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Interaction of visual interface and academic levels with young students’ anxiety, playfulness, and enjoyment in programming for robot control

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Abstract

Young students’ engagement in computer programming has been recognized as a crucial issue in educational settings nowadays. In this study, a block-based programming approach was employed to investigate its impacts on the learning anxiety, playfulness, and enjoyment of young students with different academic levels. A total of 175 10th graders participated in the study. The participants were asked to use block-based programming to control a robot. The experimental results show that the block-based programming, which engages students in programming tasks using a building block-like visual interface, significantly reduced the students’ learning anxiety while also promoting their playfulness and enjoyment in the perspectives of computational thinking. It was also found that the block-based programming benefited the low- and medium-achievement more than the high-achievement students did. Therefore, it was inferred that block-based programming would be useful for those people who have worse learning performance in conventional programming learning so they need further remedial instruction. Moreover, male students had lower learning anxiety and higher playfulness than the female students. The findings could be a good reference for researchers and school teachers who intend to conduct programming activities for young children.

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References

  1. Grover, S., Pea, R.: Computational thinking in K-12: a review of the state of the field. Educ. Res. 42(1), 38–43 (2013)

    Article  Google Scholar 

  2. Ouahbi, I., Kaddari, F., Darhmaoui, H., Elachqar, A., Lahmine, S.: Learning basic programming concepts by creating games with scratch programming environment. Procedia Soc. Behav. Sci. 191, 1479–1482 (2015)

    Article  Google Scholar 

  3. Wang, H.Y., Huang, I., Hwang, G.J.: Effects of a question prompt-based concept mapping approach on students’ learning achievements, attitudes and 5C competences in project-based computer course activities. Educ. Technol. Soc. 19(3), 351–364 (2016)

    Google Scholar 

  4. Falloon, G.: An analysis of young students’ thinking when completing basic coding tasks using Scratch Jnr on the iPad. J Comput-Assist Learn 32(6), 576–593 (2016)

    Article  Google Scholar 

  5. Kölling, M., Quig, B., Patterson, A., Rosenberg, J.: The Blue J system and its pedagogy. J. Comput. Sci. Educ. 13, 249–269 (2003)

    Article  Google Scholar 

  6. Yang, T.C., Hwang, G.J., Yang, S.J., Hwang, G.H.: A two-tier test-based approach to improving students’ computer-programming skills in a web-based learning environment. Edu Technol Soc 18(1), 198–210 (2015)

    Google Scholar 

  7. Gomes, A., Areias, C.M., Henriques, J., Mendes, A.: Aprendizagem de programação de computadores: dificuldades e ferramentas de suporte. Revista Portuguesa De Pedagogia 42(2), 161–179 (2008)

    Article  Google Scholar 

  8. Jeon, Y., Kim, J., Hong, C.: Kim T (2014) A mobile programming course based on computational thinking process for elementary IT-gifted students. World Conf E-Learn Corp, Gov, Healthc, High Edu 1, 915–920 (2014)

    Google Scholar 

  9. Rubio, M.A., Romero-Zaliz, R., Mañoso, C., Angel, P.: Closing the gender gap in an introductory programming course. Comput. Educ. 82, 409–420 (2015)

    Article  Google Scholar 

  10. Weintrop, D., Wilensky, U.: To block or not to block, that is the question: students' perceptions of blocks-based programming. In Proceedings of the 14th international conference on interaction design and children (pp. 199–208). (2015)https://doi.org/10.1145/2771839.2771860

  11. Barnes, D.J.: Teaching introductory Java through Lego Mindstorms models. ACM SIGCSE Bulletin 34(1), 147–151 (2001)

    Article  Google Scholar 

  12. Csikszentmihalyi, M.: Beyond boredom and anxiety. Jossey-Bass, San Francisco (2000)

    Google Scholar 

  13. Esteves, M., Fonseca, B., Morgado, L., Martins, P.: Improving teaching and learning of computer programming through the use of the Second Life virtual world. Br. J. Edu. Technol. 42(4), 624–637 (2011)

    Article  Google Scholar 

  14. Jormanainen, I., Kannusmäki, O., Sutinen, E.: IPPE-How to visualize programming with robots. In Proceedings of the Second Program Visualization Workshop (pp. 69–73) (2002)

