Azhar MQ, Goldman R, Sklar E (2006) An agent-oriented behavior-based interface framework for educational robotics. In: Proceedings of the conference on autonomous agents and multiagent systems (AAMAS 2006)

Basawapatna A, Koh KH, Repenning A, Webb DC, Marshall KS (2011) Recognizing computational thinking patterns. In: Proceedings of the 42nd ACM technical symposium on computer science education. SIGCSE 2011, pp 245–250

Ben-Ari M (2001) Constructivism in computer science education. J Comput Math Sci Teach 20(1):45–73

Google ScholarBerland M (2008) VBOT: Motivating complex systems and computational literacies in virtual and physical robotics learning environments. Retrieved from ProQuest Digital Dissertations. AAT 3307005

Berland M, Wilensky U (2005) Complex play systems—results from a classroom implementation of VBOT. In: The annual meeting of the American Educational Research Association, Montreal, Canada, April 11–15, 2005

Berland M, Wilensky U (2008) VBOT (computer software)

Berland M, Martin T, Benton T, Petrick C (2011) Programming on the move: design lessons from IPRO. In: Proceedings of ACM SIG-CHI 2011, pp 2149–2154

Berland M, Martin T, Benton T, Smith CP, Davis D (2013) Using learning analytics to understand the learning pathways of novice programmers. J Learn Sci 22(4):564–599. doi:

10.1080/10508406.2013.836655
CrossRefGoogle ScholarBlikstein P, Wilensky U (2009) An atom is known by the company it keeps: a constructionist learning environment for materials science using agent-based modeling. Int J Comput Math Learn 14(2):81–119

CrossRefGoogle ScholarBoehm BW, Brown JR, Lipow M (1976) Quantitative evaluation of software quality. In: Proceedings of the 2nd international conference of software engineering, Los Alamitos, CA

Braitenberg V (1984) Vehicles: Experiments in synthetic psychology. MIT Press, Cambridge, MA

Google ScholarBundy A (2007) Computational thinking is pervasive. J Sci Pract Comput 1(2):67–69

Google ScholarChi M (2005) Commonsense conceptions of emergent processes: why some misconceptions are robust. J Learn Sci 14(2):161–199

CrossRefGoogle ScholarCobb P, Confrey J, diSessa A, Lehrer R (2003) Design experiments in educational research. Educ Res 32(1):9–13

CrossRefGoogle ScholarColella V (2000) Participatory simulations: building collaborative understanding through immersive dynamic modeling. J Learn Sci 9(4):471–500

CrossRefGoogle ScholarCollier N (2003) Repast: an extensible framework for agent simulation. The University of Chicago’s Social Science Research, p 36

Collins A, Joseph D, Bielaczyc K (2004) Design research: theoretical and methodological issues. J Learn Sci 13(1):15–42

CrossRefGoogle ScholarDavis B, Sumara D (2006) Complexity and education: inquiries into learning, teaching, and research. Lawrence Erlbaum, Mahwah, NJ

Google ScholardiSessa A (2001) Changing minds: computers, learning, and literacy. MIT Press, Cambridge, MA

Google ScholardiSessa A, Cobb P (2004) Ontological innovation and the role of theory in design experiments. J Learn Sci 13(1):77–103

CrossRefGoogle ScholarDruin A, Hendler JA (2000) Robots for kids: exploring new technologies for learning. Morgan Kaufmann, Burlington

Goldstone RL, Wilensky U (2008) Promoting transfer by grounding complex systems principles. J Learn Sci 17(4):465–516

CrossRefGoogle ScholarGrotzer TA, Basca BB (2003) How does grasping the underlying causal structures of ecosystems impact students’ understanding? J Biol Educ 38(1):16–29

CrossRefGoogle ScholarGuzdial M, Forte A (2005) Design process for a non-majors computing course. ACM SIGCSE Bulletin 37(1):361–365

CrossRefGoogle ScholarHancock C (2003) Real-time programming and the big ideas of computational literacy. Unpublished doctoral dissertation, MIT, Cambridge, MA

