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dc.contributor.authorKhan, Masood
dc.contributor.authorDong, Yu
dc.contributor.authorAfsari Manesh, Nasrin
dc.date.accessioned2023-11-09T08:16:24Z
dc.date.available2023-11-09T08:16:24Z
dc.date.issued2023
dc.identifier.citationKhan, M. and Dong, Y. and Afsari Manesh, N. 2023. Authentic assessment design for meeting the challenges of Generative Artificial Intelligence. In Proceedings of 2023 IEEE ASEE Frontiers in Education Conference, 18-21 Oct 2023, College Station, Texas USA.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/93711
dc.description.abstract

Authentic Assessments are generally seen as alternate to traditional assessments though the scope of an authentic assessment is much larger than that of a traditional assessment. Authentic assessments help students in comprehending the subject matter and, if properly designed, can also ensure student workplace readiness. During the authentic assessment design, five most important aspects are considered and their incorporation is sought. These aspects include; the assessment objectives, the physical context of an assessment, the social context, the outcome of the assessment and the assessment criteria. Emergence of the Generative Artificial Intelligence (GAI) supported applications and the Large Language Model (LLM) tools has posed new challenges to the authentic assessment design. Student access to these new applications and tools has also changed the socio-technological realities of the Learning and Teaching (L&T) practices. Therefore, we need to reimagine both, the L&T practices and the design and execution of authentic assessments. Keeping the prevailing socio-technological context in perspective, this work in progress paper proposes extending the scope of authentic assessments. The aim is to use them for quelling the growing problem of plagiarism as plagiarism can be facilitated by the use of GAI and LLM tools. Instead of considering authentic assessments as merely ‘an alternate to the traditional examination’ or ‘a tool for evaluating student workplace readiness,’ we propose adding ‘GAI redundancy’ to the scope of authentic assessments. For incorporating GAI redundancy we propose using either the game-based learning environment or a simulation environment. These two environments can be used for generating ‘close to real life’ problem-solving scenarios while assessing student comprehension and workplace readiness. In order to help practitioners, this paper also presents two examples of authentic assessments that were developed for combating plagiarism vis-à-vis enhancing student learning and evaluating their workplace readiness. In the first example, we show how to use a game environment and in the second example we demonstrate use of a simulation environment. The two examples also show how course contents can be embedded and how GAI redundancy can be incorporated in authentic assessments. The reported teaching assessment data and student feedback suggest that the proposed authentic assessment design and implementation strategies were able to engage students, help their comprehension and evaluate their workforce readiness.

dc.titleAuthentic assessment design for meeting the challenges of Generative Artificial Intelligence
dc.typeConference Paper
dcterms.source.title2023 Frontiers in Education (FIE) Conference
dcterms.source.conference2023 IEEE ASEE Frontiers in Education Conference
dcterms.source.conference-start-date18 Oct 2023
dcterms.source.conferencelocationCollege Station, Texas USA
dc.date.updated2023-11-09T08:16:23Z
curtin.departmentSchool of Civil and Mechanical Engineering
curtin.accessStatusOpen access
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidKhan, Masood [0000-0002-2769-2380]
dcterms.source.conference-end-date21 Oct 2023
curtin.contributor.scopusauthoridKhan, Masood [7410317782]
curtin.repositoryagreementV3


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