Publication Date
| In 2026 | 0 |
| Since 2025 | 1 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 2 |
| Since 2007 (last 20 years) | 7 |
Descriptor
| Computer Attitudes | 8 |
| Gender Differences | 8 |
| Personality Traits | 8 |
| Age Differences | 4 |
| College Students | 4 |
| Self Efficacy | 4 |
| Student Attitudes | 4 |
| Student Characteristics | 4 |
| Academic Achievement | 3 |
| Correlation | 3 |
| Foreign Countries | 3 |
| More ▼ | |
Source
Author
Publication Type
| Journal Articles | 7 |
| Reports - Research | 6 |
| Dissertations/Theses -… | 1 |
| Reports - Evaluative | 1 |
| Tests/Questionnaires | 1 |
Education Level
| Higher Education | 7 |
| Postsecondary Education | 6 |
| Adult Education | 1 |
| Elementary Education | 1 |
| High Schools | 1 |
| Junior High Schools | 1 |
| Middle Schools | 1 |
| Secondary Education | 1 |
Audience
Location
| China (Shanghai) | 1 |
| Hong Kong | 1 |
| Japan | 1 |
| Macau | 1 |
| Maryland | 1 |
| Nigeria | 1 |
| South Korea | 1 |
| Taiwan (Taipei) | 1 |
| Turkey | 1 |
| Virginia | 1 |
Laws, Policies, & Programs
Assessments and Surveys
| Computer Anxiety Scale | 1 |
| NEO Five Factor Inventory | 1 |
| Program for International… | 1 |
What Works Clearinghouse Rating
Linda J. Sax; Kaitlyn N. Stormes; Maxx F. Pereyra – ACM Transactions on Computing Education, 2025
To cultivate more computing talent (including more diverse talent), it is important to understand how college students experience their computing courses and if such experiences vary based on students' gender and racial/ethnic identities. In this paper, we focus on course modality to understand whether taking courses in-person, online, or a hybrid…
Descriptors: Computer Science Education, Electronic Learning, Online Courses, Delivery Systems
Sultan, Sarwat; Kanwal, Frasat – Bulletin of Education and Research, 2017
In distance learning, an internet-based learning has been developed as a learning platform for courses, and a distance learner's acquisition depends on his/her personal characteristics. Thus the present study was planned to investigate personal attributes of distance learners that may contribute to their levels of computer anxiety and computer…
Descriptors: Distance Education, Educational Technology, Technology Uses in Education, Anxiety
Lu, Jiamei; Li, Daqi; Stevens, Carla; Ye, Renmin – Journal of Educational Computing Research, 2016
Using Program for International Student Assessment (PISA) 2012, an international education database, this study analyzed the evaluations of computer use for academic learning by 15-year-old students from seven Edu-systems (unit in PISA) in Eastern Asia. Six variables were identified in association with students' evaluations of computer use…
Descriptors: Foreign Countries, College Students, Computer Attitudes, Computer Uses in Education
Adebowale, Olusegun – International Journal of Education and Development using Information and Communication Technology, 2014
An online guidance and counselling services was established at the Obafemi Awolowo University (OAU) in December, 2010. This study was designed to examine the undergraduates' disposition to the online counselling services after 24 months. It also investigated the prevalent disposition, dispositional types and distribution of students across the…
Descriptors: Foreign Countries, Undergraduate Students, Student Attitudes, Measures (Individuals)
Gulten, Dilek Cagirgan; Yaman, Yavuz; Deringol, Yasemin; Ozsari, Ismail – Turkish Online Journal of Educational Technology - TOJET, 2011
Nowadays, "lifelong learning individual" concept is gaining importance in which curiosity is one important feature that an individual should have as a requirement of learning. It is known that learning will naturally occur spontaneously when curiosity instinct is awakened during any learning-teaching process. Computer self-efficacy…
Descriptors: Personality Traits, Self Efficacy, Lifelong Learning, Measures (Individuals)
Harris, Kenneth J.; Harris, Ranida B.; Lambert, Alysa D. – Information Systems Education Journal, 2011
Introduction to data management classes are often times students' first exposure to advanced material in these areas. Many factors are likely to influence success in these classes, but empirical investigations have focused on relatively few variables. In this study, we extend this research by examining the relative contributions of the previously…
Descriptors: Academic Achievement, Prediction, Self Efficacy, Computer Attitudes
Kwon, Hyuckhoon – ProQuest LLC, 2009
This study seeks to gain a holistic understanding of how older Korean-American adults' socio-demographic factors affect their attitudes toward the computer. The research was guided by four main questions: (1) What do participants describe as the consequences of their using the computer? (2) What attitudes toward the computer do participants…
Descriptors: Korean Americans, Older Adults, Computer Attitudes, Social Influences
Contreras, Carlos L. M. – Quarterly Review of Distance Education, 2004
Demographic and personality variables and computer use were used to predict computer self-confidence with a sample of students enrolled in online college-credit classes. Computer self-confidence was measured with one 10-choice question. Demographic variables included age, annual income, geographic region, gender, and ethnicity. Computer use was…
Descriptors: Income, Age Differences, Ethnic Groups, Gender Differences

Peer reviewed
Direct link
