The effectiveness of simulated robots for supporting the learning of introductory programming: a multi-case case study

References

• ACM/IEEE. (2008). Computer science curriculum 2008: An interim revision of CS 2001. Report from the Interim Review Task Force. Retrieved August 2, 2014, from http://www.acm.org/education/curricula/ComputerScience2008.pdf
   Google Scholar
• Alavi, M. (1994). Computer-mediated collaborative learning: An empirical evaluation. MIS Quarterly, 18, 159–174.10.2307/249763
   Web of Science ®Google Scholar
• Alimisis, D., Moro, M., Arlegui, J., Pina, A., Frangou, S., & Papanikolaou, K. (2007). Robotics & constructivism in education: The TERECoP project. EuroLogo, 40, 19–24).
   Google Scholar
• ANSI Standards Committee on Dental Informatics. (2001). Guidelines for the design of educational software. Working Group Educational Software Systems.
   Google Scholar
• Beale, R., & Sharples, M. (2002). Design guide for developers of educational software. British Educational Communications and Technology Agency. Retrieved August 2, 2014, from http://www.eee.bham.ac.uk/sharplem/Papers/Design%20Guide.pdf
   Google Scholar
• Becker, B. W. (2001). Teaching CS1 with karel the robot in Java. ACM SIGCSE Bulletin, 33, 50–54.10.1145/366413
   Google Scholar
• Biggs, J. (2003). Aligning teaching and assessing to course objectives. Teaching and Learning in Higher Education: New Trends and Innovations, 2, 13–17.
   Google Scholar
• Borge, R., Fjuk, A., & Groven, A. K. (2004). Using Karel J collaboratively to facilitate object-oriented learning. In C. L. Kinshuk, E. Sutinen, D. G. Sampson, I. Aedo, L. Uden, & E. Kähkönen (Eds.), Proceedings of IEEE International Conference on Advanced Learning Technologies (pp. 580–584). Joensuu: IEEE.
   Google Scholar
• Braitenberg, V. (1986). Vehicles: Experiments in synthetic psychology. MIT Press.
   Google Scholar
• Brereton, P., Kitchenham, B., Budgen, D., & Li, Z. (2008). Using a protocol template for case study planning. In G. Visaggio, M. T. Baldassarre, S. Linkman, & M. Turner (Eds.), Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering. Italy: University of Bari.
   Google Scholar
• Buck, D., & Stucki, D. J. (2001). JKarelRobot. ACM SIGCSE Bulletin, 33, 16–20.10.1145/366413
   Google Scholar
• Burdea, G. C., Cioi, D., Kale, A., Janes, W. E., Ross, S. A., & Engsberg, J. R. (2012). Robotics and gaming to improve ankle strength, motor control and function in children with cerebral palsy – A case study series. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 21, 165–173.
   PubMed Web of Science ®Google Scholar
• Case, J. (2008). Education theories on learning: An informal guide for the engineering education scholar. Higher Education Academy Engineering Subject Centre (HEA).
   Google Scholar
• Čermák, P., & Kelemen, J. (2011). An attempt to teaching programming with robots. In A. Gottscheber & D. Obdržálek (Ed.), Research and education in robotics-EUROBOT 2011 (pp. 78–87). Berlin: Springer.
   Google Scholar
• Cowden, D., O’Neill, A., Opavsky, E., Ustek, D., & Walker, H. M. (2012). A C-based introductory course using robots. In L. S. King & D. R. Musicant (Eds.), Proceedings of the 43rd ACM technical symposium on Computer Science Education (pp. 27–32). Raleigh, NC: ACM.
   Google Scholar
• Dann, W., Cooper, S., & Pausch, R. (2006). Learning to program with Alice. Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• desJardins, M., Ciavolino, A., Deloatch, R., & Feasley, E. (2011). Playing to program: Towards an intelligent programming tutor for RUR-PLE. In Second AAAI Symposium on Educational Advances in Artificial Intelligence.
   Google Scholar
• Douglas, S., Farley, A., Lo, G., Proskurowski, A., & Young, M. (2010). Internationalization of computer science education. In G. Lewandowski & S. Wolfman (Eds.), Proceedings of the 41st ACM Technical Symposium on Computer Science Education (pp. 411–415). Milwaukee, WI: ACM.
   Google Scholar
• Easterbrook, S., Singer, J., Storey, M. A., & Damian, D. (2008). Selecting empirical methods for software engineering research. In Guide to advanced empirical software engineering (pp. 285–311). London: Springer.
