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Learning to Program with Personal Robots: Influences on Student Motivation

Published: 01 March 2012 Publication History

Abstract

One of the goals of using robots in introductory programming courses is to increase motivation among learners. There have been several types of robots that have been used extensively in the classroom to teach a variety of computer science concepts. A more recently introduced robot designed to teach programming to novice students is the Institute for Personal Robots in Education (IPRE) robot. The author chose to use this robot and study its motivational effects on non-computer science students in a CS0 course. The purpose of this study was to determine whether using the IPRE robots motivates students to learn programming in a CS0 course. After considering various motivational theories and instruments designed to measure motivation, the author used Keller’s Instructional Materials Motivation Survey to measure four components of motivation: attention, relevance, confidence, and satisfaction. Additional items were added to the survey, including a set of open-ended questions. The results of this study indicate that the use of these robots had a positive influence on participants’ attitudes towards learning to program in a CS0 course, but little or no effect on relevance, confidence, or satisfaction. Results also indicate that although gender and students interests may affect individual components of motivation, gender, technical self-perception, and interest in software development have no bearing on the overall motivational levels of students.

References

[1]
Adams, D. B. 2010. Explore-create-present: A project series for CS. In Proceedings of the ASEE North Central Sectional Conference (ASEE’10).
[2]
AAUW. 2000. Tech-Savvy: Educating Girls in the New Computer Age. American Association of University Women Education Foundation, New York.
[3]
Apiola, M., Lattu, M., and Pasanen, T. 2010. Creativity and intrinsic motivation in computer science education: Experimenting with robots. In Proceedings of the 15th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE’10). 199--203.
[4]
Balch, T., Summet, J., Blank, D., Kumar, D., Guzdial, M., O’Hara, K., Walker, D., Sweat, M., Gupta, G., Tansley, S., Jackson, J., Gupta, M., Muhammad, M. N., Prashad, S., Eilbert, N., and Gavin, A. 2008. Designing personal robots for education: Hardware, software, and curriculum. IEEE Pervas. Comput. 7, 2, 5--9.
[5]
Bandura, A. 1997. Self-Efficacy: The Exercise of Control. Freeman, New York.
[6]
Barker, L. J., McDowell, C., and Kalahar, K. 2009. Exploring factors that influence computer science introductory course students to persist in the major. In Proceedings of 40th SIGCSE Technical Symposium on Computer Science Education (SIGSCE’09).
[7]
Barnes, T., Powell, E., Chaffin, A., and Lipford, H. 2008. Game2Learn: Improving the motivation of CS1 Students. In Proceedings of Game Development in Computer Science Education (GDCSE’08).
[8]
Barr, J., Cooper, S., Goldweber, M., and Walker, H. 2010. What everyone needs to know about computation. In Proceedings of the SIGCSE Technical Symposium on Computer Science Education (SIGCSE’10).
[9]
Becker, B. 2001. Teaching CS1 with Karel the robot in Java. In Proceedings of the 32nd SIGCSE Technical Symposium on Computer Science Education (SIGCSE’01). 50--54.
[10]
Besana, G. and Dettori, L. 2004. Together is better: Strengthening the confidence of women in computer science via a learning community. In Proceedings of the Consortium for Computing Sciences in Colleges, Northeastern Conference (CSCC’04). 130--139.
[11]
Bierre, K., Ventura, P., Phelps, A., and Eggert, C. 2006. In Proceedings of the 32nd SIGCSE Technical Symposium on Computer Science Education (SIGCSE’01). 354--358.
[12]
Biggs, J. B. 1987a. The Study Process Questionnaire (SPQ): Manual. Australian Council for Educational Research, Hawthorn, Vic.
[13]
Biggs, J. B. 1987b. The Learning Process Questionnaire (LPQ): Manual. Australian Council for Educational Research, Hawthorn, Vic.
[14]
Boyer, K. E., Phillips, R., Wallis, M. D., Vouk, M. A., and Lester, J. C. 2009. Investigating the role of student motivation in computer science education through one-on-one tutoring. Comput. Sci. Ed. 19, 2, 111--135.
[15]
Bransford, J., Brown, A., and Cocking, R., Eds. 1999. How people learn: Brain, mind, experience, and school. National Academy Press, Washington, D.C.
[16]
Byrne, P. and Lyons, G. 2001. The effect of student attributes on success in programming. In Proceedings of the 15th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE’01). 49--52.
[17]
Chan, T. S. and Ahern, T. C. 1999. Targeting motivation -- Adapting flow theory to instructional design. J. Ed. Comput. Res. 21, 2, 152--163.
