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The role of authentic assessment to preserve academic integrity and promote skill development and employability
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Promoting authenticity and academic integrity in assessment continues to present a priority for educational institutions. Besides providing the foundation for high academic standards and best practice, authentic assessments and academic integrity enrich students with skills that advance their employability. Given the multilayered significance of, and need for promoting academic integrity, this study used a suite of scaffolded authentic assessments that culminated with interactive oral examinations. A survey evaluated the effectiveness of interactive oral exams in offering authentic assessments that would prevent students from engaging in academic misconduct and help them improve their skill and employability prospects. The results show that scaffolded assessment tasks that include interactive orals help prevent academic misconduct. The more relevant the assessment to real-world scenarios, the less likely students are to engage in misconduct. Additionally, interactive oral exams enabled students to develop their professional identity and awareness, and communications skills, and help promote employability.
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“Authentic, cognitively demanding tasks incorporating oral defenses, experiential components, and disciplinary problem-solving help preserve academic integrity while building employability skills (Salinas-Navarro et al., 2024; Sotiriadou et al., 2019; Villarroel et al., 2019).”
From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Sotiriadou et al., 2019
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“Furthermore, oral assessments provide authentic evaluation opportunities that align closely with professional workplace requirements (Iannone et al., 2020;Sotiriadou et al., 2020;Turjamaa et al., 2018)”
From Replacing Traditional Written Laboratory Reports with Interactive Oral Assessments: Enhancing Laboratory Skill Assessment in Undergraduate Genetics Education (2026) · cites this paper as Sotiriadou et al., 2020
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“while making academic misconduct more difficult (Kang et al., 2019;Sotiriadou et al., 2020).”
From Replacing Traditional Written Laboratory Reports with Interactive Oral Assessments: Enhancing Laboratory Skill Assessment in Undergraduate Genetics Education (2026) · cites this paper as Sotiriadou et al., 2020
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Metadata
- Authors
- Sotiriadou, P., Logan, D., Daly, A., & Guest, R.
- Affiliations
- Griffith University (AU)
- Learning & Teaching Consultant (Design), Griffith Business School, Griffith University, Gold Coast, Australia
- Corresponding author
- Sotiriadou, Popi
- Venue
- Studies in Higher Education
- Publisher
- Informa UK Limited
- Published
- 2019-02-26
- Volume
- 45
- Issue
- 11
- Pages
- 2132-2148
- ISSN
- 0307-5079 (ISSN-L)
- 1470-174X
- OpenAlex
- W2917546397
- Cited by
- 265
- References
- 36
- Citations by year
- 2026: 37 · 2025: 49 · 2024: 51 · 2023: 56 · 2022: 31 · 2021: 26 · 2020: 14
- FWCI
- 31.01
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- Studies in Higher Education (publishedVersion)
- Griffith Research Online (submittedVersion)
- Topics
- Social Sciences › Education › Academic integrity and plagiarism
- Social Sciences › Education › Student Assessment and Feedback
- Social Sciences › Education › Higher Education and Employability
- Keywords
- authentic assessment, academic integrity, academic misconduct, employability, skill development, professional identity, communication skills, higher education assessment
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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