  15. Rollins, M.: Beginning Lego Mindstorms Ev3. Apress, New York, NY (2014)

    Book  Google Scholar 

  16. Zhong, B., Xia, L.: A systematic review on exploring the potential of educational robotics in mathematics education. Int. J. Sci. Math. Educ. 18(1), 79–101 (2020)

    Article  Google Scholar 

  17. Dorouka, P., Papadakis, S., Kalogiannakis, M.: Tablets and apps for promoting robotics, mathematics, STEM education and literacy in early childhood education. Int J Mob Learn Org 14(2), 255–274 (2020)

    Google Scholar 

  18. Franklin, D., Skifstad, G., Rolock, R., Mehrotra, I., Ding, V., Hansen, A., Weintrop, D., Harlow, D.: Using upper-elementary student performance to understand conceptual sequencing in a blocks-based curriculum. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (pp. 231–236). (2017) https://doi.org/10.1145/3017680.3017760

  19. Venkatesh, V.: Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inf. Syst. Res. 11(4), 342–365 (2000)

    Article  Google Scholar 

  20. Yi, M.Y., Hwang, Y.: Predicting the use of web-based information systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. Int. J. Hum Comput Stud. 59(4), 431–449 (2003)

    Article  Google Scholar 

  21. Chang, C.K.: Effects of using Alice and Scratch in an introductory programming course for corrective instruction. J Edu Comput Res 51(2), 185–204 (2014)

    Article  Google Scholar 

  22. Weintrop, D., Wilensky, U.: Comparing block-based and text-based programming in high school computer science classrooms. ACM Transactions Comput Edu (TOCE) 18(1), 1–25 (2017). https://doi.org/10.1145/3089799

    Article  Google Scholar 

  23. Shin J, Magnenat S (2014) Visual programming language for Thymio II robot. Aarhus, Denmark: ETH-Zürich

  24. Smith, N., Sutcliffe, C., Sandvik, L.: Code club: Bringing programming to uk primary schools through scratch. In Proceedings of the 45th ACM technical symposium on Computer science education (pp. 517–522). ACM (2014)

  25. Wing, J.: Computational thinking. Commun. ACM 49(3), 33–35 (2006)

    Article  Google Scholar 

  26. Qualls, J.A., Sherrell, L.B.: Why computational thinking should be integrated into the curriculum. J. Comput. Sci. Coll. 25(5), 66–71 (2010)

    Google Scholar 

  27. Jenkins, T.: On the difficulty of learning to program. In Proceedings of 3rd Annual LTSN_ICS Conference, Loughborough University, UK, August 27–29, 2002 (pp. 53–58). (2002) York: The Higher Education Academy

  28. Lahtinen, E., Mutka, K. A., Jarvinen, H.M.: A study of the difficulties of novice programmers. In Proceedings of the 10th Annual SIGSCE Conference on Innovation and Technology in Computer Science Education (ITICSE 2005). Monte da Caparica, Portugal, June 27–29, 2005 (pp. 14–18). New York: ACM Press (2005)

  29. Lu, O.H., Huang, J.C., Huang, A.Y., Yang, S.J.: Applying learning analytics for improving students engagement and learning outcomes in an MOOCs enabled collaborative programming course. Interact. Learn. Environ. 25(2), 220–234 (2017)

    Article  Google Scholar 

  30. Schulte, C., Bennedsen, J.: What do teachers teach in introductory programming? In Proceedings of the Second International Workshop on Computing Education Research, Canterbury, UK, 2006 (pp. 17–28). (2006) ICER ‘06. New York: ACM

  31. Daungcharone, K., Panjaburee, P., Thongkoo, K.: A mobile game-based C programming language learning: results of university students’ achievement and motivations. Int J Mob Learn Org 13(2), 171–192 (2019)

    Google Scholar 

  32. Daungcharone, K., Panjaburee, P., Thongkoo, K.: Implementation of mobile game-transformed lecture-based approach to promoting C programming language learning. Int J Mob Learn Org 14(2), 236–254 (2020)

    Google Scholar 

  33. Carlisle, M.C., Wilson, T.A., Humphries, J.W., Hadfield, S.M.: RAPTOR: a visual programming environment for teaching algorithmic problem solving. In Proceedings of the 36th SIGCSE Technical Symposium on Computer Science Education (St. Louis, MO, February 23–27, 2005). SIGCSE ’05 (pp. 176–180). New York: ACM (2005)

