Matthew W. Ohland

Task conflict should, theoretically, benefit team outcomes, yet prior research has yielded inconsistent results. We propose this inconsistency reflects configurations of conflict types (task, relationship, process) within teams. Though these types have been examined in isolation or pairwise, their three-way interaction remains unexplored. Using multilevel modeling on 34,668 individuals (7,891 teams), we tested conflict types’ three-way interaction on psychological safety. Results revealed task conflict was positively related to psychological safety when relationship and process conflict were low, but negatively related when relationship conflict was high, regardless of process conflict. Findings underscore conflict configurations’ role in conflict theory and practice.

Contribution: This article describes an effort to quantitatively characterize the “complexity” of engineering programs across the United States using a burgeoning framework called curricular analytics. A new dataset is introduced to facilitate these analyses for researchers and practitioners, tied to an existing data-sharing agreement. Several avenues for future research using this dataset are outlined, such as connecting curricular data with student course-taking data. Background: As curriculum development and evaluation adopt a more data-driven approach to understanding how to best retain and graduate engineers, curricular analytics offers the engineering education community a method for uncovering the complexities of curricula that may be deterring students from the field. Curricular analytics involves representing program requirements as a network to assign a measure of complexity, called “structural complexity,” which has been empirically shown to correlate with completion rates. Research question: How does the complexity of engineering programs vary across institutions, disciplines, and time? Methodology: The research question was approached using a quantitative research design. The sampling frame consisted of the multiple-institution database for investigating engineering longitudinal development (MIDFIELD), a data-sharing agreement encompassing 21 institutions (and still expanding). Plans of study were collected from 13 institutions for five disciplines—Mechanical, Electrical, Chemical, Industrial, and Civil—spanning a decade since their most recent record in MIDFIELD ( $n$ = 494). Then, network analysis was applied to calculate the structural complexity of the programs. The results were explored using descriptive statistics, boxplots, and plotting the complexities longitudinally. Findings: Across the years 2012–2022, a range of 307–372 was observed for structural complexity, with a mean of 325 and a median of 323. In the sample, Chemical Engineering was found to be the most structurally complex discipline, followed by Mechanical Engineering. The remaining disciplines were more tightly clustered together. Over time, chemical engineering and civil engineering marginally increased in complexity by 4%, whereas electrical and mechanical engineering decreased by 2% and 0.7%, respectively. Industrial engineering exhibited the most significant decrease of 11%.