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Qiong Wang; Guoqing Zhao; Jinglan Zeng – Australasian Journal of Educational Technology, 2024
Although studies have highlighted the importance of facilitating conditions in enhancing students' digital informal learning (DIL), the effect mechanism is still unclear. This study examined the mediating role of digital competence and the moderating role of technostress between facilitating conditions and DIL. Data were collected from 385…
Descriptors: Educational Technology, Technology Uses in Education, Technological Literacy, Stress Variables
Nehir Yasan-Ak; Soner Yildirim – Technology, Knowledge and Learning, 2024
Mobile phones have become essential learning tools with their extensive features and functionalities, contributing to the emergence of mobile learning. These devices enable communication and collaboration both inside and outside the classrooms while also aiding in information seeking, collection, and content generation. Yet, the use of mobile…
Descriptors: Telecommunications, Handheld Devices, Technology Uses in Education, Undergraduate Students
McCarthy, Tessa; Holbrook, Cay; Kamei-Hannan, Cheryl; D'Andrea, Frances Mary – Journal of Special Education Technology, 2023
This study provides information on the use of a refreshable braille display in relation to reading speeds and accuracy for students with visual impairments. The characteristics and variables which were statistically significant predictors of reading speed were explored. Forty-nine students in grades 1-9 participated with their teachers of students…
Descriptors: Braille, Students with Disabilities, Visual Impairments, Blindness
Lee, Jang Ho; Lee, Hansol – Language Awareness, 2023
As digital technology is becoming an increasingly critical component of education, learners' socioeconomic status (SES) and technology use are becoming more important in their learning. In the context of English learning, the present study modeled how learners' SES and their perception of technology use for language learning are linked to their…
Descriptors: Socioeconomic Status, English (Second Language), Second Language Learning, Second Language Instruction
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
Lebenicnik, Maja; Istenic Starcic, Andreja – British Journal of Educational Technology, 2020
The contemporary digital divide is characterised by the uneven distribution of access to information communication technology (ICT), originating in the different motivation, physical access and skills of users. We synthesised existing theories and frameworks to develop and then empirically validate a theoretical model to predict university…
Descriptors: College Students, Special Needs Students, Access to Computers, Educational Technology
Coelho Junior, Francisco Antonio; Botelho, Erica de Aguiar; Rego, Mariana Carolina Barbosa; Faiad, Cristiane; Ramos, Wilsa Maria – Turkish Online Journal of Distance Education, 2019
The purpose of this study was twofold. First, it aimed to determine whether there are differences in Brazilian students' attitudes towards online learning compared to their purpose in seeking for this modality and the localization of the pole where they received face-to-face support. Second, it aimed to identify if Brazilian students' attitudes…
Descriptors: Foreign Countries, Student Attitudes, Online Courses, Self Concept
Polyzou, Agoritsa; Karypis, George – International Educational Data Mining Society, 2018
Developing tools to support students and learning in a traditional or online setting is a significant task in today's educational environment. The initial steps towards enabling such technologies using machine learning techniques focused on predicting the student's performance in terms of the achieved grades. The disadvantage of these approaches…
Descriptors: Low Achievement, Predictor Variables, Classification, Student Characteristics
Scheffert, Aynsley H. M.; Parrish, Danielle E.; Harris, Helen – Journal of Social Work Education, 2021
The COVID-19 pandemic has impacted individuals across the world and disrupted societal systems, including educational institutions. The aim of the current cross-sectional survey of U.S. social work students was to describe: (1) students' experiences of COVID-19-related stress, academic stress, and access to supports; (2) changes in academic stress…
Descriptors: Social Work, COVID-19, Pandemics, Stress Variables
Canchola González, José Antonio; Glasserman-Morales, Leonardo David – Knowledge Management & E-Learning, 2020
In Mexico, there has been a rise in Massive Open Online Course (MOOC) enrollments through platforms such as MexicoX. However, this rise in interest has not been accompanied by a corresponding increase in completion rates. This article examines the factors that influence Mexican learners' retention rates and learner engagement to determine the…
Descriptors: Foreign Countries, Online Courses, Large Group Instruction, Educational Technology
Kilicer, Kerem; Bardakci, Salih; Arpaci, Ibrahim – Contemporary Educational Technology, 2018
For today's societies trying to cope with the current globally increased competition, existence of individuals who can take risks, solve problems and adopt changes an innovation has gained more importance when compared to the past. This situation brings responsibility to educational institutions for increasing the number of innovative individuals…
Descriptors: Predictor Variables, Technology Uses in Education, Innovation, Student Characteristics
Stoltz, Bonnie K. – ProQuest LLC, 2019
The number of non-traditional, asynchronous, post-secondary online students enrolled in a business administration major has increased dramatically over the past decade. At the same time, attrition rates are rising in this population indicating that non-traditional students are not successful in their online experience. This quantitative,…
Descriptors: Nontraditional Students, Asynchronous Communication, College Students, Online Courses
Chaka, John Gyang; Govender, Irene – South African Journal of Education, 2017
Access to quality education is becoming a huge challenge in Nigeria, in view of the exponential growth in its population, coupled with ethno-religious crises and other acts of terrorism. A large chunk of the country's population--about 26% have no access to education, as existing teaching and learning facilities have become inadequate. Some…
Descriptors: Foreign Countries, Telecommunications, Handheld Devices, Technology Uses in Education
Zimmerman, Whitney Alicia – International Journal of E-Learning & Distance Education, 2017
Expectancies of success and values were used to predict success in an online undergraduate-level introductory statistics course. Students who identified as primarily face-to-face learners were compared to students who identified as primarily online learners. Expectancy value theory served as a model. Expectancies of success were operationalized as…
Descriptors: Online Courses, Educational Technology, Technology Uses in Education, Teaching Methods
Crossley, Scott; Liu, Ran; McNamara, Danielle – Grantee Submission, 2017
A number of studies have demonstrated links between linguistic knowledge and performance in math. Studies examining these links in first language speakers of English have traditionally relied on correlational analyses between linguistic knowledge tests and standardized math tests. For second language (L2) speakers, the majority of studies have…
Descriptors: Predictor Variables, Mathematics Achievement, English (Second Language), Natural Language Processing