  34. Kremer, R.: Visual languages for knowledge representation. Proc. of 11th Workshop on Knowledge Acquisition, Canada (1998)

  35. Johnston, W.M., Hanna, J.R.P., Millar, R.J.: Advances in dataflow programming languages. ACM Comput Surv (CSUR) 36(1), 1–34 (2004)

    Article  Google Scholar 

  36. Lam, C.T., Ke, W., Im, S.K., Gomes, A., Mendes, A.J., Marcelino, M.J.: Students’ characteristics in programming learning and the design of a mobile learning platform. Int J Mob Learn Org 13(4), 352–391 (2019)

    Google Scholar 

  37. Park, E.J.: Exploring LEGO Mindstorms EV3: Tools and techniques for building and programming robots. Wiley, Indianapolis, Indiana (2014)

    Google Scholar 

  38. Cockburn, A., Bryant, A.: Leogo: an equal opportunity user interface for programming. J. Vis. Lang. Comput. 8(5), 601–619 (1997)

    Article  Google Scholar 

  39. Hackbarth, G., Grover, V., Mun, Y.Y.: Computer playfulness and anxiety: positive and negative mediators of the system experience effect on perceived ease of use. Inform Manag 40(3), 221–232 (2003)

    Article  Google Scholar 

  40. Wu, W.Y., Chang, C.K., He, Y.Y.: Using Scratch as game-based learning tool to reduce learning anxiety in programming course. In Global Learn (Vol. 2010, No. 1, pp. 1845–1852) (2010)

  41. Felleisen, M., Findler, R.B., Flatt, M., Krishnamurthi, S.: The TeachScheme! project: computing and programming for every student. Comput. Sci. Educ. 14(1), 55–77 (2004)

    Article  Google Scholar 

  42. Ellis, M.J.: Why people play. Prentice-Hall, Englewood Cliffs, NJ (1973)

    Google Scholar 

  43. Lieberman, J.N.: Playfulness and divergent thinking: An investigation of their relationship at the kindergarten level. J. Genet. Psychol. 107(2), 219–224 (1965)

    Article  Google Scholar 

  44. Lieberman, N.J.: Playfulness: Its relationship to imagination and creativity. Academic Press, New York (1977)

    Google Scholar 

  45. Webster, J., Martocchio, J.J.: Microcomputer playfulness: development of a measure with workplace implications. MIS Q. 16(2), 201–226 (1992)

    Article  Google Scholar 

  46. Csikszentmihalyi, M.: Flow, the psychology of optimal experience. Harper & Row Publishers Inc, New York (1990)

    Google Scholar 

  47. Moon, J.W., Kim, Y.G.: Extending the TAM for a World-Wide-Web context. Inform Manage 38, 217–230 (2001)

    Article  Google Scholar 

  48. Byoung-Chan, L., Jeong-Ok, Y., In, L.: Learners’ acceptance of e-learning in South Korea: theories and results. Comput. Educ. 53(4), 1320–1329 (2009)

    Article  Google Scholar 

  49. Roca, J.C., Chiu, C.M., Martinez, F.J.: Understanding e-learning continuance intention: an extension of the technology acceptance model. Int. J. Hum Comput Stud. 64(8), 683–696 (2006)

    Article  Google Scholar 

  50. Lee, K.O.M., Cheung, C.M.K., Chen, Z.: Acceptance of internet-based learning medium: the role of extrinsic and intrinsic motivation. Inform Manage 42(8), 1095–1104 (2005)

    Article  Google Scholar 

  51. Jordan, P.W.: Designing pleasurable products: an introduction to the new human factors. Taylor & Francis, London, UK (2002)

    Google Scholar 

  52. Litman, J.A.: Curiosity and the pleasures of learning: wanting and liking new information. Cogn. Emot. 19(6), 793–814 (2005)

    Article  Google Scholar 

  53. Smith, P.A., Webb, G.I.: The efficacy of a low-level program visualization tool for teaching programming concepts to novice C programmers. J Edu Comput Res 22(2), 187–215 (2000)

    Article  Google Scholar 

  54. Pintrich, P.R., Smith, D.A.F., Garcia, T., McKeachie, W.J.: A manual for the use of the Motivational Strategies Learning Questionnaire (MSLQ). Ann Arbor, MI: University of Michigan, National Center for Research to Improve Postsecondary Teaching and Learning (1991)

  55. Bozionelos, N.: Computer anxiety: relationship with computer experience and prevalence. Comput. Hum. Behav. 17, 213–224 (2001)

