Abstract
In response to the need to broaden participation in computer science, we designed a summer camp to teach middle-school-aged youth to code apps with MIT App Inventor. For the past four summers, we have observed significant gains in youth's interest and self-efficacy in computer science, after attending our camps. The majority of these youth, however, were youth from our local community. To provide equal access across the state and secure more diversity, we were interested in examining the effect of the camp on a broader population of youth. Thus, we partnered with an outreach program to reach and test our camps on youth from low-income high-poverty areas in the Intermountain West. During the summer of 2019, we conducted two sets of camps: locally advertised app camps that attracted youth from our local community and a second set of camps as part of a larger outreach program for youth from low-income high-poverty areas. The camps for both populations followed the same design of personnel, camp activities, structure, and curriculum. However, the background of the participants was slightly different. Using survey data, we found that the local sample experienced significant gains in both self-efficacy and interest, while the outreach group only reported significant gains in self-efficacy after attending the camp. However, the qualitative data collected from the outreach participants indicated that they had a positive experience both with the camp and their mentors. In this article, we discuss the camp design and findings in relation to strategies for broadening participation in Computer Science education.
- Mohammed Al-Bow, Debra Austin, Jeffrey Edgington, Rafael Fajardo, Joshua Fishburn, Carlos Lara, Scott Leutenegger, and Susan Meyer. 2009. Using game creation for teaching computer programming to high school students and teachers. ACM SIGCSE Bull. 41, 3 (2009), 104--108.Google ScholarDigital Library
- Amnah Alshahrani, Isla Ross, and Murray I. Wood. 2018. Using social cognitive career theory to understand why students choose to study computer science. In Proceedings of the ACM Conference on International Computing Education Research (ICER’18). Association for Computing Machinery, New York, NY, 205--214. DOI:https://doi.org/10.1145/3230977.3230994Google Scholar
- Chulakorn Aritajati, Mary Beth Rosson, Joslenne Pena, Dana Cinque, and Ana Segura. 2015. A socio-cognitive analysis of summer camp outcomes and experiences. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education. ACM, 581--586.Google ScholarDigital Library
- Catherine Ashcraft, Elizabeth Eger, and Michelle Friend. 2012. Girls in iT: The facts. National Center for Women 8 IT. Boulder, CO. Retrieved from http://www.bgwomeninict.org/language/en/uploads/files/documents__0/documents__4f2236edd9c4aefc792678bbb3c58e63.pdf.Google Scholar
- Flávio S. Azevedo. 2013. The tailored practice of hobbies and its implication for the design of interest-driven learning environments. J. Learn. Sci. 22, 3 (2013), 462--510. DOI:https://doi.org/10.1080/10508406.2012.730082Google ScholarCross Ref
- Lecia J. Baker, Eric Snow, Kathy Garvin-Doxas, and Tim Weston. 2006. Recruiting middle school girls into IT: Data on girls’ perceptions and experiences from a mixed-demographic group. In Women and Information Technology: Research on Underrepresentation., J. McGrath Cohoon and William Aspray (Eds.). MIT Press, Cambridge, MA.Google Scholar
- Yael M. Bamberger. 2014. Encouraging girls into science and technology with feminine role model: Does this work? J. Sci. Educ. Technol. 23, 4 (2014), 549--561. DOI:https://doi.org/10.1007/s10956-014-9487-7Google ScholarCross Ref
- Albert Bandura. 1977. Self-efficacy: Toward a unifying theory of behavioral change. Psychol. Rev. 84, 2 (1977), 191.Google ScholarCross Ref
- Albert Bandura. 1986. Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice Hall, Englewood Cliffs, NJ.Google Scholar
