Abstract
Based on connectivism pedagogy crowd-based education provides a practical method to extensively exploit wisdoms of core learners in education organization and external crowds on Internet. However, when applying such a method in education field, several design questions about why, what, when, who, where and how to adopt such method should be clarified and elaborated. In this paper, we introduce our successful applications of the crowd-based method in software engineering course for undergraduates. We design an organization structure consisting of “small-core crowd” and “large-external crowd” for our course projects in which both learners and crowds on Internet work together to contribute their wisdoms. Two kinds of wisdoms of crowds are exploited in our practices. One is the high-quality open source software (OSS) developed by crowds on the Internet, the other is the diverse software development issues, knowledges, experiences, expertise, etc., that are discussed and interacted by crowds in OSS communities and course communities. We design several course practice activities to exploit crowds’ wisdoms, including reading high-quality OSS, searching and reusing OSS in course project, joining and getting helps from OSS communities. The results show that the crowd-based method applied in our software engineering course can significantly improve learner’s engineering capabilities of developing high-quality and large-scale software.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Fox, A.: From MOOCs to SPOCs. Commun. ACM 56(12), 38–40 (2013)
Weld, D.S., Adar, E., Chilton, L., et al.: Personalized online education - a crowdsourcing challenge In: Workshops at the 26th AAAI Conference on Artificial Intelligence, pp. 1–31 (2012)
Levy, P.: Collective intelligence for educators. Educ. Philos. Theory 47(8), 749–754 (2015)
Zhao, Y., Zhu, Q.: Evaluation on crowdsourcing research: Current status and future direction. Inf. Syst. Front. 16(3), 417–434 (2014)
Brabham, D.C.: Crowdsourcing as a model for problem solving: an introduction and cases. Convergence 14(1), 75–90 (2008)
Foulger, T.S.: The 21st-century teacher educator and crowdsourcing. J. Digit. Learn. Teach. Educ. 30(3), 110 (2014)
Li, W., Tsai, W.-T., Wu, W.: Crowdsourcing for large-scale software development. In: Li, W., Huhns, Michael N., Tsai, W.-T., Wu, W. (eds.) Crowdsourcing. PI, pp. 3–23. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-47011-4_1
Graziosi, S., Ferrise, F.: Crowdsourcing and organizational forms: emerging trends and research implications. Appl. Cogn. Psychol. 19(1), 137–138 (2015)
Al-Jumeily, D., Hussain, A., Alghamdi, M., et al.: Educational crowdsourcing to support the learning of computer programming. Res. Pract. Technol. Enhanc. Learn. 10(1), 1–15 (2015)
Sylaiou, S., Tampaki, S.: Crowdsourcing in education: challenges and perspectives, In: International Conference on Reimagining Schooling (2013)
Howe, J.: The Rise of Crowdsourcing; Jenkins, H.: Convergence Culture Where Old & New Media Collide 14(14), 15 (2006)
Al Sohibani, M., Al Osaimi, N., Al Ehaidib, R., Al Muhanna, S., Dahanayake, A.: Factors that influence the quality of crowdsourcing. In: Bassiliades, N., Ivanovic, M., Kon-Popovska, M., Manolopoulos, Y., Palpanas, T., Trajcevski, G., Vakali, A. (eds.) New Trends in Database and Information Systems II. AISC, vol. 312, pp. 287–300. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-10518-5_22
Anderson, T., Dron, J.: Three generations of distance education pedagogy. Int. Rev. Res. Open Distrib. Learn. 12(3), 1–8 (2011)
Kultawanich, K., Koraneekij, P., Na-Songkhla, J.: A proposed model of connectivism learning using cloud-based virtual classroom to enhance information literacy and information literacy self-efficacy for undergraduate students. Procedia - Soc. Behav. Sci. 191, 87–92 (2015)
Dunaway, M.K.: Connectivism: learning theory and pedagogical practice for networked information landscapes. Ref. Serv. Rev. 39(4), 675–685 (2011)
Reese, S.A.: Online learning environments in higher education: Connectivism vs. dissociation. Educ. Inf. Technol. 20(3), 579–588 (2015)
Siemens, G.: Connectivism: a learning theory for the digital age. Int. J. Instr. Technol. Distance Learn. (2004). Retrieved from http://www.elearnspace.org/Articles/connectivism.htm
Salter, M.B.: Crowdsourcing: student-driven learning using web 2.0 technologies in an introduction to globalization. J. Polit. Sci. Educ. 9(3), 362–365 (2013)
Crompton, H., Burke, D., Gregory, K.H., Gräbe, C.: The use of mobile learning in science: a systematic review. J. Sci. Educ. Technol. 25(2), 149–160 (2017)
Clarà, M., Barberà, E.: Learning online: massive open online courses (MOOCs), connectivism, and cultural psychology. Distance Educ. 34(1), 129–136 (2013)
Mao, X., Hou, F., Wu, W.: Multi-agent system approach for modeling and supporting software crowdsourcing. In: Li, W., Huhns, M.N., Tsai, W.-T., Wu, W. (eds.) Crowdsourcing. PI, pp. 73–89. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-47011-4_5
Skaržauskaitė, M.: The application of crowd sourcing in educational activities. Soc. Technol. 15(1), 43–53 (2012)
Hong, H.-Y., Chai, C.S., Tsai, C.-C.: College students constructing collective knowledge of natural science history in a collaborative knowledge building community. J. Sci. Educ. Technol. 24(5), 549–561 (2016)
Acknowledgments
We greatly thank the project supports of National Key R&D Program of China (2018YFB1004202) and National Science Foundation of China (61532004), the undergraduates that participate in the practices, the Trustie development and technical support team.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Mao, X., Lu, Y., Yin, L., Wang, T., Yin, G. (2018). Model and Practice of Crowd-Based Education. In: U, L., Xie, H. (eds) Web and Big Data. APWeb-WAIM 2018. Lecture Notes in Computer Science(), vol 11268. Springer, Cham. https://doi.org/10.1007/978-3-030-01298-4_25
Download citation
DOI: https://doi.org/10.1007/978-3-030-01298-4_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01297-7
Online ISBN: 978-3-030-01298-4
eBook Packages: Computer ScienceComputer Science (R0)