, squatting, lifting, turning). The team at the firm is working together to come up withways to change an existing exoskeleton to make it even more helpful to people no matter theirage ability.The team includes a materials and science engineer, a human factors specialist, a clinicalexpert, a mechanical engineer, a computer engineer, and a biomedical engineer.Review each engineering team conversation to answer the following questions: 1. Which team's method seems like it would come up with the best result(s)? Why? 2. What are the pros and cons of each team’s method of solving the main problems and sub-problems? Use the teams' conversations to support your answers. 3. What skills do the engineers on each team have? 4. Which team would
families and educators may serve as a useful approach.Lastly, while participants in this study spanned grade levels, gender, and ethnic social groups,future research may expand upon this sample to include a broader spectrum of demographicbackgrounds.AcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No.1759314 (Binghamton University) and Grant No. 1759259 (Indiana University). Any opinions,findings, and conclusions or recommendations expressed in this material are those of theauthor(s) and do not necessarily reflect the views of the National Science Foundation.References[1] E. R. Banilower, P. S. Smith, K. A. Malzahn, C. L. Plumley, E. M. Gordon, and M. L. Hayes, Report of the 2018 NSSME
-ended survey responses to further analyize faculty viewsand how they align with quantitative data. These perspectives provide a starting point fordeveloping authentic learning goals for K-12 students.References[1] Mason, C., Twomey, J., Wright, D., & Whitman, L. (2018). Predicting engineering student attrition risk using a probabilistic neural network and comparing results with a backpropagation neural network and logistic regression. Research in Higher Education, 59, 382–400.[2] Uddin, M., & Johnson, K. (2019). Faculty learning from the advisors for students’ retention and persistence to graduation. 2019 Conference for Industry and Education Collaboration[3] Guzey, S. S., Ring-Whalen, E. A
Example “I would use a parallel circuit because if one light 1 light(s) 48 goes off, the other will continue working.” “Maybe we could take this, tape it or drill it on a 2 tape 39 tree or something.” “It didn't work the first time, so we tried a second 3 work 36 time and it didn't really work. It just didn't move.” “So we were reading in the kit that the
Regional Education Board.Brophy, S., Klein, S., Portsmore, M., & Rogers, C. (2008). Advancing engineering education inP‐12 classrooms. Journal of Engineering Education, 97(3), 369-387.Gottfried, M. A., & Plasman, J. S. (2018). Linking the timing of career and technical educationcoursetaking with high school dropout and college-going behavior. American EducationalResearch Journal, 55(2), 325-361.Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do studentslearn?. Educational psychology review, 16, 235-266.Lynch, S. J., Peters-Burton, E., Behrend, T., House, A., Ford, M., Spillane, N., Matray, S., &Means, S. (2017). Understanding inclusive STEM high schools as opportunity structures forunderrepresented students: Critical
Paper ID #42723Board 157: Design of a Geospatial Skills Camp for Rural Youth (Work inProgress)Dr. Jeanette Chipps, Montana State University Jeanette Chipps is an assistant teaching professor at Montana State University and the educator professional development lead at the Science Math Resource Center.Suzanne G Taylor, Montana State UniversityDr. Nicholas Lux Lux, Montana State University Dr. Nicholas Lux has is an Associate Professor of Curriculum and Instruction in MSUˆa C™s Department ˆ He has of Education. His teaching and
integration of AI tools into STEMpedagogy. This collaborative network among key stakeholders will serve to support equity andaccessibility in education and create a more inclusive learning environment for all futurelearners.AcknowledgmentThis material is based upon work supported by the AI.R-NISTH AI for Social Good ResearchGrant at Nanyang Technological University in Singapore. Any opinions, findings, conclusions,or recommendations expressed in this material are those of the author(s) and do not necessarilyreflect the views of the AI.R program. We would like to acknowledge all the researchers, datacollectors, and students who participated in the study.ReferencesAbulibdeh, A., Zaidan, E., & Abulibdeh, R. (2024). Navigating the confluence of