- Albert Bandura. 1997. Self-efficacy: The Exercise of Control. Macmillan, New York, NY. Retrieved from https://doi.org/10.1007/SpringerReference_223312.Google Scholar
- Sylvia Beyer. 2008. Gender differences and intra-gender differences amongst management information systems students. J. Info. Syst. Edu. 19, 3 (2008), 301.Google Scholar
- Sylvia Beyer. 2014. Why are women underrepresented in Computer Science? Gender differences in stereotypes, self-efficacy, values, and interests and predictors of future CS course-taking and grades. Comput. Sci. Edu. 24, 2–3 (2014), 153--192. DOI:https://doi.org/10.1080/08993408.2014.963363Google ScholarCross Ref
- Sylvia Beyer and Susan Haller. 2006. Gender differences and intragender differences in computer science students: Are female cs majors more similar to male cs majors or female nonmajors? JWM 12, 4 (2006). DOI:https://doi.org/10.1615/JWomenMinorScienEng.v12.i4.50Google Scholar
- Sylvia Beyer, Kristina Rynes, Julie Perrault, Kelly Hay, and Susan Haller. 2003. Gender differences in computer science students. In Proceedings of the 34th Technical Symposium on Computer Science Education (SIGCSE’03). ACM, Reno, NV, 49--53. DOI:https://doi.org/10.1145/611892.611930Google ScholarDigital Library
- Jennifer M. Blaney and Jane G. Stout. 2017. Examining the relationship between introductory computing course experiences, self-efficacy, and belonging among first-generation college women. In Proceedings of the ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE’17). Association for Computing Machinery, New York, NY, 69--74. DOI:https://doi.org/10.1145/3017680.3017751Google Scholar
- Jennifer Burg, V. Paúl Pauca, William Turkett, Errin Fulp, Samuel S. Cho, Peter Santago, Daniel Cañas, and H. Donald Gage. 2015. Engaging non-traditional students in computer science through socially-inspired learning and sustained mentoring. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education (SIGCSE’15). ACM, New York, NY, 639--644. DOI:https://doi.org/10.1145/2676723.2677266Google Scholar
- Jody Clarke-Midura, Victor R. Lee, Jessica F. Shumway, and Megan M. Hamilton. 2019. The building blocks of coding: A comparison of early childhood coding toys. Info. Learn. Sci. (2019). DOI:https://doi.org/10.1108/ILS-06-2019-0059Google Scholar
- Jody Clarke-Midura, Frederick J. Poole, Katarina Pantic, Chongning Sun, and Vicki Allan. 2018. How mother and father support affect youths’ interest in computer science. In Proceedings of the 2018 ACM Conference on International Computing Education Research (ICER’18). ACM, New York, NY, 215--222. DOI:https://doi.org/10.1145/3230977.3231003Google ScholarDigital Library
- Jody Clarke-Midura, Frederick Poole, Katarina Pantic, Megan Hamilton, Chongning Sun, and Vicki Allan. 2018. How near peer mentoring affects middle school mentees. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE’18). ACM, New York, NY, 664--669. DOI:https://doi.org/10.1145/3159450.3159525Google ScholarDigital Library
- Jody Clarke-Midura, Chongning Sun, Megan Marie Hamilton, Katarina Pantic, Frederick Poole, and Vicki Allan. 2018. Near-peer mentoring as a way to foster self-efficacy in informal computer science environments. In Roundtable, Toronto, Canada.Google Scholar
- Jody Clarke-Midura, Chongning Sun, Katarina Pantic, Frederick Poole, and Vicki Allan. 2019. Using informed design in informal computer science programs to increase youths’ interest, self-efficacy, and perceptions of parental support. ACM Trans. Comput. Educ. 19, 4 (2019), 37:1–37:24. DOI:https://doi.org/10.1145/3319445Google ScholarDigital Library
- College Board. 2018. AP Program Participation and Performance Data 2017. Retrieved from https://research.collegeboard.org/programs/ap/data/participation/ap-2017.Google Scholar
- Computing Research Association. 2016. Generation CS: Report on CS enrollment. CRA. Retrieved from https://cra.org/data/generation-cs/.Google Scholar
