The enterprise of higher education faces increasing demographic, commoditization, and technological challenges, including online programs, for-profit firms, and questions about relevance. Yet, to date there is little research on student development that could be a source of competitive advantage. Broadly, student development includes (Delors 1996): 1. learning to do - the acquisition of skills and competencies, 2. learning to know - the ability to think and integrate new information, 3. learning to live together - understanding others, managing conflicts, and 4. learning to be - developing one’s personality and judgment. Since there is a significant body of work on pedagogy - the acquisition of skills and knowledge or learning to do – we focus on exploring the theoretical development and implementation of learning to know, live, and be. Therefore, we ask: Can technology improve student development in higher education? To address this question, we apply complex adaptive systems (CAS) as a theoretical lens (Holland, 1995) to iteratively generate an artifact, evaluate usage across several hundred users at our university and several others, and propose generalizable design principles (Sein et al. 2011). We also developed a systematic measure of student development, quantified through a system of points and assessed through a novel student development index. To assess the relevance and applicability of our results, we conducted an applicability check (Rosemann and Vessey, 2008). Following their guidelines, we created three focus groups of six to eight participants. The first group included recent alumni who participated in the student development program. The second group consisted of Human Resource professionals experienced in recruiting students. The third focus included alums who graduated before we implemented the student development program. The three groups allowed us to compare the artifact’s applicability for individuals who participated in the program with those who did not, while also incorporating recruiters’ views to assess value across multiple institutions. We will discuss the results of the applicability check and how we can extend the study to further justify and validate our results.