Skip to main content
SpringerLink
Log in

Understanding Public Perceptions of K-12 Computational Thinking Education Through an Analysis of Quora

  • Conference paper
  • First Online:
Social Computing and Social Media (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14026))

Included in the following conference series:

  • 562 Accesses

Abstract

As more education systems integrate mandatory computational thinking (CT) classes into their curricula, understanding how the public perceives this issue is an important step in making educational policies and implementing educational reform. In this paper, we retrieved all accessible texts related to K-12 CT education on the Quora platform. The textual data obtained ranged from June 2010 to September 2022. We then performed topic modeling analysis to identify major topics and uncover meaningful themes of the public responses to CT education initiatives. In general, people expressed positive comments about CT education. However, they were still concerned about the difficulties in learning and education equality for disadvantaged groups. In addition, since CT practices develop students' essential skills in the job market, people may overestimate the outcomes of CT education. Our findings provide insights into public perceptions of children’s CT education. The results of this study can facilitate education policymaking, curriculum design, and further research directions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Papert, S.: Mindstorms: children, computers, and powerful ideas. Basic Books, New York (1980)

    Google Scholar 

  2. Wing, J.M.: Computational thinking. Commun. ACM. 49, 33–35 (2006). https://doi.org/10.1145/1118178.1118215

    Article  Google Scholar 

  3. Computer Science Teachers Association (CSTA), International Society for Technology Education (ISTE): operational definition of computational thinking (2011)

    Google Scholar 

  4. Yu, J., Bai, C., Roque, R.: Considering parents in coding kit design. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–14. ACM, New York (2020). https://doi.org/10.1145/3313831.3376130

  5. Maruyama, Y.: Investigation into parents’ impressions of computer programming with comparisons before and after a programming workshop. In: Uskov, V., Howlett, R., and Jain, L., (eds.) Smart Innovation, Systems and Technologies. pp. 421–431. Springer Nature Singapore (2019). https://doi.org/10.1007/978-981-13-8260-4_38/TABLES/5

  6. Kong, S.-C., Wang, Y.-Q.: The influence of parental support and perceived usefulness on students’ learning motivation and flow experience in visual programming: investigation from a parent perspective. Br. J. Educ. Technol. 52, 1749–1770 (2021). https://doi.org/10.1111/bjet.13071

    Article  Google Scholar 

  7. Davis III, C.H.F., Deil-Amen, R., Rios-Aguilar, C., González Canché, M.S.: Social media, higher education, and community colleges: a research synthesis and implications for the study of two-year institutions. Community Coll. J. Res. Pract. 39, 409–422 (2015). https://doi.org/10.1080/10668926.2013.828665

  8. Goodyear, V.A., Casey, A., Kirk, D.: Tweet me, message me, like me: using social media to facilitate pedagogical change within an emerging community of practice. Sport. Educ. Soc. 19, 927–943 (2014). https://doi.org/10.1080/13573322.2013.858624

    Article  Google Scholar 

  9. Malin, J.R., Lubienski, C.: Educational expertise, advocacy, and media influence. Educ. Policy Anal. Arch. 23, 6 (2015). https://doi.org/10.14507/epaa.v23.1706

  10. Daly, A.J., Supovitz, J., Fresno, M.D.: The social side of educational policy: how social media is changing the politics of education. Teach. Coll. Rec. Voice Scholarsh. Educ. 121, 1–26 (2019). https://doi.org/10.1177/016146811912101402

    Article  Google Scholar 

  11. Barr, V., Stephenson, C.: Bringing computational thinking to K-12. ACM Inroads. 2, 48–54 (2011). https://doi.org/10.1145/1929887.1929905

    Article  Google Scholar 

  12. Bocconi, S., et al.: Reviewing computational thinking in compulsory education. Publications Office of the European Union, Luxembourg (2022). https://doi.org/10.2760/126955

  13. Hsu, T.-C., Chang, S.-C., Hung, Y.-T.: How to learn and how to teach computational thinking: suggestions based on a review of the literature. Comput. Educ. 126, 296–310 (2018). https://doi.org/10.1016/j.compedu.2018.07.004

    Article  Google Scholar 

  14. Shute, V.J., Sun, C., Asbell-Clarke, J.: Demystifying computational thinking. Educ. Res. Rev. 22, 142–158 (2017). https://doi.org/10.1016/j.edurev.2017.09.003

    Article  Google Scholar 

  15. Bers, M.U.: Coding as a playground. Routledge, New York (2017). https://doi.org/10.4324/9781315398945

  16. Buitrago Flórez, F., Casallas, R., Hernández, M., Reyes, A., Restrepo, S., Danies, G.: Changing a generation’s way of thinking: teaching computational thinking through programming. Rev. Educ. Res. 87, 834–860 (2017). https://doi.org/10.3102/0034654317710096

