Journal of College Student Development

Students navigate complex educational ecosystems and, in the process, engage in interactions that influence their college experiences, development, and outcomes. They traverse educational environments that include, but extend beyond, the college campus. Family, friends, and community influence college access, transition, and engagement (Astin, 1993; Renn & Reason, 2012). Teachers from high school play important roles in shaping whether students enroll (Engberg & Wolniak, 2010), and instructors in college influence whether they persist (Astin, 1993; Renn & Reason, 2012). Educational administrators, policymakers, and advocates set the contexts within which students navigate education systems (Renn & Arnold, 2003; Renn & Reason, 2012). Understanding students' relationships with their multiple home, community, and educational environments provides a more holistic understanding of students and recognizes that many spheres of influence shape their college experiences, development, and outcomes.

Ecological Systems Theory (EST) directs higher education researchers and practitioners to examine students in their educational ecosystems. Within EST, the interactions between students and their contexts shape their educational experiences and development (Bronfenbrenner, 1994; Renn, 2003). Bronfenbrenner (1979, 1994) argued that humans actively engage within evolving, interconnected, nested environments. He believed that human experience is best understood holistically. While predominant college impact theories (e.g., Astin, 1993; Tinto, 1993) similarly direct attention to the role of environment and students' interactions with their environment, EST extends this tradition by taking a more holistic and systems-based approach. Many in higher education appreciate the comprehensive and integrated approach of EST as a way to more fully understand students' college experiences (Renn, 2003; Renn & Arnold, 2003). However, the complexity of implementing EST has limited its use, and there are few effective tools for gathering this kind of information. In this research brief, we share a qualitative interview protocol we designed to facilitate application of EST to understand students' ecological systems and their interactions with those systems.

A thorough discussion of EST is beyond the scope of this brief (see Renn, 2003, for a fuller explanation). Here, we summarize the core aspects of the model developed by [End Page 489] Bronfenbrenner (1979, 1994) and Bronfenbrenner and Morris (2006). The mature EST model consists of four cardinal elements: person, process, context, and time (PPCT). The person brings with them a range of characteristics into their contexts (e.g., age, race, emotional resources, social and material resources, motivation, temperament). Context encompasses nested ecological systems that range from the microsystem, consisting of contexts closest to the individual, out to distal contexts in the macrosystem. The quality and nature of those contexts can influence "proximal processes" (i.e., interactions) between the person and their environment. Process is the primary mechanism that links person and context and shapes students' experiences. For example, students' experiences in contexts where they are validated by faculty (i.e., a proximal process) may lead to different outcomes as compared to contexts where they are not validated. Time encompasses historical or cultural events (e.g., elections) as well as social and biological transitions that shape an individual's college experience.

Overall, EST frameworks allow for multiple pathways to college success; taking into account students' varying backgrounds and the many contexts they interact with across time, centering the interaction between students' characteristics and contexts as the driver of students' experiences and outcomes. This eschews singular notions of transition into college—and engagement with more narrowly defined contexts during college—that are offered by many traditional theoretical perspectives (e.g., Tinto's integration model, 1993). While EST proves conceptually helpful, it can be difficult to integrate within a study design or in practice.