[18]
Cliburn, D. 2006. A CS0 course for the liberal arts. In Proceedings of the 37th ACM Technical Symposium on Computer Science Education (SIGCSE’06). 77--81.
[19]
Cooper, S. and Cunningham, S. 2010. Teaching computer science in context. Inroads 1, 1, 5--8.
[20]
Covington, M. V. 2000. Goal theory, motivation and school achievement: An integrative review. Ann. Rev. Psych. 51, 171--200.
[21]
Csikszentmihalyi, M. 1975. Beyond Boredom and Anxiety. Jossey-Bass, San Francisco, CA.
[22]
Creswell, J. W. 2008. Educational Research. Planning, Conducting, and Evaluating Quantitative and Qualitative Research. Pearson Education, Upper Saddle River, NJ.
[23]
Cutts, Q., Cutts, E., Draper, S., O’Donnell, P., and Saffrey, P. 2010. Manipulating mindset to positively influence introductory programming performance. In Proceedings of the SIGCSE Technical Symposium on Computer Science Education (SIGCSE’10). 431--435.
[24]
Deci, E. L. and Ryan, R. M. 1985. Intrinsic Motivation and Self-Determination in Human Behavior. Plenum, New York.
[25]
Deci, E. L., Schwartz, A., Sheinman, L., and Ryan, R. M. 1981. An instrument to assess adults’ orientations toward control versus autonomy with children: Reflections on intrinsic motivation and perceived competence. J. Ed. Psych. 73, 642--650.
[26]
Egbert, J. 2003. A study of flow theory in the foreign language classroom. Mod. Lang. J. 87, 4, 499--518.
[27]
Elliott, E. S. and Dweck, C. S. 1988. Goals: An approach to motivation and achievement. J. Person. Soc. Psych. 54, 5--12.
[28]
Entwistle, N. J. and Ramsden, P. 1983. Understanding Student Learning. Croom Helm, London.
[29]
Fagin, B. and Merkle, L. 2003. Measuring the effectiveness of robots in teaching computer science. SIGCSE Bull. 35, 1, 307--311.
[30]
Fishbein, M. and Ajzen, I. 1972. Beliefs, Attitudes, Intentions and Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading, MA.
[31]
Friedman, B. A. and Mandel, R. G. 2010. The prediction of college student academic performance and retention: Application of expectancy and goal setting theories. J. Coll. Stud. Retent. 11, 2, 227--246.
[32]
Fry, H., Ketteridge, S., and Marshall, S. 2003. A Handbook for Teaching & Learning in Higher Education. Routledge Farmer, New York, NY.
[33]
Glanz, K., Riber, B. K., and Lewis, F. M. 2002. Health Behavior and Health Education. Theory, Research and Practice. Wiley & Sons, New York.
[34]
Goto, S. T. and Martin, C. 2009. Psychology of success: Overcoming barriers to pursuing further education. J. Contin. High. Ed. 57, 1, 10--21.
[35]
Gregg, C. M. 2009. Self-Determination, Culture, and School Administration: A Phenomenological Study on Student Success. ProQuest LLC.
[36]
Guzdial, M. 2008. Teaching computing to everyone. Comm. ACM 52, 5, 31--33.
[37]
Guzdial, M. 2010. Does contextualized computing education help? Inroads 1, 4, 4--6.
[38]
Heider, F. 1958. The Psychology of Interpersonal Relations. Wiley, New York.
[39]
Hoegh, A. and Moskal, B. M. 2009. Examining science and engineering students’ attitudes toward computer science. In Proceedings in the 39th ASEE/IEEE Frontiers in Education Conference (ASEE’09).
[40]
Huang, W., Huang, W., Diefes-Dux, H., and Imbrie, P. K. 2006. A preliminary validation of attention, relevance, confidence and satisfaction model-based instructional material motivational survey in a computer-based tutorial setting. Brit. J. Ed. Technol. 37, 16.
[41]
Huang, W.-H., Huang, W.-Y., and Tschopp, J. 2010a. Sustaining iterative game playing processes in DGBL: The relationship between motivational processing and outcome processing. Comput. Ed. 55, 2, 789--797.
[42]
Huang, Y., Backman, S. J., and Backman, K. F. 2010b. Student attitude toward virtual learning in second life: A flow theory approach. J. Teach. Travel & Tour. 10, 4, 312--334.
[43]
Hundley, J. and Pritt, W. 2009. Engaging students in software development course projects. In Proceedings of the Richard Tapia Celebration of Diversity in Computing Conference (TAPIA’09). 87--92.
