New Epistemological Perspectives on Quantitative Methods: An Example Using Topological Data Analysis
References
- Abiodun, O. I., Jantan, A., Omolara, A. E., Dada, K. V., Mohamed, N. A., & Arshad, H. (2018). State-of-the-art in artificial neural network applications: A survey. Heliyon, 4(11),
e00938 . DOI: 10.1016/j.heliyon.2018.e00938 - Acker, J. (1990). Hierarchies, jobs, bodies: A theory of gendered organizations. Gender & Society, 4(2), 139–158. DOI: 10.1177/089124390004002002
- Akpanudo, U. M., Huff, J. L., Williams, J. K., & Godwin, A. (2017, October). Hidden in plain sight: Masculine social norms in engineering education. In IEEE Frontiers in Education Conference. DOI: 10.1109/FIE.2017.8190515
- Baillie, C., & Douglas, E. P. (2014). Confusions and conventions: Qualitative research in engineering education. Journal of Engineering Education, 103(1), 1–7. DOI: 10.1002/jee.20031
- Bairaktarova & Pilotte. (2020). Person or thing oriented: A comparative study of individual differences of first-year engineering students and practitioners. Journal of Engineering Education, 109(2), 230–242. DOI: 10.1002/jee.20309
- Benedict, B., Baker, R. A., Godwin, A., & Milton, T. (2018). Uncovering latent diversity: Steps towards understanding ‘what counts’ and ‘who belongs’ in engineering culture. In ASEE Annual Conference & Exposition, Salt Lake City, UT. DOI: 10.18260/1-2-31164
- Benson, L., Potvin, G., Kirn, A., Godwin, A., Doyle, J., Rohde, J. A., Verdín, D., & Boone, H. (2017). Characterizing student identities in engineering: Attitudinal profiles of engineering majors. In ASEE Annual Conference & Exposition, Columbus, OH. DOI: 10.18260/1-2--27950
- Biesta, G. (2010).
Pragmatism and the philosophical foundations of mixed methods research . In A. Tashakkori & C. Teddlie (Eds.), Handbook of Mixed Methods in Social and Behavioral Research (pp. 95–118), SAGE. DOI: 10.4135/9781506335193.n4 - Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and Regression Trees. New York, NY: Routledge. DOI: 10.1201/9781315139470
- Bowleg, L. (2008). When Black+ lesbian+ woman≠ Black lesbian woman: The methodological challenges of qualitative and quantitative intersectionality research. Sex Roles, 59(5–6), 312–325. DOI: 10.1007/s11199-008-9400-z
- Bryman, A. (2008).
The end of the paradigm wars? In Alasuutari, P., Bickman, L. and Brannen, J. (Eds.), The SAGE Handbook of Social Research Methods (pp. 13–25), London, UK: SAGE. DOI: 10.4135/9781446212165 - Cech, E. (2015). Engineers and engineeresses? Self-conceptions and the development of gendered professional identities. Sociological Perspectives, 58(1), 56–77. DOI: 10.1177/0731121414556543
- Cejka, M. A., & Eagly, A. H. (1999). Gender-stereotypic images of occupations correspond to the sex segregation of employment. Personality and Social Psychology Bulletin, 25(4), 413–423. DOI: 10.1177/0146167299025004002
- Chazal, F., & Michel, B. (2017). An introduction to Topological Data Analysis: Fundamental and practical aspects for data scientists. Retrieved from
http://arxiv.org/abs/1710.04019 - Codiroli Mcmaster, N., & Cook, R. (2019). The contribution of intersectionality to quantitative research into educational inequalities. Review of Education, 7(2), 271–292. DOI: 10.1002/rev3.3116
- Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Earlbaum Associates.
- Collins, P. H. (1990). Black feminist thought: Knowledge, consciousness, and the politics of empowerment. Unwin Hyman.
- Collins, P. H., & Bilge, S. (2016). Intersectionality. Cambridge, UK: Polity Press.
- Connell, R. W. (2009). Gender: Short introductions (2nd ed.). Cambridge, UK: Polity Press.
- Creswell, J. W., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research (2nd Ed.). SAGE.
- Crotty, M. (1998). The foundations of social research: Meaning and perspective in the research process. SAGE.
