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.

中文翻译：

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欣赏性探究在项目评估和研究中的潜力

目的

本文的目的是提供对人工智能的描述，并记录和比较人工智能的两种应用，一种用于项目评估，另一种用于应用研究。

设计/方法/方法

焦点小组、访谈和观察被用来收集丰富的定性数据，这些数据用于详细说明欣赏式探究在评估和研究中的价值。

发现

人工智能帮助研究人员与参与者建立联系并评估他们分享的内容。在这两项研究中，人工智能的使用积累了回答研究问题的信息，提供了对背景和发现的丰富描述，并导致数据饱和。作者描述并比较了两种人工智能应用的经验：程序评估和研究。本文有助于进一步了解公共教育机构中人工智能的使用。研究人员还探索了在定性研究中使用人工智能的功效，并推荐将其用于多种用途。

研究限制/影响

由于使用积极的观点，并且因为所研究的计划和合作伙伴关系都是新的，用于设计更美好未来的数据有限，因此在 AI 设计阶段出现了限制。因此，作者建议通过相同的 4D 模型重新审视这两项研究。

实际影响

这份手稿表明人工智能对评估和研究很有用。它通过最喜欢的故事和成功来放大参与者的声音。人工智能有许多未被发现的用途。

社会影响

通过使用人工智能，作者可以： 改进理论观点；进行研究以产生更真实的数据；使参与者能够深入反思他们的实践并感到自己被赋予了力量；并最终影响和改善世界。

原创性/价值

人工智能被用作高中课程的评估工具和识别教育伙伴关系的优势和看法的研究方法。在这两项研究中，人工智能打破了受访者在期望为决定和行动辩护或辩护时经常竖立的墙壁。本文有助于进一步了解公共教育机构中人工智能的使用。