Education Sciences · 2023 · 350 citations · 30 references
EducationEducational AssessmentHigher EducationArtificial IntelligenceArtificial Intelligence In EducationAssessment FairnessAcademic Integrity DetectionGenerative Ai In EducationInternationalization Of Higher EducationLanguage Bias In AssessmentNatural Language Processing In EducationAccess For International StudentsAi LiteracyAi-based PracticeArtificial Intelligence LiteracyAssessmentsBias In Educational AiDiscrimination Against International StudentsEquity For International Students
Generative Artificial Intelligence (GAI) is transforming higher education, offering opportunities while raising concerns about academic integrity and the use of AI detection tools. The paper investigates GAI’s impact on student life, especially international students, and proposes a culturally competent AI competency framework aligned with Revised Bloom’s Taxonomy to guide equitable teaching. The authors analyze GAI’s influence on student life and international students and construct a culturally competent AI competency framework mapped to Revised Bloom’s Taxonomy. The essay finds that detecting AI‑generated content is unreliable, raising false‑accusation risks; AI models exhibit biases that disproportionately affect international students; yet AI can provide language support and accessibility, underscoring the need for a balanced, ethically informed approach that promotes AI literacy and equity.
Generative Artificial Intelligence (GAI) has emerged as a transformative force in higher education, offering both challenges and opportunities. This paper explores the multifaceted impact of GAI on academic work, with a focus on student life and, in particular, the implications for international students. While GAI, exemplified by models like ChatGPT, has the potential to revolutionize education, concerns about academic integrity have arisen, leading to debates on the use of AI detection tools. This essay highlights the difficulties in reliably detecting AI-generated content, raising concerns about potential false accusations against students. It also discusses biases within AI models, emphasizing the need for fairness and equity in AI-based assessments with a particular emphasis on the disproportionate impact of GAI on international students, who already face biases and discrimination. It also highlights the potential for AI to mitigate some of these challenges by providing language support and accessibility features. Finally, this essay acknowledges the disruptive potential of GAI in higher education and calls for a balanced approach that addresses both the challenges and opportunities it presents by emphasizing the importance of AI literacy and ethical considerations in adopting AI technologies to ensure equitable access and positive outcomes for all students. We offer a coda to Ng et al.’s AI competency framework, mapped to the Revised Bloom’s Taxonomy, through a lens of cultural competence with AI as a means of supporting educators to use these tools equitably in their teaching.
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A Revision of Bloom's Taxonomy: An Overview
David R. Krathwohl · Theory Into Practice · 2002 · 7.5K citations · Full text
What is AI Literacy? Competencies and Design Considerations
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Computing, Computer Science, Design +13