diverse perspectives andfemale role models in STEM (Konowitz et al., 2022). Introducing students to the narratives andaccomplishments of women, minorities, and people from various cultural backgrounds canmotivate and empower underrepresented groups to pursue careers in STEM (Cheryan et al.,2015; Gilberth, 2015). Institutions, including K-12 and higher education, should develop moreinclusive and supportive environments for students interested in STEM. This involves offeringmentorship programs, networking opportunities, professional development for teachers, andresources suited to the needs of different student demographics. Such efforts align with Yeo etal.’s (2024) preliminary work that teachers use verbal and non-verbal cues to facilitate
analysis to analyze the interviews and video transcripts since it allows for asystematic way of seeing and processing qualitative data [38]. We followed Braun and Clarke[38]’s six-phase method for thematic analysis, which encompassed familiarizing yourself withdata, generating initial codes, searching for themes, reviewing, defining, and naming the themes,and creating the report. First, statements in the interview were coded with descriptive labelsthrough emergent coding, and these codes were categorized into themes. Constant comparison,first within each interview and then within each group (i.e., children as a group and parents as agroup), was used to continually sort the data until a robust set of themes explaining the data wasdeveloped for each
, girls were found to draw male scientists three times more often than female scientists[31]. Similar trends were found in Capobianco et al.’s [23] study. About 40% of the engineersthat first grade girls drew were female and about 30% were male, but when examining thedrawings of fifth grade girls, just under 60% drew male engineers and about 30% drew femaleengineers. Given the age of the participants, previous research suggests it is likely that theywould draw male engineers.The study took place in the context of a Girl Scout troop environment. This may have influenced theparticipants’ conception of engineers for several reasons. First, the national Girl Scout organizationrecently began a significant focus on STEM opportunities within the
-based practices, that can specifically be leveraged to broadenaccess and participation in engineering education. References1. Aceves, T. C. and Kennedy, M. J. (Eds.) (2024, February). High-leverage practices for students with disabilities. 2nd edition.2. Anderson, J., Anderson, Z., Beaton, K., Bhandari, S., Bultinck, E., Ching, J., ... & Duerstock, B. S. (2022). Challenges in Inclusiveness for People with Disabilities within STEM Learning and Working Environments.3. Baxter, P., & Jack, S. (2008). Qualitative Case Study Methodology: Study Design and Implementation for Novice Researchers. The Qualitative Report, 13(4), 544-559. https://doi.org/10.46743/2160-3715/2008.15734. Bogdan
, this may be an area for future research. ReferencesBottoms, G., & Uhn, J. (2007). Project Lead the Way works: A new type of career and technical program. Atlanta, GA: Southern Regional Education Board.Brophy, S., Klein, S., Portsmore, M., & Rogers, C. (2008). Advancing engineering education in P‐12 classrooms. Journal of Engineering Education, 97(3), 369-387.Cassady, J. C., Heath, J. A., Thomas, C. L. & Kornmann, M. (2020). Engaging students in STEM with non-traditional educational programs: Bridging the gaps between experts and learners. In A. Macdonald, L. Dania, & S. Murphy (Eds.), STEM Education Across the Curricula: Early Childhood to Senior
educational psychology, vol. 77, pp. 15-46, 1996.[5] J. S. Brown, A. Collins, and P. Duguid, “Situated cognition and the culture of learning,” Educational Researcher, vol. 18, no. 1, pp. 32-42, 1989.[6] J. Lave and E. Wenger, Situated learning: Legitimate peripheral participation. New York, NY: Cambridge University Press, 1991.[7] R. T. Putnam and H. Borko, ‘What do new views of knowledge and thinking have to say about research on teacher learning?,” Educational researcher, vol. 29, no. 1, pp. 4-15, 2000.[8] S. Semken, “Sense of place and place-based introductory geoscience teaching for American Indian and Alaska Native undergraduates,” Journal of Geoscience Education, vol. 53, pp. 149-157, 2005.[9] L. M
Science and Engineering Road Show mobile lab and creates programs for local youth to educate and entertain with hands-on projects to challenge students’ math and science skills.Tala Katbeh, Texas A&M University at Qatar Tala Katbeh is a STEM Instructor and Program Coordinator at Texas A&M University at Qatar (TAMUQ) where she applies her enthusiasm for engineering to create curricula and engineering courses for school students. Katbeh is currently also pursuing her PhD at Texas A&M University, having graduated from TAMUQ with a BSc and MSc both in chemical engineering.Prof. Hassan Said Bazzi, Texas A&M University at Qatar Dr. Hassan S. Bazzi is the senior associate dean for research and advancement and