    Article  Google Scholar 

  56. Chua, S., Chen, D., Wong, A.F.L.: Computer anxiety and its correlates: a meta-analysis. Comput. Hum. Behav. 15, 609–623 (1999)

    Article  Google Scholar 

  57. Wilfong, J.D.: Computer anxiety and anger: the impact of computer use, computer experience, and self-efficacy beliefs. Comput. Hum. Behav. 22(6), 1001–1011 (2006)

    Article  Google Scholar 

  58. Huffman, A.H., Whetten, J., Huffman, W.H.: Using technology in higher education: the influence of gender roles on technology self-efficacy. Comput. Hum. Behav. 29(4), 1779–1786 (2013)

    Article  Google Scholar 

  59. Singh, A., Bhadauria, V., Jain, A., Gurung, A.: Role of gender, self-efficacy, anxiety and testing formats in learning spreadsheets. Comput. Hum. Behav. 29(3), 739–746 (2013)

    Article  Google Scholar 

  60. Maurer, M.M., Simonson, M.R.: Development and validation of a Measure of computer anxiety: Paper presented at the Annual Meeting of the Association for Educational Communications and Technology (1984)

  61. Seraj, M., Katterfeldt, E.S., Autexier, S., Drechsler, R.: Impacts of Creating Smart Everyday Objects on Young Female Students' Programming Skills and Attitudes. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (pp. 1234–1240) (2020)

  62. Luo, F., Antonenko, P.D., Davis, E.C.: Exploring the evolution of two girls’ conceptions and practices in computational thinking in science. Comput. Educ. 146, 103759 (2020)

    Article  Google Scholar 

  63. Bishop-Clark, C., Courte, J., Howard, E.V.: Programming in pairs with Alice to improve confidence, enjoyment, and achievement. J Edu Comput Res 34(2), 213–228 (2006)

    Article  Google Scholar 

  64. Lewis, C.M.: How programming environment shapes perception, learning and goals: logo vs. scratch. In Proceedings of the 41st ACM technical symposium on Computer science education (pp. 346–350) (2010) https://doi.org/10.1145/1734263.1734383

  65. Bishop-Clark, C., Courte, J., Evans, D., Howard, E.V.: A quantitative and qualitative investigation of using Alice programming to improve confidence, enjoyment and achievement among non-majors. J Edu Comput Res 37(2), 193–207 (2007)

    Article  Google Scholar 

  66. Fiorini, P.: LEGO kits in the lab [robotics education]. Robot Autom Mag, IEEE 12(4), 5 (2005)

    Article  Google Scholar 

  67. Venkatesh, V., Bala, H.: Technology acceptance model 3 and a research agenda on interventions. Decis. Sci. 39(2), 273–315 (2008)

    Article  Google Scholar 

  68. Webb, N.M.: The role of gender in computer programming learning processes. J Edu Comput Res 1(4), 441–458 (1985)

    Article  Google Scholar 

  69. Schaefer, L., Sprigle, J.E.: Gender differences in the use of the Logo programming language. J Edu Comput Res 4(1), 49–55 (1988)

    Article  Google Scholar 

  70. Serrano-Cámara, L.M., Paredes-Velasco, M., Alcover, C.M., Velazquez-Iturbide, J.Á.: An evaluation of students’ motivation in computer-supported collaborative learning of programming concepts. Comput. Hum. Behav. 31, 499–508 (2014)

    Article  Google Scholar 

  71. Abdul-Rahman, S.S., Du Boulay, B.: Learning programming via worked-examples: relation of learning styles to cognitive load. Comput. Hum. Behav. 30, 286–298 (2014)

    Article  Google Scholar 

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Acknowledgements

This study is supported in part by the Ministry of Science and Technology of the Republic of China under contract numbers MOST-108-2511-H-011-005-MY3.

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Correspondence to Gwo-Jen Hwang.

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This study has been reviewed and approved by the academic ethics committee of the institution. The participants were protected by hiding their personal information during the research process. They knew that their participation was voluntary and they could withdraw from the study at any time.

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Hsu, TC., Hwang, GJ. Interaction of visual interface and academic levels with young students’ anxiety, playfulness, and enjoyment in programming for robot control. Univ Access Inf Soc 22, 213–225 (2023). https://doi.org/10.1007/s10209-021-00821-3

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