   Google Scholar
• Edwards, S. H. (2003). Rethinking computer science education from a test-first perspective. In R. Crocker & G. L. Steele Jr (Eds.), Companion of the 18th Annual ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications (pp. 148–155). Anaheim, CA: ACM.
   Google Scholar
• Enderle, S. (2009). Grape–graphical robot programming for beginners. In A. Gottscheber, S. Enderle, & D. Obdrzalek (Eds.), Research and education in robotics – EUROBOT 2008 (pp. 180–192). Berlin: Springer.
   Google Scholar
• Esteves, M., Antunes, R., Fonseca, B., Morgado, L., & Martins, P. (2008). Using Second Life in programming’s communities of practice. In Groupware: Design, implementation, and use (pp. 99–106). Berlin: Springer.
   Google Scholar
• Fagin, B. S., Merkle, L. D., & Eggers, T. W. (2001). Teaching computer science with robotics using Ada/Mindstorms 2.0. ACM SIGAda Ada Letters, XXI, 73–78.10.1145/507546
   Google Scholar
• Flot, J., Schunn, C., Liu, A., & Sharp, R. (2012, November/December). Learning how to program via robot simulation. Robot Magazine. ISSN: 1555-1016. 68-70.
   Google Scholar
• Gibbert, M., & Ruigrok, W. (2010). The “what” and “'how” of case study rigor: Three strategies based on published work. Organizational Research Methods, 13, 710–737.10.1177/1094428109351319
   Web of Science ®Google Scholar
• Gibbs, G. R. (2007). Analyzing qualitative data (Book 6 of The SAGE qualitative research kit). London: Sage.
   Google Scholar
• Goldweber, M., Congdon, C., Fagin, B., Hwang, D., & Klassner, F. (2001). The use of robots in the undergraduate curriculum. ACM SIGCSE Bulletin, 33, 404–405.10.1145/366413
   Google Scholar
• Jerez, J. M., Bueno, D., Molina, I., Urda, D., & Franco, L. (2012). Improving motivation in learning programming skills for engineering students. International Journal of Engineering Education, 28, 202–208.
   Web of Science ®Google Scholar
• Jones, M. (2010). An extended case study on the introductory teaching of programming (Doctoral dissertation). University of Southampton.
   Google Scholar
• Kammer, T., Brauner, P., Leonhardt, T., & Schroeder, U. (2011). Simulating LEGO Mindstorms robots to facilitate teaching computer programming to school students. In Towards ubiquitous learning (pp. 196–209). Berlin: Springer.
   Google Scholar
• Kasurinen, J., Purmonen, M., & Nikula, U. (2008). A study of visualization in introductory programming. In Proceedings of the 20th Annual Meeting of Psychology of Programming Interest Group. Lancaster: PPIG.
   Google Scholar
• Kinnunen, P., & Malmi, L. (2006). Why students drop out CS1 course? In R. Anderson, S. A. Fincher, & M. Guzdial (Eds.), Proceedings of the Second International Workshop on Computing Education Research (pp. 97–108). Canterbury: ACM.
   Google Scholar
• Kitchenham, B. (2004). Procedures for undertaking systematic reviews. Joint Technical Report, Keele University TR/SE-0401 and NICTA 0400011T.
   Google Scholar
• Kitchenham, B. A., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE-2007-01. Keele University and Durham University Joint Report.
   Google Scholar
• Ladd, B., & Harcourt, E. (2005). Student competitions and bots in an introductory programming course. Journal of Computing Sciences in Colleges, 20, 274–284.
   Google Scholar
• Lahtinen, E., & Ahoniemi, T. (2009). Kick-start activation to novice programming – A visualization-based approach. Electronic Notes in Theoretical Computer Science, 224, 125–132.10.1016/j.entcs.2008.12.056
   Google Scholar
• Lee, A. S. (1989). A scientific methodology for MIS case studies. MIS Quarterly, 13, 33–50.10.2307/248698
   Web of Science ®Google Scholar
• Lemone, K. A., & Ching, W. (1996). Easing into C++. ACM SIGCSE Bulletin, 28, 45–49.10.1145/242649
   Google Scholar
• Lister, R., & Leaney, J. (2003). Introductory programming, criterion-referencing, and bloom. ACM SIGCSE Bulletin, 35, 143–147.10.1145/792548
   Google Scholar
• Liu, A. S., Schunn, C. D., Flot, J., & Shoop, R. (2013). The role of physicality in rich programming environments. Computer Science Education, 23, 315–331.10.1080/08993408.2013.847165
   Google Scholar
• Major, L. (2014, March). An empirical investigation into the effectiveness of a robot simulator as a tool to support the learning of introductory programming (PhD Thesis). Keele University. Retrieved from http://opac.keele.ac.uk/record=b1558010~S4
   Google Scholar
• Major, L., Kyriacou, T., & Brereton, P. (2011). Experiences of prospective high school teachers using a programming teaching tool. In A. Korhonen & R. McCartney (Eds.), Proceedings of the 11th Koli Calling International Conference on Computing Education Research (pp. 126–131). Koli: ACM.