- Edward L. Deci, Haleh Eghrari, Brian C. Patrick, and Dean R. Leone. 1994. Facilitating Internalization: The self-determination theory perspective. J. Personal. 62, 1 (1994), 119--142. DOI:https://doi.org/10.1111/j.1467-6494.1994.tb00797.xGoogle ScholarCross Ref
- Jennifer Dempsey, Richard T. Snodgrass, Isabel Kishi, and Allison Titcomb. 2015. The emerging role of self-perception in student intentions. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education (SIGCSE’15). Association for Computing Machinery, New York, NY, 108--113. DOI:https://doi.org/10.1145/2676723.2677305Google ScholarDigital Library
- Jill Denner, Linda Werner, L. O'Connor, and J. Glassman. 2014. Community college men and women: A test of three widely held beliefs about who pursues computer science. Commun. Coll. Rev. 42, (2014), 342--362. DOI:https://doi.org/10.1177/0091552114535624Google Scholar
- Anita DeWitt, Julia Fay, Madeleine Goldman, Eleanor Nicolson, Linda Oyolu, Lukas Resch, Jovan Martinez Saldaña, Soulideth Sounalath, Tyler Williams, and Kathryn Yetter. 2017. Arts coding for social good: A pilot project for middle-school outreach. In Proceedings of the ACM SIGCSE Technical Symposium on Computer Science Education. ACM, 159--164.Google ScholarDigital Library
- Daryl D'Souza, Margaret Hamilton, James Harland, Peter Muir, Charles Thevathayan, and Cecily Walker. 2008. Transforming learning of programming: A mentoring project. In Proceedings of the 10th Conference on Australasian Computing Education—Volume 78 (ACE’08). Australian Computer Society, Inc., Darlinghurst, Australia, Australia, 75--84. Retrieved from http://dl.acm.org/citation.cfm?id=1379249.1379256.Google ScholarDigital Library
- Wendy DuBow and L. James-Hawkins. 2016. What influences female interest and persistence in computing?: Preliminary findings from a multiyear study. Comput. Sci. Engineer. 18, 2 (2016), 58--67. DOI:https://doi.org/10.1109/MCSE.2016.20Google ScholarDigital Library
- Jacquelynne S. Eccles and Allan Wigfield. 1995. In the mind of the actor: The structure of adolescents’ achievement task values and expectancy-related beliefs. Pers. Soc. Psychol. Bull. 21, 3 (1995), 215--225. DOI:https://doi.org/10.1177/0146167295213003Google ScholarCross Ref
- Elizabeth Fennema and Julia A. Sherman. 1976. Fennema-sherman mathematics attitudes scales: Instruments designed to measure attitudes toward the learning of mathematics by females and males. J. Res. Math. Edu. 7, 5 (1976), 324--326.Google ScholarCross Ref
- Deborah Fields, Lisa Quirke, Tori Horton, Jason Maughan, Xavier Velasquez, Janell Amely, and Katarina Pantic. 2016. Working toward equity in a constructionist scratch camp lessons learned in applying a studio design model. Bangkok, Thailand.Google Scholar
- Allan Fisher, Jane Margolis, and Faye Miller. 1997. Undergraduate women in computer science: Experience, motivation and culture. In ACM SIGCSE Bulletin. ACM, 106--110. DOI:https://doi.org/10.1145/268085.268127Google Scholar
- Michelle Friend. 2015. Middle school girls’ envisioned future in computing. Comput. Sci. Edu. 25, 2 (2015), 152--173. DOI:https://doi.org/10.1080/08993408.2015.1033128Google ScholarCross Ref
- Gerald C. Gannod, Janet E. Burge, Victoria McIe, Maureen Doyle, and Karen C. Davis. 2014. Increasing awareness of computer science in high school girls. In Proceedings of the IEEE Frontiers in Education Conference (FIE’14). 1--8. DOI:https://doi.org/10.1109/FIE.2014.7044456Google Scholar
- T. St Georgiev. 2019. Students’ viewpoint about using MIT app inventor in education. In Proceedings of the 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO’19). 611--616. DOI:https://doi.org/10.23919/MIPRO.2019.8756671Google ScholarCross Ref
- Sandy Graham and Celine Latulipe. 2003. CS girls rock: Sparking interest in computer science and debunking the stereotypes. In ACM SIGCSE Bulletin. ACM, 322--326.Google Scholar
