Soft skills such as critical thinking, communication, and teamwork have been repeatedly called out as essential skills by employers. Despite this, essential skills are often inconsistently developed and measured within higher education institutions. In this session we will focus on where and how soft skills are developed as well as why that information is relevant to assessment strategy. By the end of the session, you will have a high-level understanding of where and how these skills develop to inform good assessment practice and validation of soft skills that are, traditionally, more difficult to measure. 

An increasing trend in higher education, especially for institutional research professionals, is data governance. There is a lot of literature pointing to the benefits, a few software programs to support it, and lots of people throwing the words around, but what does data governance actually look like? How is it established on a campus? And when the team is assembled, what do you do? When we began data governance at John Carroll University we were told to eat the elephant one bite at a time, but we didn’t even know where to start “eating”! This workshop will walk you through the first three years of John Carroll University’s data governance initiative, and give you time to plan yours. 

The Postsecondary Data Partnership (PDP) is a nationwide effort to help colleges and universities gain a fuller picture of student successes and areas to target for improvement.   With the PDP Tableau dashboards that include both leading and lagging measures, you can assess whether students are on track, and where to intervene, access data on all new students, save time and resources on reporting and accreditation requirements, identify where to focus your resources, and identify equity gaps.   This session will begin with a brief overview and then explore the PDP through case studies within the dashboards that explore insights for equity gaps and/or the impact of reform with a focus on leading indicators and the ability to benchmark against peer institutions 

This session will provide examples of how the Canvas learning management

platform can collect student achievement data of outcomes and the component assessed criteria

 directly from coursework, the impact of automation on facilitating efficient and effective assessment

processes, enhanced techniques of analysis by programs through interactive

tables and graphs of the achievement data, and examples of instructional/curricular considerations 

that can result.

Using Python, a massive data mine went underway to determine sentiment towards a regional university in Oklahoma. Various social media and review sites were scraped for comments about the university. Analysis was performed to determine general sentiment towards the university and if it changed over time. Word clouds were also created to help visualize the words and comments yielded towards the university. These are used to determine how to help improve areas not favorably viewed. 

This study examines the salary disparity between female and male faculty at K-State. Rather than making comparisons on the population level, this study uses propensity score matching (PSM) model to establish cohorts of female and male faculty with the same/similar race, contract type, years in rank and college. Based on the matched cohorts, the significances of their salary differences by academic rank were analyzed using t test. The effect of PSM process on the results was investigated. 

In 2021, Northwest Missouri State University became aware of a grant opportunity meant to improve recruitment and completion rates of domestic underrepresented teacher preparation students. To predict what factors were related to the success of domestic underrepresented students in the past, staff underwent an analysis of 10 years worth of data. Analyses included logistic regression and algorithms, using tools such as SPSS, Python, Weka and Rapid Miner. Lecture style presentation. 

OTC's Center for Academic Innovation needed a way to track information related to faculty's teaching experiences, trainings, contact information, and more. The team also wanted to engage adjunct instructors/connect them with relevant supports through an on-going calling campaign. The result? This session will walk through the development of an interactive, self-updating Power BI report using data from OTC's SIS, Qualtrics, and Excel. Unsure how to connect those dots? Let's learn together! 

CATS 2.0 is a unique process utilized and implemented at all levels of the institution to assist leaders in making key strategic decisions. There are 7 key steps covered in this model: creating problem statements, Restating the task, Analyze the problem, Develop possible solutions, Decision brief, Implementation and Result sharing. This session also identifies the key roles for this process complete with a "real-world example" as part of this session. 

This study predicts admitted applicants’ likelihood to enroll based on several key characteristics, including variables from demographics, preparedness, time-related, and financial categories. K-State’s applicant data from 2018 to 2020 were used. Bivariate analysis between enrollment result and each variable was conducted at first. A two-level hierarchical logistic regression model was also built to identify and compare each factor’s effects on enrollment probability. 

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