   Google Scholar
• Major, L., Kyriacou, T., & Brereton, O. P. (2012a). Systematic literature review: Teaching novices programming using robots. IET Software, 6, 502–513.10.1049/iet-sen.2011.0125
   Web of Science ®Google Scholar
• Major, L., Kyriacou, T., & Brereton, O. P. (2012b). Teaching novices programming using a robot simulator: Case study protocol. In Y. Jing (Ed.), Proceedings of the 24th Psychology of Programming Interest Group PPIG 2012 (pp. 93–104). London: London Metropolitan University, PPIG.
   Google Scholar
• Marshall, C., Brereton, P., & Kitchenham, B. (2014). Tools to support systematic reviews in software engineering: A feature analysis. In M. Shepperd, T. Hall, & I. Myrtveit (Eds.), Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering (p. 13). London: ACM.
   Google Scholar
• Martin, C., & Hughes, J. (2011, September 6–8). Robot dance: Edutainment or engaging learning. In Proceedings of the 23rd Psychology of Programming Interest Group PPIG 2011. York: PPIG.
   Google Scholar
• Matlock-Hetzel, S. (1997). Basic concepts in item and test analysis. Texas A&M University.
   Google Scholar
• McCracken, M., Wilusz, T., Almstrum, V., Diaz, D., Guzdial, M., Hagan, D., … Utting, I. (2001). A multi-national, multi-institutional study of assessment of programming skills of first-year CS students. ACM SIGCSE Bulletin, 33, 125–180.10.1145/572139
   Google Scholar
• McWhorter, W. I., & O’Connor, B. C. (2009). Do LEGO Mindstorms motivate students in CS1? ACM SIGCSE Bulletin, 41, 438–442.10.1145/1539024
   Google Scholar
• Merriam, S. B. (1998). Qualitative research and case study applications in education. San Francisco, CA: Jossey-Bass.
   Google Scholar
• Miliszewska, I., & Tan, G. (2007). Befriending computer programming: A proposed approach to teaching introductory programming. Informing Science: International Journal of an Emerging Transdiscipline, 4, 277–289.
   Google Scholar
• Nevalainen, S., & Sajaniemi, J. (2006). An experiment on short-term effects of animated versus static visualization of operations on program perception. In Proceedings of the Second International Workshop on Computing Education Research (pp. 7–16). ACM.
   Google Scholar
• Oppenheim, A. N. (2000). Questionnaire design, interviewing and attitude measurement. Continuum International Publishing Group.
   Google Scholar
• Paliokas, I., Arapidis, C., & Mpimpitsos, M. (2011). Playlogo 3d: A 3d interactive video game for early programming education: Let logo be a game. In F. Liarokapis, A. Doulamis, & V. Vescoukis (Eds.), Third International Conference on Games and Virtual Worlds for Serious Applications (VS-GAMES) (pp. 24–31). Athens: IEEE.
   Google Scholar
• Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. Basic Books.
   Google Scholar
• Papert, S. (1993). The children’s machine: Rethinking school in the age of the computer. Basic Books.
   Google Scholar
• Pattis, R. E. (1981). Karel the robot: A gentle introduction to the art of programming. Wiley.
   Google Scholar
• Pattis, R. E., Roberts, J., & Stehlik, M. (1995). Karel the robot: A gentle introduction to the art of programming (2nd ed.). Wiley.
   Google Scholar
• Pears, A., Seidman, S., Malmi, L., Mannila, L., Adams, E., Bennedsen, J., … Devlin, M. (2007). A survey of literature on the teaching of introductory programming. ACM SIGCSE Bulletin, 39, 204–223.10.1145/1345375
   Google Scholar
• Piaget, J. (1967). The child’s conception of the world. Routledge & Kegan Paul.
