Commentary: ChatGPT-supported student assessment – can we rely on it?

ChatGPT-supported student assessmentcan we rely on it?The advent of generative AI, particularly ChatGPT, in the educational sector is sparking a multifaceted debate on its reliability for student assessment.Recent literature focuses on the potential of ChatGPT to revolutionize assessment methods, raising both enthusiastic endorsements for its capabilities and serious concerns about the integrity and effectiveness of AI-driven evaluations (Klyshbekova and Abbott, 2024).ChatGPT's advanced natural language processing (NLP) capabilities can mimic humanlike text generation, suggesting a shift from traditional, linear models of learning assessment toward more dynamic and personalized approaches (Dama sevi cius, 2023).This transition could enhance learning outcomes by tailoring educational experiences to individual needs and providing immediate feedback.The reliability of such AI assessments is under scrutiny, particularly concerning the depth and academic rigor of the responses.The integration of ChatGPT for student grading has presented various challenges, juxtaposing traditional assessment methods against emerging AI-driven approaches (Jukiewicz, 2024).ChatGPT when used for grading can handle large volumes of assessments quickly, providing immediate feedback that is consistent as long as the input remains within the model's training data scope (Kooli and Yusuf, 2024).ChatGPT can grade assignments across different subjects, demonstrating a moderate correlation with human graders, which highlights its potential as a supportive tool (Kooli and Yusuf, 2024).However, ChatGPT's grading performance can lack depth, missing nuanced insights that experienced educators might offer (Ghapanchi and Purarjomandlangrudi, 2023).The complexity and subtlety of student responses can be underappreciated by AI, which may struggle with interpretations that require deep understanding and contextual awareness.The standardization of feedback may not address specific developmental needs of individual students, which are critical for personalized learning.The adoption of ChatGPT and similar AI technologies in student grading and assessment heralds significant broader implications for the field of education (Yang et al., 2023).One of the most transformative impacts is the potential shift in the role of educators.With AI handling more routine and administrative tasks, educators can 1 2 redirect their focus towards more in-depth, interactive and personalized teaching methods.This could lead to an enhancement of the pedagogical process, where the emphasis shifts from teaching to the test to fostering deeper understanding and critical thinking skills (Damasevicius and Sidekerskiene, 2024).The integration of AI into assessment processes challenges and could reshape the traditional assessment paradigms.AI's capability to analyze vast amounts of data can lead to the development of more sophisticated and adaptive learning environments, where JRIT 17,

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Journal
Journal of Research in Innovative Teaching & Learning
Published
2024-08-20
DOI
https://doi.org/10.1108/jrit-09-2024-195
Citations
7
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.84
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article

Commentary: ChatGPT-supported student assessment – can we rely on it?

Robertas Damaševičius
7 citations
Journal of Research in Innovative Teaching & Learning
Artificial Intelligence in Healthcare and Education
0.84
article

Commentary: ChatGPT-supported student assessment – can we rely on it?

Robertas Damaševičius
article en
7 citations

Abstract

ChatGPT-supported student assessmentcan we rely on it?The advent of generative AI, particularly ChatGPT, in the educational sector is sparking a multifaceted debate on its reliability for student assessment.Recent literature focuses on the potential of ChatGPT to revolutionize assessment methods, raising both enthusiastic endorsements for its capabilities and serious concerns about the integrity and effectiveness of AI-driven evaluations (Klyshbekova and Abbott, 2024).ChatGPT's advanced natural language processing (NLP) capabilities can mimic humanlike text generation, suggesting a shift from traditional, linear models of learning assessment toward more dynamic and personalized approaches (Dama sevi cius, 2023).This transition could enhance learning outcomes by tailoring educational experiences to individual needs and providing immediate feedback.The reliability of such AI assessments is under scrutiny, particularly concerning the depth and academic rigor of the responses.The integration of ChatGPT for student grading has presented various challenges, juxtaposing traditional assessment methods against emerging AI-driven approaches (Jukiewicz, 2024).ChatGPT when used for grading can handle large volumes of assessments quickly, providing immediate feedback that is consistent as long as the input remains within the model's training data scope (Kooli and Yusuf, 2024).ChatGPT can grade assignments across different subjects, demonstrating a moderate correlation with human graders, which highlights its potential as a supportive tool (Kooli and Yusuf, 2024).However, ChatGPT's grading performance can lack depth, missing nuanced insights that experienced educators might offer (Ghapanchi and Purarjomandlangrudi, 2023).The complexity and subtlety of student responses can be underappreciated by AI, which may struggle with interpretations that require deep understanding and contextual awareness.The standardization of feedback may not address specific developmental needs of individual students, which are critical for personalized learning.The adoption of ChatGPT and similar AI technologies in student grading and assessment heralds significant broader implications for the field of education (Yang et al., 2023).One of the most transformative impacts is the potential shift in the role of educators.With AI handling more routine and administrative tasks, educators can 1 2 redirect their focus towards more in-depth, interactive and personalized teaching methods.This could lead to an enhancement of the pedagogical process, where the emphasis shifts from teaching to the test to fostering deeper understanding and critical thinking skills (Damasevicius and Sidekerskiene, 2024).The integration of AI into assessment processes challenges and could reshape the traditional assessment paradigms.AI's capability to analyze vast amounts of data can lead to the development of more sophisticated and adaptive learning environments, where JRIT 17,

Journal of Research in Innovative Teaching & LearningVol. 17(2)
Vytautas Magnus University (LT)
Quality Education
Openalex Percentile: Top 24%
Artificial Intelligence in Healthcare and Education
0.84
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