Abelson, H., & DiSessa, A. (1981). Turtle geometry: The computer as a medium for exploring mathematics (The mit press series in artificial intelligence). Cambridge, MA: MIT Press.
Google Scholar
Alexander, R. J. (2008). Towards dialogic teaching: Rethinking classroom talk. Cambridge: Dialogos.
Google Scholar
Allamanis, M., Barr, E. T., Devanbu, P., & Sutton, C. (2018). A survey of machine learning for big code and naturalness. ACM Computing Surveys (CSUR),
51(4), 81.
Article
Google Scholar
Barrouillet, P., & Lecas, J. (1999). Mental models in conditional reasoning and working memory. Thinking & Reasoning,
5(4), 289–302.
Article
Google Scholar
Bers, M. (2008). Blocks to robots: Learning with technology in the early childhood classroom. New York, NY: Teachers College Press.
Google Scholar
Bers, M. (2012). Designing Digital experiences for positive youth development: from playpen to playground. Oxford: Oxford University Press.
Book
Google Scholar
Bers, M. (2018a). Coding as a playground: Computational thinking and programming in early childhood. London, UK: Routledge.
Google Scholar
Bers, M. U. (2018b). Coding, playgrounds and literacy in early childhood education: The development of KIBO Robotics and ScratchJr. In 2018 IEEE Global Engineering Education Conference (EDUCON), 2100.
Bers, M. (2019). Coding as another language: Why computer science in early childhood should not be stem. In Key Issues in Technology and Early Childhood (Editor Chip Donohue). NY: Routledge.
Bers, M., & Resnick, M. (2015). The official ScratchJr Book: Help your kids learn to code. San Francisco, CA: No Starch Press.
Google Scholar
Bialystok, E. (1991). Letters, sounds, and symbols: Changes in children’s understands of written language. Applied Psycholinguistics.,
12, 75–89.
Article
Google Scholar
Bredekamp, S. (1987). Developmentally appropriate practice in early childhood pro- grams serving children from birth through age 8. Washington, DC: National Association for the Education of Young Children.
Google Scholar
Carnine, D. W., Silbert, J., Kame’enui, E., Tarver, S., & Jungjohann, K. (2006). Teaching struggling and at-risk readers: A direct instruction approach. Upper Saddle River, NJ: Pearson.
Google Scholar
Chall, J. S. (1983). Stages of reading development. New York: McGraw-Hill.
Google Scholar
Clarke, S., Resnick, L. B., & Rosé, C. P. (2015). Dialogic instruction: A new frontier (3rd ed., pp. 378–389). New York: Handbook of Educational Psychology.
Google Scholar
Clements, D. H. (2007). Curriculum research: Toward a framework for research-basedCu rricula. Journal for Research in Mathematics Education,
38(1), 35–70.
Google Scholar
Clements, D. H., & Sarama, J. (2004). Learning trajectories in mathematics education. Mathematical Thinking and Learning,
6, 81–89.
Article
Google Scholar
Code.org. (2018). 2018 annual report. Seattle, WA. Retrieved from https://code.org/files/annual-report-2018.pdf.
Code.org. (2019). https://code.org/.
Cunha, F., & Heckman, J. (2007). The technology of skill formation. American Economic Review,
97(2), 31–47.
Article
Google Scholar
Dalbey, J., & Linn, M. C. (1985). The demands and requirements of computer programming: A literature review. Journal of Educational Computing Research,
1(3), 253–274.
Article
Google Scholar
Dehaene, S. (2010). Reading in the Brain: The new science of how we read. New York: Penguin Books.
Google Scholar
de Strulle, A., & Shen, C. (n.d.). STEM + Computing K-12 Education (STEM + C). National Science Foundation. Retrieved from https://wwwnsf.gov/funding/pgm_summ.jsp?pims_id=505006.
Duke, N., & Pearson, P. D. (2002). Effective practices for developing reading comprehension. In A. Farstrup & S. Samuels (Eds.), What research has to say about readinginstruction (3rd ed., pp. 205–242). Newark, DE: International Reading Association.
Google Scholar
Elkin, M., Sullivan, A., & Bers, M. U. (2016). Programming with the KIBO robotics kit in preschool classrooms. Computers in the Schools,
33(3), 169–186. https://doi.org/10.1080/07380569.2016.1216251.
Article
Google Scholar
Fayer, S., Lacey, A., & Watson, A. (2017). BLS spotlight on statistics: STEM occupations-past, present, and future. Washington, DC: U.S. Department of Labor, Bureau of Labor Statistics.
Google Scholar
Fedorenko, E., Ivanova, A., Dhamala, R., & Bers, M. U. (In press). The language of programming: A cognitive perspective. Trends in Cognitive Development.
Ferreiro, E., & Teberosky, A. (1982). Literacy before schooling. Exeter, NH: Heinemann.
Google Scholar
Floyd, B., Santander, T., & Weimer, W. (2017). Decoding the representation of code in the brain: An fMRI study of code review and expertise. In Proceedings of the 39th International Conference on Software Engineering (pp. 175–186). IEEE Press.