   Google Scholar
• Price, B. A., Richards, M., Petre, M., Hirst, A., & Johnson, J. (2003). Developing robotics e-teaching for teamwork. International Journal of Continuing Engineering Education and Life Long Learning, 13, 190–205.
   Google Scholar
• Resnick, M. (1994). Turtles, termites, and traffic jams: Explorations in massively parallel microworlds. MIT Press.
   Google Scholar
• Resnick, M., Silverman, B., Kafai, Y., Maloney, J., Monroy-Hernández, A., Rusk, N., … Eastmond, E. (2009). Scratch. Communications of the ACM, 52, 60–67.10.1145/1592761
   Web of Science ®Google Scholar
• Rieber, L. P. (1996). Seriously considering play: Designing interactive learning environments based on the blending of microworlds, simulations, and games. Educational Technology Research and Development, 44, 43–58.10.1007/BF02300540
   Web of Science ®Google Scholar
• Ring, B. A., Giordan, J., & Ransbottom, J. S. (2008). Problem solving through programming: Motivating the non-programmer. Journal of Computing Sciences in Colleges, 23, 61–67.
   Google Scholar
• Robson, C. (2011). Real world research (3rd ed.). Wiley.
   Google Scholar
• Runeson, P., Höst, M., & Rainer, A., & Regnell, B. (2012). Case study research in software engineering. Wiley.10.1002/9781118181034
   Google Scholar
• Satratzemi, M., Xinogalos, S., & Dagdilelis, V. (2003). An environment for teaching object-oriented programming: ObjectKarel. In V. Devedzic, J. Spector, D. Sampson, & Kinshuk (Eds.), Proceedings of IEEE Advanced Learning (pp. 342–343). Athens: IEEE.
   Google Scholar
• Siegel, S. (1957). Nonparametric statistics. The American Statistician, 11, 13–19.
   Web of Science ®Google Scholar
• Sklar, E., Parsons, S., & Azhar, M. Q. (2006). Robotics across the curriculum. Technical Report. Department of Computer and Information Science. Brooklyn College, City University of New York.
   Google Scholar
• Smith, M. K., Wood, W. B., & Knight, J. K. (2008). The genetics concept assessment: A new concept inventory for gauging student understanding of genetics. Cell Biology Education, 7, 422–430.10.1187/cbe.08-08-0045
   Google Scholar
• Solin, P. (2013). Learn how to think with Karel the Robot. NCLAB Public Computing. FEMhub Inc.
   Google Scholar
• Soule, T., & Heckendorn, R. B. (2011). COTSBots: Computationally powerful, low-cost robots for Computer Science curriculums. Journal of Computing Sciences in Colleges, 27, 180–187.
   Google Scholar
• Squires, D., & Preece, J. (1999). Predicting quality in educational software. Interacting with Computers, 11, 467–483.10.1016/S0953-5438(98)00063-0
   Web of Science ®Google Scholar
• Stewart, L. G., & White, M. A. (1976). Teacher comments, letter grades, and student performance: What do we really know? Journal of Educational Psychology, 68, 488.10.1037/0022-0663.68.4.488
   Web of Science ®Google Scholar
• Talbot, H. (2000). wxPython, a GUI Toolkit. Linux Journal, 74.
   Google Scholar
• Thota, N., & Whitfield, R. (2010). Holistic approach to learning and teaching introductory object-oriented programming. Computer Science Education, 20, 103–127.10.1080/08993408.2010.486260
   Google Scholar
• Varma, S. (2006). Preliminary item statistics using point-biserial correlation and p-values (Vol. 16). Morgan Hill, CA: Educational Data Systems.
   Google Scholar
• Verner, J. M., Sampson, J., Tosic, V., Bakar, N. A. A., & Kitchenham, B. A. (2009). Guidelines for industrially-based multiple case studies in software engineering. In A. Flory & M. Collard (Eds.), Third International Conference on Research Challenges in Information Science 2009 (pp. 313–324). Fes: IEEE.
   Google Scholar
• Wulf, T. (2005). Constructivist approaches for teaching computer programming. In Proceedings of the 6th Conference on Information Technology Education (pp. 245–248). ACM.
   Google Scholar
• Yadin, A. (2011). Reducing the dropout rate in an introductory programming course. ACM Inroads, 2, 71–76.10.1145/2038876
   Google Scholar
• Yin, R. K. (2009). Case study research: Design and methods (4th ed.). Sage.
   Google Scholar