Toward Uncovering Meaning in Human-Robot Interactions

Contribution: This study qualitatively uncovered meaning for why and what was motivating to undergraduates participating in an educational human—robot interaction (HRI) experience. A data corpus of four documents (groups) was evaluated from a quasi-experimental, nonequivalent control (
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61) research design revealing three themes attributing meaning for why and what was motivating to students. Background: Engineering education literature has indicated a positive impact on student motivation and academic success from HRIs. However, rigorous research that attributes meaning for why and what are motivating to students in these HRI experiences is not readily available. Intended Outcomes: Results of this study represent substantial findings that answer questions of why and what are motivating in HRI experiences. However, future research is needed to further understand the nuanced dynamics and multidimensional aspects of motivation in HRIs. Application Design: To analyze the qualitative open-ended survey responses from students, structured term frequency (tf), tf – inverse document frequency (tf-idf), latent Dirichlet allocation (LDA) modeling, and content analysis were used, as these approaches are typical in computational text mining. Findings: When describing motivation toward the HRI, students were found to form a common lexicon to attribute why and what was motivating (e.g., “…[being] abl[e]” [to] see [the] robot follow [the line]…”). This suggests that the tangible, visual, immediate feedback experienced by students was why and what motivated them.