Abstract
Computer programming tools for young children are being created and used in early childhood classrooms more than ever. However, little is known about the relationship between a teacher’s unique instructional style and their students’ ability to explore and retain programming content. In this mixed-methods study, quantitative and qualitative data were collected from N = 6 teachers and N = 222 Kindergarten through second grade students at six schools across the United States. These teachers and students participated in an investigation of the relationship between teaching styles and student learning outcomes. All participants engaged in a minimum of two lessons and a maximum of seven lessons using the ScratchJr programming environment to introduce coding. Teachers reported on their classroom structure, lesson plan, teaching style and comfort with technology. They also administered ScratchJr Solve It assessments to capture various aspects of students’ programming comprehension, which were analyzed for trends in learning outcomes. Results from this descriptive, exploratory study show that all students were successful in attaining foundational ScratchJr programming comprehension. Statistically significant findings revealed higher programming achievement in students whose educators demonstrated flexibility in lesson planning, responsiveness to student needs, technological content expertise, and concern for developing students’ independent thinking. Implications for research in the development of computational thinking strategies are discussed, as well as suggestions for successfully implementing early childhood classroom interventions with ScratchJr.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Baddeley, A. (1992). Working memory. Science, 255(5044), 556–559. doi:10.1126/science.1736359.
Bebell, D., Russell, M., & O’Dwyer, L. (2004). Measuring teachers’ technology uses: Why multiple-measures are more revealing. Journal of Research on Technology in Education, 37(1), 45–63.
Bers, M. (2008). Blocks to robots: Learning with technology in the early childhood classroom. New York, NY: Teachers College Press.
Bers, M. U. (2012). Designing digital experiences for positive youth development: From playpen to playground. Oxford: Cary, NC.
Bers, M. & Kazakoff, E. (2012). Chapter 26. Developmental technologies: Technology and human development. In R. M.Lerner, M. A. Easterbrooks, J. Mistry, & I. B. Weiner (Eds.), Handbook of psychology, developmental psychology. Thousand Oaks, CA.
Bers, M. U., Seddighin, S., & Sullivan, A. (2013). Ready for robotics: Bringing together the T and E of STEM in early childhood teacher education. Journal of Technology and Teacher Education, 21(3), 355–377.
Blazer, C. (2008). Literature review: Educational technology. Research services, Miami-Dade County Public Schools. Miami-Dade: Research Services Office of Assessment, Research, and Data Analysis Miami-Dade County Public Schools.
Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. In Proceedings from AERA ‘12: The 2012 annual meeting of the American Educational Research Association, Vancouver, Canada.
Chen, C. (2008). Why do teachers not practice what they believe regarding technology integration? The Journal of Educational Research, 102(1), 65–75. doi:10.3200/JOER.102.1.65-75.
Chikofsky, E., & Cross, J. (1990). Reverse engineering and design recovery: A taxonomy. IEEE Software, 7(1), 13–17.
Clements, D. H., & Gullo, D. F. (1984). Effects of computer programming on young children’s cognition. Journal of Educational Psychology, 76(6), 1051–1058. doi:10.1037/0022-0663.76.6.1051.
Cuban, L., Kirkpatrick, H., & Peck, C. (2001). High access and low use of technologies in high school classrooms: Explaining an apparent paradox. American Educational Research Journal, 38(4), 813–834. doi:10.3102/00028312038004813.
Cuny, J., Snyder, L., & Wing, J. M. (2010). Demystifying computational thinking for noncomputer scientists. Unpublished manuscript in progress, referenced in http://www.cs.cmu.edu/~CompThink/resources/TheLinkWing.pdf.
Edwards, C., Gandini, L., & Forman, G. (Eds.). (1993). The hundred languages of children. Norwood, NJ: Ablex.
Fessakis, G., Gouli, E., & Mavroudi, E. (2013). Problem solving by 5–6 years old kindergarten children in a computer programming environment: A case study. Computers & Education, 63, 87–97.