- Kenneth E. Graves and Leigh Ann DeLyser. 2017. Interested in class, but not in the hallway: A latent class analysis (LCA) of CS4All student surveys. In Proceedings of the ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE’17). Association for Computing Machinery, New York, NY, 243--248. DOI:https://doi.org/10.1145/3017680.3017722Google Scholar
- Shuchi Grover and Roy Pea. 2013. Computational thinking in K–12: A review of the state of the field. Education. Res. 42, 1 (2013), 38--43. DOI:https://doi.org/10.3102/0013189X12463051Google ScholarCross Ref
- Denise Gürer and Tracy Camp. 2002. An ACM-W literature review on women in computing. SIGCSE Bull. 34, 2 (2002), 121--127. DOI:https://doi.org/10.1145/543812.543844Google ScholarDigital Library
- Denise Gürer and Tracy Camp. 2003. Investigating the incredible shrinking pipeline for women in computer science. Retrieved from /paper/Investigating-the-Incredible-Shrinking-Pipeline-for-Denise-Camp/548a891c28203afc0c92092443f81daadd2219f1.Google Scholar
- Cathy Hall, Jeremy Dickerson, David Batts, Paul Kauffmann, and Michael Bosse. 2011. Are we missing opportunities to encourage interest in STEM fields? J. Technol. Edu. 23, 1 (2011).Google Scholar
- Judith M. Harackiewicz, Kenneth E. Barron, John M. Tauer, Suzanne M. Carter, and Andrew J. Elliot. 2000. Short-term and long-term consequences of achievement goals: Predicting interest and performance over time. J. Edu. Psychol. 92, 2 (2000), 316--330. DOI:https://doi.org/10.1037/0022-0663.92.2.316Google ScholarCross Ref
- Judith M. Harackiewicz, Christopher S. Rozek, Chris S. Hulleman, and Janet S. Hyde. 2012. Helping parents to motivate adolescents in mathematics and science: An experimental test of a utility-value intervention. Psychol. Sci. 23, 8 (2012), 899--906. DOI:https://doi.org/10.1177/0956797611435530Google ScholarCross Ref
- Judith M. Harackiewicz, Jessi L. Smith, and Stacy J. Priniski. 2016. Interest matters: The importance of promoting interest in education. Retrieved from https://journals.sagepub.com/doi/full/10.1177/2372732216655542.Google Scholar
- Suzanne Hidi and K. Ann Renninger. 2006. The four-phase model of interest development. Education. Psychol. 41, 2 (2006), 111--127. DOI:https://doi.org/10.1207/s15326985ep4102_4Google ScholarCross Ref
- John L. Holland. 1973. Making Vocational Choices: A Theory of Careers. Engelwood Cliffs.Google Scholar
- John L. Holland. 1997. Making Vocational Choices: A Theory of Vocational Personalities and Work Environments, 3rd ed. Psychological Assessment Resources, Odessa, FL.Google Scholar
- Vincent Hoogerheide, Sofie M. M. Loyens, and Tamara van Gog. 2016. Learning from video modeling examples: Does gender matter? Instr. Sci. 44, 1 (2016), 69--86. DOI:https://doi.org/10.1007/s11251-015-9360-yGoogle ScholarCross Ref
- Caitlin Hulsey, Toni B. Pence, and Larry F. Hodges. 2014. Camp CyberGirls: Using a virtual world to introduce computing concepts to middle school girls. In Proceedings of the 45th ACM Technical Symposium on Computer Science Education. ACM, 331--336.Google Scholar
- Susan Jamieson. 2004. Likert scales: how to (ab) use them. Med. Edu. 38, 12 (2004), 1217--1218.Google ScholarCross Ref
- Yasmin Kafai, Jean Griffin, Quinn Burke, Michelle Slattery, Deborah Fields, Rita Powell, Michele Grab, Susan Davidson, and Joseph Sun. 2013. A cascading mentoring pedagogy in a CS service-learning course to broaden participation and perceptions. In Proceeding of the 44th ACM Technical Symposium on Computer Science Education (SIGCSE’13). ACM, Denver, Colorado, 101--106. DOI:https://doi.org/10.1145/2445196.2445228Google ScholarDigital Library
- Shereen Khoja, Camille Wainwright, Juliet Brosing, and Jeffrey Barlow. 2012. Changing girls’ attitudes towards computer science. J. Comput. Sci. Coll. 28, 1 (2012), 210--216.Google ScholarDigital Library
- Päivi Kinnunen and Beth Simon. 2011. CS majors’ self-efficacy perceptions in CS1: results in light of social cognitive theory. In Proceedings of the 7th International Workshop on Computing Education Research (ICER’11). Association for Computing Machinery, New York, NY, 19--26. DOI:https://doi.org/10.1145/2016911.2016917Google ScholarDigital Library
