Search results

Companies of all types are investing significant time and resources in regularly “assessing” themselves according to an internally designed set of criteria. More and more, these assessments are focused broadly on entire company systems and less on pure quality criteria, such as the quality of products and services. Although each firm strives to find the “right” set of criteria for their unique position, set of circumstances, and idiosyncratic culture, most seem to gravitate toward a set of loosely defined, generic characteristics which, to a remarkable extent, reflect the broad categories of the Malcolm Baldrige National Quality Award Criteria. This article examines the linkages between broadly defined assessment criteria and the comprehensive structure of the Malcolm Baldrige National Quality Award.

Black Male faculty are severely underrepresented in public universities (Harper, 2010; Li & Koedel, 2017), especially in the department of engineering where they frequently have no representation at all (Nelson et al., 2010). The problem is often attributed (especially by employers) to a pipeline issue, suggesting a lack of a recruitment pool of Black male faculty. However, it is increasingly recognized that turnover and attrition may play a critical role in contributing to the lack of Black engineering faculty (Whittaker et al., 2015). This chapter reports results from a larger national survey of 1,161 engineering faculty at research intensive institutions, of which only 14 identified as Black males (further evidencing underrepresentation). We focus on the responses from the latter group, through a qualitative analysis of their responses to inquiries concerning barriers in their institution for tenure, research, funding, and teaching; diversity concerns; and sentiments regarding their job satisfaction and consideration for employment resignation. Issues identified by participants included feelings of isolation, exclusion and even discrimination at their workplace. Based on these concerns, we suggest talent centered education leadership (TCEL) as a guiding framework to help higher education employers improve the equity and inclusivity of their workspace by creating a more engaging environment for their Black male faculty. TCEL is a recently introduced inclusive talent management framework (Tran, 2022; Tran & Smith, 2020) that emphasizes humanizing the education workplace. Essential to that humanization is creating and maintaining a work environment where all employees feel a sense of belonging.

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.

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.

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.

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.

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.

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.

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.