- Danielak, B. A., Gupta, A., & Elby, A. (2014). Marginalized identities of sense-makers: Reframing engineering student retention. Journal of Engineering Education, 103(1), 8–44. DOI: 10.1002/jee.20035
- Delgado, R., & Stefancic, J. (2012). Critical race theory: An introduction (2nd ed.). New York, NY: New York University Press.
https://ssrn.com/abstract=1640643 - Douglas, E. P., Koro-Ljungberg, M., & Borrego, M. (2010). Challenges and promises of overcoming epistemological and methodological partiality: Advancing engineering education through acceptance of diverse ways of knowing. European Journal of Engineering Education, 35(3), 247–257. DOI: 10.1080/03043791003703177
- Douglas, K. A., & Purzer, Ş. (2015). Validity: Meaning and relevancy in assessment for engineering education research. Journal of Engineering Education, 104(2), 108–118. DOI: 10.1002/jee.20070
- Doyle, J. (2017). Describing and mapping the interactions between student affective factors related to persistence in science, physics, and engineering (Publication No. 10747700). [Doctoral dissertation, Florida International University]. ProQuest Dissertations & Theses Global.
- Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (2011). Cluster analysis (5th ed.). John Wiley & Sons, Inc. DOI: 10.1002/9780470977811
- Eye, A., & Wiedermann, W. (2015).
Person-Centered Analysis . In Emerging Trends in the Social and Behavioral Sciences (pp. 1–18). John Wiley & Sons, Inc. DOI: 10.1002/9781118900772.etrds0251 - Fanelli, D. (2010). “Positive” results increase down the hierarchy of the sciences. PloS one, 5(4),
e10068 . DOI: 10.1371/journal.pone.0010068 - Fernandez, T., & Godwin, A., & Doyle, J., & Verdín, D., & Boone, H., & Kirn, A., & Benson, L., & Potvin, G. (2016). More comprehensive and inclusive approaches to demographic data collection. In ASEE Annual Conference & Exposition, New Orleans, LA. DOI: 10.18260/p.25751
- Foor, C. E., Walden, S. E., & Trytten, D. A. (2007). “I wish that I belonged more in this whole engineering group”: Achieving individual diversity. Journal of Engineering Education, 96(2), 103–115. DOI: 10.1002/j.2168-9830.2007.tb00921.x
- Garcia-Dias, R., Vieira, S., Pinaya, W. H. L., & Mechelli, A. (2020).
Clustering analysis . In Machine Learning (pp. 227–247). Academic Press. DOI: 10.1016/B978-0-12-815739-8.00013-4 - Gero, J., & Milovanovic, J. (2020). A framework for studying design thinking through measuring designers’ minds, bodies and brains. Design Science, 6, E19. DOI: 10.1017/dsj.2020.15
- Gero, J. S., & Peng, W. (2009). Understanding behaviors of a constructive memory agent: A Markov chain analysis. Knowledge-Based Systems, 22(8), 610–621. DOI: 10.1016/j.knosys.2009.05.006
- Gillborn, D. (2018). QuantCrit: Rectifying quantitative methods through Critical Race Theory [Special Issue]. Race Ethnicity and Education, 21(2), 149–273. DOI: 10.1080/13613324.2017.1377675
- Gillborn, D., Warmington, P., & Demack, S. (2018). QuantCrit: education, policy, ‘Big Data’ and principles for a critical race theory of statistics. Race Ethnicity and Education, 21(2), 158–179. DOI: 10.1080/13613324.2017.1377417
- Godwin, A. (2017). Unpacking latent diversity. In ASEE Annual Conference & Exposition, Columbus, OH. DOI: 10.18260/1-2--29062
- Godwin, A., Benedict, B. S., Verdín, D., Thielmeyer, A. R. H., Baker, R. A., & Rohde, J. A. (2018). Board 12: CAREER: Characterizing latent diversity among a national sample of first-year engineering students. In ASEE Annual Conference & Exposition, Tampa, FL.
https://peer.asee.org/32207 - Godwin, A., Thielmeyer, A. R. H., Rohde, J. A., Verdín, D., Benedict, B. S., Baker, R. A., Doyle, J. (2019). Using topological data analysis in social science research: Unpacking decisions and opportunities for a new method. In ASEE Annual Conference and Exposition, Tampa, FL.
https://peer.asee.org/33522 - Goldschmidt, G. (2014). Linkography: unfolding the design process. MIT Press. DOI: 10.7551/mitpress/9455.001.0001
- Greenacre, M., & Hastie, T. (1987). The geometric interpretation of correspondence analysis. Journal of the American Statistical Association, 82(398), 437–447. DOI: 10.1080/01621459.1987.10478446
- Hammersley, M. (2008).
