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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
Hilliger, Isabel; Ruipérez-Valiente, José A.; Alexandron, Giora; Gaševic, Dragan – Journal of Computer Assisted Learning, 2022
Background: Online learning has grown significantly during the past two decades, and COVID-19 pandemic has expedited this process. However, previous research has shown how academic dishonesty is more prevalent under these modalities. Therefore, there is the challenge of performing trustworthy remote assessments, in order to obtain valid and…
Descriptors: Online Courses, Ethics, Student Evaluation, Evaluation Methods
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
Marco Rüth; Maria Jansen; Kai Kaspar – Journal of Computer Assisted Learning, 2024
Background: Online exams have become a more common form of assessment at universities due to the COVID-19 pandemic. However, cheating behaviour in online exams is widespread and threatens exam validity as well as student learning and well-being. Objective: To better understand the role of university students' needs, conceptions and reasons…
Descriptors: Foreign Countries, College Students, Computer Assisted Testing, Cheating
LaFlair, Geoffrey T.; Langenfeld, Thomas; Baig, Basim; Horie, André Kenji; Attali, Yigal; von Davier, Alina A. – Journal of Computer Assisted Learning, 2022
Background: Digital-first assessments leverage the affordances of technology in all elements of the assessment process--from design and development to score reporting and evaluation to create test taker-centric assessments. Objectives: The goal of this paper is to describe the engineering, machine learning, and psychometric processes and…
Descriptors: Computer Assisted Testing, Affordances, Scoring, Engineering

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