Abstract
In order to reduce students’ difficulties in programming learning, this study developed a mobile platform called Dquiz with the advantage of distributed effects, which can provide 2-3 multiple-choice questions per day. The study applied it to C programming courses and explored whether the system can improve students’ learning outcome and which factor influence the outcome. A total number of 74 freshmen were randomly divided into two groups. One group can practice every 3 days at least. The other students practice once a week. Both groups of students practice the same number of questions. The result showed that the students who used the platform several times a week score higher than students who used it once a week. The factors that affect students’ learning outcomes during their practice include intervals of platform usage, correctness and the total number of comments.
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References
[1] Truong, N., Bancroft, P., Roe, P.: A web-based environment for learning to program. In Proceedings of the 26th Australasian computer science conference-Volume 16. Australian Computer Society, Inc. (2003)
[2] Wang, L., Pan J.B., Feng H.Y.: Study on the New Teaching Mode of College Classroom Based on BYOD. Modern Educational Technology. (1), 39–45(2015)
[3] Huang J. F.: Research on fragmented learning strategies based on “Internet+”—transformation from “fragmentation” to “whole”. E-education Research. 38(8), 78–82 (2017)
[4] Winslow, L. E.: Programming pedagogy—a psychological overview. ACM Sigcse Bulletin. 28(3), 17–22(1996)
[5] Dunlosky, J., Rawson, K. A.: Practice tests, spaced practice, and successive relearning: Tips for classroom use and for guiding students’ learning. Scholarship of Teaching and Learning in Psychology. 1(1), 72(2015)
[6] Roediger III, H. L., Marsh, E. J.: The positive and negative consequences of multiple-choice testing.Journal of Experimental Psychology: Learning, Memory, and Cognition.31(5), 1155 (2005)
[7] Butler, A. C., Roediger, H. L.: Feedback enhances the positive effects and reduces the negative effects of multiple-choice testing. Memory & Cognition. 36(3), 604–616(2008)
[8] Hovemeyer, D., pacco, J.: CloudCoder: a web-based programming exercise system. Journal of Computing Sciences in Colleges, 28(3), 30–30 (2013)
[9] Pritchard, D., Vasiga, T.: CS circles: an in-browser python course for beginners. In Proceeding of the 44th ACM technical symposium on Computer science education (pp. 591–596). ACM (2013)
[10] Marcelino, M., Mihaylov, T., Mendes, A.: H-SICAS, a handheld algorithm animation and simulation tool to support initial programming learning. In Frontiers in Education Conference, 2008. FIE 2008. 38th Annual (pp. T4A–7). IEEE (2008)
[11] Tillmann, N., Moskal, M., De Halleux, J., Fahndrich, M., Bishop, J., Samuel, A., Xie, T.: The future of teaching programming is on mobile devices. In Proceedings of the 17th ACM annual conference on Innovation and technology in computer science education (pp. 156–161). ACM (2012)
[12] Karpicke, J. D., Roediger III, H. L.: Repeated retrieval during learning is the key to long-term retention. Journal of Memory and Language. 57(2), 151–162 (2007)
[13] Gerbier, E., Toppino, T. C.: The effect of distributed practice: Neuroscience, cognition, and education. Trends in Neuroscience and Education. 4(3), 49–59 (2015)
[14] Barry, N. H.: The effects of practice strategies, individual differences in cognitive style, and gender upon technical accuracy and musicality of student instrumental performance. Psychology of Music. 20(2), 112–123 (1992)
[15]Rohrer, D., Taylor, K.: The effects of overlearning and distributed practice on the retention of mathematics knowledge. Applied Cognitive Psychology: The Official Journal of the Society for Applied Research in Memory and Cognition. 20(9), 1209–1224 (2006)
[16] Alzaid, M., Trivedi, D., Hsiao, I. H.: The effects of bite-size distributed practices for programming novices. In Frontiers in Education Conference (FIE) (pp. 1–9). IEEE (2017)
[17] Zhang, L.S., Li, B.P. Zhang, Q.J., Hsiao. Can distributed practice improve students’ efficiency in learning their first programming language? [C]. Proceedings of the 25th International Conference on Computers in Education. New Zealand ( 2017)
[18] Ma, Y.H., Zhao, L., Li, N.N., Wang, S.S.: A New Type of Mobile Learning Resources—A Probe into the Development Model of Education APP [J]. China Educational Technology. 64–70 (2016)
[19] Yang, T. C., Hwang, G. J., Yang, S. J. H., Hwang, G. H.: A Two-Tier Test-based Approach to Improving Students’ Computer-Programming Skills in a Web-Based Learning Environment. Journal of Educational Technology & Society. 18(1), 198–210 (2015)
[20] Cetin, I., Sendurur, E., Sendurur, P.: Assessing the Impact of Meta-Cognitive Training on Students’ Understanding of Introductory Programming Concepts. Journal of Educational Computing Research. 50(4), 507–524 (2014)
[21] Gerbier, E., Toppino, T. C.: The effect of distributed practice: Neuroscience, cognition, and education. Trends in Neuroscience and Education. 4(3), 49–59 (2015)
[22] Karpicke, J. D., Roediger III, H. L.: Repeated retrieval during learning is the key to long-term retention. Journal of Memory and Language. 57(2), 151–162 (2007)
[23] Chai, S.M., Li, K.D.: Research on the Construction of Collaborative Meaning Based on Dialogue in CSCL [J]. Journal of Distance Education. 28(04),19–26(2010)
[24] Wu X. j., Zhang H., Ni J. Q.: Deep Learning Based on Reflection: Connotation and Process. E-education Research. 35(12), 23–28(2014)
[25] Dunleavy, J., Milton, P.: Student engagement for effective teaching and deep learning. Education Canada.48(5), 4–8(2008)
Acknowledgments
This research was supported by Open Funding Project of the Key Laboratory of Modern Teaching Technology, MOE of PRC(Grant No. SYSK201802).
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Zhang, L., Li, B., Zhou, Y., Chen, L. (2019). Can Fragmentation Learning Promote Students’ Deep Learning in C Programming?. In: Chang, M., et al. Foundations and Trends in Smart Learning. Lecture Notes in Educational Technology. Springer, Singapore. https://doi.org/10.1007/978-981-13-6908-7_7
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DOI: https://doi.org/10.1007/978-981-13-6908-7_7
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