Assessing validity in social research . In P. Alasuutari, L. Bickman, & J. Brannen (Eds.), The SAGE Handbook of Social Research Methods (pp. 42–53), SAGE. DOI: 10.4135/9781446212165.n4 - Hanel, P. H., Maio, G. R., & Manstead, A. S. (2019). A new way to look at the data: Similarities between groups of people are large and important. Journal of Personality and Social Psychology, 116(4), 541–562. DOI: 10.1037/pspi0000154
- Harding, S. (2016). Whose science? Whose knowledge? Thinking from women’s lives. Cornell University Press. DOI: 10.7591/9781501712951
- Hesse-Biber, S. N., & Piatelli, D. (2012).
The feminist practice of holisitic reflexivity . In S. N. Hesse-Biber (Ed.), Handbook of Feminist Research Theory and Praxis (2nd ed., pp. 557–582). SAGE. DOI: 10.4135/9781483384740.n27 - Holland, P. W. (2008).
Causation and race . In T. Zuberi & E. Bonilla-Silva (Eds.), White logic, white methods: Racism and methodology. Rowman & Littlefield. - Hout, M. C., Papesh, M. H., & Goldinger, S. D. (2013). Multidimensional scaling. Wiley Interdisciplinary Reviews: Cognitive Science, 4(1), 93–103. DOI: 10.1002/wcs.1203
- Hundleby, C. E. (2012).
Feminist empiricism . In S. N. Hesse-Biber (Ed.), Handbook of Feminist Research: Theory and Praxis (2nd ed., pp. 28–45). SAGE. DOI: 10.4135/9781483384740.n2 - Jack, R. E., Crivelli, C., & Wheatley, T. (2018). Data-Driven Methods to Diversify Knowledge of Human Psychology. Trends in Cognitive Sciences, 22(1), 1–5. DOI: 10.1016/j.tics.2017.10.002
- Jagger, A. M. (2014).
Introduction: The project of feminist methodology . In A. M. Jagger (Ed.), Just Methods: An Interdisciplinary Feminist Reader (2nd ed., pp. vii–xiii). Paradigm Publishers. DOI: 10.4324/9781315636344 - Jesiek, B. K., Newswander, L. K., & Borrego, M. (2009). Engineering education research: Discipline, community, or field? Journal of Engineering Education, 98(1), 39–52. DOI: 10.1002/j.2168-9830.2009.tb01004.x
- Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed methods research: A research paradigm whose time has come. Educational Researcher, 33(7), 14–26. DOI: 10.3102/0013189X033007014
- Kan, J. W., & Gero, J. S. (2010). Exploring quantitative methods to study design behavior in collaborative virtual workspaces. In New Frontiers, Proceedings of the 15th International Conference on CAADRIA (pp. 273–282).
- Kant, V., & Kerr, E. (2019). Taking stock of engineering epistemology: Multidisciplinary perspectives. Philosophy & Technology, 32(4), 685–726. DOI: 10.1007/s13347-018-0331-5
- Kaushik, V., & Walsh, C. A. (2019). Pragmatism as a research paradigm and its implications for social work research. Social Sciences, 8(255), 1–17. DOI: 10.3390/socsci8090255
- Kherif, F., & Latypova, A. (2020).