- Antti-Jussi Lakanen and Tommi Kärkkäinen. 2019. Identifying pathways to computer science: The long-term impact of short-term game programming outreach interventions. ACM Trans. Comput. Educ. 19, 3 (2019), 20:1–20:30. DOI:https://doi.org/10.1145/3283070Google ScholarDigital Library
- Kathleen J. Lehman, Linda J. Sax, and Hilary B. Zimmerman. 2016. Women planning to major in computer science: Who are they and what makes them unique? Comput. Sci. Edu. 26, 4 (2016), 277--298. DOI:https://doi.org/10.1080/08993408.2016.1271536Google ScholarCross Ref
- Robert W. Lent, Steven D. Brown, and Gail Hackett. 1994. Toward a unifying social cognitive theory of career and academic interest, choice, and performance. J. Vocation. Behav. 45, 1 (1994), 79--122. DOI:https://doi.org/10.1006/jvbe.1994.1027Google ScholarCross Ref
- Robert W. Lent, Antonio M. Lopez, Frederick G. Lopez, and Hung-Bin Sheu. 2008. Social cognitive career theory and the prediction of interests and choice goals in the computing disciplines. J. Vocation. Behav. 73, 1 (2008), 52--62. DOI:https://doi.org/10.1016/j.jvb.2008.01.002Google ScholarCross Ref
- Guan-Yu Lin. 2016. Self-efficacy beliefs and their sources in undergraduate computing disciplines: An examination of gender and persistence. J. Education. Comput. Res. 53, 4 (2016), 540--561. DOI:https://doi.org/10.1177/0735633115608440Google ScholarCross Ref
- Hilary M. Lips and Linda Temple. 1990. Majoring in computer science: Causal models for women and men. Res. High Edu. 31, 1 (1990), 99--113. DOI:https://doi.org/10.1007/BF00992559Google ScholarCross Ref
- Alex Lishinski and Joshua Rosenberg. 2020. Accruing interest: What experiences contribute to students developing a sustained interest in computer science over time? In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (SIGCSE’20). Association for Computing Machinery, New York, NY, 1414. DOI:https://doi.org/10.1145/3328778.3372568Google ScholarDigital Library
- Penelope Lockwood. 2006. “Someone like me can be successful”: Do college students need same-gender role models? Psychol. Women Quart. 30, 1 (2006), 36--46. DOI:https://doi.org/10.1111/j.1471-6402.2006.00260.xGoogle ScholarCross Ref
- Andy Luse, Julie A. Rursch, and Doug Jacobson. 2014. Utilizing structural equation modeling and social cognitive career theory to identify factors in choice of IT as a major. Trans. Comput. Edu. 14, 3 (2014), 19:1–19:19. DOI:https://doi.org/10.1145/2623198Google Scholar
- Pruthikrai Mahatanankoon. 2018. Exploring the antecedents to computer programming self-efficacy. In Proceedings of the 10th International Conference on Advances in Information Technology (IAIT’18). Association for Computing Machinery, New York, NY, 1--6. DOI:https://doi.org/10.1145/3291280.3291791Google ScholarDigital Library
- David M. Marx and Jasmin S. Roman. 2002. Female role models: Protecting women's math test performance. Pers. Soc. Psychol. Bull. 28, 9 (2002), 1183--1193. DOI:https://doi.org/10.1177/01461672022812004Google ScholarCross Ref
- Allison Master, Sapna Cheryan, and Andrew N. Meltzoff. 2016. Computing whether she belongs: Stereotypes undermine girls’ interest and sense of belonging in computer science. J. Education. Psychol. 108, 3 (2016), 424--437. DOI:https://doi.org/10.1037/edu0000061Google ScholarCross Ref
- Microsoft. 2018. Closing the STEM Gap: Why STEM Classes and Careers Still Lack Girls and What We Can Do About It. Retrieved from https://youthrex.com/report/closing-the-stem-gap-why-stem-classes-and-careers-still-lack-girls-and-what-we-can-do-about-it/.Google Scholar
- Iwona Miliszewska, Gayle Barker, Fiona Henderson, and Ewa Sztendur. 2006. The issue of gender equity in computer science – what students say. J. Info. Technol. Edu.: Res. 5, 1 (2006), 107--120.Google ScholarCross Ref
