Developing transferable skills for the public good

Transferable skills are crucial for undergraduates to be prepared to enter the workforce after college. Previous research has shown how effective educational approaches enhance student learning. There is, however, limited research that understands how the emphasis on transferable skills relates to the value of deep approaches to student learning. This paper analyzes how faculty emphasis of transferable skills, through analytical writing and problem-solving, is related to deep approaches to learning in higher education. Data come from a large-scale, multi-institutional study that surveys faculty at four-year institutions. Findings indicate that the intentional development of transferable skills has a positive relationship with emphases on deep approaches to learning. The study reinforces the importance of collaboration between multiple stakeholders to foster student learning

Person centered approaches to inclusive data analysis

Demographic questions are critical to our understanding of student and faculty experiences, allowing us to learn about marginalized subpopulations, find areas of inequity, and close gaps in achievement. Although this work is necessary, it does present challenges for critical and inclusive approaches to data analysis. Person-centered approaches, grouping people based on similar experiences or outcomes, allow for more nuanced stories of experiences. To illustrate the benefits of this approach, facilitators will guide participants through a series of examples using person-centered explorations, unpacking the challenges and possible solutions for using such methods for more critical and inclusive quantitative analyses and reporting

Lost at the Crossing? Tips for Assessing Intersectional Experiences

Faculty and administrators are often tasked with educating the whole student upon their arrival at college, so it is important to understand ways to assess the whole student. Often student demographics and characteristics are examined one at a time such as by examining differences by racial/ethnic, gender, or other known influences on the student experience. Disaggregating data in this way, allows us to better understand how different students understand and participate in their environment. This poster provides an overview of four different examples to better examine small populations with attention to intersections of identity