Modeling Method and Application of College Comprehensive Teaching Mode Based on Artificial Intelligence

This paper introduces AI intelligence technology in English distance education and establishes a learning analytics model that includes information collection and acquisition, data storage, cleaning, integration, analysis, visualization, and action. Each component corresponds to a series of specific technologies and processes, and generates information such as learner portrait modeling profiling learning behaviors, using data mining to provide personalized learning solutions for learning. The assessment system is constructed from three perspectives: contextual, cognitive, and technological, which ensures accurate teaching for the personalized needs of English learners. It has been verified that the contextual interaction effect on students’ performance accounts for 78% of the total sample in the English distance education system after applying AI intelligent technology. Students in the experimental class showed positive interest in the distance education system 47.44±7.15, which was significantly higher than that of the control class 29.65±8.21. This integration model provides a new development direction for English distance education, and also provides strong support for personalized teaching and continuous optimization of the educational process.

Section: Construction Of Teaching System Under the Integration Of Ai ...mentioning

confidence: 99%

Research on the Integration Path and Practice of AI Intelligent Technology and English Distance Education

Jiang

2023

“…With the continuous development of science and technology, Internet information technology, automation technology, and intelligent technology are widely used in various fields, which brings great convenience to people's lives and work [1][2][3]. At the same time, the field of education also plays an extremely important role as a teaching aid, teaching methods, etc., to make teaching activities more efficient [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Research on Precision Teaching Reform of Japanese Language Education in Colleges and Universities Based on the CRS Model

Zhao

2024

The traditional Japanese language teaching method is challenging to mobilize students’ enthusiasm, and it is impossible to objectively understand students’ mastery of knowledge points. To address this teaching problem, this paper combines the CRS model with K-Means cluster analysis to construct a precise teaching model for teaching Japanese language in colleges and universities based on the CRS model. Through the CRS model to obtain the students’ mastery of knowledge and differentiated data, the K-Means algorithm is used to analyze the teaching model accurately, so Japanese teachers can make timely adjustments to the classroom teaching situation and improve the quality of teaching. After the model design was completed, a controlled teaching experiment was conducted in two colleges and universities in a province, and an independent square root t-test was performed. The ratio of teachers’ verbal behavior in the experimental class of Japanese language in colleges and universities was 71.58%, which was 18.86% lower than the ratio of teachers’ verbal behavior in the classroom of the control case, and the ratio of students’ verbal behavior was 21.58%, which was 18.36% higher. The average probability of students’ mastery of the Japanese language points studied in the semester was above 0.6. The independent square root t-test for the two classes was less than 0.05, showing a significant difference.

“…In the area of intelligent interaction and curriculum teaching, Karadeniz, A. et al explored the use of AI technology in the field of education from 1970 to 2020 and analyzed the impact of AI technology on education [17]. Wenjing, Y. et al constructed an integrated teaching model for colleges and universities based on AI, explored the paradigm of instructional design in the context of AI, and analyzed the impact of AI on higher education [18]. Huang, J. et al investigated the instructional design specification under AI technology and explored the impact of AI on teaching activities and instructional design [19].…”

Section: Introductionmentioning

confidence: 99%

Application of AI Interaction Design in the Teaching Model of Landscape Topics Course

Zhou,

Xia

2023

In this paper, we first define the limb node coordinates through the established limb node coordinate system and evaluate the behavior of the human body through the constructed posture sequence to analyze the human body’s body characteristics, such as the area of concern and the emotional level. Then, a new model of landscape theme course teaching was designed based on AI interaction design technology, the human-computer interaction learning needs were analyzed, and a human-computer interaction landscape course learning system was established. Finally, the differences in students’ cognitive ability, learning motivation, and learning emotion under the AI interactive teaching environment and traditional teaching methods were compared, and the advantages of AI interactive teaching were analyzed. The results show that the SD value of students’ behavioral attitudes in the teaching mode based on interactive technology is 27.78±2.34, which is more than the SD value of the ordinary teaching mode.2 In terms of goal attitudes, the SD value of the experimental class is about 4.05 more than that of the control class, and the difference is significant. The interactive teaching mode of AI effectively promotes students’ learning of the landscape topic course, and this study provides positive reference value.