[44]
Imberman, S. and Klibaner, R. 2005. A robotics lab for CS1. J. Comput. Sci. Coll. 21, 2, 131--137.
[45]
Institute for Personal Robots in Education. 2011. http://wiki.roboteducation.org.
[46]
Irobot Create Forum. 2011. http://createforums.irobot.com/irobotcreate/.
[47]
Jiau, H. C., Chen, J. C., and Ssu, K. 2009. Enhancing self-motivation in learning programming using game-based simulation and metrics. IEEE Trans. Ed. 52, 4, 555--562.
[48]
Keller, J. M. 1983. Motivational design of instruction. In Instructional Design Theories and Models: An Overview of Their Current Status. C. M. Reigeluth Ed., Lawrence Erlbaum Associates, Hillsdale, NJ, 386--434.
[49]
Keller, J. M. 1987a. The systematic process of motivational design. Perform. Instruc. 26, 9/10, 1--8.
[50]
Keller, J. M. 1987b. IMMS: Instructional materials motivation survey. Florida State University.
[51]
Keller, J. M. and Subhiyah, R. G. 1987a. Course effort survey. Florida State University.
[52]
Keller, J. M. and Subhiyah, R. G. 1987b. Course interest survey. Florida State University.
[53]
Kinnunen, P. and Malmi, L. 2008. CS minors in a CS1 course. In Proceedings of the Conference on International Computing Education Research (ICER’08). 79--90.
[54]
Kinnunen, P. and Simon, B. 2010. Experiencing programming assignments in CS1: The emotional toll. In Proceedings of the Conference on International Computing Education Research (ICER’10). 77--85.
[55]
Kinnunen, P., McCartney, R., Murphy, L., and Thomas, L. 2007. Through the eyes of instructors: A phenomenographic investigation of student success. In Proceedings of the Conference on International Computing Education Research (ICER’07). 61--72.
[56]
Kölling, M. and Rosenberg, J. 2001. Guidelines for teaching object orientation with Java. SIGCSE Bull. 33, 3, 33--36.
[57]
Kumar, D., et al. 2008. Engaging computing students with AI and robotics. Using AI to motivate greater participation in computer science. Tech. rep. SS-08-08, AAAI Press.
[58]
Landson-Billings, G. 1995. Toward a theory of culturally relevant pedagogy. In Curriculum: Problems, Politics, and Possibilities, Beyer and Apple Eds.
[59]
Landry, C. L. 2003. Self-efficacy, motivation, and outcome expectation correlates of college students’ intention certainty. Doctoral dissertation, Louisiana State University.
[60]
Latta, M. R. 1974. Relation of causal attribution and success to performance. ED102474, ERIC.
[61]
Lauwers, T., Nourbakhsh, I., and Hamner, E. 2009. CSbots: Design and deployment of a robot designed for the CS1 classroom. In Proceedings of the 40th Technical Symposium on Computer Science Education (SIGCSE’09). 428--432.
[62]
Layman, L., Williams, L., and Slaten, K. 2007. Note to self: Make assignments meaningful. In Proceedings of the 40th Technical Symposium on Computer Science Education (SIGCSE’07). 459--463.
[63]
Lego. 2010. LEGO Mindstorms for education. http://mindstorms.lego.com/.
[64]
Levesque-Bristol, C. and Stanek, L. 2009. Examining self-determination in a service learning course. Teach. Psych. 36, 4, 262--266.
[65]
Levin, T. and Long, R. 1981. Effective Instruction. Association for Supervision and Curriculum Development, Alexandria, VA.
[66]
Margolis, H. 2009. Student motivation: A problem solving focus. http://www.reading2008.com/MotivationProblem_Solving_Questionnaire-HowardMargolis-2009Jan1-c.pdf.
[67]
Margolis, J. and Fisher, A. 2002. Unlocking the Clubhouse: Women in Computing. MIT Press, Cambridge, MA.
[68]
Markham, S. A. and King, K. N. 2010. Using personal robots in CS1: Experiences, outcomes, and attitudinal influences. In Proceedings of the 13th ACM Innovations and Technology in Computer Science Education (ITiCSE’10). 204--208.
[69]
Martin, A. J. 2003. The student motivation scale: Further testing of an instrument that measures school students’ motivation. Austral. J. Ed. 47, 1, 88--106.
[70]
Martins, S. W., Mendes, A. J., and Figueiredo, A. D. 2010. Diversifying activities to improve student performance in programming courses. In Proceedings of CompSysTech (CompSysTech’10). 540--545.
[71]
Maslow, A. H. 1943. A theory of human motivation. Psych. Rev. 50, 370--396.
