, and oculomotor control during reading (Drieghe, Rayner, & Pollatsek, 2005). In this article, the E-Z Reader model of eye-movement control in reading (Reichle, 2011) was used to examine the behavioral…
Descriptors: Reading Strategies, Reading Skills, Eye Movements, Protocol Analysis
Poulsen, Sten C. – 1969
On the basis of educational experience and educational research, the following two assumptions have been widely accepted: students achieving the best results work differently from those who do less well, and low achieving students may learn something from the way the "good" performers approach the learning task and will thus be able to obtain far…
Descriptors: Behavior Patterns, Definitions, Educational Research, Higher Education
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Campbell, John B.; Hawley, Charles W. – Journal of Research in Personality, 1982
Tested predictions derived from Eysenck's theory of personality in two samples by relating extraversion scores to library study locations, frequency of study breaks, and self-report of factors which influence study location. Found predicted main effects for study location with extraverts occupying locations that provided greater external…
Descriptors: Behavior Patterns, College Students, Higher Education, Individual Differences
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Murphy, P. Karen; Alexander, Patricia A. – Educational and Psychological Measurement, 1998
The psychometric properties of the Learning and Study Strategies Inventory-High School (LASSI-HS) was studied with 139 female high school students from Singapore. Results indicate that the LASSI-HS yields reliable measures of learning and study behaviors, but the underlying structure of the measure suggested in its manual was not supported. (SLD)
Descriptors: Behavior Patterns, Females, Foreign Countries, High School Students
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