Generative AI and the implications for authentic assessment
Powell, Stephen and Forsyth, Rachel LU
(2024)
p.97-105
- Abstract
This chapter aims to provide practical evidence-based guidance in the use of generative artificial intelligence (GenAI) for the design and management of authentic assessment tasks and provide a grounding for institutional policy conversations so that decisions can be influenced in a constructive learner-centric way. Drawing on the foundational principles of assessment and feedback, we critically examine how fairness, validity, and security considerations interplay with GenAI’s affordances and challenges. We explore the potential opportunities for the use of Al in the preparation and management of formative and summative assessments. We set out a case for a shift towards authentic assessment practices that empower learners, not only by... (More)
This chapter aims to provide practical evidence-based guidance in the use of generative artificial intelligence (GenAI) for the design and management of authentic assessment tasks and provide a grounding for institutional policy conversations so that decisions can be influenced in a constructive learner-centric way. Drawing on the foundational principles of assessment and feedback, we critically examine how fairness, validity, and security considerations interplay with GenAI’s affordances and challenges. We explore the potential opportunities for the use of Al in the preparation and management of formative and summative assessments. We set out a case for a shift towards authentic assessment practices that empower learners, not only by equipping them with GenAI skills for learning and future work but also by fostering their ability to contribute meaningfully to society.
(Less)
- author
- Powell, Stephen
and Forsyth, Rachel
LU
- organization
- publishing date
- 2024-01-01
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Using Generative AI Effectively in Higher Education : Sustainable and Ethical Practices for Learning, Teaching and Assessment - Sustainable and Ethical Practices for Learning, Teaching and Assessment
- pages
- 9 pages
- publisher
- Taylor & Francis
- external identifiers
-
- scopus:85204565296
- ISBN
- 9781032773988
- 9781040108239
- DOI
- 10.4324/9781003482918-15
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2024 selection and editorial matter, Sue Beckingham, Jenny Lawrence, Stephen Powell and Peter Hartley; individual chapters, the contributors. All rights reserved.
- id
- 98b1a8ee-60ea-469b-9697-e28a3573bd50
- date added to LUP
- 2024-10-04 07:58:23
- date last changed
- 2025-07-12 09:29:39
@inbook{98b1a8ee-60ea-469b-9697-e28a3573bd50,
abstract = {{<p>This chapter aims to provide practical evidence-based guidance in the use of generative artificial intelligence (GenAI) for the design and management of authentic assessment tasks and provide a grounding for institutional policy conversations so that decisions can be influenced in a constructive learner-centric way. Drawing on the foundational principles of assessment and feedback, we critically examine how fairness, validity, and security considerations interplay with GenAI’s affordances and challenges. We explore the potential opportunities for the use of Al in the preparation and management of formative and summative assessments. We set out a case for a shift towards authentic assessment practices that empower learners, not only by equipping them with GenAI skills for learning and future work but also by fostering their ability to contribute meaningfully to society.</p>}},
author = {{Powell, Stephen and Forsyth, Rachel}},
booktitle = {{Using Generative AI Effectively in Higher Education : Sustainable and Ethical Practices for Learning, Teaching and Assessment}},
isbn = {{9781032773988}},
language = {{eng}},
month = {{01}},
pages = {{97--105}},
publisher = {{Taylor & Francis}},
title = {{Generative AI and the implications for authentic assessment}},
url = {{http://dx.doi.org/10.4324/9781003482918-15}},
doi = {{10.4324/9781003482918-15}},
year = {{2024}},
}