Skip to main content
SpringerLink
Log in

Broadening Participation in Computing: Promoting Affective and Cognitive Learning in Informal Spaces

  • Original Paper
  • Published:
TechTrends Aims and scope Submit manuscript

Abstract

In this work we examine youth learning in an informal computing program implemented through a library-university partnership. In particular, we introduce and illustrate a culturally responsive computing framework which served as a foundation for the design of the program. Subsequently, we examine youth collaboration as well as affective and cognitive learning outcomes. Data were collected from university program facilitators and 30 youth over one semester. Data were collected through observations, lesson plans, computational artifacts and interviews with two case study youth. Results indicated that youth formed a variety of learning communities during the collaborative development of computing artifacts. Frequent participants were found to work with a greater number of peers compared to less frequent participants. Results from case study participants also indicated improvements in their computational competencies. Findings from this work have implications for the design of informal learning environments that help broaden participation in computing.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Ahn, J., Subramaniam, M., Bonsignore, E., Pellicone, A., Waugh, A., & Yip, J. (2014). I Want to be a game designer or scientist: Connected learning and developing identities with urban, African-American youth. In J. L. Polman, E. A. Kyza, D. K. O’Neill, I. Tabak, W. R. Penuel, A. S. Jurow, et al. (Eds.), Learning and becoming in practice: The International Conference of the Learning Sciences (ICLS) 2014 (pp. 657–664). Colorado, CO: International Society of the Learning Sciences.

  • Anderson, N. D. (2016). A call for computational thinking in undergraduate psychology. Psychology Learning & Teaching, 15, 226–234.

    Article  Google Scholar 

  • Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J., & Zagami, J. (2016). A K-6 computational thinking curriculum framework: Implications for teacher knowledge. Educational Technology & Society, 19(3), 47–57.

    Google Scholar 

  • Atmatzidou, S., Demetriadis, S. (2014). How to support students’ computational thinking skills in educational robotics activities. Proceedings of 4th International Workshop “Teaching Robotics & Teaching with Robotics” & 5th International Conference “Robotics in Education”, Padova (Italy) July 18, 2014.

  • Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48–54. https://doi.org/10.1145/1929887.1929905.

    Article  Google Scholar 

  • Barton, A. C., & Tan, E. (2010). We be burnin’! Agency, identity, and science learning. The Journal of the Learning Sciences, 19(2), 187–229.

  • Bers, M. U., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers & Education, 72, 145–157. https://doi.org/10.1016/j.compedu.2013.10.020.

    Article  Google Scholar 

  • Bliksten, P., & Moghadam, S. H. (2019). Computing education: Literature review and voices from the field. In S. A. Fincher & A. V. Robin (Eds.), The Cambridge handbook of computing education research (pp. 56–78). Cambridge University Press.

  • Brady, C., Orton, K., Weintrop, D., Anton, G., Rodriguez, S., & Wilensky, U. (2017). All roads lead to computing: Making, participatory simulations, and social computing as pathways to computer science. IEEE Transactions on Education, 60(1), 59–66.

  • Braun, L., & Visser, M. (2017). Read to code: Connecting youth to CS opportunity through libraries. American library association: Office for information technology policy. Retrieved from http://www.ala.org/advocacy/sites/ala.org.advocacy/files/content/pp/Ready_To_Code_Report_FINAL.pdf.

  • Brennan, K., & Resnick, M. (2012). Using artifact-based interviews to study thedevelopment of computational thinking in interactive media design. Paper presented at annual American Educational Research Association meeting, April 13–17. BC, Canada: Vancouver.

  • Codding, D., Mouza, C., Rolon-Dow, R., & Pollock, L. (2019). Positionality and belonging: Analyzing an informally situated and culturally responsive computer science program. In Proceedings of 8th Annual Conference on Maker Education (FabLearn ‘19). Mar 9–10. New York: ACM.

  • Coviello, N. E. (2005). Integrating qualitative and quantitative techniques in network analysis. Qualitative Market Research: An International Journal, 8(1), 39–60.

