Submitted:
06 January 2025
Posted:
07 January 2025
Read the latest preprint version here
Abstract
Keywords:
0. Introduction
1. Analysis of Current Teaching Situation of Horse Veterinary Course
1.1. Single Teaching Method
1.2. Imperfect Teaching Content
1.3. Student Participation Is Not High
2. Hybrid Teaching Path of Horse Veterinary Course Based on Artificial Intelligence
2.1. Selection and Application of Information Platform
2.2. Transformation and Upgrading of Offline Teaching Mode
2.3. Establishment and Operation of Model System
2.3.1. Reconstruction and Planning of Course Content and Teaching Design According to the Characteristics of Mixed Teaching Mode
2.3.2. Constructing Hybrid Teaching Process Based on Artificial Intelligence
- Sorting out knowledge points and determining network class hours
- 2.
- Compiling teaching objectives and evaluation methods
- 3.
- Draw up teaching strategies and arrange teaching activities
- 4.
- Implement teaching and feedback adjustment
2.3.3. Establish Intelligent Evaluation and Feedback Mechanism
- Class Participation (15%): This category encompasses classroom speeches, group discussions, and presentations, aimed at encouraging active class interactions and enhancing students' thinking and expression skills.
- Regular Assignments (10%): Through a variety of assignments, we evaluate students' understanding and mastery of key concepts, fostering their practical and innovative abilities.
- Interim Tests (10%): Throughout the semester, several interim tests are scheduled to promptly assess students' learning progress and identify any issues, allowing for targeted tutoring and adjustments to the teaching plan.
- Online Video Learning (10%): Prior to class, students are required to watch specified online videos that cover course material and related background information.
- Attendance (5%): Attendance is tracked using the Chaoxing Learning Platform to ensure timely class participation. It is included as part of the process assessment and contributes to the final grade.
3. Application Challenges and Countermeasures of Artificial Intelligence in Hybrid Teaching of Horse Veterinary Course
3.1. Application Challenges
3.1.1. Challenges of Teaching Mode Transformation
3.1.2. Challenges of Teaching Evaluation and Feedback
3.1.3. Challenges of Teacher Training and Development
3.1.4. Challenges of Students' Psychological and Emotional
3.2. Countermeasure
3.2.1. Innovative Teaching Mode
3.2.2. Making Scientific and Reasonable Teaching Evaluation and Feedback Mechanism
3.2.3. Strengthen AI Training for Teachers
3.2.4. Pay Attention to Students' Mental Health and Emotional Communication
4. Conclusions
Funding
Data Availability Statement
Conflicts of Interest
References
- Li Xiaomei. The Application Status and Development Trends of Artificial Intelligence in Education [J]. China's Educational Informatization, 2022(10): 12-18.
- Zhang Wei. Design and Practice of Blended Learning Model [J]. China Educational Technology & Equipment, 2021(20): 45-48.
- Liu Yun, Liu Yuan, Lai Jie, et al. Innovative Practice of Online and Offline Blended Teaching Based on BIM Technology: A Case Study of the Course "Fundamentals of Concrete Structures" [J]. Journal of Higher Education, 2024, 10(36): 76-80. [CrossRef]
- Wang Qiang. Teaching Reform and Practice of Equine Veterinary Courses [J]. Journal of Animal Husbandry and Veterinary Medicine, 2020(06): 34-37.
- Liu Fang. Design of Personalized Teaching System Based on Artificial Intelligence [J]. China Educational Technology & Equipment, 2023(05): 78-81.
- Shen Qi, Wang Shuxian, Liu Hui, et al. Analysis of Influencing Factors and Countermeasures on Learning Effectiveness of Online Open Courses in Medical Colleges [J]. China Modern Distance Education of Traditional Chinese Medicine, 2021, 19(5): 19-21.
- Jing Qin, Wang Wei, Wu Zhaoli, et al. Application of Blended Learning Mode in the Teaching of Acupuncture and Moxibustion Clinical Courses [J]. China Modern Distance Education of Traditional Chinese Medicine, 2020, 18(1): 18-20.
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