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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
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Min Zhang; Qiang Jiang; Weiyan Xiong; Qi Li; Wei Zhao – Educational Technology & Society, 2024
Self-directed learning with mobile technology (SDLMT) is critical to students' learning success. However, only minimal research has been conducted on the manner by which significant aspects (e.g., selfefficacy, student engagement) are related to SDLMT. This study analyzed the answers of 485 Chinese students (seventh to ninth grades) who were…
Descriptors: Self Efficacy, Predictor Variables, Secondary School Students, Independent Study
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Tainsh, Ryan D. – International Journal of Research in Education and Science, 2023
Despite similarities between self-directed learners and successful postsecondary online learners, infrequently has self-directedness been examined in this population. Understanding the impact of self-directedness on online learner academic success and persistence may clarify the profile of a successful online student. Independent samples t-tests…
Descriptors: Academic Achievement, Academic Persistence, Electronic Learning, Independent Study
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Abubakari, Mussa Saidi; Nurkhamid, Nurkhamid; Priyanto, Priyanto – Turkish Online Journal of Distance Education, 2022
The study was intended to model online learning engagement of international students studying in Indonesia to determine which factors affect learner engagement. A survey was conducted online, and 102 international students filled the questionnaire. Partial Least Squares-Structural Equation Modeling (PLS-SEM) technique was used for data analysis.…
Descriptors: Electronic Learning, Foreign Students, Learner Engagement, Predictor Variables
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Stephen, Jacqueline S.; Rockinson-Szapkiw, Amanda J.; Dubay, Chelsie – American Journal of Distance Education, 2020
This quantitative non-experimental correlational study examined the associations among the predictor variables of first year, first semester nontraditional online learners' self-regulation, self-direction, and self-efficacy with the criterion variable of semester-to semester persistence. A nonprobability convenience sampling method was used to…
Descriptors: Academic Persistence, Nontraditional Students, Electronic Learning, Self Efficacy
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Hilpert, Jonathan C.; Greene, Jeffrey A.; Bernacki, Matthew – British Journal of Educational Technology, 2023
Capturing evidence for dynamic changes in self-regulated learning (SRL) behaviours resulting from interventions is challenging for researchers. In the current study, we identified students who were likely to do poorly in a biology course and those who were likely to do well. Then, we randomly assigned a portion of the students predicted to perform…
Descriptors: Learning Theories, Independent Study, Artificial Intelligence, Biology
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Çetin, Baris – Educational Policy Analysis and Strategic Research, 2022
This study aims to determine whether university students' levels of online self-regulated learning, online technologies self-efficacy, and motivated strategies for learning predict their general academic achievement and online academic achievement. In this study, the scanning design and the prediction research design were used. The participants of…
Descriptors: Foreign Countries, College Students, Independent Study, Electronic Learning
Oliver Wang – ProQuest LLC, 2023
Online education has grown rapidly in the United States and has accelerated since COVID-19. The prior history of online learning through online charter schools and online learning during COVID-19 failed to meet the needs of disadvantaged student populations, especially students of color and students with lower socioeconomic status. This study…
Descriptors: Electronic Learning, In Person Learning, Elementary School Students, Public Schools
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Yeh, Yu-Chen; Kwok, Oi-Man; Chien, Hsiang-Yu; Sweany, Noelle Wall; Baek, Eunkyeng; McIntosh, William Alex – Online Learning, 2019
The purpose of this study was to examine the underlying mechanism between goal orientations and academic expectation for online learners. We simultaneously studied the structural relationships among 2×2 achievement goal orientations, self-regulated learning (SRL) strategies, supportive online learning behaviors, and expected academic outcome in…
Descriptors: College Students, Goal Orientation, Predictor Variables, Electronic Learning
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Heo, JeongChul; Han, Sumi – Education and Information Technologies, 2018
The purpose of this study is to determine whether the self-directed learning readiness (SDLR) among online students might be significantly predicted by motivation, academic stress, and age. To complete the purpose of this study, the Pearson correlation and multiple-regression are analyzed. The participants for this study are college students who…
Descriptors: Motivation, Independent Study, Online Courses, Electronic Learning
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Lepp, Andrew; Barkley, Jacob E.; Karpinski, Aryn C.; Singh, Shweta – SAGE Open, 2019
This study compared college students' multitasking in online courses with their multitasking in face-to-face courses and explored the significance of potential predictors of multitasking in each setting. Students taking both online and face-to-face courses completed surveys assessing multitasking in each setting, self-efficacy for self-regulated…
Descriptors: College Students, Student Behavior, Time Management, Online Courses
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Xie, Jingrong; Basham, James D.; Marino, Matthew T.; Rice, Mary F. – Journal of Special Education Technology, 2018
Mobile technologies have shown great potential in various educational settings. Moreover, there is an emerging research base demonstrating how students view and interact with mobile devices to learn. As more of these technologies enter inclusive educational settings, an understanding of the extant research base for mobile learning (M-learning) and…
Descriptors: Electronic Learning, Elementary Secondary Education, Disabilities, Special Needs Students
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Umek, Lan; Tomaževic, Nina; Aristovnik, Aleksander; Keržic, Damijana – International Association for Development of the Information Society, 2018
In the paper, we present the results of a case study conducted at Faculty of Administration, University of Ljubljana among 1st year undergraduate students. We investigated the correlations between students' activities in the e-classroom and grades at the final exam. The sample included 92 participants who took part at the final exam in the course…
Descriptors: Foreign Countries, College Freshmen, Electronic Learning, Learning Activities
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Cigdem, Harun; Ozturk, Mustafa – Turkish Online Journal of Distance Education, 2016
This study aimed to examine the relationship between certain factors of online learning readiness and learners' end-of-course achievements. The study was conducted at a two-year post-secondary Turkish military school within the scope of the course titled Computer Literacy, which was designed and implemented in a blended way. The data were…
Descriptors: Foreign Countries, Military Schools, Vocational Education, College Students
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Kirby, Dale; Barbour, Michael K.; Sharpe, Dennis B. – American Journal of Distance Education, 2012
University students who had completed at least one distance education course were surveyed during their first and fourth year of postsecondary studies. When controlled for those who had previous distance education experience in high school, it was found that self-regulatory learning behaviors, which are frequently linked to positive experiences…
Descriptors: Foreign Countries, Web Based Instruction, Electronic Learning, Independent Study
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