{"id":20242,"date":"2021-10-01T00:00:38","date_gmt":"2021-10-01T00:00:38","guid":{"rendered":"https:\/\/www.tamus.edu\/data-science\/?p=20242"},"modified":"2023-02-28T22:56:30","modified_gmt":"2023-02-28T22:56:30","slug":"does-student-faculty-similarity-improve-graduation-outcomes","status":"publish","type":"post","link":"https:\/\/www.tamus.edu\/data-science\/2021\/10\/01\/does-student-faculty-similarity-improve-graduation-outcomes\/","title":{"rendered":"Does student-faculty similarity improve graduation outcomes?"},"content":{"rendered":"\t\t
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Does student-faculty similarity improve graduation outcomes?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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As has been the case with past data blogs<\/a>, many of the conversations occurring in higher education are focused on the concepts associated with diversity, equity, and inclusion (DEI). Universities, systems, and state boards of higher education are grappling with the implications of DEI, especially in terms of identifying equity gaps in enrollment, persistence, and graduation, and plotting a course of action to continue closing those gaps. One such line of inquiry that has come to the forefront has been whether gaps exist between student and faculty demographic representation on campus. We briefly explored this concept in an <\/span>earlier blog post<\/a>, finding that, in general at Texas public universities, female faculty identified as Asian, African American, or Hispanic\/Latinx are underrepresented when compared with the proportion of students in the same demographic group, as are male faculty identified as African American or Hispanic\/Latinx. <\/span>As an extension to the previous analysis, we now return to this concept of student-faculty representation in this blog post, which will start a series of posts that will attempt to answer the following question: <\/span>Does closing the representation gap promote increased student outcomes for historically underrepresented minority students?<\/b><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Measuring Demographic Similarities: Location Quotient (LQ)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Previously described in other blog posts, we are calculating the location quotient (LQ) that allows comparison across demographic groups within different grouping variables. As a \u201cratio of ratios\u201d metric, the LQ takes the percentage of faculty within a specific demographic as the numerator and uses the percentage of students in that same demographic as the denominator to calculate the LQ score.\u00a0Interpreting the LQ score is relatively straightforward:<\/p>\n

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  • LQ score = 1.0:\u00a0<\/span>faculty\u2019s concentration is\u00a0very similar<\/span>\u00a0to the student\u2019s concentration.<\/li>\n
  • LQ score > 1.0:<\/span>\u00a0faculty\u00a0over-represented <\/span>when compared to student’s concentration<\/span>.<\/li>\n
  • LQ score < 1.0:<\/span>\u00a0faculty under<\/b>-represented\u00a0<\/span>when compared to student’s concentration<\/span>.<\/span><\/li>\n<\/ul>\n

    The visualization to the right shows the average LQ score for each race\/ethnicity category by Carnegie Classification for all public universities in the United States. The data show that\u00a0White faculty are over-represented, while Black or African American faculty and Hispanic or Latinx faculty are under-represented across all three Carnegie Classification groups.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t

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