A Systematic Review on AI-based Proctoring Systems: Past, Present and Future
Open accessAbstract
There have been giant leaps in the field of education in the past 1-2 years.. Schools and colleges are transitioning online to provide more resources to their students. The COVID-19 pandemic has provided students more opportunities to learn and improve themselves at their own pace. Online proctoring services (part of assessment) are also on the rise, and AI-based proctoring systems (henceforth called as AIPS) have taken the market by storm. Online proctoring systems (henceforth called as OPS), in general, makes use of online tools to maintain the sanctity of the examination. While most of this software uses various modules, the sensitive information they collect raises concerns among the student community. There are various psychological, cultural and technological parameters need to be considered while developing AIPS. This paper systematically reviews existing AI and non-AI-based proctoring systems. Through the systematic search on Scopus, Web of Science and ERIC repositories, 43 paper were listed out from the year 2015 to 2021. We addressed 4 primary research questions which were focusing on existing architecture of AIPS, Parameters to be considered for AIPS, trends and Issues in AIPS and Future of AIPS. Our 360-degree analysis on OPS and AIPS reveals that security issues associated with AIPS are multiplying and are a cause of legitimate concern. Major issues include Security and Privacy concerns, ethical concerns, Trust in AI-based technology, lack of training among usage of technology, cost and many more. It is difficult to know whether the benefits of these Online Proctoring technologies outweigh their risks. The most reasonable conclusion we can reach in the present is that the ethical justification of these technologies and their various capabilities requires us to rigorously ensure that a balance is struck between the concerns with the possible benefits to the best of our abilities. To the best of our knowledge, there is no such analysis on AIPS and OPS. Our work further addresses the issues in AIPS in human and technological aspect. It also lists out key points and new technologies that have only recently been introduced but could significantly impact online education and OPS in the years to come.
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In K-12 contexts and particularly within Türkiye, there is a lack of empirical research examining how teachers conceptualize AI, articulate expectations and concerns, and position AI within pedagogical norms.
“In K-12 contexts and particularly within Türkiye, there is a lack of empirical research examining how teachers conceptualize AI, articulate their expectations and concerns, and position AI within existing pedagogical norms (Chiu et al., 2023;Nigam et al., 2021).”
From Teachers' Experiences with AI in K–12 Education: Opportunities and Challenges (2026) · cites this paper as Nigam et al., 2021
The Conclusion and Discussions section identifies a research gap concerning trust in AI-based versus classroom proctoring, not teachers’ views of AI. Searches for K-12 teachers’ conceptualizations, pedagogical norms, and Türkiye found no passage addressing the claimed empirical-research gap; page numbers were not available in our copy. (LLM, conf=0.74)
Experimental — accuracy not yet measuredEmpirical studies focusing on K-12 contexts remain limited.
“empirical studies focusing on K-12 contexts remain limited (Chiu et al., 2023;Nigam et al., 2021;Roll & Wylie, 2016).”
From Teachers' Experiences with AI in K–12 Education: Opportunities and Challenges (2026) · cites this paper as Nigam et al., 2021
The Search Criteria section (page unavailable) describes a review of 43 papers on online proctoring but does not classify them by educational level. Searches for K-12, primary and secondary schools, and limited empirical studies found no passage assessing whether K-12 research is scarce. (LLM, conf=0.75)
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Online Examination and Evaluation System
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- Authors
- Nigam, A., Pasricha, R., Singh, T., & Churi, P.
- Affiliations
- Narsee Monjee Institute of Management Studies (IN)
- Corresponding author
- Churi, Prathamesh
- ORCID
- Churi, Prathamesh
- Venue
- Education and Information Technologies
- Published
- 2021-06-23
- Volume
- 26
- Issue
- 5
- Pages
- 6421-6445
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- PMC
- PMC8220875
- OpenAlex
- W3173651060
- Cited by
- 267
- References
- 41
- Citations by year
- 2026: 34 · 2025: 64 · 2024: 65 · 2023: 63 · 2022: 36 · 2021: 5
- FWCI
- 7.91
- Type
- journal article
- Language
- en
- Update notices
- correction (2021-12-15)
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Education and Information Technologies (publishedVersion, other-oa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- online proctoring, online examinations, online assessment, privacy concerns, security challenges, ethical considerations, trust in AI, student privacy, online learning, COVID-19 pandemic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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