A collection of theoretical, review, and empirical articles that discuss the field of computational thinking education and the integration of computational thinking in disciplinary content, specifically, science.

Basu, S., McElhaney, K. W., Grover, S., Harris, C. J., & Biswas, G. (2018). A principled approach to designing assessments that integrate science and computational thinking. https://www.researchgate.net/profile/Satabdi_Basu/publication/327045211_A_principled_approach_to_designing_assessments_that_integrate_science_and_computational_thinking/links/5b74ca0a299bf14c6da8ad5 3/A-principled-approach-to-designing-assessments-that-integrate-science-and-computational-thinking.pdf

Basu, S. (2016). Fostering Synergistic Learning of Computational Thinking and Middle School Science in Computer-based Intelligent Learning Environments. (Unpublished Doctoral Dissertation). Vanderbilt University. Nashville, TN.

Burbaitė, R., Drąsutė, V., & Štuikys, V. (2018, 17-20 April 2018). Integration of computational thinking skills in STEM-driven computer science education. Paper presented at the 2018 IEEE Global Engineering Education Conference (EDUCON).Berland, M., & Wilensky, U. (2015). Comparing Virtual and Physical Robotics Environments for Supporting Complex Systems and Computational Thinking. Journal of Science Education and Technology, 24(5), 628– 647.

Cateté, V., Lytle, N., Dong, Y., Boulden, D., Akram, B., Houchins, J., … Boyer, K. (2018). Infusing Computational Thinking into Middle Grade Science Classrooms: Lessons Learned. In Proceedings of the 13th Workshop in Primary and Secondary Computing Education (pp. 21:1–21:6). New York, NY, USA: ACM. https://doi.org/10.1145/3265757.3265778

Grover, S. & Pea, R. (2013). Computational Thinking in K–12: A Review of the State of the Field. EDUCATIONAL RESEARCHER, 42, 38–43. https://doi.org/10.3102/0013189X12463051

Grover, S., & Pea, R. (2018). Computational Thinking: A competency whose time has come.Computer Science Education: Perspectives on Teaching and Learning in School, 19.

Guo, Y., Wagh, A., Brady, C., Levy, S. T., Horn, M. S., & Wilensky, U. (2016). Frogs to Think with: Improving Students’ Computational Thinking and Understanding of Evolution in A Code-First Learning Environment. In Proceedings of The 15th International Conference on Interaction Design and Children (pp. 246- 254). ACM.

Hambrusch, S., Hoffmann, C., Korb, J. T., Haugan, M., & Hosking, A. L. (2009). A multidisciplinary approach towards computational thinking for science majors. ACM SIGCSE Bulletin, 41(1), 183-187. 

Hasan, A., & Biswas, G. (2017). Domain specific modeling language design to support synergistic learning of STEM and computational thinking. Siu-cheung KONG The Education University of Hong Kong, Hong Kong, 28.

Haseski, H. I., Ilic, U., & Tugtekin, U. (2018). Defining a New 21st Century Skill-Computational Thinking: Concepts and Trends. International Education Studies, 11(4), 29-42.

Israel, M., Pearson, J. N., Tapia, T., Wherfel, Q. M., & Reese, G. (2015). Supporting all learners in school-wide computational thinking: A cross-case qualitative analysis. Computers and Education. https://doi.org/10.1016/j.compedu.2014.11.022

Jona, K., Wilensky, U., Trouille, L., Horn, M. S., Orton, K., Weintrop, D., & Beheshti, E. (2014). Embedding computational thinking in science, technology, engineering, and math (CT-STEM). In future directions in computer science education summit meeting, Orlando, FL.

Kalelioğlu, F., Gülbahar, Y., & Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing, 4(3), 583. 

Kalelioğlu, F. (2018). Characteristics of Studies Conducted on Computational Thinking: A Content Analysis Computational Thinking in the STEM Disciplines (pp. 11-29): Springer.

Kite, V., & Park, S. (2018). BOOM BUST BUILD. The Science Teacher, 85(3), 22-28.

Lin, C.-C., Zhang, M., Beck, B., & Olsen, G. (2009). Embedding computer science concepts in K-12 science curricula. In Proceedings of the 40th ACM technical symposium on Computer science education (pp. 539– 543). Chattanooga, TN, USA: ACM.

Lockwood, J., & Mooney, A. (2017). Computational Thinking in Education: Where does it fit? A systematic literary review. International Journal of Computer Science Education in Schools 2(1). DOI: 10.21585/ijcses.v2i1.26

Louca, L. T., & Zacharia, Z. C. (2008). The use of computer‐ based programming environments as computer modelling tools in early science education: The cases of textual and graphical program languages. International Journal of Science Education, 30(3), 287-323.

Navlakha, S., & Bar‐Joseph, Z. (2011). Algorithms in nature: the convergence of systems biology and computational thinking. Molecular systems biology, 7(1), 546.

Orton, K., Weintrop, D., Beheshti, E., Horn, M., Jona, K., & Wilensky, U. (2016). BringingComputational thinking into high school mathematics and science classrooms. ICLS 2016 Proceedings. Singapore: International Society of the Learning Sciences.

Peel, A., Fulton, J., & Pontelli, E. (2015). DISSECT: An experiment in infusing computational thinking in a sixth-grade classroom. Proceedings – Frontiers in Education Conference, FIE, 2014. doi:10.1109/FIE.2015.7344240

Peel, A., & Friedrichsen, P. (2018). Algorithms, abstractions, and iterations: Teaching computational thinking using protein synthesis translation. The American Biology Teacher, 80(1), 21-28.