Fox, B., & Saracho, O. (1990). Emergent writing: Young children solving the written language puzzle. Early Child Development and Care.,
56, 81–90.
Article
Google Scholar
Gadanidis, G. (2017). Five affordances of computational thinking to support elementary mathematics education. Journal of Computers in Mathematics and Science Teaching,
36(2), 143–151.
Google Scholar
Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher,
42(1), 38–43. https://doi.org/10.3102/0013189X12463051.
Article
Google Scholar
Guzdial, M. (2008). Education: Paving the way for computational thinking. Communications of the ACM,
51(8), 25–27. https://doi.org/10.1145/1378704.1378713.
Article
Google Scholar
Guzdial, M., & Morrison, B. (2016). Seeking to making computing education as available as mathematics or science education. Communications of the ACM,
59(11), 31–33.
Article
Google Scholar
Heckman, J., & Masterov, D. (2007). The productivity argument for investing in young children. Review of Agricultural Economics,
29(3), 446–493.
Article
Google Scholar
Hubwieser, P., Armoni, M., Giannakos, M. N., & Mittermeir, R. T. (2014). Perspectives and visions of computer science education in primary and secondary (K-12) schools. ACM Transactions on Computing Education,
14(2), 7.
Article
Google Scholar
Janveau-Brennan, G., & Markovits, H. (1999). The development of reasoning with causal conditionals. Developmental Psychology,
35(4), 904–911.
Article
Google Scholar
Jenkins, T. (2002). On the difficulty of learning to program. In Proceedings of the 3rd Annual. Conference of the LTSN Centre for Information and Computer Sciences (pp. 53–58). Leeds, UK. Retrieved from http://www.psy.gla.ac.uk/~steve/localed/jenkins.html.
K-12 Computer Science Framework Steering Committee. (2016). K–12 computer science framework. Retrieved from https://k12cs.org.
Kafai, Y. B., & Resnick, M. (1996). Constructionism in practice: Designing, thinking, and learning in a digital world. Mahwah, NJ: Erlbaum.
Google Scholar
Littleton, K., & Howe, C. (2010). Educational dialogues: understanding and promoting productive interaction. London: Routledge.
Google Scholar
Lockwood, J., & Mooney, A. (2018). Computational thinking in education: Where does it fit? A systematic literary review. International Journal of Computer Science Education in Schools,
2(1), 41–60. https://doi.org/10.21585/ijcses.v2i1.26.
Article
Google Scholar
Lonigan, C. J., Schatschneider, C., & Westberg, L. (2008). Developing early literacy: Report of the National Early Literacy Panel. Washington, DC: National Institute for Literacy. Identification of children’s skills and abilities linked to later outcomes in reading, writing, and spelling (pp. 55–106).
Madill, H., Campbell, R. G., Cullen, D. M., Armour, M. A., Einsiedel, A. A., Ciccocioppo, A. L., et al. (2007). Developing career commitment in STEM-related fields: Myth versus reality. In R. J. Burke, M. C. Mattis, & E. Elgar (Eds.), Women and minorities in science, technology, engineering and mathematics: Upping the numbers (pp. 210–244). Northhampton, MA: Edward Elgar Publishing.
Google Scholar
Markert, L. R. (1996). Gender related to success in science and technology. The Journal of Technology Studies,
22(2), 21–29.
Article
Google Scholar
National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common Core State Standards. National Governors Association Center for Best Practices, Council of Chief State School Officers, Washington, DC.
National Research Council. (2011). Report of a workshop of pedagogical aspects of computational thinking. Washington, DC: National Academy Press.
Google Scholar
National Research Council. (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. Committee on a Conceptual framework for new K-12 science education standards. Board on Science Education, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.
National Research Council Committee on Early Childhood Pedagogy, Bowman, B., Donovan, S., & Burns, M. (2001). Eager to learn: Educating our preschoolers. Washington, DC: National Academy Press.
Google Scholar
Norman, K. L. (2017). Cyberpsychology: An introduction to human-computer interaction. Cambridge: Cambridge University Press.
Book
Google Scholar
Ong, W. J. (1982). Orality and literacy: The technologizing of the word. London: Methuen.
Book
Google Scholar
Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. New York: Basic Books Inc.
Google Scholar
Papert S. (1987). Computer criticism vs. technocentric thinking Educational Researcher (Vol. 16, No. I) January/February 1987.
Pea, R. D., & Kurland, D. M. (1984). On the cognitive effects of learning computer programming. New Ideas in Psychology,
2, 137–168.
Article
Google Scholar
Pearson, P. D. (2004). The reading wars. Educational policy,
18(1), 216–252.
Article
Google Scholar
Pei, C., Weintrop, D., & Wilensky, U. (2018). Cultivating computational thinking practices and mathematical habits of mind in lattice land. Mathematical Thinking and Learning,
20(1), 75–89. https://doi.org/10.1080/10986065.2018.1403543.