. Roberts, C. Jackson, S. Bush, A. Delaney, M. J. Mohr-Schroeder, & S. Y. Soledad, “Informal Learning Environments and Impact on Interest in STEM Careers”, International Journal of Science & Mathematics Education, vol. 19, no. 1, pp. 45–64, 2021. [Online]. Available: https://doi.org/10.1007/s10763-019-10038-9. [Accessed Dec. 1, 2022].[3] C. Maiorca, T. Roberts, C. Jackson, S. Bush, A. Delaney, M. J. Mohr-Schroeder, & S. Y. Soledad, “Informal Learning Environments and Impact on Interest in STEM Careers”. International Journal of Science & Mathematics Education, vol. 19, no. 1, pp. 45–64, 2021. [Online]. Available: https://doi.org/10.1007/s10763-019-10038-9. [Accessed Dec. 1, 2022].[4] K
efforts to create inclusive classrooms and programming.Dr. Melissa M. Bilec, University of Pittsburgh Dr. Bilec is an associate professor in the Swanson School of Engineeringˆa C™s Department of Civil and Environmental Engineering. Dr. Bilecˆa C™s research program focuses on the built environment, life cycle assessment, sustainable healthcare, and energy im ©American Society for Engineering Education, 2024 A Collaborative Virtual Air Quality Learning Experience with Kakenya’s Dream (Resource Exchange, Diversity) The curriculum we developed for this collaborative project focused on introducing thestudents and instructors to the importance of air quality (AQ), its impacts on
EXCHANGE it w hDr. Rachelle Pedersen Texas A&M UniversityDr. Justin Wilkerson wilkerson@tamu.eduLESSON DESCRIPTIONThis lesson is a mix of demonstrations and inquiry experiences intended to guide students throughconcepts of energy transformations (e.g., kinetic, elastic) and engineering concepts of snap-throughtransitions in both the natural and engineered world. Students will develop foundational understandingsof energy conservation with a simple ball bouncing demonstration and build to more complex conceptsof spring/elastic energy using the classic 90’s rubber popper toys to investigate the energytransformations in the system. Depending on the age of the students, we will extend this lesson
Number [EEC-1849430 & EEC-2120746]. Any opinions, findings andconclusions, or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect those of the NSF. The authors acknowledge the support of the entire e4usaproject team.References[1] “The Standards | Next Generation Science Standards.” Accessed: Feb. 07, 2024. [Online]. Available: https://www.nextgenscience.org/standards[2] “Employment in STEM occupations : U.S. Bureau of Labor Statistics.” Accessed: Feb. 07, 2024. [Online]. Available: https://www.bls.gov/emp/tables/stem-employment.htm[3] “Motivational factors predicting STEM and engineering career intentions for high school students | IEEE Conference Publication | IEEE Xplore
cultural needs of students.Future work regarding the emphasis on science teachers as agents for change will focus on thein-school context of the action research projects. In this regard, qualitative and quantitative datawill be reported on novice teachers' engineering and cultural self-efficacy for teachingengineering processes.16 References[1] T. R. Guskey, "Professional development and teacher change," Teachers and Teaching, vol.8, (3), pp. 381-391, 2002.[2] B. Huang, M. S. Jong, Y. Tu, G. Hwang, C. S. Chai, and M. Y. Jiang, "Trends and exemplarypractices of STEM teacher professional development programs in K-12 contexts: A systematicreview of empirical studies," Comput. Educ., pp. 104577, 2022.[3] J. A
effects of a biomimicry teaching approach on students’designs. The authors found that students’ designs were not only inspired by nature, but they alsoconsidered the functions behind the physical structure of the organism in their designs. Abaid et al. [21]discovered that students had more favorable perceptions of engineering after engaging in a BID activity.In Abaid et al.’s [21] study, participating students were tasked with creating the most efficientswimming robots based on various types of fish fins and testing different robot designs. As documentedin the literature, BID integration in pre-college education can inspire innovative design solutions,heighten students’ views about nature, and foster STEM engagement and understanding of
discipline, and two tables in Appendix C reportedthe results by item. Understanding of CS and CmpE was relatively high on the pretest.Understanding of IT was initially relatively low (44%) and almost doubled (81%) on the post. Table 1. Pre and Post Test of Participants’ Perceptions of Computing Skills by Discipline Discipline(s) Items Pre Post Change Computer Science 5 80% 80% +0% Computer Engineering 4 85% 98% +13% Information Technology 7 44% 81% +37% Information Technology and Computer Science 3 93