Peel, A., Sadler, T. D., & Friedrichsen, P. (2019). Learning natural selection through computational thinking: Unplugged design of algorithmic explanations. Journal of Research in Science Teaching, 1-25. doi:10.1002/tea.21545

Qin, H. (2009). Teaching computational thinking through bioinformatics to biology students. Paper presented at the ACM SIGCSE Bulletin.

Rates, C. A., Mulvey, B. K., & Feldon, D. F. (2016). Promoting conceptual change for complex systems understanding: Outcomes of an agent-based participatory simulation. Journal of Science Education and Technology, 25(4), 610-627.

Repenning, A., Webb, D. C., Han Koh, K., Nickerson, H., Miller, S. B., Brand, C., Horses, I., Basawapatna, A., Gluck, F., Grover, R., Gutierrez, K., Repenning, N. (2015). Scalable Game Design: A Strategy to Bring Systemic Computer Science Education to Schools through Game Design and Simulation Creation. ACM Transactions on Computing Education, 15(11). doi:10.1145/2700517

Rich, K.M., Binkowski, T. A., Strickland, C., & Franklin, D. (2018a). Decomposition: A K-8 Computational Thinking Learning Trajectory. In Proceedings of the 2018 ACM Conference on International Computing Education Research (pp. 124–132). Espoo, Finland: ACM.

Sabitzer, B., & Pasterk, S. (2014). Cool Informatics: A New Approach to Computer Science and Cross-Curricular Learning. Paper presented at the Proceedings of the European Conference on Technology in the Classroom 2014, Brighton, United Kingdom.

Sengupta, P., Kinnebrew, J. S., Basu, S., Biswas, G., & Clark, D. (2013). Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework. Education and Information Technologies. doi:10.1007/s10639-012-9240-x

Sengupta, P., Dickes, A., & Farris, A. (2018). Toward a Phenomenology of Computational Thinking in STEM Education. arXiv preprint arXiv:1801.09258. 

Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158. https://doi.org/10.1016/j.edurev.2017.09.003

Sneider, C., Stephenson, C., Schafer, B., & Flick, L. (2014). Computational Thinking in High School Science Classrooms: Exploring the Science “Framework” and “NGSS”. Science Teacher, 81(5), 53-59. 

Sullivan, F. R. (2008). Robotics and science literacy: Thinking skills, science process skills and systems understanding. Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching, 45(3), 373–394.

Swanson, H., Anton, G., Bain, C., Horn, M., & Wilensky, U. (2017). Computational Thinking in the Science Classroom. Paper presented at the International Conference on Computational Thinking Education 2017.

Tatar D., Harrison S., Stewart M., Frisina C., & Musaeus P. (2017) Proto-computational Thinking: The Uncomfortable Underpinnings. In: Rich P., Hodges C. (eds) Emerging Research, Practice, and Policy on Computational Thinking. EducationalCommunications And Technology: Issues and Innovations. Springer, Cham

Taub, R., Armoni, M., Bagno, E., & Ben-Ari, M. (Moti). (2015). The effect of computer science on physics learning in a computational science environment. Computers & Education, 87, 10–23. https://doi.org/10.1016/j.compedu.2015.03.013

Verhoeff, R. P., Waarlo, A. J., & Boersma, K. T. (2008). Systems modelling and the development of coherent understanding of cell biology. International Journal of Science Education, 30(4), 543–568.

Voogt, J., Fisser, P., Good, J., Mishra, P., & Yadav, A. (2015). Computational thinking in compulsory education: Towards an agenda for research and practice. Education and Information Technologies. https://doi.org/10.1007/s10639-015-9412-6

Weintrop, D., Beheshti, E., Horn, M. S., Orton, K., Trouille, L., Jona, K., & Wilensky, U. (2014). Interactive assessment tools for computational thinking in High School STEM classrooms. Paper presented at the International Conference on Intelligent Technologies for Interactive Entertainment.

Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25(1), 127-147. doi:10.1007/s10956-015-9581-5

Wieman, C. E., Adams, W. K., & Perkins, K. K. (2008). PhET: Simulations that enhance learning. Science, 322(5902), 682–683.

Wilensky, U. (2001). Modeling nature’s emergent patterns with multi-agent languages. In Proceedings of EuroLogo (pp. 1–6). Citeseer.

Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep, or a firefly: Learning biology through constructing and testing computational theories—an embodied modeling approach. Cognition and Instruction, 24(2), 171–209.

Wilensky, U., Brady, C. E., & Horn, M. S. (2014). Fostering computational literacy in science classrooms. Communications of the ACM, 57(8), 24–28.

Wilkerson-Jerde, M., Wagh, A., & Wilensky, U. (2015). Balancing Curricular and Pedagogical Needs in Computational Construction Kits: Lessons From the DeltaTick Project. Science Education. https://doi.org/10.1002/sce.21157

Yadav, A., Hong, H., & Stephenson, C. (2016). Computational Thinking for All: Pedagogical Approaches to Embedding 21st Century Problem Solving in K-12 Classrooms.TechTrends. doi:10.1007/s11528-016-0087-7

Yang, D., Swasnon, S. R., Chittoori, B. B., & Baek, Y. (2018). Board 70: Work in Progress: Integrating Computational Thinking in STEM Education through a Project-based Learning Approach. Paper presented at the 2018 ASEE Annual Conference & Exposition.