    Article  Google Scholar 

  • Creswell, J. W., & Miller, D. L. (2000). Determining validity in qualitative inquiry. Theory Into Practice, 39(3), 124–130.

    Article  Google Scholar 

  • Csardi, G., & Nepusz, T. (2006). The igraph software package for complex network research. InterJournal, Complex Systems, 1695(5), 1–9.

    Google Scholar 

  • Csizmadia, A., Standl, B., & Waite, J. (2019). Integrating the constructionist learning theory with computational thinking classroom activities. Informatics in Education, 18(1), 41–67.

    Article  Google Scholar 

  • CSTA & ISTE (2011). Computational thinking: Teacher resources. http://csta.acm.org/Curriculum/sub/CurrFiles/472.11CTTeacherResources_2ed-SP-vF.pdf.

  • Denner, J., Werner, L., & Ortiz, E. (2011). Computer games created by middle school girls: Can they be used to measure understanding of computer science concepts? Computers and Education, 58, 240–259.

    Article  Google Scholar 

  • Design-Based Research Collective (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1), 5–8.

    Article  Google Scholar 

  • Eglash, R., Gilbert, J. E., & Foster, E. (2013). Toward culturally responsive computing education. Communications of the ACM, 56(7), 33–36.

    Article  Google Scholar 

  • Estrada, M., Hernandez, P. R., & Schultz, P. W. (2018). A longitudinal study of how quality mentorship and research experience integrate underrepresented minorities into STEM careers. CBE—Life Sciences Education, 17(1), ar9.

    Article  Google Scholar 

  • Feurzeig, W., Papert, S. A., & Lawler, B. (2011). Programming-languages as a conceptual framework for teaching mathematics. Interactive Learning Environments, 19(5), 487–501.

    Article  Google Scholar 

  • Field, A. (2013). Discovering statistics (4th ed.). SAGE Publications: Sage.

  • Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.

    Article  Google Scholar 

  • Goodenow, C. (1993). The psychological sense of school membership among adolescents: Scale development and educational correlates. Psychology in the Schools, 30(1), 79–90.

    Article  Google Scholar 

  • Grover, S., & Pea, R. D. (2013). Computational thinking in K-12: A review of the state of the field. Educational Researcher, 42(1), 38–43.

    Article  Google Scholar 

  • Grunspan, D. Z., Wiggins, B. L., & Goodreau, S. M. (2014). Understanding classrooms through social network analysis: A primer for social network analysis in education research. CBE—Life Sciences Education, 13(2), 167–178.

    Article  Google Scholar 

  • Hatch, J. A. (2002). Doing qualitative research in education settings. New York: State University of New York Press.

  • Heath, S., Fuller, A., & Johnston, B. (2009). Chasing shadows: Defining network boundaries in qualitative social network analysis. Qualitative Research, 9(5), 645–661.

    Article  Google Scholar 

  • Ito, M., Gutierrez, K. D., Livingstone, S., Penuel, W. R., Rhodes, J. E., Salen, K., et al. (2013). Connected learning: An agenda for research and design, research, and practice. Irvine: Digital Media and Learning Research Hub.

  • Johnson, A., & Elliott, S. (2020). Culturally relevant pedagogy: A model to guide cultural transformation in STEM departments. Journal of Microbiology & Biology Education, 21(1), 1–12.

    Article  Google Scholar 

  • Kafai, Y. B., & Burke, Q. (2013). Computer programming goes back to school. Phi Delta Kappan, 95(1), 61–65.

    Article  Google Scholar 

  • Kafai, Y., Desai, S., Peppler, K. A., Chiu, G. M., & Moya, J. (2008). Mentoring partnership in a community technology Centre: A constructionist approach for fostering equitable service learning. Mentoring & Tutoring: Partnership in Learning, 16(2), 191–205.

    Article  Google Scholar 

  • Kafai, Y., Searle, K., Martinez, C., Brayboy, B. (2014). Ethnocomputing with electronic textiles: Culturally responsive open design to broaden participation in computing in American Indian youth and communities. In Proceedings of the 45th ACM technical symposium on Computer science education (pp. 241–246). ACM.

  • Koh, K., Abbas, J., Willett, R. (2019). Makerspaces in libraries: Social roles and community engagement. In V.R. Lee and A.L. Phillips (Eds), Reconceptualizing libraries: Perspectives form the Information and Learning sciences (pp. 17–36). Taylor & Francis.

  • Kraemer, E. T., Sitaraman, M., Che, S. M. (2019). How can we engage in inclusive, culturally responsive computer science?. In Proceedings of the 50th New York: ACM Technical Symposium on Computer Science Education (pp. 1251–1251). ACM. https://doi.org/10.1145/3287324.3293743.

  • Lachney, M., & Yadav, A. (2020). Computing and community in formal education. Communications of the ACM, 63(3), 18–21.

    Article  Google Scholar 

  • Lachney, M., Babbitt, W., Bennett, A., & Eglash, R. (2019). Generative computing: African-American cosmetology as a link between computing education and community wealth. Interactive Learning Environments. https://doi.org/10.1080/10494820.2019.1636087.

    Article  Google Scholar 

  • Ladson-Billings, G. (1995). But that’s just good teaching! The case for culturally relevant pedagogy. Theory Into Practice, 34(3), 159–165.

    Article  Google Scholar 

  • Lee, V.R. (2019). Libraries will be essential to the smart and connected communities of the future. In V.R. Lee and A.L. Phillips (Eds), Reconceptualizing libraries: Perspectives form the Information and Learning sciences (pp. 9–16). Taylor & Francis.

  • Lee, V.R., & Phillips, A.L. (2019). Introduction. In V.R. Lee and A.L. Phillips (Eds), Reconceptualizing libraries: Perspectives form the Information and Learning sciences (pp. 1–6). Taylor & Francis.

  • Lee, I., Martin, F., Denner, J., Coulter, B., Allan, W., Erickson, J., et al. (2011). Computational thinking for youth in practice. ACM Inroads, 2(1), 32–37.

    Article  Google Scholar 

  • Lee, V. R., Tzou, C., Bang, M., Bell, P., Stromholt, S., Price, N., et al. (2017). Libraries as emerging spaces for computer-supported collaborative learning in schools and communities. In B. K. Smith, M. Borge, K. Y. Lim, & E. Mercier (Eds.), Making a difference: Prioritizing equity and access in CSCL, 12th Internnational Conferencce on Computer Supported Collaborative Learning (CSCL), Volume 2. Philadelphia: ISLS.

  • Lewis, C., Shah, N., Falkner, K. (2019). Equity and diversity. In S. Fincher and A. V Robins (Eds), The Cambridge handbook of computing education research (pp. 481–510). Cambridge University Press.

  • Maestas, R., Vaquera, G. S., & Zehr, L. M. (2007). Factors impacting sense of belonging at a Hispanic-serving institution. Journal of Hispanic Higher Education, 6(3), 237–256.

    Article  Google Scholar 

  • Margolis, J., Estrella, R., Goode, J., Holme, J. J., & Nao, K. (2017). Stuck in the shallow end: Education, race, and computing. Cambridge MA: MIT Press.

    Google Scholar 

  • Martin, C. (2019). Designing for STEM in libraries serving underserved communities. In V.R. Lee and A.L. Phillips (Eds), Reconceptualizing libraries: Perspectives form the Information and Learning sciences (pp. 123–139). Taylor & Francis.

  • Martınez, A., Dimitriadis, Y., Rubia, B., Gómez, E., & De La Fuente, P. (2003). Combining qualitative evaluation and social network analysis for the study of classroom social interactions. Computers & Education, 41(4), 353–368.

    Article  Google Scholar 

  • Mejias, M., Jean-Pierre, K., Burge, L., Washington, G. (2018). Culturally relevant CS pedagogy theory & practice. In 2018 Research on Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT) (pp. 1–5). IEEE.

  • Moreno-León, J., Robles, G., & Román-González, M. (2015). Dr. scratch: Automatic analysis of scratch projects to assess and foster computational thinking. RED. Revista de Educación a Distancia, 46, 1–23.

    Google Scholar 

  • Mouza, C., Marzocchi, A., Pan, Y. C., & Pollock, L. (2016). Development, implementation, and outcomes of an equitable computer science after-school program: Findings from middle-school students. Journal of Research on Technology in Education, 48(2), 84–104.

    Article  Google Scholar 

  • Mouza, C., Yadav, A., & Leftwich, A. (2018). Developing computationally literate teachers: Current perspectives and future directions for teacher preparation in computing education. Journal of Technology and Teacher Education, 26(3), 333–352.

    Google Scholar 

  • Mouza, C., Pan, Y. C., Yang, H., & Pollock, L. (2020). A multiyear investigation of student computational thinking concepts, practices, and perspectives in an after-school computing program. Journal of Educational Computing Research, 58(5), 1029–1056.

    Article  Google Scholar 

  • Museus, S., Palmer, R., Davis, R., & Maramba, D. (2011). Special issue: Racial and ethnic minority students’ success in STEM. ASHE Higher Education Report, 36(6), 1–140.

    Article  Google Scholar 

  • Nakajima, T. M., & Goode, J. (2020). Lighting up learning: Teachers' pedagogical approaches for mak (e) ing computing culturally responsive in electronic-textiles classrooms. Computing in Science & Engineering, 22(5), 41–50.

    Article  Google Scholar 

  • Nieminen, J. (1974). On the centrality in a graph. Scandinavian Journal of Psychology, 15(1), 332–336.

    Article  Google Scholar 

  • Nieto, S. (2002). Language, culture, and teaching: Critical perspectives for a new century. Mahwah: Erlbaum.

  • Pan, Y., Yang, H., Mouza, C., Pollock, L. (2019). Employing a think-aloud approach to assess young learners’ computational thinking. In Annual Meeting of the American Educational Research Association.

  • Papert, S. (1980). Mindstorms. New York: Basic Books.

  • Penuel, W. R., Sussex, W., Korbak, C., & Hoadley, C. (2006). Investigating the potential of using social network analysis in educational evaluation. American Journal of Evaluation, 27(4), 437–451.

    Article  Google Scholar 

  • Penuel, W.R., Chang-Order, J., Michalchik, V. (2019). Using research-practice partnerships to support interest-related learning in libraries. In V.R. Lee and A.L. Phillips (Eds), Reconceptualizing libraries: Perspectives form the Information and Learning sciences (pp. 239–256). Taylor & Francis.

  • Peter, L., Christie, E., Cochran, M., Dunn, D., Elk, L., Fields, E., et al. (2003). Assessing the impact of total immersion on Cherokee language revitalization: A culturally responsive, participatory approach. In J. Reyhner, O. Trujillo, R. L. Carrasco, & L. Lockard (Eds.), Nurturing native languages (pp. 7–23). Flagstaff: Northern Arizona University.

  • Pollock, M. (2008). From shallow to deep: Toward a thorough cultural analysis of school achievement patterns. Anthropology & Education Quarterly, 39(4), 369–380.

    Article  Google Scholar 

  • Pollock, L., Mouza, C., Atlas, J., Harvey, T. (2015). Field experience in teaching computer science: Course organization and reflections. Proceedings of Special Interest Group in Computer Science Education, march 4–7, Kansas City, MO.

  • Rienties, B., Héliot, Y., & Jindal-Snape, D. (2013). Understanding social learning relations of international students in a large classroom using social network analysis. Higher Education, 66(4), 489–504.

    Article  Google Scholar 

  • Rogowski, A., Recker, M., Lee, V. R. (2018). Designing online support guides for librarians managing STEM maker activities. International Journal on Innovations in Online Education, 2(4).

