IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v12y2020i8p137-d399939.html
   My bibliography  Save this article

Progressive Teaching Improvement For Small Scale Learning: A Case Study in China

Author

Listed:
  • Bo Jiang

    (School of Educational Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

  • Yanbai He

    (School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

  • Rui Chen

    (School of Overseas Education, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

  • Chuanyan Hao

    (School of Educational Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

  • Sijiang Liu

    (School of Educational Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

  • Gangyao Zhang

    (School of Educational Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

Abstract

Learning data feedback and analysis have been widely investigated in all aspects of education, especially for large scale remote learning scenario like Massive Open Online Courses (MOOCs) data analysis. On-site teaching and learning still remains the mainstream form for most teachers and students, and learning data analysis for such small scale scenario is rarely studied. In this work, we first develop a novel user interface to progressively collect students’ feedback after each class of a course with WeChat mini program inspired by the evaluation mechanism of most popular shopping website. Collected data are then visualized to teachers and pre-processed. We also propose a novel artificial neural network model to conduct a progressive study performance prediction. These prediction results are reported to teachers for next-class and further teaching improvement. Experimental results show that the proposed neural network model outperforms other state-of-the-art machine learning methods and reaches a precision value of 74.05% on a 3-class classifying task at the end of the term.

Suggested Citation

  • Bo Jiang & Yanbai He & Rui Chen & Chuanyan Hao & Sijiang Liu & Gangyao Zhang, 2020. "Progressive Teaching Improvement For Small Scale Learning: A Case Study in China," Future Internet, MDPI, vol. 12(8), pages 1-15, August.
    • Handle: RePEc:gam:jftint:v:12:y:2020:i:8:p:137-:d:399939
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/12/8/137/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/12/8/137/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John C. Yi & Christina D. Kang-Yi & Flavia Burton & H. David Chen, 2018. "Predictive Analytics Approach to Improve and Sustain College Students’ Non-Cognitive Skills and Their Educational Outcome," Sustainability, MDPI, vol. 10(11), pages 1-14, November.
    2. Geng Sun & Tingru Cui & Ghassan Beydoun & Shiping Chen & Fang Dong & Dongming Xu & Jun Shen, 2017. "Towards Massive Data and Sparse Data in Adaptive Micro Open Educational Resource Recommendation: A Study on Semantic Knowledge Base Construction and Cold Start Problem," Sustainability, MDPI, vol. 9(6), pages 1-21, May.
    3. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 2.
    4. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 4.
    5. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 3.
    6. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 1.
    7. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 4.
    8. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 3.
    9. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 2.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chuanyan Hao & Anqi Zheng & Yuqi Wang & Bo Jiang, 2021. "Experiment Information System Based on an Online Virtual Laboratory," Future Internet, MDPI, vol. 13(2), pages 1-19, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kritana Prueksakorn & Cheng-Xu Piao & Hyunchul Ha & Taehyeung Kim, 2015. "Computational and Experimental Investigation for an Optimal Design of Industrial Windows to Allow Natural Ventilation during Wind-Driven Rain," Sustainability, MDPI, vol. 7(8), pages 1-22, August.
    2. Hualin Xie & Jinlang Zou & Hailing Jiang & Ning Zhang & Yongrok Choi, 2014. "Spatiotemporal Pattern and Driving Forces of Arable Land-Use Intensity in China: Toward Sustainable Land Management Using Emergy Analysis," Sustainability, MDPI, vol. 6(6), pages 1-17, May.