Flannery, L. P., Kazakoff, E. R., Bontá, P., Silverman, B., Bers, M. U., & Resnick, M. (2013). Designing ScratchJr: Support for early childhood learning through computer programming. In Proceedings of the 12th international conference on interaction design and children (IDC ‘13) (pp. 1–10). New York, NY: ACM. doi: 10.1145/2485760.2485785.
Ford, J. H., & Il, J. R. (2015). Teaching and learning styles in quality improvement: Identification and impact on process outcomes. Addiction Science & Clinical Practice, 10(Suppl 1), A12.
Ginsburg, H. P. (1997). Entering the child’s mind: the clinical interview in psychological research and practice. New York: Cambridge University Press.
Grasha, A. F. (1994). A matter of style: The teacher as expert, formal authority, personal model, facilitator, and delegator. College Teaching, 42(4), 142–149.
Grasha, A. F., & Riechmann-Hruska, S. (1996). Teaching style survey. Retrieved from http://longleaf.net/teachingstyle.html.
Grasha, A. F., & Yangarber-Hicks, N. (2000). Integrating teaching styles and learning styles with instructional technology. College Teaching, 48(1), 2–10. doi:10.1080/87567550009596080.
Hew, K. F., & Brush, T. (2007). Integrating technology into K-12 teaching and learning: Current knowledge gaps and recommendations for future research. Educational Technology Research and Development, 55(3), 223–252. doi:10.1007/s11423-006-9022-5.
Hofer, M., Chamberlin, B., & Scot, T. (2004). Fulfilling the need for a technology integration specialist. The Journal, 32(3), 34.
Howard, S. K. (2013). Risk-aversion: Understanding teachers’ resistance to technology integration. Technology, Pedagogy and Education, 22(3), 357–372. doi:10.1080/1475939X.2013.802995.
Jeon, L., Buettner, C. K., & Hur, E. (2014). Examining pre-school classroom quality in a state-wide quality rating and improvement system. Child & Youth Care Forum, 43(4), 469–487.
Kazakoff, E., Sullivan, A., & Bers, M. U. (2013). The effect of a classroom-based intensive robotics and programming workshop on sequencing ability in early childhood. Early Childhood Education Journal, 41(4), 245–255. doi:10.1007/s10643-012-0554-5.
Keengwe, J., & Onchwari, G. (2011). Fostering meaningful student learning through constructivist pedagogy and technology integration. International Journal of Information and Communication Technology Education, 7(4), 1–10.
Koschmann, T. (1996). CSCL, theory and practice of an emerging paradigm. Mahwah, NJ: L. Erlbaum Associates.
Kunter, M., Baumert, J., & Koller, O. (2007). Effective classroom management and the development of subject-related interest. Learning and Instruction, 17(5), 494–509.
Lee, M. S. C. (2015). Teaching Tools, Teachers' Rules: ScratchJr in the Classroom. (Unpublished master's thesis). Medford, MA: Tufts University.
Limongelli, C., Lombardi, M., Marani, A., & Sciarrone, F. (2013). A teacher model to speed up the process of building courses. In Human-computer interaction. applications and services (pp. 434–443). Berlin: Springer.
Lin, P. C., Lu, H. K., & Liu, C. H. I. A. (2013). Towards an education behavioral intention model for e-learning systems: An extension of UTAUT. Journal of Theoretical and Applied Information Technology, 47(3), 1120–1127.
Mashburn, A. J., Pianta, R. C., Hamre, B. K., Downer, J. T., Barbarin, O. A., Bryant, D., et al. (2008). Measures of classroom quality in prekindergarten and children’s development of academic, language, and social skills. Child Development, 79(3), 732–749. doi:10.1111/j.1467-8624.2008.01154.x.
Nachshon, I. (1985). Directional preferences in perception of visual stimuli. International Journal of Neuroscience, 25(3–4), 161–174.
National Assessment of Educational Progress. (2014). Technology and engineering literacy framework for the 2014 NAEP. National Assessment Governing Board.
Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. New York: Basic Books.
Papert, S. (2000). What’s the big idea? Toward a pedagogy of idea power. IBM Systems Journal, 39(3/4), 720.
