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Design of Algorithm Thinking-Based Software Basic Education for Nonmajors

비전공자를 위한 알고리즘씽킹 기반 소프트웨어 기초교육 설계

  • Received : 2019.11.07
  • Accepted : 2019.11.10
  • Published : 2019.11.30

Abstract

Purpose: The purpose of this study is to design the curriculum of Basic College Software Programming to develop creative and logical-thinking. This course is guided by algorithmic thinking and logical thinking that can be solved by computing for problem-solving, and it helps to develop by software through basic programming education. Through the stage of problem analysis, abstraction, algorithm, data structure, and algorithm implementation, the curriculum is designed to help learners experience algorithm problem-solving in various areas to develop diffusion thinking. For Learners aim to achieve the balanced development of divergent and convergent-thinking needed in their creative problem-solving skills. Research design, data and methodology: This study is to design a basic software education for improving algorithm-thinking for non-major. The curriculum designed in this paper is necessary to non-majors students who have completed the 'Creative Thinking and Coding Course' Design Thinking based are targeted. For this, contents were extracted through advanced research analysis at home and abroad, and experts in computer education, computer engineering, SW education, and education were surveyed in the form of quasi-openness. Results: In this study, based on ADD Thinking's algorithm thinking, we divided the unit college majors into five groups so that students of each major could accomplish the goal of "the ability to internalize their own ideas into computing," and extracted and designed different content areas, content elements and sub-components from each group. Through three expert surveys, we established a strategy for characterization by demand analysis and major/textbook category and verified the appropriateness of the design direction to ensure that the subjects and contents of the curriculum are appropriate for each family in order to improve algorithm-thinking. Conclusions: This study helps develop software by enhancing the ability of students who practice various subjects and exercises to explore creative expressions in various areas, such as 'how to think like a computer' that can implement and execute their ideas in computing. And it helps increase the ability to think logical and algorithmic computing based on creative solutions, improving problem-solving ability based on computing thinking and fundamental understanding of computer coding and development of logical thinking ability through programming.

Keywords

References

  1. Bennett, V., Koh Koh, K., & RepenningRepenning, A. (2013). Computing creativity: Divergence in computational thinking. Proceeding of the 44th ACM Technical Symposium on computer science education, 359-364.
  2. Cronbach, L. J., & Shavelson, R R. J. (2004). My current thoughts on coefficient Alpha and Successor Procedures. Educational and Psychological Measurement Measurement, 64(3), 391-418 . https://doi.org/10.1177/0013164404266386
  3. Denning, P. J. (2017). Remaining trouble spots with computational thinking. Communications of the ACM, 60(6), 33-39. https://doi.org/10.1145/2998438
  4. Kim, D. H., & Ju ng, H. J. (2018). Learning process monitoring of e-learning for corporate education. Journal of Industrial Distribution & Business, 9(8), 35-40. https://doi.org/10.13106/IJIDB.2018.VOL9.NO8.35.
  5. Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28 (4), 563-575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x
  6. Lee, J. E., Kwon, S. J., & Jung, H. J. (2018). Introduction and a ctivation strategies for smart training of corporate. Journal of Industrial Distribution & Business, 9(5), 83-91. https://doi.org/10.13106/IJIDB.2018.VOL9.NO5.83.
  7. Min, G. O., & Loh, J. H. (2016). Impact of e ducational service information distribution on students’ satisfaction and achievement rate. Journal of Industrial Distribution & Business, 7(4), 17-31. https://doi.org/10.13106/ijidb.2016.vol7.no4.17.
  8. Oh, K. S., & Kwon, J. I. (2019). A study on the verification of computational thinking effectiveness of understandingnderstanding-oriented SW basic education program. Journal of Digital Convergence, 17 (10), 23-35.
  9. Oh, K. S., Suh, E. K., & Chung, H. J. ( 2018). A study on development of educational contents about combining computational thinking with design thinkingthinking. Journal of Digital Convergence, 16 (5), 65-73. https://doi.org/10.14400/JDC.2018.16.5.065
  10. Pi, S. Y. ( 20162016). A s tudy on coding education of nonnon-computer majors for IT convergence education. The Korea Society of Digital Policy & Management, 1-8.
  11. Shin, Y. H., Jung, H. J., & E. K. (2019). Analysis of learning experience in design thinkinghinking-based coding education for SW non-major college s tudents. Journal of Digital Contents Society, 20 (4), 759-768. https://doi.org/10.9728/dcs.2019.20.4.759
  12. Shon S., H. (2019). A study on the exploration of the core capabilities of design future talent against the fourth Industrial Revolution. Journal of the Korean Society Design Culture, 25 (2), 305-315. https://doi.org/10.18208/ksdc.2019.25.2.305
  13. Suh, E. K. ( 2017). Development of c reative thinking and coding course method on design t hinking using flipped learning. Korean Association f or Learner Learner-Centered Curriculum and Instruction, 17 (16) 173-199. https://doi.org/10.22251/jlcci.2017.17.16.173
  14. Suh, E. K., Oh, K. S., & Chung, H. J. (2018) Creative thinking and codingoding(Engineering). YonginYongin-si, Korea:Nosvos.
  15. Tedre, M., & Denning, P. J. (2016). The long quest for computational thinking. Proceedings of the 16th Koli Calling Conference, 120-129. New York, NY: Computing Education Research. DOI: 10.1145/2999541.2999542
  16. Wang, Y., Widrow, B., Zadeh, L. A., Howard, N., Wood, S., Bhavsar, V. C., Budin, G., Chan, C., Fiorini, R. A., Gavrilova, M. L., & Shell, D. F. (2016 ). Cognitive intelligence: Deep learning, thinking, and reas oning by brainbrain-inspired systems. International Journal of Cognitive Informatics and Natural Intelligence, 10 (4), 1-20.
  17. Wing, J. M. (2006). Computational thinking thinking. Communications of the ACM, 49 (3), 33-35. https://doi.org/10.1145/1118178.1118215
  18. Yoon, O. H. (2017). A study of the instructional systems design model for STEAM educationducation: Focus on design thinking. Korean Journal of General Education, 11 (1), 443-474.

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