Principal component analysis . In Machine Learning (pp. 209–225). Academic Press. DOI: 10.1016/B978-0-12-815739-8.00012-2 - Koro-Ljungberg, M., & Douglas, E. P. (2008). State of qualitative research in engineering education: Meta-analysis of JEE articles, 2005–2006. Journal of Engineering Education, 97(2), 163–175. DOI: 10.1002/j.2168-9830.2008.tb00965.x
- Lather, P. (2006). Paradigm proliferation as a good thing to think with: Teaching research in education as a wild profusion. International Journal of Qualitative Studies in Education, 19(1), 35–57. DOI: 10.1080/09518390500450144
- Laubenbacher, R., and Hastings, A., (2019). Topological Data Analysis. Bulletin of Mathematical Biology. 81(7), 2051. DOI: 10.1007/s11538-019-00610-3
- Laursen, B., & Hoff, E. (2006). Person-centered and variable-centered approaches to longitudinal data. Merrill-Palmer Quarterly, 52(3), 377–389. DOI: 10.1353/mpq.2006.0029
- Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A. L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., & Van Alstyne, M. (2009). Computational social science. Science, 323(5915), 721–723. DOI: 10.1126/science.1167742
- Lum, P. Y., Singh, G., Lehman, A., Ishkanov, T., Vejdemo-Johansson, M., Alagappan, M., Carlsson, J. & Carlsson, G. (2013). Extracting insights from the shape of complex data using topology. Scientific Reports, 3, 1236. DOI: 10.1038/srep01236
- Major, J., Godwin, A., & Kirn, A. (2021). Working to achieve equitable access to engineering by redefining disciplinary standards for the use and dissemination of quantitative study demographics. In Collaborative Network for Engineering and Computing Diversity Conference, Washington, DC.
https://peer.asee.org/36147 - Major, J. C., & Godwin, A. (2019). An intersectional conceptual framework for understanding how to measure socioeconomic inequality in engineering education. In ASEE Annual Conference & Exposition, Tampa, FL. DOI: 10.18260/1-2--33594
- Maxcy, S. J. (2003).
Pragmatic threads in mixed methods research in the social sciences: The search for multiple modes of inquiry and the end of the philosophy of formalism . In A. Tashakkori & C. Teddlie (Eds.), Handbook of Mixed Methods in Social and Behavioral Research (pp. 51–89), SAGE. - McCall, L. (2002). Complex inequality: Gender, class, and race in the new economy. Routledge. DOI: 10.4324/9780203902455
- McGuirl, M. R., Volkening, A., & Sandstede, B. (2020). Topological data analysis of zebrafish patterns. Proceedings of the National Academy of Sciences, 117(10), 5113–5124. DOI: 10.1073/pnas.1917763117
- McNicholas, P. D. (2010). Model-based classification using latent Gaussian mixture models. Journal of Statistical Planning and Inference, 140(5), 1175–1181. DOI: 10.1016/j.jspi.2009.11.006
- Merriam, S. B., & Tisdell, E. J. (2016). Qualitative research: A guide to design and implementation (4th ed.). John Wiley & Sons.
- Miller, D. I., Eagly, A. H., & Linn, M. C. (2015). Women’s representation in science predicts national gender-science stereotypes: Evidence from 66 nations. Journal of Educational Psychology, 107(3), 631–644. DOI: 10.1037/edu0000005
- Morgan, D. L. (2014). Pragmatism as a paradigm for social research. Qualitative Inquiry, 20(8), 1045–1053. DOI: 10.1177/1077800413513733
- Morin, A. J., Bujacz, A., & Gagné, M. (2018). Person-centered methodologies in the organizational sciences: Introduction to the feature topic. Organizational Research Method, 21(4), 803–813. DOI: 10.1177/1094428118773856
- National Academy of Engineering. (2008).
