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Durak, Hatice Yildiz – Journal of Educational Computing Research, 2020
The objective of this study is to construct a model which explains and predicts the relations of university students' cyberloafing behaviors with demographic and academic variables at computing courses where online social networking sites are utilized for education and is to review whether there is longitudinal effect on these relations in terms…
Descriptors: Educational Technology, Technology Uses in Education, Social Media, Student Behavior
Hughes, Christopher; Costley, Jamie; Lange, Christopher – Interactive Technology and Smart Education, 2018
Purpose: The paper aims to examine the effect of levels of self-regulated effort (SRE) and levels of cognitive load on the watching and completing of video lectures used as the main source of instruction in online learning environments. Design/methodology/approach: A survey provided data on the students' engagement with video lectures, their level…
Descriptors: Self Management, Difficulty Level, Video Technology, Lecture Method
Yilmaz, Ramazan; Yurdugül, Halil – Journal of Computing in Higher Education, 2018
The purpose of this study is to find out the level of cyberloafing behaviors of the students in information technologies (IT) classrooms; and to examine the relationship between cyberloafing behaviors and the psycho-social perceptions, attitudes and motivation for the courses and learning strategies. Correlational method was utilized; and…
Descriptors: Educational Technology, Technology Uses in Education, Student Behavior, Correlation
Van Horne, Sam; Curran, Maura; Smith, Anna; VanBuren, John; Zahrieh, David; Larsen, Russell; Miller, Ross – Technology, Knowledge and Learning, 2018
Instructional technologists and faculty in post-secondary institutions have increasingly adopted learning analytics interventions such as dashboards that provide real-time feedback to students to support student' ability to regulate their learning. But analyses of the effectiveness of such interventions can be confounded by measures of students'…
Descriptors: Chemistry, Science Instruction, Learning Strategies, Questionnaires
Hood, Michelle – Australasian Journal of Educational Technology, 2013
This study examined predictors of students' intentions to access face-to-face (f2f) or online options for lectures and tutorials in a buffet-style blended learning 2nd-year psychology statistics course ("N" = 113; 84% female). Students were aged 18 to 51 years ("M" = 23.16; "SD"= 6.80). Practical and technological…
Descriptors: Blended Learning, Intention, Online Courses, Computer Software
Amelink, Catherine T.; Scales, Glenda; Tront, Joseph G. – Advances in Engineering Education, 2012
Pedagogical approaches that incorporate learning technologies into lessons and coursework have had promising results in relation to students' motivation to learn. Tablet PCs have been identified as one form of instructional technology that can facilitate learning among engineering undergraduates since this medium allows for drawing on the computer…
Descriptors: Handheld Devices, Technology Uses in Education, Educational Technology, Engineering Education
Zogheib, Salah – Journal of Educational Technology Systems, 2014
As the majority of educational research has focused on preservice teachers' computer use for "educational purposes," the question remains: Do preservice teachers use computer technology for daily life activities and encounters? And do preservice teachers' personality traits and motivational beliefs related to computer training provided…
Descriptors: Preservice Teachers, Computer Use, Computer Uses in Education, Educational Technology
Juarez-Collazo, Norma A.; Elen, Jan; Clarebout, Geraldine – Turkish Online Journal of Educational Technology - TOJET, 2013
It is still unclear on what and how tool and learner characteristics influence tool use and consequently performance in computer-based learning environments (CBLEs). This study examines the relationships between tool-related characteristics (tool presentation: non-/embedded tool and instructional cues: non-/explained tool functionality) and…
Descriptors: Student Characteristics, Computer Uses in Education, Correlation, Self Efficacy
Johnson, Genevieve M. – Journal of University Teaching and Learning Practice, 2015
First-year university students (n = 185) completed an online questionnaire that allowed comparison of those who reported studying on-campus with those who reported studying fully-online. Independent sample t-tests compared the means of students in the two study modes on demographics, frequency of use of digital technology and metacognitive…
Descriptors: College Freshmen, Online Surveys, Questionnaires, Comparative Analysis
Wang, Chih-Hsuan; Shannon, David M.; Ross, Margaret E. – Distance Education, 2013
The purpose of this study was to examine the relationship among students' characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning settings. Two hundred and fifty-six students participated in this study. All participants completed an online survey that included demographic information, the modified…
Descriptors: Student Characteristics, Self Management, Self Efficacy, Outcomes of Education