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  4. Vol 8, Issue 1, 2024

Innovative Design of Integrated Experimental Teaching under the Guidance of Learning Outcomes

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DOI: 10.23977/acss.2024.080110 | Downloads: 24 | Views: 137

Author(s)

Xiangping Wang 1, Qian Chen 1, Lili Sun 1

Affiliation(s)

1 School of Logistics Management and Engineering, Zhuhai College of Science and Technology, Zhuhai, Guangdong, China

Corresponding Author

Xiangping Wang

ABSTRACT

The concept of "people-oriented" education emphasizes that teachers pay attention to students' learning ability and level in the teaching process. On this basis, a set of innovative and practical experimental courses is designed to improve students' comprehensive quality and skill training. Based on the learning outcome, this paper analyzes and studies the effect of applying three-dimensional space to chemistry learning, and puts forward corresponding suggestions. After that, this paper innovatively designes the comprehensive experimental teaching model and testes and analyzes the design system. The analysis results showed that the mean time to failure (MTBF) value varied from day to day. Day 2 had a relatively low MTBF (12 hours), while day 6 had a relatively high MTBF (24 hours). The change of MTBF value indicates the stable operation of the system. This shows that the application of three-dimensional space in teaching to a wider range of disciplines can promote the development of students' ability and knowledge level. 

KEYWORDS

Learning Outcome, Comprehensive Experiment, Teaching Innovation, Comprehensive Orientation

CITE THIS PAPER

Xiangping Wang, Qian Chen, Lili Sun, Innovative Design of Integrated Experimental Teaching under the Guidance of Learning Outcomes. Advances in Computer, Signals and Systems (2024) Vol. 8: 88-95. DOI: http://dx.doi.org/10.23977/acss.2024.080110.

REFERENCES

[1] Hongying Zhao, Xiangzhe Yin, Haotian Xu, Kailai Liu, Wangyang Liu, Lixia Wang, Caiyu Zhang, Lin Bo, Xicheng Lan, Shihua Lin, Ke Feng, Shangwei Ning, Yunpeng Zhang, Li Wang: LncTarD 2.0: an updated comprehensive database for experimentally-supported functional lncRNA-target regulations in human diseases. Nucleic Acids Res. 51(D1): 199-207 (2023).
[2] Zhaoyan Sun, Xuanhe Zhou, Guoliang Li: Learned Index: A Comprehensive Experimental Evaluation. Proc. VLDB Endow. 16(8): 1992-2004 (2023).
[3] Giuseppe Cattaneo, Umberto Ferraro Petrillo, Raffaele Giancarlo, Francesco Palini, Chiara Romualdi: The power of word-frequency-based alignment-free functions: a comprehensive large-scale experimental analysis. Bioinform. 38(4): 925-932 (2022).
[4] Xinyi Zhang, Zhuo Chang, Yang Li, Hong Wu, Jian Tan, Feifei Li, Bin Cui: Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation. Proc. VLDB Endow. 15(9): 1808-1821 (2022).
[5] Sebastian Benecke, Andreas Gerlach, Roberto Leidhold: Comprehensive Design Method and Experimental Examination of an Electrical Machine for a Free-Piston Linear Generator. IEEE Trans. Ind. Electron. 69(8): 7817-7824 (2022).
[6] Thi Ngoc Anh Tran, Phong Nguyen Thanh: Effects of Socrative-Based Online Homework on Learning Outcomes in Vietnam: A Case Study. Int. J. Interact. Mob. Technol. 17(5): 182-199 (2023).
[7] Radwa El Shawi, Abdul Wahab, Ahmed Barnawi, Sherif Sakr: DLBench: a comprehensive experimental evaluation of deep learning frameworks. Clust. Comput. 24(3): 2017-2038 (2021).
[8] Mengzhao Wang, Xiaoliang Xu, Qiang Yue, Yuxiang Wang: A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search. Proc. VLDB Endow. 14(11): 1964-1978 (2021).
[9] Ahmed M. Elkhatat, Shaheen A. Al-Muhtaseb: Virtual mimic of lab experiment using the computer-based Aspen Plus® Sensitivity Analysis Tool to boost the attainment of experiment's learning outcomes and mitigate potential pandemic confinements. Comput. Appl. Eng. Educ. 31(2): 285-300 (2023).
[10] Ghada Amoudi, Dina Tbaishat: Interactive notebooks for achieving learning outcomes in a graduate course: a pedagogical approach. Educ. Inf. Technol. 28(12): 16669-16704 (2023).
[11] Konstantina Chrysafiadi, Maria Virvou, George A. Tsihrintzis, Ioannis Hatzilygeroudis: Evaluating the user's experience, adaptivity and learning outcomes of a fuzzy-based intelligent tutoring system for computer programming for academic students in Greece. Educ. Inf. Technol. 28(6): 6453-6483 (2023).
[12] Omer Sami Kaya, Erinc Ercag:The impact of applying challenge-based gamification program on students' learning outcomes: Academic achievement, motivation and flow. Educ. Inf. Technol. 28(8): 10053-10078 (2023).
[13] Siri Sollied Madsen, Helge Habbestad, Iris H. Borch:Valuable unintended learning outcomes when practicum for student teachers in kindergartens is carried out online. Educ. Inf. Technol. 28(1): 37-55 (2023).
[14] Taras Panskyi, Ewa Korzeniewska: Statistical and clustering validation analysis of primary students' learning outcomes and self-awareness of information and technical online security problems at a post-pandemic time. Educ. Inf. Technol. 28(6): 6423-6451 (2023).
[15] Murat Sercemeli, Ozlem Baydas Onlu: Prediction of students' learning outcomes by various variables in gamified online accounting courses. Educ. Inf. Technol. 28(12): 16979-17007 (2023).
[16] Ufuk Tugtekin, Hatice Ferhan Odabasi: Effect of multitasking and task characteristics interaction on cognitive load and learning outcomes in virtual reality learning environments. Educ. Inf. Technol. 28(11): 14915-14942 (2023).
[17] Nazar Zaki, Sherzod Turaev, Khaled Shuaib, Anusuya Krishnan, Elfadil A. Mohamed: Automating the mapping of course learning outcomes to program learning outcomes using natural language processing for accurate educational program evaluation. Educ. Inf. Technol. 28(12): 16723-16742 (2023).
[18] David A. Miranda, A. R. Lizcano-Dallos, Edgar F. Pinzón: Improving the Physics Learning Outcomes of Engineering Students Through Just in Time Teaching (JiTT). Rev. Iberoam. de Tecnol. del Aprendiz. 18(2): 190-197 (2023).
[19] Jianhua Ma, Yaping Tao: Learning Outcomes of Civil Engineering Students in PBL Based on Building Information Modeling. Int. J. Emerg. Technol. Learn. 18(7): 89-102 (2023).
[20] Sotiris Kirginas: Digital Game-Based L1 Language Learning Outcomes for Preschool through High-School Students: A Literature Review. Int. J. Gaming Comput. Mediat. Simulations 15(1): 1-16 (2023).

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