Research Experiences for Undergraduate Students: The Role of Mentorship in Transferring Circularity and Digitalization Skills, Attitudes, and Knowledge in Food Systems
DOI:
https://doi.org/10.56103/nactaj.v68i1.220Keywords:
Circularity, Mentorship, Performance, Social Learning, Undergraduate Research ExperienceAbstract
Developing knowledge, skills, and research attitudes is crucial for undergraduate students to address issues and innovation in food systems. Universities play a significant role in addressing these needs by providing students with high-quality educational experiences. This research employed a case study research design to obtain insights and perceptions from one group of previous Research and Extension Experience for Undergraduates (REEU) mentors. Drawing on the lenses of the Social Cognitive Career Theory’s Performance model (Lent et al., 1994), we rationalize the role of reflection and feedback from mentors in enhancing the learning environment. Data were collected through a focus group and analyzed using open and axial coding to identify recurring themes, patterns, and insights. Four major themes emerged:sense of preparation, the pairing process, relationship challenges, and mentors’ implications, to better understand the ability and past performance related to mentorship and this program. These themes provide a broader picture of the nature of mentorship within this REEU, highlighting the need for scaffolding, effective communication, and collaborative strategies for fostering positive mentorship experiences.
Downloads
References
Andrews, D. (2015). The circular economy, design thinking and education for sustainability. Local Economy, 30(3), 305–315. https://doi.org/10.1177/0269094215578226/FORMAT/EPUB
Atkins, K., Dougan, B. M., Dromgold-Sermen, M. S., Potter, H., Sathy, V., & Panter, A. T. (2020). “Looking at myself in the future”: how mentoring shapes scientific identity for STEM students from underrepresented groups. International Journal of STEM Education, 7(1), 1–15. https://doi.org/10.1186/S40594-020-00242-3/TABLES/2
Bandura, A. (1969). Social learning theory of identificatory processes. In Goslin, D. A (Ed.), Handbook of socialization theory and research (pp. 213–262). Rand McNally & Company.
Bandura, A. (1989). Human agency in social cognitive theory. American Psychologist Association Inc. 44, No. 9, 1175-1184
Bandura, A. (1991a). Social cognitive theory of self-regulation. Organizational Behavior and Human Decision Processes, 248–287.
Bandura, A. (1991b). Social cognitive theory of self-regulation. Organizational Behavior and Human Decision Processes, 50(2), 248–287. https://doi.org/10.1016/0749-5978(91)90022-L
Bandura, A. (2002). Social cognitive theory in cultural context. Applied Psychology, 51(2), 269–290. https://doi.org/10.1111/1464-0597.00092
Burger, M., Stavropoulos, S., Ramkumar, S., Dufourmont, J., & Van Oort, F. (2018). The heterogeneous skill-base of circular economy employment. Research Policy, 48(2019), 248–261. https://doi.org/10.1016/j.respol.2018.08.015
Canet-Martí, A., Pineda-Martos, R., Junge, R., Bohn, K., Paço, T. A., Delgado, C., Alenčikienė, G., Skar, S. L. G., & Baganz, G. F. M. (2021). Nature-based solutions for agriculture in circular cities: Challenges, gaps, and opportunities. Water (Switzerland), 13(18). https://doi.org/10.3390/w13182565
Doolittle, P. E., & Camp, W. G. (1999). Constructivism: The career and technical education perspective. Journal of Vocational and Technical Education,16(1). http://scholar.lib.vt.edu/ejournals/JVTE/v16n1/doolittle.html
Hedberg, A., & Šipka, S. (2021). Toward a circular economy: The role of digitalization. One Earth, 4(6), 783–785. https://doi.org/10.1016/j.oneear.2021.05.020
Kuchynka, S., Reifsteck, T. V., Gates, A. E., & Rivera, L. M. (2021). Developing self-efficacy and behavioral intentions among underrepresented students in STEM: The role of active learning. Frontiers in Education, 6. https://doi.org/10.3389/feduc.2021.668239
Lent, R. W., & Brown, S. D. (2019). Social cognitive career theory at 25: Empirical status of the interest, choice, and performance models. Journal of Vocational Behavior, 115. https://doi.org/10.1016/j.jvb.2019.06.004
Roberts, T. G. (2006). A philosophical examination of experiential learning for agricultural education. Journal of Agricultural Education, 47(1), 17–29. https://doi.org/10.5032/jae.2006.01017
Schunk, D. H. (2012). Social cognitive theory. In APA educational psychology handbook, Vol 1: Theories, constructs, and critical issues. (pp. 101–123). American Psychological Association. https://doi.org/10.1037/13273-005
Tang, S., Zhu, Q., Zhou, X., Liu, S., & Wu, M. (2002, June 24). A Conception of digital agriculture. IEEE International Geoscience and Remote Sensing Symposium, Toronto, Ontario, Canada, 2002, pp. 3026-3028 vol.5, https://ieeexplore.ieee.org/document/1026858
Vygotsky, L. S. (1978). Interaction between learning and development. In Mind and Society (2nd ed., pp. 79–91). Harvard University Press.