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Lab Kits and the Self-Beliefs and STEM Beliefs of Students at a Black Majority High School

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2021 CoNECD


Virtual - 1pm to 5pm Eastern Time Each Day

Publication Date

January 24, 2021

Start Date

January 24, 2021

End Date

January 28, 2021

Conference Session

CoNECD Session : Day 3 Slot 1 Technical Session 3

Tagged Topics

Diversity and CoNECD Paper Submissions

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Paper Authors


Casey Lynn Haney Purdue University at West Lafayette (COE) Orcid 16x16

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Casey Lynn Haney is a Ph.D. student in engineering education at Purdue University and a research assistant in Dr. Jennifer DeBoer's Lab. She completed her undergraduate degree in Engineering/Technology Teacher Education. Her interests include STEM self-efficacy for diverse students and data analysis within educational datasets.

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Claudio Freitas Purdue University at West Lafayette

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Dr. Claudio Freitas is a Postdoctoral Research Associate in the School of Engineering Education at Purdue University (USA). Claudio received his Bachelor of Science degree from the Higher Education Institute of Amazonia, in Brazil, in 2011. In 2014 he received his Master of Science degree in Electrical Engineering from the State University of Campinas in Brazil. In May 2020, he completed his Ph.D. at Purdue University. His research interests lie in the area of educational technology and digital learning in diverse settings.

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Gregory John Gage Backyard Brains

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Dr. Gregory Gage is a Neuroscientist and the Co-Founder and CEO of Backyard Brains. Greg is an Adjunct Assistant Professor in the Molecular & Integrative Physiology department of the University of Michigan. His research focuses on democratizing advanced neuroscience labs for K12.

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Jennifer Deboer Purdue University at West Lafayette (COE)

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Jennifer DeBoer is currently Assistant Professor of Engineering Education at Purdue University. Her research focuses on international education systems, individual and social development, technology use and STEM learning, and educational environments for diverse learners.

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Lab-kits and the Self-Beliefs and STEM Beliefs of Students at a Black Majority High School Keywords: Pre-College, Engineering Technology, Race/Ethnicity, Socio-economic status

Introduction Technology tools used in education can positively affect student motivation (Preston et al., 2015). Active learning, often promoted by educational technology, has been shown to also have a significant effect on both learning gains and self-efficacy for underrepresented minority students (URM) in STEM (Ballen et al., 2017; Garibay, 2016). However, both new technologies and new teaching practices present unique challenges for implementation. Historically, teachers and students have faced many challenges of improving teaching and learning practices in diverse contexts (Blanchard et al., 2016; Miniawi & Brenjekjy, 2015; Strecker et al., 2018). Thus, we need to understand how teachers and students interact with technology and teaching practice to continue to adapt these tools to their needs and use them to benefit the self-beliefs of URM students in diverse school contexts. This study examines the combined benefits and areas for improvement of technology tools and active learning through a neuroscience lab-kit implemented with a curriculum that focuses on active learning centered around science and engineering concepts. In order to understand student attitudes related to STEM, this paper examines the self-efficacy, self-concept, and STEM motivations of students. Self-efficacy is student’s beliefs about their ability to perform skills related to a specific area (Schunk & Pajares, 2002). Self-concept relates to student’s self-beliefs about a specific area (Skaalvik & Skaalvik, 2002). For instance, a student may think “I am an engineer/scientist” (self-concept) or “I can do a specific engineering or science skill” (self-efficacy). STEM self-efficacy and self-concept are influenced by the STEM experiences and encouragement received (Schunk & Pajares, 2002; Skaalvik & Skaalvik, 2002). For URM students in particular, self-beliefs have been found to significantly influence academic outcomes and to be linked with active or problem-based learning environments (Estrada et al., 2016; Garibay, 2016). STEM motivations are made up of the learning strategies, values, aspirations, and overall motivations that students have related to science (Tuan et al., 2005) which are linked with URM persistence in STEM (Estrada et al., 2016).This paper recognizes schools offer vastly different role models, resources, and teacher support and attitudes, all of which contribute to student success and persistence in STEM (Hare, 2017; Knowles, 2017; Zee & Koomen, 2016). This paper will specifically evaluate the impact of this intervention on self-beliefs and motivations for students in an Black majority urban school.