- Ralph Morelli, Nina Limardo, Trishan de Lanerolle, and Elizabeth Tamotsu. 2011. Can Android app inventor bring computational thinking to K-12? Retrieved from https://www.researchgate.net/publication/228442759_Can_Android_App_Inventor_Bring_Computational_Thinking_to_K-12.Google Scholar
- Engineering National Academies of Sciences. 2017. Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments. DOI:https://doi.org/10.17226/24926Google Scholar
- National Science Foundation. 2017. Women, minorities, and persons with disabilities in science and engineering. Retrieved from https://www.nsf.gov/statistics/2017/nsf17310/.Google Scholar
- National Science Foundation. 2018. CISE - Broadening Participation in Computing (BPC) | NSF - National Science Foundation. Retrieved from https://www.nsf.gov/cise/bpc/.Google Scholar
- Lijun Ni, Farzeen Harunani, and Fred Martin. 2017. Empowering middle school students to create data-based social apps. J. Comput. Sci. Colleges 32, 6 (2017), 88--100.Google ScholarDigital Library
- Lijun Ni, Mark Sherman, Diane Schilder, and Fred Martin. 2016. Computing with a community focus: An app inventor summer camp for middle school students. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education. ACM, 690--690.Google ScholarDigital Library
- Katarina Pantic, Deborah A. Fields, and Lisa Quirke. 2016. Studying situated learning in a constructionist programming camp: A multimethod microgenetic analysis of one girl's learning pathway. In Proceedings of the The 15th International Conference on Interaction Design and Children (IDC’16). ACM, New York, NY, 428--439. DOI:https://doi.org/10.1145/2930674.2930725Google ScholarDigital Library
- Stamatios Papadakis and Vasileios Orfanakis. 2018. Comparing novice programing environments for use in secondary education: App inventor for android vs. Alice. Int. J. Technol. Enhanced Learn. 10, 1/2 (2018), 44. DOI:https://doi.org/10.1504/IJTEL.2018.10008587Google ScholarCross Ref
- Michael Quinn Patton. 2002. Designing qualitative studies. Qualitat. Res. Eval. Methods 3, (2002), 230--246.Google Scholar
- Markeya S. Peteranetz, Shiyuan Wang, Duane F. Shell, Abraham E. Flanigan, and Leen-Kiat Soh. 2018. Examining the impact of computational creativity exercises on college computer science students’ learning, achievement, self-efficacy, and creativity. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE’18). Association for Computing Machinery, New York, NY, 155--160. DOI:https://doi.org/10.1145/3159450.3159459Google ScholarDigital Library
- Nichole Pinkard, Sheena Erete, Caitlin K. Martin, and Maxine McKinney de Royston. 2017. Digital youth divas: Exploring narrative-driven curriculum to spark middle school girls’ interest in computational activities. J. Learn. Sci. 26, 3 (2017), 477--516. DOI:https://doi.org/10.1080/10508406.2017.1307199Google ScholarCross Ref
- Lori Pollock, Kathleen McCoy, Sandra Carberry, Namratha Hundigopal, and Xiaoxin You. 2004. Increasing high school girls’ self confidence and awareness of CS through a positive summer experience. In ACM SIGCSE Bulletin. ACM, 185--189.Google Scholar
- Vennila Ramalingam, Deborah LaBelle, and Susan Wiedenbeck. 2004. Self-efficacy and mental models in learning to program. In Proceedings of the 9th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (ITiCSE’04). Association for Computing Machinery, New York, NY, 171--175. DOI:https://doi.org/10.1145/1007996.1008042Google ScholarDigital Library
- K. Ann. Renninger and Suzanne Hidi. 2011. Revisiting the conceptualization, measurement, and generation of interest. Education. Psychol. 46, 3 (2011), 168--184. DOI:https://doi.org/10.1080/00461520.2011.587723Google ScholarCross Ref
- Jean E. Rhodes, Ranjini Reddy, Jean B. Grossman, and Judy Maxine Lee. 2002. Volunteer mentoring relationships with minority youth: An analysis of same- versus cross-race matches1. J. Appl. Soc. Psychol. 32, 10 (2002), 2114--2133. DOI:https://doi.org/10.1111/j.1559-1816.2002.tb02066.xGoogle ScholarCross Ref