school students participated in a week-long summer camp thatfocused on electrical and computer engineering (ECE) concepts and practices. The five-daysummer camp consisted of hands-on activities, tours of different laboratories in ECE disciplines,and a group project that spanned the whole week where students built circuits using theSparkFun Inventor’s kit. During the group activity, the students were organized into eightgroups, and each group was mentored by an undergraduate mentor who facilitated thecollaborative hands-on activities. The middle school students completed validated and reliablepre and post-surveys adapted from the Student Attitudes Toward STEM (S-STEM) Survey andthe Group Work Skills Questionnaire Manual. The S-STEM survey is
purpose.Acknowledgment: “This material is based upon work supported by the National ScienceFoundation under Grant EEC-BPE 2135080” Disclaimer: Any opinions, findings, andconclusions or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the National Science Foundation.”References[1] National Science Board, Science and Engineering Indicators 2020. Arlington: National SciBoard. Available: https://www.nsf.gov/nsb/news/news_summ.jsp?cntn_id=299268&org=NSB.[2] E.L Kryst, S Kotok and A. Hagedorn, Pursuing higher education in rural Pennsylvaniaschools: Shaping the college path. The Rural Educator, pp. 1 – 11, Winter 2018.[3] G. Saw, C. N. Chang, and H. Y. Chan, Cross-sectional and longitudinal
/aimag.v40i4.5289[2] S. Anwar, N. A. Bascou, M. Menekse, & A. Kardgar, (2019). “A Systematic Review of Studies on Educational Robotics”. Journal of Pre-College Engineering Education Research (J-PEER), 9(2), Article 2. https://doi.org/10.7771/2157-9288.1223[3] National Science and Technology Council Committee on Technology. 2016. “Preparing for the future of Artificial Intelligence”. Technical Report. Office of Science and Technology Policy.[4] J. J. Lu and L. A. Harris. 2018. “Artificial Intelligence (AI) and Education”. Technical Report. Congressional Research Service. https://fas.org/sgp/crs/misc/IF10937.pdf[5] T. Narahara and Y. Kobayashi. 2018. “Personalizing homemade bots with plug & play AI for
reported no difference between the pre- and post-test survey, a0 was given for that question. If a student reported a negative difference between the pre- andpost-test survey, a -1 was given for that question. The tallies were added up and a positive sumcorresponded to a positive progression, a sum of 0 corresponded to no progression, a negativesum corresponded to a negative progression. More formally: s = student c = construct Q(c, s)ij = numerically scaled Likert response matrix for each student and construct n(c) = number of questions in a constructFor each student in a construct, a score is calculated through Eq. 1 as: n
completion of a full cross-case analysis of all sixcase-studies which include primary (elementary) and secondary education contexts.AcknowledgementsWe are deeply grateful to our case-study coaches and students for sharing their time andexperience with us.References[1] For Inspiration and Recognition of Science and Technology (FIRST), "FIRST annual impact report: More than robots," 2022. [Online]. Available: https://firstinspiresst01.blob.core.windows.net/annual-report/annual-report/first-fy22-annual- impact-report.pdf[2] S. Evripidou, K. Georgiou, L. Doitsidis, A. A. Amanatiadis, Z. Zinonos, and S. A. Chatzichristofis, "Educational robotics: Platforms, competitions and expected learning outcomes," IEEE Access, vol
and by Spanish- and English-language preferences. Table 1shows the family composition and languages spoken by the ten families in each of the threerounds.Table 1Family Composition and Language Preferences for Each Round Family ID Language(s) Spoken Family Composition 1 Spanish and English Adult and child 5 Spanish and English Adult and three children 6 Spanish* Adult and three children** 7 Spanish and English Adult and two children 10 English Adult and child 11 English Adult and child 13 English
professional development model as a lens.Participants were nine sixth grade science teachers from three rural and Appalachian schoolsystems who engaged in the first year of the VT-PEERS project. The participants wereinterviewed prior to the first intervention activity, at the end of the first academic year, observedduring interventions, and asked to fill out an online questionnaire to capture their demographicinformation. The interviews lasted approximately 30-minutes. Pertinent questions for thisanalysis were: “What influenced your decision to participate in this project?”; What role(s) doyou expect to have during this collaboration?”; “What role(s) do you expect other partners(Industry or University) to have?”Through open coding (Miles, Huberman