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Tianchen Sun – ProQuest LLC, 2023
Students spend little time completing tasks when deadlines are far off; however, they tend to increase their work amounts as deadline approaches. This phenomenon, which is called deadline rush, can be modeled by exponential distributions. Deadline reactivity, represented by a rate parameter of the exponential distribution, parameterizes individual…
Descriptors: Time Management, Decision Making, College Students, Educational Environment
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
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
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
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
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
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
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