Publication Date
| In 2026 | 0 |
| Since 2025 | 5 |
| Since 2022 (last 5 years) | 26 |
| Since 2017 (last 10 years) | 37 |
| Since 2007 (last 20 years) | 51 |
Descriptor
Source
| Journal of Computer Assisted… | 58 |
Author
| Resing, Wilma C. M. | 3 |
| Vogelaar, Bart | 3 |
| Bacca-Acosta, Jorge | 2 |
| Tymms, P. | 2 |
| Veerbeek, Jochanan | 2 |
| Wang, Tzu-Hua | 2 |
| Alexandron, Giora | 1 |
| Andrea Carr | 1 |
| Andreas Mühling | 1 |
| Angxuan Chen | 1 |
| Annette Saunders | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 58 |
| Reports - Research | 44 |
| Reports - Evaluative | 8 |
| Reports - Descriptive | 6 |
| Information Analyses | 4 |
| Speeches/Meeting Papers | 1 |
| Tests/Questionnaires | 1 |
Education Level
| Higher Education | 21 |
| Postsecondary Education | 20 |
| Elementary Secondary Education | 6 |
| Secondary Education | 6 |
| Elementary Education | 4 |
| Grade 7 | 2 |
| Middle Schools | 2 |
| Grade 5 | 1 |
| Grade 6 | 1 |
| High Schools | 1 |
| Intermediate Grades | 1 |
| More ▼ | |
Audience
Location
| Taiwan | 3 |
| Netherlands | 2 |
| Australia | 1 |
| Germany | 1 |
| Greece | 1 |
| Hong Kong | 1 |
| Israel (Tel Aviv) | 1 |
| New Zealand | 1 |
| United Kingdom | 1 |
| Utah | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Dongkwang Shin; Suh Keong Kwon; Wonjun Izac Noh; Yohan Hwang – Journal of Computer Assisted Learning, 2025
Background: This study examines the evolution of English speaking proficiency test methods, which have traditionally relied on face-to-face interactions to assess communicative language competence. Recently, computer-based language tests have also been used on a larger scale, albeit with concerns about their impact on measurement. Objectives: This…
Descriptors: Computer Simulation, Technology Uses in Education, English (Second Language), Second Language Learning
Duncan, Alex; Joyner, David – Journal of Computer Assisted Learning, 2022
Background: It is important for institutions of higher education to maintain academic integrity, both for students and the institutions themselves. Proctoring is one way of accomplishing this, and with the increasing popularity of online courses--along with the sudden shift to online education sparked by the COVID-19 pandemic--digital proctoring…
Descriptors: Computer Assisted Testing, Supervision, Integrity, COVID-19
Surahman, Ence; Wang, Tzu-Hua – Journal of Computer Assisted Learning, 2022
Background: Academic dishonesty (AD) and trustworthy assessment (TA) are fundamental issues in the context of an online assessment. However, little systematic work currently exists on how researchers have explored AD and TA issues in online assessment practice. Objectives: Hence, this research aimed at investigating the latest findings regarding…
Descriptors: Ethics, Trust (Psychology), Computer Assisted Testing, Educational Technology
Xiong, Yao; Schunn, Christian D.; Wu, Yong – Journal of Computer Assisted Learning, 2023
Background: For peer assessment, reliability (i.e., consistency in ratings across peers) and validity (i.e., consistency of peer ratings with instructors or experts) are frequently examined in the research literature to address a central concern of instructors and students. Although the average levels are generally promising, both reliability and…
Descriptors: Peer Evaluation, Computer Assisted Testing, Test Reliability, Test Validity
Froehlich, Laura; Sassenberg, Kai; Jonkmann, Kathrin; Scheiter, Katharina; Stürmer, Stefan – Journal of Computer Assisted Learning, 2023
Background: The use of e-exams in higher education is increasing. However, the role of student diversity in the acceptance of e-exams is an under-researched topic. In the current study, we considered student diversity in terms of three sociodemographic characteristics (age, gender, and second language) and three dispositional student…
Descriptors: Student Diversity, Student Attitudes, Computer Assisted Testing, Student Characteristics
Conijn, Rianne; Kleingeld, Ad; Matzat, Uwe; Snijders, Chris – Journal of Computer Assisted Learning, 2022
Background: Online and blended learning need an appropriate assessment strategy which ensures academic integrity. During the pandemic, many universities have chosen for online proctoring. Although some earlier examples suggest that online proctoring may reduce cheating, the potential side-effects of proctoring are largely unknown. Objectives:…
Descriptors: Supervision, Computer Assisted Testing, Integrity, Cheating
Gulnur Tyulepberdinova; Madina Mansurova; Talshyn Sarsembayeva; Sulu Issabayeva; Darazha Issabayeva – Journal of Computer Assisted Learning, 2024