Changing the conversation: Messages for improving public understanding of engineering . Washington DC, National Academies Press. DOI: 10.17226/12187 - Oakley, A. (1998). Gender, methodology and people’s ways of knowing: Some problems with feminism and the paradigm debate in social science. Sociology, 32(4), 707–731. DOI: 10.1177/0038038598032004005
- Oberski, D. (2016)
Mixture Models: Latent Profile and Latent Class Analysis . In J. Robertson, M. Kaptein (Eds.) Modern Statistical Methods for HCI. Human–Computer Interaction Series. Springer. DOI: 10.1007/978-3-319-26633-6_12 - Omi, M., & Winant, H. (2014). Racial formation in the United States (3rd ed.). Routledge. DOI: 10.4324/9780203076804-6
- Pallas, A. M. (2001) Preparing education doctoral students for epistemological diversity. Educational Researcher, 30(5), 1–6. DOI: 10.3102/0013189X030005006
- Pawley, A. L. (2017). Shifting the “default”: The case for making diversity the expected condition for engineering education and making whiteness and maleness visible. Journal of Engineering Education, 106(4), 531–533. DOI: 10.1002/jee.20181
- Pawley, A. L. (2018). Learning from small numbers: Studying ruling relations that gender and race the structure of US engineering education. Journal of Engineering Education, 108(1), 13–31. DOI: 10.1002/jee.20247
- Perdomo Meza, D. A. (2015). Topological data analysis with metric learning and an application to high-dimensional football data [Master’s thesis, Bogotá-Uniandes]. Retrieved from
https://repositorio.uniandes.edu.co/bitstream/handle/1992/12963/u713491.pdf?sequence=1 - Qiu, L., Chan, S. H. M., & Chan, D. (2018). Big data in social and psychological science: theoretical and methodological issues. Journal of Computational Social Science, 1(1), 59–66. DOI: 10.1007/s42001-017-0013-6
- R Core Team. (2018). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from
https://www.R-project.org . - Ram, N., & Grimm, K. J. (2009). Methods and measures: Growth mixture modeling: A method for identifying differences in longitudinal change among unobserved groups. International journal of behavioral development, 33(6), 565–576. DOI: 10.1177/0165025409343765
- Ray, V. (2019). A theory of racialized organizations. American Sociological Review, 84(1), 26–53. DOI: 10.1177/0003122418822335
- Reed, I. A. (2010). Epistemology contextualized: Social-scientific knowledge in a postpositivist era. Sociological Theory, 28(1), 20–39. DOI: 10.1111/j.1467-9558.2009.01365.x
- Riley, D. (2017). Rigor/Us: Building boundaries and disciplining diversity with standards of merit. Engineering Studies, 9(3), 249–265. DOI: 10.1080/19378629.2017.1408631
- Scheurich, J. J., & Young, M. D. (1997). Coloring epistemologies: Are our research epistemologies racially biased? Educational researcher, 26(4), 4–16. DOI: 10.3102/0013189X026004004
- Secules, S., Gupta, A., Elby, A., & Turpen, C. (2018). Zooming out from the struggling individual student: An account of the cultural construction of engineering ability in an undergraduate programming class. Journal of Engineering Education, 107(1), 56–86. DOI: 10.1002/jee.20191
- Sellbom, M., & Tellegen, A. (2019). Factor analysis in psychological assessment research: Common pitfalls and recommendations. Psychological Assessment, 31(12), 1428–1441. DOI: 10.1037/pas0000623
- Sigle-Rushton, W. (2014).
Essentially quantified? Towards a more feminist modeling strategy . In M. Evans, C. Hemmings, M. Henry, H. Johnstone, S. Madhok, A. Plomien, & S. Wearing (Eds.), The SAGE Handbook of Feminist Theory (pp. 431–445). SAGE. DOI: 10.4135/9781473909502.n29 - Slaton, A. E. (2015).
Meritocracy, technocracy, democracy: Understandings of racial and gender equity in American engineering education . In International perspectives on engineering education (pp. 171–189). Springer. DOI: 10.1007/978-3-319-16169-3_8 - Slaton, A. E., & Pawley, A. L. (2018). The power and politics of engineering education research design: Saving the ‘Small N’. Engineering Studies, 10(2–3), 133–157. DOI: 10.1080/19378629.2018.1550785
- Sprague, J. (2005).
How feminists count: Critical strategies for quantitative methods . In J. Sprague (Ed.), Feminist Methodology for Critical Researchers: Bridging Differences (1st ed., pp. 81–117). Rowman & Littlefield. - Sprague, J., & Zimmerman, M. K. (1989). Quality and quantity: Reconstructing feminist methodology. The American Sociologist, 20(1), 71–86. DOI: 10.1007/BF02697788
- Streveler, R., & Smith, K. A. (2006). Rigorous research in engineering education. Journal of Engineering Education, 95(2), 103–105. DOI: 10.1002/j.2168-9830.2006.tb00882.x
- Su, R., & Rounds, J. (2015). All STEM fields are not created equal: People and things interests explain gender disparities across STEM fields. Frontiers in Psychology, 6(Article 189), 1–20. DOI: 10.3389/fpsyg.2015.00189
- Tashakkori, A., & Teddlie, C. (2008).