    Article  Google Scholar 

  17. Zhang, L., Nouri, J.: A systematic review of learning computational thinking through scratch in K-9. Comput. Educ. 141, 103607 (2019). https://doi.org/10.1016/j.compedu.2019.103607

    Article  Google Scholar 

  18. Lye, S.Y., Koh, J.H.L.: Review on teaching and learning of computational thinking through programming: what is next for K-12? Comput. Human Behav. 41, 51–61 (2014). https://doi.org/10.1016/j.chb.2014.09.012

    Article  Google Scholar 

  19. Wong, G.K.-W., Cheung, H.-Y.: Exploring children’s perceptions of developing twenty-first century skills through computational thinking and programming. Interact. Learn. Environ. 28, 438–450 (2020). https://doi.org/10.1080/10494820.2018.1534245

    Article  Google Scholar 

  20. Maruyama, Y., Kanoh, H., Adachi, K.: A preliminary investigation into parents’ concerns about programming education in Japanese primary schools. In: Proceedings of the 14th International Conference on Cognition and Exploratory Learning in Digital Age, pp. 286–290. Springer, Vilamoura (2017)

    Google Scholar 

  21. Vivian, R., Falkner, K., Szabo, C.: Can everybody learn to code? In: Proceedings of the 14th Koli Calling International Conference on Computing Education Research, pp. 41–50. ACM, New York (2014). https://doi.org/10.1145/2674683.2674695

  22. Kong, R., Wong, G.K.W.: Teachers’ perception of professional development in coding education. In: 2017 IEEE 6th International Conference on Teaching, Assessment, and Learning for Engineering (TALE), pp. 377–380. IEEE, Hongkong (2017). https://doi.org/10.1109/TALE.2017.8252365

  23. Wong, G.K.W., Cheung, H.Y., Ching, E.C.C., Huen, J.M.H.: School perceptions of coding education in K-12: A large scale quantitative study to inform innovative practices. In: 2015 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), pp. 5–10. IEEE, Zhuhai (2015). https://doi.org/10.1109/TALE.2015.7386007

  24. Humble, N., Mozelius, P., Sällvin, L.: Remaking and reinforcing mathematics and technology with programming – teacher perceptions of challenges, opportunities and tools in K-12 settings. Int. J. Inf. Learn. Technol. 37, 309–321 (2020). https://doi.org/10.1108/IJILT-02-2020-0021

    Article  Google Scholar 

  25. Greifenstein, L., Graßl, I., Fraser, G.: Challenging but full of opportunities: teachers’ perspectives on programming in primary schools. 21st Koli Call. Int. Conf. Comput. Educ. Res. 1–10 (2021). https://doi.org/10.1145/3488042.3488048

  26. Cohen, L., Manion, L., Morrison, K.: Research methods in education, 8th edn. Routledge, London (2017)

    Book  Google Scholar 

  27. Blackstone, A.: Principles of sociological inquiry: qualitative and quantitative methods. Saylor Academy Open Textbooks (2018)

    Google Scholar 

  28. Aelieve: website rankings for the best question and answer sites. https://aelieve.com/rankings/websites/category/reference/best-question-and-answer-sites/. Accessed 25 Jan 2023

  29. Jiang, H., Qiang, M., Zhang, D., Wen, Q., Xia, B., An, N.: Climate change communication in an online Q&A community: a case study of Quora. Sustainability. 10, 1509 (2018). https://doi.org/10.3390/su10051509

    Article  Google Scholar 

  30. Maity, S.K., Kharb, A., Mukherjee, A.: Language use matters: analysis of the linguistic structure of question texts can characterize answerability in Quora. In: Proceedings of the 11th International Conference on Web and Social Media, ICWSM 2017, pp. 612–615. AAAI, California (2017). https://doi.org/10.48550/arXiv.1703.04001

  31. Maity, S.K., Kharb, A., Mukherjee, A.: Analyzing the linguistic structure of question texts to characterize answerability in Quora. IEEE Trans. Comput. Soc. Syst. 5, 816–828 (2018). https://doi.org/10.1109/TCSS.2018.2859964

    Article  Google Scholar 

  32. Zhao, Y., Min, C., Han, X., Deng, S., Wang, H., Li, J.: Listening to the user’s voice: a temporal analysis of autism-related questions on Quora. Proc. Assoc. Inf. Sci. Technol. 56, 513–516 (2019). https://doi.org/10.1002/pra2.57

    Article  Google Scholar 

  33. Le, T.D., Dobele, A.R., Robinson, L.J.: Information sought by prospective students from social media electronic word-of-mouth during the university choice process. J. High. Educ. Policy Manag. 41, 18–34 (2019). https://doi.org/10.1080/1360080X.2018.1538595