- Ricarose Roque, Yasmin Kafai, and Deborah Fields. 2012. From tools to communities: Designs to support online creative collaboration in scratch. In Proceedings of the Conference on Interaction Design and Children (IDC’12). ACM, New York, NY, 220--223. DOI:https://doi.org/10.1145/2307096.2307130Google ScholarDigital Library
- Mary Beth Rosson, John M. Carroll, and Hansa Sinha. 2011. Orientation of undergraduates toward careers in the computer and information sciences: Gender, self-efficacy and social support. Trans. Comput. Edu. 11, 3 (2011), 14:1–14:23. DOI:https://doi.org/10.1145/2037276.2037278Google Scholar
- Krishnendu Roy. 2012. App inventor for android: report from a summer camp. In Proceedings of the 43rd ACM Technical Symposium on Computer Science Education. ACM, 283--288.Google ScholarDigital Library
- Miguel Angel Rubio, Rocio Romero-Zaliz, Carolina Mañoso, and Angel P. de Madrid. 2015. Closing the gender gap in an introductory programming course. Comput. Edu. 82, (2015), 409--420. DOI:https://doi.org/10.1016/j.compedu.2014.12.003Google Scholar
- Richard M. Ryan. 1982. Control and information in the intrapersonal sphere: An extension of cognitive evaluation theory. J. Personal. Soc. Psychol. 43, 3 (1982), 450--461. DOI:http://dx.doi.org/10.1037/0022-3514.43.3.450Google ScholarCross Ref
- Richard M. Ryan and Edward L. Deci. 2000. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Amer. Psychol. 55, 1 (2000), 68--78. DOI:https://doi.org/10.1037/0003-066X.55.1.68Google ScholarCross Ref
- Mihaela Sabin, Rosabel Deloge, Adrienne Smith, and Wendy DuBow. 2017. Summer learning experience for girls in grades 7–9 boosts confidence and interest in computing careers. J. Comput. Sci. Colleges 32, 6 (2017), 79--87.Google ScholarDigital Library
- Philip M. Sadler, Gerhard Sonnert, Zahra Hazari, and Robert Tai. 2012. Stability and volatility of STEM career interest in high school: A gender study. Sci. Edu. 96, 3 (2012), 411--427.Google Scholar
- Milagros Sáinz and Jacquelynne Eccles. 2012. Self-concept of computer and math ability: Gender implications across time and within ICT studies. J. Vocation. Behav. 80, 2 (2012), 486--499. DOI:https://doi.org/10.1016/j.jvb.2011.08.005Google ScholarCross Ref
- Johnny Saldaña. 2015. The Coding Manual for Qualitative Researchers. SAGE.Google Scholar
- Linda J. Sax, Kathleen J. Lehman, Jerry A. Jacobs, M. Allison Kanny, Gloria Lim, Laura Monje-Paulson, and Hilary B. Zimmerman. 2017. Anatomy of an enduring gender gap: The evolution of women's participation in computer science. J. Higher Edu. 88, 2 (2017), 258--293. DOI:https://doi.org/10.1080/00221546.2016.1257306Google ScholarCross Ref
- Pasqueline Dantas Scaico, Ruy José G. B. de Queiroz, and José Jorge Lima Dias. 2017. Analyzing how interest in learning programming changes during a CS0 course: A qualitative study with brazilian undergraduates. In Proceedings of the ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE’17). Association for Computing Machinery, New York, NY, 16--21. DOI:https://doi.org/10.1145/3059009.3059015Google Scholar
- Kusum Singh, Katherine R. Allen, Rebecca Scheckler, and Lisa Darlington. 2007. Women in computer-related majors: A critical synthesis of research and theory from 1994 to 2005. Rev. Education. Res. 77, 4 (2007), 500--533.Google ScholarCross Ref
- Renée Spencer. 2007. “It's Not What I Expected”: A qualitative study of youth mentoring relationship failures. J. Adolesc. Res. 22, 4 (2007), 331--354. DOI:https://doi.org/10.1177/0743558407301915Google ScholarCross Ref
- Courtney Starrett, Marguerite Doman, Chlotia Garrison, and Merry Sleigh. 2015. Computational bead design: A pilot summer camp in computer aided design and 3D printing for middle school girls. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education. ACM, 587--590.Google ScholarDigital Library
- Chongning Sun and Jody Clarke-Midura. Testing the efficacy of a near-peer mentoring model for recruiting youth into computer science. In review.Google Scholar
- Edna Tan and Angela Calabrese Barton. 2018. Towards critical justice: Exploring intersectionality in community-based STEM-rich making with youth from non-dominant communities. Equity Excell. Edu. 51, 1 (2018), 48--61. DOI:https://doi.org/10.1080/10665684.2018.1439786Google ScholarCross Ref
- Cathy van Tuijl and Juliette H. Walma van der Molen. 2016. Study choice and career development in STEM fields: An overview and integration of the research. Int. J. Technol. Des. Edu. 26, 2 (2016), 159--183. DOI:https://doi.org/10.1007/s10798-015-9308-1Google ScholarCross Ref
- Timothy Urness and Eric D. Manley. 2013. Generating interest in computer science through middle-school android summer camps. J. Comput. Sci. Colleges 28, 5 (2013), 211--217.Google ScholarDigital Library
- Marie E. Vachovsky, Grace Wu, Sorathan Chaturapruek, Olga Russakovsky, Richard Sommer, and Li Fei-Fei. 2016. Toward more gender diversity in CS through an artificial intelligence summer program for high school girls. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education. ACM, 303--308.Google ScholarDigital Library
- Roli Varma. 2002. Women in information technology: A case study of undergraduate students in a minority-serving institution. Bull. Sci. Technol. Soc. 22, 4 (2002), 274--282. DOI:https://doi.org/10.1177/0270467602022004003Google ScholarCross Ref
- Tamar Vilner and Ela Zur. 2006. Once she makes it, she is there: Gender differences in computer science study. In Proceedings of the 11th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (ITICSE’06). ACM, New York, NY, 227--231. DOI:https://doi.org/10.1145/1140124.1140185Google ScholarDigital Library
- Anna Vitores and Adriana Gil-Juárez. 2016. The trouble with ‘women in computing’: A critical examination of the deployment of research on the gender gap in computer science. J. Gender Studies 25, 6 (2016), 666--680. DOI:https://doi.org/10.1080/09589236.2015.1087309Google ScholarCross Ref
- Jayce R. Warner, Carol L. Fletcher, and Lisa S. Garbrecht. 2019. Better data, better progress: Methods for measuring inequities in computer science education. In Proceedings of the American Educational Research Association (AERA’19).Google Scholar
- Heidi C. Webb and Mary Beth Rosson. 2011. Exploring careers while learning Alice 3D: A summer camp for middle school girls. In Proceedings of the 42nd ACM Technical Symposium on Computer Science Education. ACM, 377--382.Google Scholar
- Brenda Cantwell Wilson. 2002. A study of factors promoting success in computer science including gender differences. Comput. Sci. Edu. 12, 1–2 (2002), 141--164. DOI:https://doi.org/10.1076/csed.12.1.141.8211Google ScholarCross Ref
Index Terms
- Making Apps: An Approach to Recruiting Youth to Computer Science
Recommendations
Diversity Barriers in K-12 Computer Science Education: Structural and Social
SIGCSE '17: Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science EducationAs computer science (CS) education expands at the K-12 level, we must be careful to ensure that CS neither exacerbates existing equity gaps in education nor hinders efforts to diversify the field of CS. In this paper, we discuss structural and social ...
How Near Peer Mentoring Affects Middle School Mentees
SIGCSE '18: Proceedings of the 49th ACM Technical Symposium on Computer Science EducationIn response to the national demand to increase participation in CS, we argue that youth's interest in computer science (CS) can be sparked by providing them with role models who are relatable and who resonate with their identities. To that end, we ...
Landscape of K-12 Computer Science Education in the U.S.: Perceptions, Access, and Barriers
SIGCSE '16: Proceedings of the 47th ACM Technical Symposium on Computing Science EducationThrough surveys of 1,673 students, 1,685 parents, 1,013 teachers, 9,693 principals, and 1,865 superintendents across the United States, this study explores perceptions, access, and barriers to computer science education at the K-12 level. We found most ...
Comments