Background: This study aims to assess how well several machine learning (ML) algorithms predict the physical, social, and mental health condition of university students. Objectives: The physical health measurements used in the study include BMI (Body Mass Index), %BF (percentage of Body Fat), BSC (Blood Serum Cholesterol), SBP (Systolic Blood…
Descriptors: Artificial Intelligence, Algorithms, Predictor Variables, Physical Health
Stadler, Matthias; Brandl, Laura; Greiff, Samuel – Journal of Computer Assisted Learning, 2023
Background: Over the last 20 years, educational large-scale assessments have undergone dramatic changes moving away from simple paper-pencil assessments to innovative, technology-based assessments. This comprehensive switch has led to some rather technical improvements such as identifying early guessing or improving standardization. Objectives: At…
Descriptors: Interaction, Measurement, Data Processing, Sustainability
Hewson, Claire; Charlton, John P. – Journal of Computer Assisted Learning, 2019
The use of e-assessment methods raises important concerns regarding the reliability and validity of these methods. Potential threats to validity include mode effects and the possible influence of computer-related attitudes. Although numerous studies have now investigated the validity of online assessments in noncourse-based contexts, few studies…
Descriptors: Computer Assisted Testing, Test Reliability, Test Validity, College Students
Khalil, Mohammad; Prinsloo, Paul; Slade, Sharon – Journal of Computer Assisted Learning, 2022
Background: The COVID-19 pandemic disrupted higher education in many ways, such as the move to Emergency Remote Online Teaching and Learning (EROTL), often including a move to online assessments and examinations. With evidence of increased academic dishonesty in unproctored online assessment, institutions sought ways to ensure academic and…
Descriptors: Integrity, Observation, Computer Assisted Testing, COVID-19
Wen Xin Zhang; John J. H. Lin; Ying-Shao Hsu – Journal of Computer Assisted Learning, 2025
Background Study: Assessing learners' inquiry-based skills is challenging as social, political, and technological dimensions must be considered. The advanced development of artificial intelligence (AI) makes it possible to address these challenges and shape the next generation of science education. Objectives: The present study evaluated the SSI…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Inquiry, Active Learning
Richard Say; Denis Visentin; Annette Saunders; Iain Atherton; Andrea Carr; Carolyn King – Journal of Computer Assisted Learning, 2024
Background: Formative online multiple-choice tests are ubiquitous in higher education and potentially powerful learning tools. However, commonly used feedback approaches in online multiple-choice tests can discourage meaningful engagement and enable strategies, such as trial-and-error, that circumvent intended learning outcomes. These strategies…
Descriptors: Feedback (Response), Self Management, Formative Evaluation, Multiple Choice Tests
Ute Mertens; Marlit A. Lindner – Journal of Computer Assisted Learning, 2025
Background: Educational assessments increasingly shift towards computer-based formats. Many studies have explored how different types of automated feedback affect learning. However, few studies have investigated how digital performance feedback affects test takers' ratings of affective-motivational reactions during a testing session. Method: In…
Descriptors: Educational Assessment, Computer Assisted Testing, Automation, Feedback (Response)
Bacca-Acosta, Jorge; Fabregat, Ramon; Baldiris, Silvia; Kinshuk; Guevara, Juan – Journal of Computer Assisted Learning, 2022
Background: Mobile-based assessment has been an active area of research in the field of mobile learning. Prior research has demonstrated that mobile-based assessment systems positively affect student performance. However, it is still unclear why and how these systems positively affect student performance. Objectives: This study aims to identify…
Descriptors: Academic Achievement, Electronic Learning, Handheld Devices, Computer Assisted Testing
Gruss, Richard; Clemons, Josh – Journal of Computer Assisted Learning, 2023
Background: The sudden growth in online instruction due to COVID-19 restrictions has given renewed urgency to questions about remote learning that have remained unresolved. Web-based assessment software provides instructors an array of options for varying testing parameters, but the pedagogical impacts of some of these variations has yet to be…
Descriptors: Test Items, Test Format, Computer Assisted Testing, Mathematics Tests

Peer reviewed
Direct link