Harel I, Papert S (1990) Software design as a learning environment. Interact Learn Environ 1(1):1–32

CrossRefGoogle ScholarHmelo CE, Holton DL, Kolodner JL (2000) Designing to learn about complex systems. J Learn Sci 9(3):247–298

CrossRefGoogle ScholarHmelo-Silver C, Pfeffer MG (2004) Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions. Cogn Sci 28(1):127–138

CrossRefGoogle ScholarHolland JH (1995) Hidden order: how adaptation builds complexity. Basic Books

Holland J (1999) Emergence: from chaos to order. Basic Books, New York, NY

Google ScholarIoannidou A, Repenning A, Lewis C, Cherry G, Rader C (2003) Making constructionism work in the classroom. Int J Comput Math Learn 8(1):63–108

CrossRefGoogle ScholarIshii H (2008) Tangible bits: beyond pixels. In: Proceedings of the 2nd international ACM conference on tangible and embedded interaction, pp xv–xxv

Jacobson M, Wilensky U (2006) Complex systems in education: scientific and educational importance and implications for the learning sciences. J Learn Sci 15(1):11–34

CrossRefGoogle ScholarJohnson S (2002) Emergence: the connected lives of ants, brains, cities, and software. Scribner, New York, NY

Google ScholarKelleher C, Pausch R, Kiesler S (2007) Storytelling ALICE motivates middle school girls to learn computer programming. In: Proceedings of the SIGCHI conference on Human factors in computing systems, pp 1455–1464. San Jose, CA, April 28–May 3, 2007

Klopfer E, Colella V, Resnick M (2002) New paths on a StarLogo adventure. Comput Graph 26(4):615–622

CrossRefGoogle ScholarKlopfer E, Yoon S, Rivas L (2004) Comparative analysis of palm and wearable computers for participatory simulations. J Comput Assist Learn 20(5):347–359

CrossRefGoogle ScholarKlopfer E, Yoon S, Um T (2005) Young adventurers—modeling of complex dynamic systems with elementary and middle-school students. J Comput Math Sci Teach 24(2):157–178

Google ScholarLahtinen E, Ala-Mutka K, Järvinen HM (2005) A study of the difficulties of novice programmers. ACM SIGCSE Bull 37(3):14–18

CrossRefGoogle ScholarLevy ST, Wilensky U (2008) Inventing a “mid level” to make ends meet: reasoning between the levels of complexity. Cogn Instruct 26(1):1–47

CrossRefGoogle ScholarLuke S, Cioffi-Revilla C, Panait L, Sullivan K, Balan G (2005) MASON: a multiagent simulation environment. Simulation 81(7):517

CrossRefGoogle ScholarMaes P (1990) Designing autonomous agents: theory and practice from biology to engineering and back. MIT Press, Cambridge, MA

Google ScholarMartin FG (1996) Ideal and real systems: a study of notions of control in undergraduates who design robots. In: Kafai Y, Resnick M (eds) Constructionism in practice: rethinking the roles of technology in learning. MIT Press, Cambridge, MA

Google ScholarMartin T, Berland M, Benton T, Smith CP (2013) Learning programming with IPRO: the effects of a mobile, social programming environment. J Interact Learn Res 24(3):301–328

Google ScholarNational Research Council (2010) Report of a workshop on the scope and nature of computational thinking. National Academies Press, Washington, DC

Google ScholarPapert S (1975) Teaching children thinking. J Struct Lang 4:219–229

Google ScholarPapert S (1980) Mindstorms: children, computers, and powerful ideas. Basic Books, New York, NY

Google ScholarParker LE, Schultz A (eds) (2005) Multi-robot systems: from swarms to intelligent automata, vol III. Kluwer, Netherlands

Google ScholarPea RD (1987) Cognitive technologies for mathematics education. In: Schoenfeld A (ed) Cognitive science and mathematics education. Lawrence Erlbaum Associates Inc, Hillsdale, NJ, pp 89–122

Google ScholarPea RD, Kurland DM (1984) On the cognitive effects of learning computer programming. New Ideas Psychol 2(2):137–168

