Investigating Micro-Behaviors in Team Interactions between Engineering Students
Abstract
This thesis examines the interpersonal behaviors between first and second-year undergraduate students pursuing a STEM field, in a group setting. Dynamics in team settings can contribute to the overall success of a team, mental health of the students, and even long-term success of the students’ career. Interdisciplinary research has begun to study how technology can improve human interactions and communication for humans to reduce racism, sexism, and hate speech. Many of these technologies have been built by taking textual examples from social media and other such platforms. This thesis explores the linguistic markers of team interactions between Engineering students. The data comes from a newly collected corpus of team interactions conducted in an online format, where teams of 3 students (1 female, 2 male; or 1 male, 2 female) and 4 students (2 female, 2 male) work together to solve a set of programming problems. These teams met daily for 5 consecutive days solving 2 coding challenges taken from Leetcode medium to hard problems at each meeting, with 35 minutes to solve each problem. From the conducted linguistic analysis, we identified over 100 statistically significant correlations between linguistic features generated by the Linguistic Inquiry and Word Count (LIWC) toolbox and self-reported psycho-social constructs related to individual emotion and team interaction quality that the participants filled out at various points throughout the study. These relationships give us further insight to the categories of verbal language and its associative underlying emotion. As part of the future work, this dataset will be coded for microaggressions and microaffirmations and will then be used to design an Artificial Intelligence model that can predict, from a real time interaction, whether a statement is a microaggression or microaffirmation. A technology such as this can be used to enhance interactions in group settings and improve individuals’ communications to reduce microaggressions.
Subject
microaggressionmicroaffirmation
artificial intelligence
interpersonal behaviors
team performance
linguistic analysis
multimodal interactions
psychological constructs
Citation
Berry, Kiara (2023). Investigating Micro-Behaviors in Team Interactions between Engineering Students. Undergraduate Research Scholars Program. Available electronically from https : / /hdl .handle .net /1969 .1 /199646.