Petrina, S. (1998). The politics of research in technology education: A critical content and discourse analysis of the Journal of Technology Education, 10(1–8). doi:10.21061/jte.v10i1.a.3.
Portelance, D. J., & Bers, M. U. (2015). Code and tell: Assessing young children’s learning of computational thinking using peer video interviews with ScratchJr. In Proceedings of IDC ‘15: The 14th international conference on interaction design and children. Boston, MA: ACM.
Pretz, K. (November 21, 2014). Computer science classes for kids becoming mandatory. The institute. http://theinstitute.ieee.org/career-and-education/preuniversity-education/computer-science-classes-for-kids-becoming-mandatory.
Resnick, M., Maloney, J., Monroy-Hernandez, A., Rusk, N., Eastmond, E., Brennan, K., et al. (2009). Scratch: Programming for all. Communications of the ACM, 52(11), 60–67. doi:10.1145/1592761.1592779.
Resnick, M., & Silverman, B. (2005). Some reflections on designing construction kits for kids. In Proceedings of IDC ‘05: The 4th international conference on interaction design and children. New York, NY: ACM.
Rimm-Kaufman, S., Curby, T. W., Grimm, K. J., Nathanson, L., & Brock, L. L. (2009). The contribution of children’s self-regulation and classroom quality to children’s adaptive behaviors in the kindergarten classroom. Developmental Psychology, 45(4), 958–972. doi:10.1037/a0015861.
Ringstaff, C., & Kelly, L. (2002). The learning return on our educational technology investment: A review of findings from research. San Francisco, CA: WestEd RTEC.
Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Technological pedagogical content knowledge (TPCK): The development and validation of an assessment instrument for preservice teachers. Journal of Research on Technology in Education, 42(2), 27.
Strawhacker, A. L., & Bers, M. U. (2015). “I want my robot to look for food”: Comparing children’s programming comprehension using tangible, graphical, and hybrid user interfaces. International Journal of Technology and Design Education, 25(3), 293–319.
Strawhacker, A., Lee, M., Caine, C., & Bers, M. U. (2015). ScratchJr Demo: A coding language for Kindergarten. In Proceedings of the 14th international conference on interaction design and children (IDC ‘15). Boston, MA: ACM.
Sullivan, A., & Bers, M. U. (2016). Robotics in the early childhood classroom: Learning outcomes from an 8-week robotics curriculum in pre-kindergarten through second grade. International Journal of Technology and Design Education, 26(1), 3–20.
Technology for All Americans Project, & International Technology Education Association. (2000). Standards for technological literacy: Content for the study of technology. International Technology Education Association.
US Census Bureau. (2015, September 24). State & county QuickFacts. http://quickfacts.census.gov/qfd/states/00000.html.
US Department of Education. (2010, November 1). Transforming American education: Learning powered by technology. https://www.ed.gov/sites/default/files/netp2010.pdf.
US Department of Education. (2013, June). Private elementary and secondary enrollment, number of schools, and average tuition, by school level, orientation, and tuition: Selected years, 1999–2000 through 2011–2012. https://nces.ed.gov/programs/digest/d13/tables/dt13_205.50.asp.
US Department of Education, National Center for Education Statistics (2015a). 2013–2014 Private school universe survey [Data File]. https://catalog.data.gov/dataset/201314-private-school-universe-survey.
US Department of Education, National Center for Education Statistics. (2015b). Common core of data [Data File]. https://nces.ed.gov/ccd/ccddata.asp.
Vygotsky, L. S. (1978). Interaction between learning and development (M. LopezMorillas, Trans.). In M. Cole, V. John-Steiner, S. Scribner, & E. Souberman (Eds.), Mind in society: The development of higher psychological processes (pp. 79–91). Cambridge, MA: Harvard University Press.
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. https://www.cs.cmu.edu/~15110-s13/Wing06-ct.pdf.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Strawhacker, A., Lee, M. & Bers, M.U. Teaching tools, teachers’ rules: exploring the impact of teaching styles on young children’s programming knowledge in ScratchJr. Int J Technol Des Educ 28, 347–376 (2018). https://doi.org/10.1007/s10798-017-9400-9
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10798-017-9400-9