Generative AI: Is Authentic Qualitative Research Data Collection Possible?
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| Title: | Generative AI: Is Authentic Qualitative Research Data Collection Possible? |
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| Language: | English |
| Authors: | Cheryl Burleigh (ORCID |
| Source: | Journal of Educational Technology Systems. 2024 53(2):89-115. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 27 |
| Publication Date: | 2024 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Artificial Intelligence, Data Collection, Doctoral Dissertations, Research Methodology, Natural Language Processing, Integrity, Educational Policy, Higher Education |
| DOI: | 10.1177/00472395241270278 |
| ISSN: | 0047-2395 1541-3810 |
| Abstract: | With the advent of readily accessible generative artificial intelligence (GAI), a concern exists within the academic community that research data collected in the context of conducting doctoral dissertation research is authentic. The purpose of the present study was to explore the role of GAI in the production of new research paying particular attention to the use of GAI in collecting new data for a doctoral dissertation. This study employed qualitative methodology examining how GAI, specifically ChatGPT, responded to interview questions from a previously published article by the researchers to determine how closely chatbots mimic responses from the actual study participants. The researchers found that data integrity in qualitative research may be at risk if higher education institutions do not set clear policies and specific parameters for how doctoral research data is obtained and validated in light of GAI. |
| Abstractor: | As Provided |
| Entry Date: | 2024 |
| Accession Number: | EJ1443789 |
| Database: | ERIC |
| Abstract: | With the advent of readily accessible generative artificial intelligence (GAI), a concern exists within the academic community that research data collected in the context of conducting doctoral dissertation research is authentic. The purpose of the present study was to explore the role of GAI in the production of new research paying particular attention to the use of GAI in collecting new data for a doctoral dissertation. This study employed qualitative methodology examining how GAI, specifically ChatGPT, responded to interview questions from a previously published article by the researchers to determine how closely chatbots mimic responses from the actual study participants. The researchers found that data integrity in qualitative research may be at risk if higher education institutions do not set clear policies and specific parameters for how doctoral research data is obtained and validated in light of GAI. |
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| ISSN: | 0047-2395 1541-3810 |
| DOI: | 10.1177/00472395241270278 |
