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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] 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. [3] Susanty L, Hartati Z, Sholihin R, Syahid A, Liriwati YF. 2021, Why English teaching truth on digital trends as an effort for effective learning and evaluation: opportunities and challenges: analysis of teaching English. Linguistics and Culture Review, 5(S1): 303-316. [4] Cook C, Jones J, Al-Twal A. 2022, Validity and fairness of utilising student evaluation of teaching (SET) as a primary performance measure. Journal of Further and Higher Education, 46(2): 172-184. [5] De-kun J, Memon F H. 2022, Design of mobile intelligent evaluation algorithm in physical education teaching. Mobile Networks and Applications, 27(2): 527-534. [6] Marks B, Thomas J. 2022, Adoption of virtual reality technology in higher education: An evaluation of five teaching semesters in a purpose-designed laboratory. Education and information technologies, 27(1): 1287-1305. [7] 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. [8] Al-Maamari F S. 2021, The potential in student evaluation of teaching for EFL teacher professional development. Cogent Education, 8(1): 1888670. [9] YanRu L. 2021, An artificial intelligence and machine vision based evaluation of physical education teaching. Journal of Intelligent & Fuzzy Systems, 40(2): 3559-3569. [10] Peciuliauskiene P, Tamoliune G, Trepule E. 2022, Exploring the roles of information search and information evaluation literacy and pre-service teachers’ ICT self-efficacy in teaching. International Journal of Educational Technology in Higher Education, 19(1): 1-19. [11] Sun X, Cai C, Pan S, Bao N, Liu N. 2021,A university teachers’ teaching performance evaluation method based on type-II fuzzy sets. Mathematics, 9(17): 2126. [12] Weston T J, Hayward C N, Laursen S L. 2021, When seeing is believing: Generalizability and decision studies for observational data in evaluation and research on teaching. American Journal of Evaluation, 42(3): 377-398. [13] Liu S. 2021,Research on the teaching quality evaluation of physical education with intuitionistic fuzzy TOPSIS method. Journal of Intelligent & Fuzzy Systems, 40(5): 9227-9236. [14] Man Z. 2022, Research on the evaluation method for English teaching efficiency based on data mining. International Journal of Continuing Engineering Education and Life Long Learning, 32(3): 295-312. [15] 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. [16] Chen R. 2021,Research on Teaching Quality Evaluation in Applied Undergraduate Universities. Creative Education, 12(10): 2322-2327. [17] Wang N. 2021,Teaching Reform of Art Design Major Based on Obe Education Concept. Journal of Frontiers in Educational Research, 1(8): 13-16. [18] Bi H H. 2022, Applying statistical process control to teaching quality assurance at higher education institutions. Quality Management Journal, 29(2): 145-157. [19] Wang G, Williamson A. 2022, Course evaluation scores: valid measures for teaching effectiveness or rewards for lenient grading?. Teaching in Higher Education, 27(3): 297-318. [20] Huang J, Shen G, Ren X. 2021,Connotation Analysis and Paradigm Shift of Teaching Design under Artificial Intelligence Technology. International Journal of Emerging Technologies in Learning (iJET), 16(5): 73-86. |
Tsuruta Institute of Medical Information Technology
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