BP-CM Model: A teaching model for improving the teaching quality of IoT hardware technology based on BOPPPS and memory system

被引:0
|
作者
Rongjun Chen
Xiaomei Luo
Qiong Nie
Leijun Wang
Jiawen Li
Xianxian Zeng
机构
[1] Guangdong Polytechnic Normal University,School of Computer Science
[2] College of Fine Arts,undefined
[3] Guangdong Polytechnic Normal University,undefined
来源
关键词
IoT; Hardware; BP-CM; Cyclic memory; Memory system; Teaching model;
D O I
暂无
中图分类号
学科分类号
摘要
This paper proposes the BP-CM teaching model to solve the problems of lagging classroom feedback, poor learning initiative of students and students rapidly forgetting what they have learned in Internet of Things (IoT) hardware technology courses. This BP-CM(BOPPPS, PAD, cyclic memory, memory system) teaching model is based on BOPPPS(Bridge in, Objective, Pre-assessment, Participatory learning, Post-assessment, and Summary), PAD(Presentation, Assimilation, and Discussion), and the memory system model. This paper compares the BP-CM teaching model with the traditional teaching model by having research participants teach and learn separately in each teaching model. Taking the Microcontroller Unit (MCU) course as an example, this paper introduces each link of the teaching design of this model. It also explains the design method and intention of each link. Finally, the practical results indicate that the BP-CM teaching model proposed in this article positively impacts students’ learning initiative and memory. In addition, teachers can obtain timely feedback using the BP-CM model, and the model significantly improves students' knowledge and ability levels. It enhances the teaching quality of IoT hardware technology courses and is conducive to cultivating students' sustainable learning abilities. This research not only promotes education and teaching reform but also provides a reference case.
引用
收藏
页码:6249 / 6268
页数:19
相关论文
共 50 条
  • [41] RESEARCH AND APPLICATION OF UNIVERSITY BIOLOGICAL SPECIALTY TEACHING QUALITY EVALUATION MODEL BASED ON BP NEURAL NETWORK
    Li, X. Y.
    Zhao, L.
    Wang, P. W.
    BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2016, 118 : 80 - 80
  • [42] Teaching Model of Soccer Training Based on Virtual Simulation Technology
    Wang, Bin
    JOURNAL OF ELECTRICAL SYSTEMS, 2024, 20 (03) : 610 - 619
  • [43] Analysis of music teaching technology based on a data mining model
    Liu Y.
    Applied Mathematics and Nonlinear Sciences, 2023, 8 (02) : 3013 - 3022
  • [44] Research on Multimedia English Teaching Model Based on Information Technology
    Han, Shuying
    Guo, Xiuli
    PROCEEDINGS OF THE 2012 INTERNATIONAL CONFERENCE OF MODERN COMPUTER SCIENCE AND APPLICATIONS, 2013, 191 : 283 - 287
  • [45] Analysis on Hierarchical Model of Teaching Skills Based on Multimedia Technology
    Sun, Jie
    Kang, Cui
    Wang, YunWu
    ADVANCES IN COMPUTER SCIENCE, ENVIRONMENT, ECOINFORMATICS, AND EDUCATION, PT III, 2011, 216 : 516 - +
  • [46] Research on Teaching Model of Multimedia Application Technology Based on MOOC
    Li, Qian
    Wang, Yanling
    2015 2nd International Conference on Education and Education Research (EER 2015), Pt 2, 2015, 6 : 101 - 105
  • [47] Teaching Evaluation Model Research based on Integration of Information Technology
    Jun, Zhang
    Ying, Zhang Mei
    PROCEEDINGS OF 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION (ICICTA 2015), 2015, : 913 - 916
  • [48] Construction of a mathematical modeling teaching quality assessment system for universities based on Eviews model
    Lv, Xiyuan
    Yi, Qiang
    APPLIED MATHEMATICS AND NONLINEAR SCIENCES, 2023, 9 (01)
  • [49] Rough Set-Based Quality Evaluation Model of Teaching and Learning with Multimedia System
    Yang Zuqiao
    Liu Guimei
    2012 INTERNATIONAL CONFERENCE ON INTELLIGENCE SCIENCE AND INFORMATION ENGINEERING, 2012, 20 : 183 - 186
  • [50] An Evaluation Model of Moral Education Teaching Quality in Universities Based on System Control Theory
    Ming, Zheng
    2021 13TH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA 2021), 2021, : 535 - 538