Research Questions This paper examines the following questions: • How does a combined lab kit and neuroscience curriculum relate to STEM motivation in an urban Black majority school? • How does the lab kit and neuroscience curriculum relate to self-beliefs?

Methods This paper is part of a larger study investigating the experiences of high school students and teachers with neuroscience lab kits and lessons that incorporate neuroscience and electrical engineering concepts. These lab kits were developed to increase the access of K-12 students to neuroscience education, given a lack of educational opportunities to teach neuroscience during earlier educational stages. This study involves several runs of testing on various neuroscience kits paired with comprehensive curriculums. Specifically, the first two runs were conducted on a basic lab kit that uses bugs to show spikes created when an electrical current is run through the neuron. Further runs are planned on additional lab kits. The next lab kit to be tested will expand on previous implementations by employing computational and robotic models of working brains allowing students to understand more of the functionality of brains. This paper seeks to understand how such technology benefits underrepresented students across diverse school systems and potential improvements that can be made to better benefit these groups.

This study specifically chose schools that varied in resource levels, race/ethnicity, areas, and socioeconomic status. School 2 was a low resource, rural school with 55% of students on free/reduced lunch and 59% non-white students. School 3 was a high resource, urban school with 70% of students on free/reduced lunch and 99% non-white students (Public School Review, 2018). Teachers incorporated the materials into their traditional units for the semester during a week chosen by them. School 1 served as a test for data collection methods and thus is not directly comparable to the results of Schools 2 and 3. Thus, this paper will focus on the second run done with schools 2 and 3 who have large population of students in groups typically underrepresented in STEM.

Students completed two types of surveys during the week to understand their learning experiences: a pre/post survey and a daily understanding survey. All surveys were given digitally and accessed on the students’ phones. The focus of this paper is the pre- and post-test examining changes in students’ self-beliefs and beliefs related to STEM. This survey was built using the pieces of the MSLQ (Motivated Strategies for Learning Questionnaire) to assess self-beliefs (Pintrich et al., 1993), pieces of the SMTSL (Students' Motivation Toward Science Learning to assess STEM beliefs and strategies (Tuan et al., 2005), and pieces of the Science Motivation Questionnaire II to assess perception of science courses (Glynn et al., 2011). Students were told that their teachers would not have access to the survey results.


How does a combined lab kit and neuroscience curriculum differentially relate to STEM motivation between diverse school systems?

Results from the pre- and post-test show that students in the initial test already have high motivations, value of science, and learning habits. As these tests were conducted near the end of the school year, this result may reflect work of the science teachers who self-selected into the study that had already helped boast these beliefs and attitudes in their students throughout the year. Since each of these were already high, a ceiling effect was observed, as very little change could be achieved from the lab kit and curriculum.

The same pattern was not true for neuroscience aspirations, which was a student’s view of neurosciences and sciences in general as a potential career path. Neuroscience aspirations did not start out high, and for students in school 3, their aspirations towards neuroscience did increase significantly.

How does the lab kit and neuroscience curriculum relate to self-beliefs? Self-efficacy and self-concept for both schools started out low to medium for both schools. Thus, unlike the other measures, there was much more room for growth. However, there was no significant change detected. Thus, we cannot conclude that the lab kit or curriculum relate to self-beliefs.

Conclusion and Future Directions

Overall, the lab kit and neuroscience curriculum were most successful in the area of improving science aspirations for diverse students. Since high self-efficacy and self-concept predict higher achievement(Schunk & Pajares, 2002), encouraging these in students who are traditionally underrepresented is important. Additional changes need to be made in future iterations to the curricular materials to increase students’ self-beliefs. Further, interviews will be conducted with students and teachers to qualitatively understand and better explain students’ self-beliefs. Future studies will continue to explore the impact of our educational tools in a larger population with female and male students of multiple ethnicities from multiple socioeconomic backgrounds.

