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World Journal of Advanced Research and Reviews
Article . 2024 . Peer-reviewed
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ZENODO
Article . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
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Comprehensive analysis of human and AI task allocation in the education sector: Defining futuristic roles and responsibilities

Authors: Rashmi Mishra; Deepika Varshney;

Comprehensive analysis of human and AI task allocation in the education sector: Defining futuristic roles and responsibilities

Abstract

This research explores the integration of AI chatbots in higher education, examining their impact on teaching practices, learning outcomes and student engagement. AI's ability to predict and adapt offers transformative potential for educational environments, shifting skill demands and enhancing accessibility. Using the Technological Pedagogical Content Knowledge (TPACK) framework, we assess the integration of AI tools by educators. At the same time, the Technology Acceptance Model (TAM) gauges teacher’s perceptions and Constructivist Learning Theory (CLT) explores AI's support for interactive, student-centered learning. Our developed framework includes the roles and responsibilities of human educators and AI chatbots, strategies for maximizing educational benefits and addressing challenges and best practices for fostering human-AI partnerships and promoting inclusivity. The findings reveal that AI chatbots can significantly reduce administrative burdens on educators, offer personalized learning experiences, and enhance real-time feedback. This study underscores the importance of teacher training and ethical considerations in AI integration. Ultimately, we aim to contribute to the effective integration of AI in education, promoting a balanced synergy between human and technological efforts to enhance educational practices.

Keywords

Conversational agent chatbots, Constructivist Learning Theory (CLT), Technological Pedagogical Content Knowledge (TPACK), Human-AI partnerships, AI chatbots, Technology Acceptance Model (TAM), Artificial intelligence (AI), Student-centered learning

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
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gold
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