Wearable Textiles to Support STEM Learning and Attitudes

• In Event: 34.079 - Interactive Stitch Sampler of Equitable Learning and Teaching With E-Textiles in K–12 Education

Abstract

OBJECTIVES & PERSPECTIVES. Wearable technologies for learning consists of an array of engineering and aesthetic concepts (Peppler, & Glosson, 2013). Specifically, wearables use electronic and crafting materials that work together to allow students to create personal artifacts that involve sewing, designing circuits, and writing code. But the technology itself, with all its integrative advantages, is not enough to guarantee educational impacts. It must be coupled with well-designed curriculum and effective pedagogical strategies. To insure widespread use in formal education environments, it must also be directly tied to educational standards.
METHODS & DATA. These elements were all integrated into the wearable technologies project (WearTec) designed for upper elementary students and delivered to 25 Midwest schools. The project utilized a large sample of 808 students both in and out-of-school learning contexts by formal and informal educators, and targeted upper elementary students using a quasi-experimental, pre-post design with two-groups (treatment and control) to measure (a) the impact of a wearable technology intervention on students’ knowledge of circuitry, programming, and engineering design and (b) self-efficacy in making a wearable e-textile product. The three-level multilevel (i.e., children nested within teachers which were nested within schools) ANCOVAs were estimated for each outcome of interest (knowledge of circuitry, programming, engineering design, engineering self-efficacy and programming self-efficacy).
FINDINGS. Differential results between males and females underscores the need to infuse gender-appropriate pedagogical practices to ensure that females develop needed self-confidence to successfully complete tasks involving these two skill areas. The final model reveals that the only significant predictors of electricity knowledge were the pre- score and the treatment group. Controlling for pre-score differences, the treatment group was predicted to score .98 points higher than the control, p < .05, effect size = .80. A similar pattern of results was found for the programming knowledge outcome. Controlling for pre-score differences, the treatment group was predicted to score .34 points higher than the control, p < .05, effect size = .32. The treatment status had a significant effect on engineering self-efficacy such that the treatment group was predicted to be .14 points higher than the control, p <.05, effect size = .17. Treatment, gender, and pre-score all had a significant positive relationship with programming self-efficacy. The treatment group was predicted to have post-scores that were .28 higher, p < .05, effect size = .28. Also, males were predicted to score .21 points higher at post when controlling for treatment and the pre-programming self-efficacy score. Gender, group and the pre-score was a significant predictor. Each had a positive relationship, the treatment group was predicted to have post-scores that were .29 points higher for the treatment than the control, p < .05, effect size = .31. Once again, the males had significantly higher self-efficacy, predicted to score .19 points higher at post than females.
SIGNIFICANCE. Results indicate that wearable technology’s integration of engineering, computing and aesthetics promises to be an excellent interdisciplinary context to support students’ STEM learning and attitudes.

Authors

• Bradley S. Barker, University of Nebraska - Lincoln

• Gwen Nugent, University of Nebraska - Lincoln

• Jennifer Keshwani, University of Nebraska - Lincoln

• Carl Nelson, University of Nebraska - Lincoln

• Dagen Valentine, University of Nebraska - Lincoln

• Neal Grandgenett, University of Nebraska - Omaha