Citations: Ballen, C. J., Wieman, C., Salehi, S., Searle, J. B., & Zamudio, K. R. (2017). Enhancing Diversity in Undergraduate Science: Self-Efficacy Drives Performance Gains with Active Learning. CBE Life Sciences Education, 16(4). Blanchard, M. R., LePrevost, C. E., Tolin, A. D., & Gutierrez, K. S. (2016). Investigating Technology-Enhanced Teacher Professional Development in Rural, High-Poverty Middle Schools: Educational Researcher. Estrada, M., Burnett, M., Campbell, A. G., Campbell, P. B., Denetclaw, W. F., Gutiérrez, C. G., Hurtado, S., John, G. H., Matsui, J., McGee, R., Okpodu, C. M., Robinson, T. J., Summers, M. F., Werner-Washburne, M., & Zavala, M. (2016). Improving Underrepresented Minority Student Persistence in STEM. CBE Life Sciences Education, 15(3). Garibay, G. (2016). Self-efficacy beliefs of underrepresented minorities in science, technology, engineering, and math [Ed.D., University of Southern California]. Glynn, S. M., Brickman, P., Armstrong, N., & Taasoobshirazi, G. (2011). Science motivation questionnaire II: Validation with science majors and nonscience majors. Journal of Research in Science Teaching, 48(10), 1159–1176. Hare, L. N. (2017). The Perceptions of STEM from Eighth-Grade African-American Girls in a High-Minority Middle School [Ed.D., Gardner-Webb University]. Knowles, J. G. (2017). Impacts of Professional Development in Integrated STEM Education on Teacher Self-Efficacy, Outcome Expectancy, and Stem Career Awareness [Ph.D., Purdue University]. Miniawi, H. E., & Brenjekjy, A. (2015). Educational Technology, Potentials, Expectations and Challenges. Procedia - Social and Behavioral Sciences, 174, 1474–1480. Pintrich, P. R., Smith, D. A. F., Garcia, T., & Mckeachie, W. J. (1993). Reliability and Predictive Validity of the Motivated Strategies for Learning Questionnaire (Mslq). Educational and Psychological Measurement, 53(3), 801–813. Preston, J. P., Wiebe, S., Gabriel, M., McAuley, A., Campbell, B., & MacDonald, R. (2015). Benefits and Challenges of Technology in High Schools: A Voice from Educational Leaders with a Freire Echo. Interchange, 46(2), 169–185. Public School Review. (2018). Public School Review—Profiles of USA Public Schools. Public School Review. Schunk, D. H., & Pajares, F. (2002). Chapter 1—The Development of Academic Self-Efficacy. In A. Wigfield & J. S. Eccles (Eds.), Development of Achievement Motivation (pp. 15–31). Academic Press. Skaalvik, E. M., & Skaalvik, S. (2002). Internal and External Frames of Reference for Academic Self-Concept. Educational Psychologist, 37(4), 233–244. Strecker, S., Kundisch, D., Lehner, F., Leimeister, J. M., & Schubert, P. (2018). Higher Education and the Opportunities and Challenges of Educational Technology. Business & Information Systems Engineering, 60(2), 181–189. Tuan, H.-L., Chin, C.-C., & Shieh, S.-H. (2005). The development of a questionnaire to measure students’ motivation towards science learning. International Journal of Science Education, 27(6), 639–654. Zee, M., & Koomen, H. M. Y. (2016). Teacher Self-Efficacy and Its Effects on Classroom Processes, Student Academic Adjustment, and Teacher Well-Being: A Synthesis of 40 Years of Research. Review of Educational Research.

Haney, C. L., & Freitas, C., & Gage, G. J., & Deboer, J. (2021, January), Lab Kits and the Self-Beliefs and STEM Beliefs of Students at a Black Majority High School Paper presented at 2021 CoNECD, Virtual - 1pm to 5pm Eastern Time Each Day . 10.18260/1-2--36104

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