    3. Stephan E. Maurer & Andrei V. Potlogea, 2021. "Male‐biased Demand Shocks and Women's Labour Force Participation: Evidence from Large Oil Field Discoveries," Economica, London School of Economics and Political Science, vol. 88(349), pages 167-188, January.
    4. Tie Hua Zhou & Ling Wang & Keun Ho Ryu, 2015. "Supporting Keyword Search for Image Retrieval with Integration of Probabilistic Annotation," Sustainability, MDPI, vol. 7(5), pages 1-18, May.
    5. T. Karski, 2019. "Opinions and Controversies in Problem of The So-Called Idiopathic Scoliosis. Information About Etiology, New Classification and New Therapy," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 12(5), pages 9612-9616, January.
    6. Wesley Mendes-da-Silva, 2020. "What Makes an Article be More Cited?," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 24(6), pages 507-513.
    7. Wisdom Akpalu & Mintewab Bezabih, 2015. "Tenure Insecurity, Climate Variability and Renting out Decisions among Female Small-Holder Farmers in Ethiopia," Sustainability, MDPI, vol. 7(6), pages 1-16, June.
    8. Wei Chen & Shu-Yu Liu & Chih-Han Chen & Yi-Shan Lee, 2011. "Bounded Memory, Inertia, Sampling and Weighting Model for Market Entry Games," Games, MDPI, vol. 2(1), pages 1-13, March.
    9. David Harborth & Sebastian Pape, 2020. "Empirically Investigating Extraneous Influences on the “APCO” Model—Childhood Brand Nostalgia and the Positivity Bias," Future Internet, MDPI, vol. 12(12), pages 1-16, December.
    10. Taeyeoun Roh & Yujin Jeong & Byungun Yoon, 2017. "Developing a Methodology of Structuring and Layering Technological Information in Patent Documents through Natural Language Processing," Sustainability, MDPI, vol. 9(11), pages 1-19, November.
    11. He-Yau Kang & Amy H. I. Lee & Tzu-Ting Huang, 2016. "Project Management for a Wind Turbine Construction by Applying Fuzzy Multiple Objective Linear Programming Models," Energies, MDPI, vol. 9(12), pages 1-15, December.
    12. A. B. Atkinson & Stephen P. Jenkins, 2020. "A Different Perspective on the Evolution of UK Income Inequality," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(2), pages 253-266, June.
    13. Haiyan Xu & Yanhui Ding & Jing Sun & Kun Zhao & Yuanjian Chen, 2019. "Dynamic Group Recommendation Based on the Attention Mechanism," Future Internet, MDPI, vol. 11(9), pages 1-15, September.
    14. Adina Letiţia Negruşa & Valentin Toader & Aurelian Sofică & Mihaela Filofteia Tutunea & Rozalia Veronica Rus, 2015. "Exploring Gamification Techniques and Applications for Sustainable Tourism," Sustainability, MDPI, vol. 7(8), pages 1-30, August.
    15. Ahmad N. Alkenani & Mohammad Ashraf & Ghulam Mohammad, 2020. "Quantum Codes from Constacyclic Codes over the Ring F q [ u 1 , u 2 ]/〈 u 1 2 - u 1 , u 2 2 - u 2 , u 1 u 2 - u 2 u 1 〉," Mathematics, MDPI, vol. 8(5), pages 1-11, May.
    16. Shang-Yuan Chen & Jui-Ting Huang, 2012. "A Smart Green Building: An Environmental Health Control Design," Energies, MDPI, vol. 5(5), pages 1-16, May.
    17. Yanhong Feng & Xu Yu & Gai-Ge Wang, 2019. "A Novel Monarch Butterfly Optimization with Global Position Updating Operator for Large-Scale 0-1 Knapsack Problems," Mathematics, MDPI, vol. 7(11), pages 1-31, November.
    18. Xiaoshu Cao & Feiwen Liang & Huiling Chen & Yongwei Liu, 2017. "Circuity Characteristics of Urban Travel Based on GPS Data: A Case Study of Guangzhou," Sustainability, MDPI, vol. 9(11), pages 1-21, November.
    19. S. B. Reshetnikov & M. R. Skirdov, 2017. "Analysis of methodological approaches to determination and assessment of the human capital," Russian Journal of Industrial Economics, MISIS, vol. 10(1).
    20. Mi Jung Son & Jin Han Park & Ka Hyun Ko, 2019. "Some Hesitant Fuzzy Hamacher Power-Aggregation Operators for Multiple-Attribute Decision-Making," Mathematics, MDPI, vol. 7(7), pages 1-33, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:12:y:2020:i:8:p:137-:d:399939. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.