Article
Google Scholar
Perlis, A. J. (1962). The computer in the university. In M. Greenberger (Ed.), Computers and the world of the future (pp. 180–219). Cambridge, MA: MIT Press.
Google Scholar
Piaget, J. (1952). The origins of intelligence in children (Vol. 8, p. 18). New York: International Universities Press.
Book
Google Scholar
Puranik, C., & Lonigan, C. (2011). From scribbles to scrabble: Preschool children’s developing knowledge of written language. Reading and Writing,
24(5), 567–589.
Article
Google Scholar
Resnick, M. (2017). Lifelong kindergarten: Cultivating creativity through projects, passion, peers, and play. Cambridge: MIT Press.
Book
Google Scholar
Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., et al. (2009). Scratch: programming for all. Communications of the ACM,
52(11), 60–67.
Article
Google Scholar
Resnick, L. B., Michaels, S., & O’Connor, C. (2010). How (well-structured) talk builds the mind. In D. Preiss & R. Sternberg (Eds.), Innovations in educational psychology: Perspectives on learning, teaching and human development (pp. 163–194). New York: Springer.
Google Scholar
Resnick, M., & Siegel, D. (2015). A different approach to coding. International Journal of People-Oriented Programming,
4(1), 1–4.
Google Scholar
Ryan, M. (2011). The encyclopedia of literary and cultural theory. Hoboken, NJ: Wiley-Blackwell.
Google Scholar
Shanahan, T., Callison, K., Carriere, C., Duke, N., Pearson, D., Schatschneider, C., & Torgesen, J. (2010). Improving reading comprehension in kindergarten through 3rd grade: ies practice guide. NCEE 2010-4038. What Works Clearinghouse.
Shonkoff, J., Phillips, D., & National Research Council (U.S.). Committee on Integrating the Science of Early Childhood Development. (2000). From neurons to neighborhoods: The science of early child development. Washington, DC: National Academy Press.
Siegmund, J., Kästner, C., Apel, S., Parnin, C., Bethmann, A., Leich, T., & Brechmann, A. (2014). Understanding source code with functional magnetic resonance imaging. In Proceedings of the 36th International Conference on Software Engineering (pp. 378–389). ACM.
STEM Education Act of 2015, House of Representatives 1020, 114th Congress. (2015). Retrieved from https://www.congress.gov/bill/114th-congress/house-bill/1020.
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.
Article
Google Scholar
Sulzby, E. (1989). Assessment of writing and of children’s language while writing. In L. Morrow & J. Smith (Eds.), The role of assessment and measurement in early literacy instruction (pp. 83–109). Prentice-Hal: Englewood Cliffs, NJ.
Google Scholar
Sulzby, E., & Teale, W. (1991). Emergent literacy. In R. Barr, M. Kamil, P. Mosenthal, & P. D. Pearson (Eds.), Handbook of reading research (Vol. 2, pp. 727–758). New York: Longman.
Google Scholar
Tolchinsky, L. (2003). The cradle of culture and what children know about writing and numbers before being taught. Mahwah, NJ: Lawrence Erlbaum Associates.
Book
Google Scholar
Vee, A. (2013). Understanding computer programming as a literacy. Literacy in Composition Studies,
1(2), 42–64. https://doi.org/10.21623/1.1.2.4.
Article
Google Scholar
Vizner, M. Z. (2017). Big robots for little kids: Investigating the role of sale in early childhood robotics kits (Master’s thesis). Available from ProQuest Dissertations and Theses database. (UMI No. 10622097).
Vygotsky, L. S. (1978). Mind in society: The Development of higher psychological processes. Cambridge, MA: Harvard University Press.
Google Scholar
Whitehurst, G., & Lonigan, C. (2001). Emergent literacy: Development from prereaders to readers. In S. B. Neuman & D. K. Dickensen (Eds.), Handbook of early literacy research (pp. 11–29). New York: Guilford Press.
Google Scholar
Wilson, C., Sudol, L. A., Stephenson, C., & Stehlik, M. (2010). Running on empty: The failure to teach K-12 computer science in the digital age. New York, NY: The Association for Computing Machinery and the Computer Science Teachers Association.
Google Scholar
Wing, J. (2006a). Computational thinking. Communications of Advancing Computing Machinery,
49(3), 33–36. https://doi.org/10.1145/1118178.1118215.
Article
Google Scholar
Wing, J. M. (2006b). Computational thinking. Communications of the ACM,
49(3), 33–35.
Article
Google Scholar
Wing, J. (2011). Research notebook: Computational thinking—What and why? The link magazine, Spring. Carnegie Mellon University, Pittsburgh. Retrieved from https://www.cs.cmu.edu/link/research-notebookcomputational-thinking-what-and-why.
Wittgenstein, Ludwig. (1997). Philosophical Investigations. Trans. G.E.M. Anscombe (2nd ed.). Cambridge: Blackwell. Print.
Google Scholar
Wolf, M., & Stoodley, C. J. (2007). Proust and the squid: The story and science of the reading brain (1st ed.). New York, NY: HarperCollins.
Google Scholar