Appreciative Inquiry's Potential in Program Evaluation and Research

Autor/inn/en	Griggs, Dana M.; Crain-Dorough, Mindy
Titel	Appreciative Inquiry's Potential in Program Evaluation and Research
Quelle	In: Qualitative Research Journal, 21 (2021) 4, S.375-393 (19 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Griggs, Dana M.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1443-9883
DOI	10.1108/QRJ-06-2020-0059
Schlagwörter	Program Evaluation; Artificial Intelligence; Research Methodology; Qualitative Research; Inquiry; Data Collection; Public Education; Technology Uses in Education; Models; High Schools; Partnerships in Education; Educational Technology + Suchen Sie Ihr Suchwort? Programme evaluation; Programmevaluation; Künstliche Intelligenz; Research method; Forschungsmethode; Qualitative Forschung; Data capture; Datensammlung; Öffentliche Erziehung; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Analogiemodell; High school; Oberschule; Hochschulpartnerschaft; Unterrichtsmedien
Abstract	Purpose: The purposes of this paper are to provide a description of AI and to document and compare two applications of AI, one in program evaluation and another in an applied research study. Design/methodology/approach: Focus groups, interviews and observations were used to gather rich qualitative data which was used to detail Appreciative Inquiry's value in evaluation and research. Findings: AI aided the researcher in connecting with the participants and valuing what they shared. In both studies, the use of AI amassed information that answered the research questions, provided a rich description of the context and findings, and led to data saturation. The authors describe and compare experiences with two applications of AI: program evaluation and a research study. This paper contributes further understanding of the use of AI in public education institutions. The researchers also explore the efficacy of using AI in qualitative research and recommend its use for multiple purposes. Research limitations/implications: Limitations occurred in the AI-Design Stage by using a positive viewpoint and because both program and partnership studied were new with limited data to use for designing a better future. So, the authors recommend a revisit of both studies through the same 4D Model. Practical implications: This manuscript shows that AI is useful for evaluation and research. It amplifies the participants' voices through favorite stories and successes. AI has many undiscovered uses. Social implications: Through the use of AI the authors can: improve theoretical perspectives; conduct research that yields more authentic data; enable participants to deeply reflect on their practice and feel empowered; and ultimately impact and improve the world. Originality/value: AI is presented as an evaluation tool for a high-school program and as a research approach identifying strengths and perceptions of an educational partnership. In both studies, AI crumbled the walls that are often erected by interviewees when expecting to justify or defend decisions and actions. This paper contributes further understanding of the use of AI in public education institutions. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01