Quality of inferences in mixed methods research: Calling for an integrative framework . In M. M. Bergman (Ed.), Advances in Mixed Methods Research (pp. 101–119), SAGE. DOI: 10.4135/9780857024329.d10 - Tuli, F. (2010). The basis of distinction between qualitative and quantitative research in social science: Reflection on ontological, epistemological and methodological perspectives. Ethiopian Journal of Education and Sciences, 6(1), 97–108. DOI: 10.4314/ejesc.v6i1.65384
- Tynjälä, P., Salminen, R. T., Sutela, T., Nuutinen, A., & Pitkänen, S. (2005). Factors related to study success in engineering education. European Journal of Engineering Education, 30(2), 221–231. DOI: 10.1080/03043790500087225
- Uhlar, J. R., & Secules, S. (2018). Butting heads: Competition and posturing in a paired programming team. In IEEE Frontiers in Education Conference, San Jose, CA. DOI: 10.1109/FIE.2018.8658654
- Verdín, D., Godwin, A., Kirn, A., Benson, L., & Potvin, G. (2018). Engineering women’s attitudes and goals in choosing disciplines with above and below average female representation. Social Sciences, 7(3), 44. DOI: 10.3390/socsci7030044
- Villanueva, I., Di Stefano, M., Gelles, L., Osoria, P. V., & Benson, S. (2019). A race re-imaged, intersectional approach to academic mentoring: Exploring the perspectives and responses of womxn in science and engineering research. Contemporary Educational Psychology, 59(2019), 101786. DOI: 10.1016/j.cedpsych.2019.101786
- Villanueva, I., Husman, J., Christensen, D., Youmans, K., Khan, M. T., Vicioso, P., Lampkins, S., & Graham, M. C. (2019). A cross-disciplinary and multi-modal experimental design for studying near-real-time authentic examination experiences. JoVE (Journal of Visualized Experiments), (151),
e60037 . DOI: 10.3791/60037 - Walther, J., Pawley, A. L., & Sochacka, N. W. (2015). Exploring ethical validation as a key consideration in interpretive research quality. In ASEE Annual Conference & Exposition, Seattle, WA. DOI: 10.18260/p.24063
- Walther, J., Sochacka, N. W., Benson, L. C., Bumbaco, A. E., Kellam, N., Pawley, A. L., & Phillips, C. M. (2017). Qualitative research quality: A collaborative inquiry across multiple methodological perspectives. Journal of Engineering Education, 106(3), 398–430. DOI: 10.1002/jee.20170
- Walther, J., Sochacka, N. W., & Kellam, N. N. (2013). Quality in interpretive engineering education research: Reflections on an example study. Journal of Engineering Education, 102(4), 626–659. DOI: 10.1002/jee.20029
- Wang, M., Sinclair, R. R., Zhou, L., & Sears, L. E. (2013).
Person-centered analysis: Methods, applications, and implications for occupational health psychology . In R. R. Sinclair, M. Wang, & L. E. Tetrick (Eds.), Research methods in occupational health psychology: Measurement, design, and data analysis (p. 349–373). Routledge/Taylor & Francis Group. DOI: 10.4324/9780203095249 - Wasserman, L. (2018). Topological data analysis. Annual Review of Statistics and Its Application, (5), 501–532. DOI: 10.1146/annurev-statistics-031017-100045
- Wickham, H. (2009).
ggplot2: elegant graphics for data analysis . Springer.http://had.co.nz/ggplot2/book . Accessed: August, 5, 2014.
DOI: https://doi.org/10.21061/see.18 | Journal eISSN: 2690-5450
Language: English
Page range: 16 - 34
Submitted on: Jan 14, 2020
Accepted on: Mar 29, 2021
Published on: May 4, 2021
Published by: Virginia Tech Publishing
In partnership with: Paradigm Publishing Services
Keywords:
© 2021 Allison Godwin, Brianna Benedict, Jacqueline Rohde, Aaron Thielmeyer, Heather Perkins, Justin Major, Herman Clements, Zhihui Chen, published by Virginia Tech Publishing
This work is licensed under the Creative Commons Attribution 4.0 License.