[72]
Mawhorter, P., Shaver, E., Koziol, Z., and Dodds, Z. 2009. A tale of two platforms: Low-cost robotics in the CS curriculum. J. Comput. Sci. Coll., 180--188.
[73]
McNally, M. F. 2006. Walking the grid: Robotics in CS 2. In Proceedings of the 8th Australian Conference on Computing Education (ACE’06). D. Tolhurst and S. Mann Eds., vol. 52, Australian Computer Society, Inc., 151--155.
[74]
McWhorter, W. and O’Connor, B. 2009. Do LEGO Mindstorms motivate students in CS1? In Proceedings of the 40th ACM Technical Symposium on Computer Science Education (SIGCSE’09). 438--442.
[75]
Mills, N., Pajares, F., and Herron, C. 2007. Self-efficacy of college intermediate French students: Relation to achievement and motivation. Lang. Learn. 57, 3, 417--442.
[76]
Mosley, P. and Kline, R. 2006. Engaging students: A framework using LEGO robotics to teach problem solving. Inf. Technol., Learn. Perform. J. 24, 1, 39--45.
[77]
Mueller, R. J. 1984. Building an Instrument to Measure Study Behaviors and Attitudes: A Factor Analysis of 46 Items. University of Northern Illinois, De Kalb, IL.
[78]
O’Kelly, J. and Gibson, J. P. 2006. RoboCode & problem-based learning: A non-prescriptive approach to teaching programming. In Proceedings of the 11th Annual ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE’06). 217--221.
[79]
Pintrich, P. 1999. A Manual for the Use of the Motivated Strategies for Learning Questionnaire (MSLQ). National Center for Research to Improve Postsecondary Training and Learning, Ann Arbor, MI.
[80]
Pintrich, P. R. and De Groot, E. V. 1990. Motivational and self-regulated learning components of classroom academic performance. J. Ed. Psych. 82, 33--40.
[81]
Pittenger, A. and Doering, A. 2010. Influence of motivational design on completion rates in online self-study pharmacy-content courses. Dist. Ed. 31, 3, 275--293.
[82]
Ramalingam, V. and Wiedenbeck, S. 1998. Development and validation of scores on a computer programming self-efficacy scale and group analyses of novice programmer self-efficacy. J. Ed. Comput. Res. 19, 4, 365--379.
[83]
Rheinberg, F., Vollmeyer, R., and Burns, B. 2001. FAM: A questionnaire on motivation in learning and performance situations. Diagnostika 2, 57--66.
[84]
Rich, L., Perry, H., and Guzdial, M. 2004. A CS1 course designed to address interests of women. In Proceedings of the 34th ACM Technical Symposium on Computer Science Education (SIGCSE’04). 190--195.
[85]
Rodgers, D. and Withrow-Thorton, B. 2005. The effect of instructional media on learner motivation. Int. J. Instruc. Media 21, 4, 333--342.
[86]
Roebken, H. 2007. The influence of goal orientation on student satisfaction, academic engagement and achievement. Electron. J. Res. Ed. Psychol. 5, 3, 679--704.
[87]
Roundtree, N., Rountree, J., Robins, A., and Hannah, R. 2004. Interacting factors that predict success and failure in a CS1 course. SIGCSE Bull. 35, 4, 101--104.
[88]
Ryan, R. M. 1982. Control and information in the intrapersonal sphere: An extension of cognitive evaluation theory. J. Person. Soc. Psychol. 43, 450--461.
[89]
Ryan, R. M. and Deci, E. L. 2000. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Amer. Psychol. 55, 68--78.
[90]
Ryan, R. M., Frederick, C. M., Lepes, D., Rubio, N., and Sheldon, K. M. 1997. Intrinsic motivation and exercise adherence. Int. J. Sport Psychol. 28, 335--354.
[91]
Schonwetter, D. J., et al. 1994. Implications for higher education in the linkages of student differences and effective teaching. Annual Meeting of the American Eduactional Research Association.
[92]
Schuler, H., Thornton, G., Frintrup, A., and Mueller-Hanson, R. 2004. AMI Achievement Motivation Inventory: Technical and User’s Manual. Hogrefe & Huber.
[93]
Simon, S., Robins, A., Sutton, K., Baker, B., Box, I., De Raadt, M., Hamer, J., Hamilton, M., Lister, R., Petre, M., Tolhurst, D., and Tutty, J. 2006. Predictors of success in a first programming course. In Proceedings of the 8th Australian Conference on Computing Education (ACE’06). D. Tolhurst and S. Mann Eds., vol. 52, 181--188.
[94]
Skinnger, B. F. 1954. The science of learning and the art of teaching. Harvard Ed. Rev. 24, 2, 86--97.
