Keywords
Teaching
Machine translation
Submitted : 2022-09-26
Accepted : 2022-10-11
Published : 2022-10-26
Abstract
eaching evaluation can be divided into different types, additionally their functions and applicable conditions are different. According to different standards, teaching evaluation can be divided into different types: (1) according to different evaluation functions, it can be divided into pre-evaluation, intermediate evaluation, and post-evaluation; (2) according to different evaluation reference standards, it can be divided into relative evaluation, absolute evaluation, and individual difference evaluation; (3) according to different evaluation and analysis methods, it can be divided into qualitative and quantitative evaluation; (4) according to the different evaluation subjects, it can be divided into self-evaluation and others’ evaluation. This paper introduced research work using different types of teaching evaluation in the machine translation course according to different situations. The research results showed that the rational selection of different types of teaching evaluation methods and the combination of these methods can greatly promote teaching.
References
Novak JD, Gowin DB, 1984, Learning How to Learn. Cambridge University Press, Cambridge. https://doi.org/10.1017/CBO9781139173469
Schueler BE, Bleiberg JF, 2022, Evaluating Education Governance: Does State Takeover of School Districts Affect Student Achievement. Journal of Policy Analysis and Management, 41(1): 162-192. https://doi.org/10.1002/pam.22338
Gavin M, Fitzgerald S, Mcgrath-Champ S, 2022, From Marketizing to Empowering: Evaluating Union Responses to Devolutionary Policies in Education. The Economic and Labor Relations Review, 33(1): 80-99. https://doi.org/10.1177/10353046221077276
Kabassi K, 2021, Comparing Multi-Criteria Decision-Making Models for Evaluating Environmental Education Programs. Sustainability MDPI, 13(20): 1-17. https://doi.org/10.3390/ su132011220
Rao GV, Vijayalakshmi D, 2022, Preference for Mode of Learning for Knowledge and Skills by Professional Management Students During the COVID-19 Pandemic Period. Management and Labor Studies, 47(1): 22-39. https://doi.org/10.1177/0258042X211020604
Reaves S, Martinez-Torteya C, 2022, Understanding the Relation between Family Engagement in Education and Preschoolers’ Socioemotional and Behavioral Functioning in a Primarily Latinx Sample. Urban Education, 57(4): 630-661. https://doi.org/10.1177/0042085920974073
Wu HL, Zhang F, Cheng JW, et al., 2019, Determine Teaching Content Using a Bottom-up Approach. Advances in Social Science, Education and Humanities Research, 369: 597-600. https://doi.org/10.2991/ichess-19.2019.125
Jojo S, 2022, Efficacy of an Online Reading Intervention Program “Literacy Pro” in Classifying Students as “At Risk” and “Not at Risk” among ESL School Students. A Logistic Regression Analysis, Creative Education, 13(3): 19. https://doi.org/10.4236/ce.2022.133063
Buzan T, Buzan B, 1996, The Mind Map Book: How to Use Radiant Thinking to Maximize Your Brain’s Untapped Potential, New York: Plume.
Wu HL, Zhou RY, Wang K, 2017, The Structure of Domain Entity Attribute Semantic Knowledge Base for Natural Language Processing: Proceedings of the International Conference on Computer. Electronics and Communication Engineering, DEStech Transactions on Computer Science and Engineering, 616-619. https://doi.org/10.12783/dtcse/cece2017/14609
Wu HL, Zhou RY, Wang K, 2017, Knowledge Representation of Entity Attribute Frame for Natural Language Understanding. DEStech Transactions on Computer Science and Engineering, 173-176. https://doi.org/10.12783/dtcse/ameit2017/12296
Stufflebeam DL, Coryn CLS, 2014, Evaluation Theory, Models, and Applications, 2nd Edition, Jossey-Bass, Indianapolis.
Wu HL, Wang K, 2020, Design of the Introduction Part of Information Processing and Machine Translation Course for Students Majoring in Computer Science and Technology. Proceedings of the 2020 International Conference on Information Science and Education, 543-546. https://doi.org/10.1109/ICISE51755.2020.00122
Millman J, 1981, The New Handbook of Teacher Evaluation, Sage Publications, London.
Bilro RG, Loureiro S, Angelino F, 2022, The Role of Creative Communications and Gamification in Student Engagement in Higher Education: A Sentiment Analysis Approach. Journal of Creative Communications, 17(1): 7-21. https://doi.org/10.1177/0973258621992644
Wu HL, Wang K, 2021, Natural Language Processing Subject Organizing by TTD Model Based on Stepwise Refinement Framework. Proceedings of the 2nd International Conference on Information Science and Education, 353-356.
Chatterjee S, 2022, The Higher Education Experience of Students During theCOVID-19 Pandemic and the Impact on Mental Well-Being: A Review of the Literature, Mental Health and Higher Education in Australia, 209-238. https://doi.org/10.1007/978-981-16-8040-3_13
Perry RP, Smart JC, 2007, The Scholarship of Teaching and Learning in Higher Education: An Evidence-Based Perspective, Springer, Dordrecht.
Phye GD, 1996, Handbook of Classroom Assessment: Learning, Achievement and Adjustment, Academic Press, Cambridge.
Akdeniz G, 2020, A Survey of Attitudes, Anxiety Status, and Protective Behaviors of the University Students During the COVID-19 Outbreak in Turkey. Frontiers in Psychiatry, 695(11): 1-9. https://doi.org/10.3389/fpsyt.2020.00695
Wu HL, Wang K, 2020, Organization of Knowledge Engineering Subject Using TTD Model Based on Stepwise Refinement Framework. Proceedings of the 2020 International Conference on Information Science and Education, 319-322. https://doi.org/10.1109/ICISE51755.2020.00077