  • Roque, R. & Jain, R. (2018). Becoming Facilitators of Creative Computing in Out-of-School Settings. In Kay, J. and Luckin, R. (Eds.) Rethinking Learning in the Digital Age: Making the Learning Sciences Count. Proceedings of International Conference of the Learning Sciences (ICLS) 2018, volume 1. London: International Society of the Learning Sciences.

  • Ryoo, J. J. (2019). Pedagogy that supports computer science for all. ACM Transactions on Computing Education, 19(4) article 36, 23.

    Article  Google Scholar 

  • Saldaña, J. (2015). The coding manual for qualitative researchers. Sage.

  • Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158.

    Article  Google Scholar 

  • Sullivan, F. R., Hamilton, C. E., & Foley, A. (2012). Scratch: An entrée into computational literacy and learning in young adolescents. Roundtable presentation at the annual meeting of the American Educational Research Association. Canada: Vancouver.

    Google Scholar 

  • Tzou, C., Bell, P., Bang, M., Kuver, R., Twito, A., & Braun, A. (2019). Building expansive family STEAM programming through participatory design research. In V.R. Lee and A.L. Phillips (Eds), Reconceptualizing libraries: Perspectives form the Information and Learning sciences (pp. 56–77). Taylor & Francis.

  • Veilleux, N., Bates, R., Jones, D., Allendoerfer, C., Crawford, J. (2012). The role of belonging in engagement, retention and persistence in computer science. In Proceedings of the 43rd ACM technical symposium on Computer Science Education (pp. 707–707). ACM.

  • Veilleux, N., Bates, R., Allendoerfer, C., Jones, D., Crawford, J., Floyd Smith, T. (2013). The relationship between belonging and ability in computer science. In Proceeding of the 44th ACM technical symposium on Computer science education (pp. 65-70). ACM.

  • Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge: Harvard University Press.

    Google Scholar 

  • Wing, J.M. (2006). Computational thinking. Communications of the ACM.

  • Yadav, A., Krist, C., Good, J., & Caeli, E. N. (2018). Computational thinking in elementary classrooms: Measuring teacher understanding of computational ideas for teaching science. Computer Science Education, 28(4), 371–400.

    Article  Google Scholar 

  • Yang, H., Mouza, C., & Pollock, L. (2019). Establishing equitable computing programs in informal spaces: Program design, implementation and outcomes. CoolThink@ JC, 197.

Download references

Acknowledgements

We acknowledge Dr. Florence Sullivan of the University of Massachusetts, Amherst for providing us with the Bee Maze Scratch project and accompanied interview guide. This work is supported by the National Science Foundation (Awards # 1639649 and # 1649224). All opinions are the authors and do not necessarily represent those of the funding agency.

Author information

Authors and Affiliations

  1. Cornell University, 211 Gates Hall, 107 Hoy Road, Ithaca, NY, 14853, USA

    Hui Yang

  2. University of Delaware, 116 Willard Hall, Newark, DE, 19716, USA

    Diane Codding

  3. University of Delaware, 113 Willard Hall, Newark, DE, 19716, USA

    Chrystalla Mouza

  4. University of Delaware, 436 Smith Hall, Newark, DE, 19716, USA

    Lori Pollock

Authors
  1. Hui Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Diane Codding
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chrystalla Mouza
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lori Pollock
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hui Yang.

Ethics declarations

All procedures performed in this study were conducted in accordance with the ethical standards of the institutional review board (IRB) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The methodology and research instruments for this study were approved by the IRB at the University of Delaware.

Conflict of Interest

Research reported in this article was supported by National Science Foundation under award numbers 1,649,224 and 1,639,649 to Lori Pollock (PI) and Chrystalla Mouza (co-PI).

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, H., Codding, D., Mouza, C. et al. Broadening Participation in Computing: Promoting Affective and Cognitive Learning in Informal Spaces. TechTrends 65, 196–212 (2021). https://doi.org/10.1007/s11528-020-00562-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11528-020-00562-9

Keywords

Search

Navigation