2022 Vol.5 Sep.No3

• Title: Research on the evaluation of Hybrid Teaching Reform Based on Hidden Markov
• Name: Sugita Heji
• Company: Hetian Technology Research Institute,JP
• Abstract:

  In view of the current poor effect of hybrid teaching evaluation, this paper puts forward a hybrid teaching reform evaluation method based on Hidden Markov model. First, it explores the impact indicators of hybrid curriculum teaching evaluation, divides the influence grades of the factors that should be first in teaching, improves the hybrid curriculum teaching evaluation system, and optimizes the hybrid teaching reform evaluation algorithm combined with hidden Markov model. Finally, it is confirmed by experiments, The hybrid teaching reform evaluation method based on Hidden Markov has high accuracy, and the evaluation time is significantly shortened, which fully meets the research requirements.

  
  

• Keyword: Hidden Markov; Mixed teaching; Teaching evaluation
• DOI: 10.12250/jpciams2022090213
• Citation form: Sugita Heji.Research on the evaluation of Hybrid Teaching Reform Based on Hidden Markov [J]. Computer Informatization and Mechanical System,2022,Vol.5,pp.57-64

reference

[1] LIAN Jing，FANG Siyu，ZHOU Ya-u. 2020, Model Predictive Control of the Fuel Cell Cathode System Based on State Quantity Estimation.Computer Simulation, 37(07):119-122.

[2] Mor B, Garhwal S, Kumar A. 2021, A systematic review of hidden Markov models and their applications. Archives of computational methods in engineering, 28(3): 1429-1448.

[3] Aggarwal A, Alshehri M, Kumar M, Sharma P, Alfarraj O, Deep. 2021,  Principal component analysis, hidden Markov model, and artificial neural network inspired techniques to recognize faces. Concurrency and Computation: Practice and Experience, 33(9): e6157.

[4] Pan G, Shankararaman V, Koh K, Gan S. 2021,  Students’ evaluation of teaching in the project-based learning programme: An instrument and a development process. The International Journal of Management Education, 19(2): 100501.

[5]  Ng D T K, Leung J K L, Chu K W S,  Qiao M S. 2021, AI literacy: definition, teaching, evaluation and ethical issues. Proceedings of the Association for Information Science and Technology, 58(1): 504-509.

[6] Krishnan S, Gehrtz J, Lemons P P, Dolan E L, Andrews T C. 2022, Guides to Advance Teaching Evaluation (GATEs): A Resource for STEM Departments Planning Robust and Equitable Evaluation Practices. CBE—Life Sciences Education, 21(3): ar42.

[7] Bragg D D, Eddy P L, Iverson E R, Hao Y ,O'Connell K. 2022, Lessons from research and evaluation on faculty as change agents of teaching and campus reform. New Directions for Community Colleges, 2022(199): 215-228.

[8] Fawns T, Aitken G, Jones D. 2021, Ecological teaching evaluation vs the datafication of quality: Understanding education with, and around, data. Postdigital Science and Education, 3(1): 65-82.

[9] Mazurek R, Arvinen-Barrow M, Huddleston W, Reckelberg R. 2021,  Beyond traditional peer-to-peer teaching evaluation: Using pedagogical theory in conceptualizing a collaborative teaching development program. Journal of University Teaching & Learning Practice, 18(6): 101-118.

[10] Wang Z, Lyu D. 2021,  Design and realization of a fuzzy comprehensive evaluation system for music teaching in higher education. International Journal of Emerging Technologies in Learning (iJET), 16(22): 59-72.

[11] Cahyadi A, Widyastuti S, Mufidah V N. 2021, Emergency remote teaching evaluation of the higher education in Indonesia. Heliyon, 7(8): e07788.

[12] YanRu L. 2021, An artificial intelligence and machine vision based evaluation of physical education teaching. Journal of Intelligent & Fuzzy Systems, 40(2): 3559-3569.

[13] Han Y. 2021,  Evaluation of English online teaching based on remote supervision algorithms and deep learning. Journal of Intelligent & Fuzzy Systems, 40(4): 7097-7108.

[14] Mok K H, Xiong W, Bin Aedy Rahman H N. 2021,COVID-19 pandemic’s disruption on university teaching and learning and competence cultivation: Student evaluation of online learning experiences in Hong Kong. International Journal of Chinese Education, 10(1): 22125868211007011.

[15] Lihong H A N. 2021,  The strategies of reform of categories evaluation of teaching talents in colleges of Hebei Province. Journal of Hebei University (Philosophy and Social Science), 46(6): 81.

[16] Sun Z, Anbarasan M, Praveen Kumar D. 2021, Design of online intelligent English teaching platform based on artificial intelligence techniques. Computational Intelligence, 37(3): 1166-1180.

[17] Çoban B T, Vardar A K. 2021,Evaluation of Distance English Language Teaching Education during COVID-19 Pandemic from the Perspectives of ELT Student Teachers and Their Instructors. Journal of Pedagogical Research, 5(3): 198-220.

[18] Jin Y. 2021, Retracted article: Evaluation of solar energy potential based on target detection and design of English vocabulary teaching platform. Arabian Journal of Geosciences, 14(15): 1-15.

[19] Kim C M, Kwak E C. 2022,  An Exploration of a Reflective Evaluation Tool for the Teaching Competency of Pre-Service Physical Education Teachers in Korea. Sustainability, 14(13): 8195.

[20] Said J T, Schwartz A W. 2021,Remote medical education: adapting Kern’s curriculum design to tele-teaching. Medical Science Educator, 31(2): 805-812.