Abstract
To solve the problem of how to apply information technology in English education field, to realize the integration of information technology and courses and also to truly improve the study efficiency, the advanced technologies were combined with some education measurement theories and applied in computer-aided test field. In addition, a computer-aided autonomous learning system with adaptive feature was developed, which was a self-adaptive learning system of junior English. The results showed that, under the guidance of the classic test theory and the project response theory, the system was designed and developed on the basis of the “people-oriented” principle. With the increasing number of students wanting to practice, the system dynamically rewrote the relevant learning record parameters, and conducted a real-time record of the true level of ability of each different student in different knowledge points. In a word, practicing according to the actual situation, the learning system can help achieve a truly personalized learning, and meanwhile enhances the efficiency of learning.
Highlights
English is the universally used language and plays an important role in students’ academic and career development
This paper focuses on the design and development of adaptive self-learning system from both theoretical and practical aspects
On the basis of introduction and analysis of the current learning platform at home and abroad, the idea of item response theory is introduced into the system, which provides the direction for determining the test parameters and the ability level of the students
Summary
English is the universally used language and plays an important role in students’ academic and career development. If we combine English teaching with flipped classroom effectively, it will have a good influence on students’ English-learning efficiency. Students answer questions that teachers have pre-designed when completing watching or in the process of watching videos, so as to evaluate their master of knowledge points. For this solution, the evaluation of individualization is not enough, which cannot accurately grasp the students’ knowledge points and students’ learning preference. Adaptive learning system relies on student model, knowledge domain model and adaptive engine It can record students’ behavior data in their learning process, and achieve the purpose of real-time evaluation and feedback through technologies such as data mining, learning analysis and etc. It helps teachers to know students’ blind spots of knowledge as well as learning preferences before class, and to provide corresponding technical support for targeted teaching in the class
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