Understanding Engineering Students' Stress and Emotions during an Introductory Engineering course.

Background This exploratory study uses multimodal approaches to explore undergraduate student engagement via topic emotions and electrodermal activity (EDA) in different engineering design method activities and with different instructional delivery formats (e.g., lecture vs. active learning). Purpose/Hypothesis The goal of this research is to improve our understanding of how students respond, via engagement, to their engineering design activities during class. This study hypothesizes that students would experience no self‐reported mean changes in topic emotions from their preassessment scores for each engineering design topic and instructional format nor would electrodermal activities (EDA) associate to these topic emotions throughout the design activities. Design/Method Eighty‐eight freshmen engineering students completed online pretopic and posttopic emotions surveys for five engineering design activities. A subset of 14–18 participants, the focal point of this study, wore an EDA sensor while completing the surveys and participating in these sessions. Results Preliminary findings suggest that EDA increased for individual and collaborative active learning activities compared to lectures. No significant changes in EDA were found between individual and collaborative active learning activities. Moderate negative correlations were found between EDA and negative topic emotions in the first engineering design activity but not across the rest. At the end of the semester, active learning activities showed higher effect sizes indicating a re‐enforcement of students' engagement in the engineering design method activities. Conclusion This study provides initial results showing how multimodal approaches can help researchers understand students' closer‐to‐real‐time engagement in engineering design topics and instructional delivery formats.

Section: Multimodal Approaches For Measuring Emotions In the Classroommentioning

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Multimodal Approaches For Measuring Emotions In the Classroommentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Multimodal Exploration of Engineering Students' Emotions and Electrodermal Activity in Design Activities

Villanueva

Campbell

Raikes

et al. 2018

Situating multi‐modal approaches in engineering education research

Villanueva

Anwar

2022

BACKGROUNDTraditionally, engineering education researchers rely on quantitative, qualitative, and mixed-or multi-method approaches for their research designs, each with its nuances, set of rules, and worldviews. Here we present a new approach that is yet to be widely accepted in engineering education research (EER): namely the multi-modal approach. This guest editorial is particularly timely because, in 2020, the EER taxonomy underwent a revision (Version 1.2), where the term "multi-modal approaches" was added to Section 12.d.iv (Finelli, 2020). With this addition to the taxonomy, it is important for EER scholars to understand what multi-modal approaches entail and how they are different from other approaches present in mixed-methods or multi-methods. To clarify this new approach further, we give examples of how multi-modal research is used in EER and other related studies. | INTRODUCTIONRooted in sociolinguistic approaches, multi-modality centers on multiple modes of communication and representation (e.g., reading, writing, and speech) to study meaning-making. In multi-modality, meaning-making includes multiple dynamics or representations of phenomena (or layers) and sensing modes by which an individual recognizes or becomes aware of the complexity of experienced phenomena (e.g., Ledin & Machin, 2017). Multiple sensing modalities are what give an individual "a wealth of information to support interaction with the world and with one another" (Turk, 2014, p. 189), and these can be interpreted through senses such as, but not limited to, hearing, seeing, touching, and feeling (e.g., Ledin & Machin, 2017). Phenomena, in the multi-modal sense, include the "binding of inputs from multiple sensory modalities and the effects of this binding" (Lachs, 2017) on individuals and accounts for the influence that one sensory modality has on another (Spence et al., 2009). Taken together, multi-modal approaches aim to capture the multi-layered and near-real-time ensemble of the intersections and dynamics of meaning-making (e.g., Archer & Newfield, 2014).Take, for example, the experience of listening to a song. When a person listens to a song, multiple events happen almost simultaneously: a person hears the song, reads the song lyrics, and thinks about how the song applies to their life. If the song connects with a person on a deeper level, their emotions manifest as excitement or joy, their heart palpitates, their mood changes, and they almost immediately begin to memorize the lyrics and tunes. Analogously, multimodal approaches try to collect many simultaneous events in order to represent the messiness and immediacy of life.Multiple layers of the phenomena include both the context and nature of discursive practices while also accounting for the convergence and divergence of its sensing modalities (Archer & Newfield, 2014). Together, the layers and immediacies of multi-modal approaches allow scholars to further nuances in meaning-making as it relates to complex realities such as access, social justice, and equity (

Everyday engineering: The effects of transformative experience in middle school engineering

Heddy

Danielson

Ross

et al. 2023

Background: Promoting engagement and motivation in early engineering experiences is important for fostering interest and retention in engineering. One method that has been effective for doing so is facilitating transformative experiences (TEs), which occurs when students apply academic content to everyday experience. Our goal was to explore the effectiveness of an intervention to encourage TE, positive emotions, and interest in middle school engineering courses in two differentially resourced schools. Purpose/Hypothesis: We explored the effectiveness of using the video software Flipgrid as a supplement to a TE intervention to impact TE, emotions, and interest. In addition, we sought to model a theorized predictive relationship between TE, emotions, and interest. Design/Method: Two hundred seventy-four engineering students across two middle schools with differing levels of resources participated. A clusterrandomized pretest-posttest survey design was used to explore the variables of interest. ANOVA and SEM were implemented to investigate the research questions and hypotheses. Results: We found mixed results, with the intervention facilitating significantly more TEs and maintaining high levels of positive emotions in a school with access to fewer resources. Furthermore, in alignment with hypotheses about interest development (Renninger and Su, Oxford handbook of human motivation 2012; pp. 167-187), the results showed that initial positive and negative emotions predicted initial interest and post-TE. However, only postpositive emotions and post-TE predicted post-interest. Negative emotions after the intervention did not predict post-intervention interest. Conclusions:The findings have theoretical implications for interest development and practical implications for targeted interventions in early engineering education, especially for schools with access to fewer resources.