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Faculty Perceptions of Generative Ar...

Nadler, Melinda D.,

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Faculty Perceptions of Generative Artificial Intelligence in the Social Sciences and Humanities: A Phenomenological Study /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Faculty Perceptions of Generative Artificial Intelligence in the Social Sciences and Humanities: A Phenomenological Study // Melinda D Nadler.
Author:	Nadler, Melinda D.,
Description:	1 electronic resource (121 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-04, Section: B.
Contained By:	Dissertations Abstracts International86-04B.
Subject:	Higher education. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31556258
ISBN:	9798384467045

Faculty Perceptions of Generative Artificial Intelligence in the Social Sciences and Humanities: A Phenomenological Study /
Nadler, Melinda D.,

Faculty Perceptions of Generative Artificial Intelligence in the Social Sciences and Humanities: A Phenomenological Study /Melinda D Nadler. - 1 electronic resource (121 pages)

Source: Dissertations Abstracts International, Volume: 86-04, Section: B.

This qualitative phenomenological study examines faculty perceptions of generative AI in the social sciences and humanities in the United States. As generative artificial intelligence (AI) tools become more widely available on higher education campuses, concerns have arisen about faculty's preparedness to manage and address the use of these technologies. The primary research question explores the participants' perceptions of generative AI, including its perceived benefits and concerns. Sub-questions focus on shifts in pedagogy, efforts to teach students ethical use of generative AI tools, and the guidance from participant institutions. The researcher developed a semi-structured interview protocol and interviewed 10 participants. The data were coded through researcher annotation and verified using AI-powered qualitative data analysis software, Atlas.ti. The researcher organized the codes into categories and subcategories, eventually forming four domains, eight themes, and ten sub-themes to address the research questions and highlight the meaning that participants attributed to their experiences with generative AI tools in higher education. The researcher concluded that faculty comfort and understanding of generative AI vary widely. Some embrace it as a tool to enhance student engagement while others avoid it due to ethical concerns. The results indicated that while faculty are interested in the potential benefits of these tools, they are also cautious about students' reliance on them. They expressed concerns about the reasons for academic dishonesty and the impact of generative AI on student learning and development. Faculty members feel unequipped to manage generative AI in their courses and want more support and discipline-specific guidance from university leadership to navigate these new technologies effectively. They seek clear institutional policies and effective support systems to help them integrate generative AI with their disciplines ethically and successfully. The study fills a gap in the literature by focusing on the experiences of social sciences and humanities faculty in the U.S. and raises questions for further investigation, such as expanding the sample to other disciplines and incorporating observational methodologies. The study underscores the need for proactive measures to ensure the ethical and effective integration of generative AI in higher education.

English

ISBN: 9798384467045Subjects--Topical Terms:

641065
Higher education.
Subjects--Index Terms:

Faculty perceptions

Faculty Perceptions of Generative Artificial Intelligence in the Social Sciences and Humanities: A Phenomenological Study /
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520 $a This qualitative phenomenological study examines faculty perceptions of generative AI in the social sciences and humanities in the United States. As generative artificial intelligence (AI) tools become more widely available on higher education campuses, concerns have arisen about faculty's preparedness to manage and address the use of these technologies. The primary research question explores the participants' perceptions of generative AI, including its perceived benefits and concerns. Sub-questions focus on shifts in pedagogy, efforts to teach students ethical use of generative AI tools, and the guidance from participant institutions. The researcher developed a semi-structured interview protocol and interviewed 10 participants. The data were coded through researcher annotation and verified using AI-powered qualitative data analysis software, Atlas.ti. The researcher organized the codes into categories and subcategories, eventually forming four domains, eight themes, and ten sub-themes to address the research questions and highlight the meaning that participants attributed to their experiences with generative AI tools in higher education. The researcher concluded that faculty comfort and understanding of generative AI vary widely. Some embrace it as a tool to enhance student engagement while others avoid it due to ethical concerns. The results indicated that while faculty are interested in the potential benefits of these tools, they are also cautious about students' reliance on them. They expressed concerns about the reasons for academic dishonesty and the impact of generative AI on student learning and development. Faculty members feel unequipped to manage generative AI in their courses and want more support and discipline-specific guidance from university leadership to navigate these new technologies effectively. They seek clear institutional policies and effective support systems to help them integrate generative AI with their disciplines ethically and successfully. The study fills a gap in the literature by focusing on the experiences of social sciences and humanities faculty in the U.S. and raises questions for further investigation, such as expanding the sample to other disciplines and incorporating observational methodologies. The study underscores the need for proactive measures to ensure the ethical and effective integration of generative AI in higher education.
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