[95]
Small, R. V. 1997. Motivation in instructional design. In ERIC Digest, ERIC Clearinghouse on Information and Technology Syracuse NY.
[96]
Stanley, D. T. and Campbell, J. C. 1963. Experimental and Quasi-Experimental Designs for Research. Houghton Mifflin Company.
[97]
Stevenson, D. E. and Wagner, P. J. 2006. Developing real-world programming assignments for CS1. In Proceedings of the ACM Innovations and Technology in Computer Science Education (ITiCSE’06). 158--162.
[98]
Summet, J., Kumar, D., O’Hara, K., Walker, D., Ni, L. L., Blank, D. L., and Balch, T. 2009. Personalizing CS1 with robots. In Proceedings of the 40th ACM Technical Symposium on Computer Science Education (SIGCSE’09). 433--437.
[99]
Svinicki, M. A. 2010. Guidebook on conceptual frameworks for research in engineering education. www.ce.umn.edu/~Smith/docs/RREE-Research-Frameworks_Svinicki.pdf.
[100]
Taylor, F. W. 1916. The Principles of Scientific Management. Bulletin of the Taylor Society.
[101]
Turner, E. A., Chandler, M., and Heffer, R. W. 2009. The influence of parenting styles, achievement motivation, and self-efficacy on academic performance in college students. J. Coll. Stud. Dev. 50, 3, 337--346.
[102]
Tyler, R. 1971. Theory and practice: Bridging the gap. Grade Teach. May/June, 46--65.
[103]
Uguroglu, M. and Walberg, H. J. 1979. Motivation and achievement: A quantitative synthesis. Amer. Ed. Res. J. 16, 375--389.
[104]
Vallerand, R. J., et al. 1992. The academic motivation scale: A measure of intrinsic, extrinsic and amotivation in education. Ed. Psychol. Measure. 52, 1003--1017.
[105]
Vollmeyer, R. and Rheinberg, F. 2006. Motivational effects on self-regulated learning with different tasks. Ed. Psychol. Rev. 18, 239--253.
[106]
Wambach, C. A. 1993. Motivational themes and academic success of at-risk freshmen. J. Dev. Ed. 16, 3, 8--10, 12, 37.
[107]
Weibe, E., Williams, L. A., Yang, K., and Miller, C. 2003. Computer science attitude survey. Tech. rep. CSC TR-2003-01, North Carolina State University, Raleigh, NC.
[108]
Weiner, B. 1974. Achievement Motivation and Attribution Theory. General Learning Press, Morristown, N.J.
[109]
Weiss, R. and Overcast, I. 2008. Finding your bot-mate: Criteria for evaluating robot kits for use in undergraduate computer science education. J. Comput. Sci. Coll., 43--49.
[110]
Wiedenbeck, S. 2005. Factors affecting the success of non-majors in learning to program. In Proceedings of the Conference on International Computing Education Research (ICER’05). 13--24.
[111]
Wilson, B. C. 2006. Gender differences in types of assignments preferred: Implications for computer science instruction. J. Ed. Comput. Res. 34, 3, 245--255.
[112]
Wilson, B. C. and Schrock, S. 2001. Contributing to success in an introductory computer science course: A study of twelve factors. ACM SIGCSE Bull. 33, 1.
[113]
Wlodkowski, R. and Ginsberg, M. 2003. Diversity and Motivation: Culturally Responsive Teaching. Jossey-Bass.
[114]
Xu, D., Blank, D. and Kumar, D. 2008. Games, robots, and robot games: Complementary contexts for introductory computing education. In Proceedings of Game Development in Computer Science Education (GDCSE’08).
[115]
Yonghiu, C. 2010. Study of flow theory and experiential learning. In Proceedings of the 2nd International Conference on Multimedia and Information Technology (MMIT’10). 2, 334--337.
[116]
Zaini, Z. and Ahmad, W. 2010. A study on students’ motivation in learning mathematics using multimedia courseware. In Proceedings of the 2010 International Symposium in Information Technology (ITSim’10). 1--3.

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cover image ACM Transactions on Computing Education
ACM Transactions on Computing Education  Volume 12, Issue 1
March 2012
106 pages
EISSN:1946-6226
DOI:10.1145/2133797
Issue’s Table of Contents
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Published: 01 March 2012
Accepted: 01 November 2011
Revised: 01 August 2011
Received: 01 January 2011
Published in TOCE Volume 12, Issue 1

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  1. CS0
  2. CS1
  3. Motivation
  4. Myro
  5. curriculum
  6. education
  7. personal robots
  8. programming

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