CrossRefGoogle ScholarPenner DE (2000) Explaining systems: investigating middle school students’ understanding of emergent phenomena. J Res Sci Teach 37(8):784–806

CrossRefGoogle ScholarPerkins DN, Grotzer TA (2005) Dimensions of causal understanding: the role of complex causal models in students’ understanding of science. Stud Sci Edu 41(1):117–166

CrossRefGoogle ScholarPortsmore M (2005) ROBOLAB: intuitive robotic programming software to support lifelong learning. Apple learning technology review. Spring/Summer, 2005

Resnick M (2003) Thinking like a tree (and other forms of ecological thinking). Int J Comput Math Learn 8(1):43–62

CrossRefGoogle ScholarResnick M, Ocko S, Papert S (1988) LEGO, logo, and design. Child Environ Q 5(4):14–18

Google ScholarResnick M, Wilensky U (1998) Diving into complexity: developing probabilistic decentralized thinking through role-playing activities. J Learn Sci 7(2):153–172

CrossRefGoogle ScholarSchoenfeld AH (1992) Learning to think mathematically: problem solving, metacognition, and sense making in mathematics. Handbook of research on mathematics teaching and learning, pp 334–370

Schunk DH (1983) Ability versus effort attributional feedback: differential effects on self-efficacy and achievement. J Educ Psychol 75(6):848

CrossRefGoogle ScholarSchweikardt E, Gross MD (2006) roBlocks: a robotic construction kit for mathematics and science education. Proceedings of the 8th international conference on Multimodal interfaces, pp 72–75

Sengupta P, Wilensky U (2009) Learning electricity with NIELS: thinking with electrons and thinking in levels. Int J Comput Math Learn 14(1):21–50

CrossRefGoogle ScholarSharlin E, Watson BA, Kitamura Y, Kishino F, Itoh Y (2004) On humans, spatiality and tangible user interfaces. Pervasive Ubiquitous Comput 8(5), 338–346. Theme issue on tangible interfaces in perspective

Sipitakiat A, Blikstein P (2010) Think globally, build locally: a technological platform for low-cost, open-source, locally-assembled programmable bricks for education. In: Presented at the conference on tangible, embedded, and embodied interaction TEI 2010, Cambridge, USA

Sklar E, Eguchi A, Johnson J (2003a) RoboCupJunior: learning with educational robotics. RoboCup 2002: robot soccer world cup VI, pp 238–253

Sklar E, Parsons S, Stone P (2003b) Robocup in higher education: a preliminary report. In: Proceedings of the 7th RoboCup symposium

Soloway E (1986) Learning to program = learning to construct mechanisms and explanations. Commun ACM 29(9):850–858

CrossRefGoogle ScholarWilensky U (1999) NetLogo [Computer software]. Evanston, IL: Northwestern University, Center for Connected Learning and Computer-Based Modeling. Retrieved September 20, 2011, from

http://ccl.northwestern.edu/netlogo
Wilensky U (2003) Statistical mechanics for secondary school: the GasLab modeling toolkit. Int J Comput Math Learn 8(1):1–4

CrossRefGoogle ScholarWilensky 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. Cogn Instruct 24(2):171–209

CrossRefGoogle ScholarWilensky U, Resnick M (1999) Thinking in levels: a dynamic systems perspective to making sense of the world. J Sci Educ Technol 8(1):3–19

CrossRefGoogle ScholarWilensky U, Stroup W (1999a) Learning through participatory simulations: network-based design for systems learning in classrooms. In: Proceedings of the 1999 conference on computer support for collaborative learning, CSCL ‘99 Palo Alto, CA

Wilensky U, Stroup W (1999b) HubNet [Computer software]. Northwestern University, Center for Connected Learning and Computer-Based Modeling, Evanston, IL

Google ScholarWing JM (2006) Computational thinking. Commun ACM 49(3):33–35

CrossRefGoogle ScholarWolfram S (2002) A new kind of science. Wolfram Media, Champaign, IL

Google ScholarWyeth P (2008) How young children learn to program with sensor, action, and logic blocks. J Learn Sci 17(4):517–550

CrossRefGoogle Scholar