Communications

Experiments

1. 
   Construction of Intelligent Teaching Platform. The intel- ligent teaching platform is based on computational intelli- gence technology, learning analysis technology, data mining technology, and machine learning technology. It provides teachers and students with personalized teaching and learning teaching systems. Its main characteristics are the use of artificial intelligence technology to intelligently
   

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analyze what learners have learned, build a knowledge map of learners, provide learners with personalized learning con- tent and learning solutions, support adaptive learning, and implement intelligent recommendations for learning content.

With the help of artificial intelligence to build a learning environment in which virtual and reality are combined, learners can conduct more personalized, immersive, and inter- esting learning in a virtual fusion environment. By personaliz- ing the image of the virtual student companion to assist the learner, let the learner concentrate, complete the learning task within the prescribed time, and optimize the learning process. The virtual companion gives praise when the learner com- pletes the learning task and gives supervision and encourage- ment when it is not completed, so that the learner feels humane care and actively completes the learning task without the pressure and demand of teachers and parents.

1. 
   Preclass teachers prepare lessons through intelligent teaching platforms, can share lesson plans with teachers across the country in real time, absorb their advanced teaching concepts, and learn their advanced teaching methods; push preclass preview materials to learners through the teaching platform, personal study space, timely interaction with stu- dents, and timely adjustment and improvement of teaching design. During the lesson, teachers can con- nect to the teaching platform through various mobile terminals to interact with the teacher in real time. Teachers can solve the problems of different students one-to-many, so that every student can participate in the classroom communication and truly return the classroom to the students. After class, students can complete homework on the platform, and they can also complete thinking collision with the learning community. The platform completes homework cor- rection and gives students real-time feedback
   
2. 
   The intelligent teaching platform provides different preview materials and assignments of different diffi- culties for each student based on the collected data and advanced algorithms, according to the students’ learning ability, mastery of the learning content, and effort. The course content will be dynamically adjusted with the progress of students’ learning, skipping the knowledge points that the students have mastered and strengthening the weak links of the students, so as to truly implement teaching accord- ing to their aptitude and achieve adaptive learning with personalized difficulty. Personalized teaching prepares different examination papers for different students, and different examination papers will not increase the teacher’s work intensity. Through the intelligent teaching platform, according to each stu- dent’s learning records, intelligent test papers can also be generated through machine corrections, and automatically generate teaching evaluation reports, personalize evaluation of student progress and defi- ciencies, and guide students’ efforts
   

3. 
   The intelligent teaching platform can also play a role of behavior monitoring for comparative analy- sis. From the perspective of teachers, it can analyze how teachers with different teaching ages and edu- cational backgrounds have different control over the teaching process and teaching effects. For the teacher who scores higher in the teaching evalua- tion, he can analyze in detail what his teaching process is. For students with poor grades, you can use the study data to find out when he started to relax, whether he was unwilling to study from beginning to end or encountered difficulties in the learning process, which caused him to shrink back, and clearly understand when the learner’s learning attitude has changed. And you can observe whether the learner changes after receiving the learning alert
   

2. 
   Introduction of Function Modules of Intelligent Teaching Platform. The intelligent teaching platform can provide services such as personalized learning analysis and intelli- gent push learning content. In data collection, the stu- dent’s learning archive data, learning behavior data, and other information data are stored in the data warehouse. On this basis, integrate artificial intelligence analysis and big data mining technologies such as adaptive technology, push technology, and semantic analysis to support learn- ^ing computing. In learning services, it provides personal- ized learning path recommendation services. It can be seen that the intelligent teaching platform relies on three core elements, data, algorithms, and services, where data is the foundation, algorithms are the core, and services are the purpose. Therefore, research attempts to analyze the functions of the intelligent teaching platform from these three aspects.
   

The data layer is the input port of education data and the basic interface for upper-layer services. It is mainly responsible for collecting, cleaning, sorting, and storing various types of education data. On the one hand, it col- lects information such as learners’ learning behaviors, learning results, and learning processes. On the other hand, it needs to collect teachers’ teaching data, including resources for preparing lessons. The algorithm layer is mainly composed of various artificial intelligence algo- rithms integrated with education business. According to a systematic method, various calculations and analyses are performed on various types of teaching data in the data layer to realize intelligent processing of data. For example, by performing intelligent academic analysis on the behavioral data, basic information data, and academic data of all students in the class, it can obtain a portrait of the individual student and the class as a whole and pro- vide different learning materials and different arrange- ments for the learners according to their learning interests. Difficult homework motivates learners’ intrinsic motivation for learning. The service layer provides the required education services to users by receiving the data processing results from the algorithm layer. In terms of learning services, based on the results of personalized

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analysis, it provides learners with recommended services covering learning content, learning interactions, and per- sonalized learning paths to assist students in personalized learning. In teaching services, by analyzing the data of teachers’ teaching process, it helps teachers sum up gains and losses, monitor teaching quality, and adjust teaching design, so as to realize the precision of teaching process.

3. 
   Questionnaire Survey. In order to have a certain under- standing of the use of artificial intelligence by teachers, this article has made a questionnaire on the topic of arti- ficial intelligence and professional development of teachers and has prepared 23 single-choice and multiple-choice questions, to understand the use of artificial intelligence in teachers, and the problems can be statistically proc- essed. According to the different content of the questions, the frequency statistics and descriptive statistics of the questions are, respectively, presented and the analysis results are presented in the form of text, tables, statistical charts, and so on. The random sampling method was used to select teachers from several schools in Qingdao City. The survey time was June 2020. A total of 96 question- naires were issued, with 96 valid samples and an effective recovery rate of 100. Therefore, the data from this ques- tionnaire is valid.
   

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