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Lajoie, Susanne P.; Poitras, Eric G.; Doleck, Tenzin; Huang, Lingyun – Education and Information Technologies, 2023
The present paper builds on the literature that emphasizes the importance of self-regulation for academic learning or self-regulated learning (SRL). SRL research has traditionally focused on count measures of SRL processing events, however, another important measure of SRL is being recognized: time-on-task. The current study captures the influence…
Descriptors: Intelligent Tutoring Systems, Self Management, Time on Task, Correlation
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Huang, Lingyun; Doleck, Tenzin; Chen, Boyin; Huang, Xiaoshan; Tan, Chengyi; Lajoie, Susanne P.; Wang, Minhong – Education and Information Technologies, 2023
Teachers' self-regulated learning (SRL) plays a crucial role in developing technological pedagogical content knowledge (TPACK), a complex professional skill. It is crucial to identify teachers' SRL activities that may lead to favorable TPACK. Previous studies have focused on the analysis of individual data sources from self-reported surveys or log…
Descriptors: Learning Analytics, Technological Literacy, Pedagogical Content Knowledge, Independent Study
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Lemay, David John; Basnet, Ram B.; Doleck, Tenzin – Education and Information Technologies, 2022
Open-source software movement presents a viable alternative to commercial operating systems. Linux-based operating systems are freely available and a competitive option for computer users who want full control of their computer software. Thus, it is relevant to inquire on how the open-source movement might influence user technology switching…
Descriptors: Open Source Technology, Computer Software, Intention, Influences
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Basnet, Ram B.; Johnson, Clayton; Doleck, Tenzin – Education and Information Technologies, 2022
The nature of teaching and learning has evolved over the years, especially as technology has evolved. Innovative application of educational analytics has gained momentum. Indeed, predictive analytics have become increasingly salient in education. Considering the prevalence of learner-system interaction data and the potential value of such data, it…
Descriptors: Prediction, Dropouts, Predictive Measurement, Data Collection
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Lemay, David John; Doleck, Tenzin – Education and Information Technologies, 2020
Massive open online courses (MOOCs) hold the promise of democratizing the learning process. However, providing effective feedback has proven hard to offer at scale since most methods require a teacher or tutor. Leveraging big data in MOOCs offers a mechanism to develop predictive models that can inform computer-based pedagogical tutors. We review…
Descriptors: Grades (Scholastic), Prediction, Online Courses, Video Technology
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Doleck, Tenzin; Lemay, David John; Basnet, Ram B.; Bazelais, Paul – Education and Information Technologies, 2020
Large swaths of data are readily available in various fields, and education is no exception. In tandem, the impetus to derive meaningful insights from data gains urgency. Recent advances in deep learning, particularly in the area of voice and image recognition and so-called complete knowledge games like chess, go, and StarCraft, have resulted in a…
Descriptors: Learning Analytics, Prediction, Information Retrieval, Accuracy
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Lemay, David John; Bazelais, Paul; Doleck, Tenzin – Education and Information Technologies, 2020
Previous research has produced contrasting findings regarding the influence of social networking on academic performance. Many have found negative relationships but some have also demonstrated a positive effect for social networking on academic performance. Still others report no links between social networking and academic performance.…
Descriptors: Social Networks, Academic Achievement, Correlation, College Students
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Doleck, Tenzin; Lajoie, Susanne P.; Bazelais, Paul – Education and Information Technologies, 2019
The effects of social networking sites (SNS) use are especially significant for students, as they tend to be the most frequent and heavy users of such platforms. In this stream of work, prior research has documented the links between SNS use and academic performance; however, surprisingly, empirical evidence is inconclusive. Whereas previous…
Descriptors: Social Networks, Academic Achievement, Correlation, Educational Benefits
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Lemay, David John; Basnet, Ram B.; Doleck, Tenzin; Bazelais, Paul – Education and Information Technologies, 2019
Social network analysis can provide insight into the educational research community as it manifests and evolves online. This study presents a social network analysis of Twitter use during the American Educational Research Association 2017 Annual Conference. The overall social network is sparse with low density, with a few very active nodes and…
Descriptors: Social Media, Social Networks, Network Analysis, Telecommunications
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Doleck, Tenzin; Lajoie, Susanne P.; Bazelais, Paul – Education and Information Technologies, 2019
Social networking sites (SNS) arguably represent one of the most consequential technological developments in recent history. As SNS use has burgeoned in recent years, increasing academic research has acknowledged the importance of SNS in students' lives. The emerging field of SNS scholarship investigates an important issue in the academic domain,…
Descriptors: Social Networks, Academic Achievement, Longitudinal Studies, Educational Technology
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Bazelais, Paul; Doleck, Tenzin; Lemay, David John – Education and Information Technologies, 2018
The purpose of this research is to investigate pre-university science "Collège d'enseignement général et professionnel" (CEGEP) students' behavioral intentions towards using online learning technologies. Heretofore, CEGEP students' use of technology has received scant attention, yet online learning technologies are found to play an…
Descriptors: Student Attitudes, Computer Attitudes, Educational Technology, Web Based Instruction
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Doleck, Tenzin; Lajoie, Susanne – Education and Information Technologies, 2018
The ubiquitous use of social networking sites by students and the potential impacts of such use on academic performance are of both theoretical and practical importance. Hence, this paper addresses the question: how does the use of social networking sites influence academic performance? The present review synthesizes the empirical findings of the…
Descriptors: Social Networks, Social Media, Academic Achievement, Web Sites
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Bazelais, Paul; Doleck, Tenzin – Education and Information Technologies, 2018
Research has suggested that learning approaches such as blended learning can enhance both the quality of instruction and student learning outcomes in STEM (Science, Technology, Engineering, & Mathematics) education. However, little is known about how such instructional approaches affect learning outcomes in the context of "Collège…
Descriptors: Blended Learning, Conventional Instruction, Mechanics (Physics), College Science
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Basnet, Ram B.; Doleck, Tenzin; Lemay, David John; Bazelais, Paul – Education and Information Technologies, 2018
Teaching programming concepts to enhance students' problem solving and computational thinking skills is a challenging task, especially when students enter college with little to no preparation, or they lack the interest or capacity for programming. Online platforms that serve as automated practice and assessment systems have been offered as…
Descriptors: Computer Science Education, Programming, Homework, Student Projects
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Lee, Lila; Lajoie, Susanne P.; Poitras, Eric G.; Nkangu, Miriam; Doleck, Tenzin – Education and Information Technologies, 2017
Learning to monitor and regulate one's learning in an academic setting is a task that all students must engage in. Learning in "group" situations requires both self- and co-regulation. This research examines a case study of a small group of medical student interactions during an on-line problem based learning activity (PBL) where…
Descriptors: Case Studies, Medical Students, Interaction, Problem Based Learning
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