    Article  Google Scholar 

  34. Blei, D.M.: Probabilistic topic models. Commun. ACM. 55, 77–84 (2012). https://doi.org/10.1145/2133806.2133826

    Article  Google Scholar 

  35. Cao, J., Xia, T., Li, J., Zhang, Y., Tang, S.: A density-based method for adaptive LDA model selection. Neurocomputing 72, 1775–1781 (2009). https://doi.org/10.1016/J.NEUCOM.2008.06.011

    Article  Google Scholar 

  36. Deveaud, R., SanJuan, E., Bellot, P.: accurate and effective latent concept modeling for ad hoc information retrieval. Doc. Numer. 17, 61–84 (2014). https://doi.org/10.3166/DN.17.1.61-84

    Article  Google Scholar 

  37. Pereira, A.I., Barros, L., Mendonça, D., Muris, P.: The relationships among parental anxiety, parenting, and children’s anxiety: the mediating effects of children’s cognitive vulnerabilities. J. Child Fam. Stud. 23(2), 399–409 (2013). https://doi.org/10.1007/s10826-013-9767-5

    Article  Google Scholar 

  38. Ma, X., Shen, J., Krenn, H.Y., Hu, S., Yuan, J.: A meta-analysis of the relationship between learning outcomes and parental involvement during early childhood education and early elementary education. Educ. Psychol. Rev. 28(4), 771–801 (2015). https://doi.org/10.1007/s10648-015-9351-1

    Article  Google Scholar 

  39. Park, S., Stone, S.I., Holloway, S.D.: School-based parental involvement as a predictor of achievement and school learning environment: an elementary school-level analysis. Child. Youth Serv. Rev. 82, 195–206 (2017). https://doi.org/10.1016/j.childyouth.2017.09.012

    Article  Google Scholar 

  40. Zellman, G.L., Waterman, J.M.: Understanding the impact of parent school involvement on children’s educational outcomes. J. Educ. Res. 91, 370–380 (1998). https://doi.org/10.1080/00220679809597566

    Article  Google Scholar 

  41. Boonk, L., Gijselaers, H.J.M., Ritzen, H., Brand-Gruwel, S.: A review of the relationship between parental involvement indicators and academic achievement. Educ. Res. Rev. 24, 10–30 (2018). https://doi.org/10.1016/j.edurev.2018.02.001

    Article  Google Scholar 

  42. Biolsi, C., Craig, S.G., Dhar, A., Sørensen, B.E.: Inequality in public school spending across space and time. Rev. Econ. Dyn. 46, 244–279 (2022). https://doi.org/10.1016/j.red.2021.09.004

    Article  Google Scholar 

  43. Katz, V., Rideout, V.: Learning at home while under-connected (2021)

    Google Scholar 

  44. Phillips-Wren, G., Adya, M.: Decision making under stress: the role of information overload, time pressure, complexity, and uncertainty. J. Decis. Syst. 29, 213–225 (2020). https://doi.org/10.1080/12460125.2020.1768680

    Article  Google Scholar 

  45. Ma, Y., Siu, A., Tse, W.S.: The role of high parental expectations in adolescents’ academic performance and depression in Hong Kong. J. Fam. Issues. 39, 2505–2522 (2018). https://doi.org/10.1177/0192513X18755194

    Article  Google Scholar 

  46. Kanter Agliata, A., Renk, K.: College students’ affective distress: the role of expectation discrepancies and communication. J. Child Fam. Stud. 18, 396–411 (2009). https://doi.org/10.1007/s10826-008-9244-8

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore, Singapore

    Stella Xin Yin & Dion Hoe-Lian Goh

  2. National Institute of Education, Nanyang Technological University, Singapore, Singapore

    Choon Lang Quek

  3. Institute for Infocomm Research, A*STAR, Singapore, Singapore

    Zhengyuan Liu

Authors
  1. Stella Xin Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dion Hoe-Lian Goh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Choon Lang Quek
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhengyuan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dion Hoe-Lian Goh .

Editor information

Editors and Affiliations

  1. University of Bucharest, Bucharest, Romania

    Adela Coman

  2. University of Tsukuba, Tsukuba, Japan

    Simona Vasilache

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yin, S.X., Goh, D.HL., Quek, C.L., Liu, Z. (2023). Understanding Public Perceptions of K-12 Computational Thinking Education Through an Analysis of Quora. In: Coman, A., Vasilache, S. (eds) Social Computing and Social Media. HCII 2023. Lecture Notes in Computer Science, vol 14026. Springer, Cham. https://doi.org/10.1007/978-3-031-35927-9_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-35927-9_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-35926-2

  • Online ISBN: 978-3-031-35927-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation