Mapping Engineering Leadership Research through an AI-enabled Systematic Literature Review.

Research in engineering leadership (EL) has seen substantial growth due to the increased recognition that engineering students' leadership development is essential to their holistic development as engineers [1]. To support the continued growth of this nascent field, it is vital to examine its history and identify growth opportunities that accelerate EL development and broaden its impact. Identifying, codifying, and synthesizing the previous research in EL will provide crucial foundations for advancement and reduce the likelihood of redundant efforts [2]. A substantial portion of the research on EL is published through the American Society for Engineering Education (ASEE). In particular, EL thought leaders often publish through a division focused on supporting EL education, educators, and researchers, the Engineering Leadership Development Division (LEAD). This review explores how the focus of research in this field has evolved over the past 26 years within ASEE and identifies patterns in research populations, theoretical frameworks, and methods. Therefore, this research paper aligns with the Inform portion of the ASEE LEAD Division's Inform/Develop/Explore/Assess strategic initiative framework and describes our systematic review of key EL literature. Using an Artificial Intelligence (AI)-enabled mixed-methods approach, modified from those outlined by Borrego et al. in [2], this systematic literature review is conducted on all papers published in the ASEE conferences' proceedings between 1996 and 2021 with the word "leadership" in the title. We also include all papers published through the LEAD division. Papers included must focus on EL and be available in a finalized state from the ASEE PEER repository. The systematic review employs both quantitative and qualitative analysis to determine the state of knowledge in the field. This analysis uses AI to quantize word frequency in the abstracts and then a cluster analysis of the resulting matrices. We then compare these clusters to an adapted version of Terenzini and Reason's college impacts framework of influences on student learning and persistence to identify potential areas for growth in the EL literature. We also map the clusters over time to explore the evolution in the research focus of the field since 1996, noting key events that may have contributed to shifts in focus. This systematic review of the EL literature is intended to advance knowledge of the field by categorizing prior work and detailing the evolution of research topics, methods, and populations. Thus, the results will expand future EL research by documenting the field's foundations, progression, and potential future. [ABSTRACT FROM AUTHOR]