Status: Past

Community college (CC) students who intend to transfer to baccalaureate programs often encounter complex curricular requirements. To navigate them, students activate their social and academic networks in a variety of ways. In this case study of a cohort of CC students in an urban system, we trace the the importance of those we call keystone agents — people in network positions which bridge campus ecologies. We find that keystone agents are important source of information and other supports. We illustrate how keystone agents share information across student networks and how their beliefs about curriculum navigation hold sway over students’ course-taking behaviors, even when these beliefs run counter to the design of guided pathways programs and other local campus-based interventions. Keystone agents’ information sharing aims to create organizational pathways that are intended to reduce friction within CC course sequences, but they also have a series of unintended consequences when students choose to transfer. We offer implications for the development of transfer support programs and interventions, curricular policy-making, and the design of campus environments.

In this update of work presented at the Pathways seminar in February 2023, we will present our approach to creating measures to describe and quantify complexity in major curricular requirements, which may act as a barrier to the students’ ability to navigate college. We discuss our general goals in creating the measures, the past work we draw upon, and our different analytic approaches, which were variably fruitful. We present descriptive results showing our measures of task complexity in major requirements in four departments at each of 32 colleges.

Doing good pathways research requires access to the right kinds of data. For example, studying students’ trajectories through college requires data that is longitudinal and relational; learning from the diverse experiences of students at different types of institutions requires data from multiple colleges; and understanding the long-term value of educational experiences requires data that follows students well beyond college. It is rare for one data source to have all these qualities—plus be accessible to all qualified researchers—which is why we constructed the College and Beyond II (CBII) data. The purpose of CBII is to democratize access to rich institutional data, and in doing so, produce new insights about how undergraduate education works. In this presentation we provide a general overview of CBII that highlights the many data types (e.g., administrative records, transcripts, survey outcomes, written responses) and measures (e.g., validated scales, National Student Clearinghouse enrollment and awards records, AP test scores) that are available. To illustrate the data’s potential, we will highlight preliminary work using the data. The presentation will also be conversational, allowing pathways researchers an opportunity to discuss how the data could be used to answer their own research questions and further their research agendas.

While existing research on academic pathways has typically observed progress via observation of course enrollments and major selection, there are more subtle aspects of students’ everyday experiences that comprise academic progress as well. My research explores the potential of large-scale digital trace data from learning-management systems (such as Canvas) to capture students’ longitudinal patterns of engagement, which is a precondition for development and success in higher education. By examining engagement patterns, I provide a more nuanced and comprehensive picture of student activity and experience, and better understand the development of academic pathways.

Social scientists have long recognized that students’ course grades are consequential for academic progress, yet they have devoted little attention to variation in the protocols through which instructors assign grades. I call these protocols “grading practices.” Their variation may be especially wide in college settings, where instructors often have considerable discretion over grading practices. In some practices, grades are criterion-based, wherein student performance is compared against a set of standards. In other cases, students are compared to the performance of other students in a practice known as curving. Students entering higher education face the challenge of recognizing variation in grading practices and making sense of them under conditions they may perceive as high stakes. I report preliminary findings from a longitudinal study of undergraduates moving through an admissions-selective university to demonstrate the breadth of variation grading practices students encounter. I find substantial variation in how grades are assigned even among courses utilizing curved grades. Perhaps remarkably, initial analyses of qualitative interview data with students in courses with curved grades surface little evidence that grading curves per se engender competition; rather, perceptions of grades in curved courses are highly dependent on course structure and students’ previous exposure to course content.

Postsecondary course-taking is of interest to researchers from diverse domains including economics, sociology, and policy. Transformations in digital infrastructure mean researchers increasingly have access to rich administrative transcripts on course-taking. However, administrative transcripts are seldom standardized across institutions or state systems, preventing researchers from easily examining trends in course-taking and course pathways at scale. To address this challenge, we apply machine learning and natural-language processing techniques to efficiently standardize administrative transcripts at scale. Drawing on four waves of the National Center for Education Statistics’ Postsecondary Education Transcripts Studies, we train logistic regression models to classify courses drawn from administrative transcripts into the College Course Map, a hierarchical taxonomy of course-taking. We apply these models to administrative transcripts from 18 institutions in the College and Beyond II dataset and use the standardized transcript measures to examine longitudinal trends in course-taking in the core liberal arts and professional disciplines from ten years of cohorts of baccalaureate graduates. Contrasting these trends in course-taking with those of majors, we find that the proportion of course enrollments in the core liberal arts is meaningfully higher than that of the proportion of majors in those fields. Examining course-taking trends within major, we descriptively observe that majors in three of the core liberal arts domains – the natural sciences, humanities, and social sciences – take substantially more of their coursework outside of their home discipline but within the liberal arts than majors in the professional disciplines and fine arts.

This is the first of two opportunities for peer review of a working draft of the Pathways Network website. We want the site to reflect your own ideas and ambitions. Please be ready to give critical feedback on a website that we hope will bear your name!

This is the second of two opportunities for peer review of a working draft of the Pathways Network website. We want the site to reflect your own ideas and ambitions. Please be ready to give critical feedback on a website that we hope will bear your name!

Educational phenomena are sequential, cumulative, and contingent, but educational social scientists have only rarely modeled their inquiries to capture this complexity. Newly available computational tools and scaled data make it possible to observe the sequential, cumulative, and contingent character of educational progress at micro, meso, and macro levels. This session is our latest effort to integrate work from a range of fields to develop heuristics for a new science of educational progress. Our goal is theoretical and methodological pluralism through conscientious matching of inquiry design, data and substantive problem.

Students and their parents hold strong convictions about how certain academic choices will affect their competitiveness on the labor market upon graduation. These beliefs influence students’ academic choices, typically in ways that increase their workload, such as taking on additional majors, minors, or challenging courses. Despite their significant impact on students’ college experiences, these beliefs are rarely grounded in evidence. This research project tests the evidentiary basis of some of the most pervasive beliefs and investigates which academic choices have been most influential for several different career outcomes. We use ten years of individual-level academic and career data at a public Land grant university in the United States. We will discuss implications for student advising, curriculum design, and persistence and equity.