Authentic assessment design for meeting the challenges of Generative Artificial Intelligence
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 studen...
| Main Authors: | , , |
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| Format: | Conference Paper |
| Published: |
2023
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| Online Access: | http://hdl.handle.net/20.500.11937/93711 |
| _version_ | 1848765770585079808 |
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| author | Khan, Masood Dong, Yu Afsari Manesh, Nasrin |
| author_facet | Khan, Masood Dong, Yu Afsari Manesh, Nasrin |
| author_sort | Khan, Masood |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T11:40:32Z |
| format | Conference Paper |
| id | curtin-20.500.11937-93711 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:40:32Z |
| publishDate | 2023 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-937112023-11-28T04:24:31Z Authentic assessment design for meeting the challenges of Generative Artificial Intelligence Khan, Masood Dong, Yu Afsari Manesh, Nasrin 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. 2023 Conference Paper http://hdl.handle.net/20.500.11937/93711 fulltext |
| spellingShingle | Khan, Masood Dong, Yu Afsari Manesh, Nasrin Authentic assessment design for meeting the challenges of Generative Artificial Intelligence |
| title | Authentic assessment design for meeting the challenges of Generative Artificial Intelligence |
| title_full | Authentic assessment design for meeting the challenges of Generative Artificial Intelligence |
| title_fullStr | Authentic assessment design for meeting the challenges of Generative Artificial Intelligence |
| title_full_unstemmed | Authentic assessment design for meeting the challenges of Generative Artificial Intelligence |
| title_short | Authentic assessment design for meeting the challenges of Generative Artificial Intelligence |
| title_sort | authentic assessment design for meeting the challenges of generative artificial intelligence |
| url | http://hdl.handle.net/20.500.11937/93711 |