Research On Adaptive Learning Path Recommendation For E-Learning

Along with the integration of information technology into the field of education, E-Learninghas been applied worldwide. However, there are still many problems in the existing E-Learning systems. The main reasons lie in the lack of adaptive decisions and strain capacity in the current E-Learning systems and the lack of effective diagnosis and assessment of the learning process. Therefore, the researchers carried out studies of adaptive learning support systems. The adaptive learning path recommendation system in this research is a specific implementation method of the adaptive learning support system. Constructing an adaptive learning path recommendation system can better solve the problems like "Learning Trek"and "Cognitive Overload", and is also an effective way to solve the following contradictions in the E-Learning system:demands for personalized dynamic resources VS static systematized teaching resources; the infinite system resources VS the demand for limited resources.However, there are still many problems in the research of the adaptive learning path recommendation system. The problems mainly lie in the following facts:the system emphasizes the improvement of intelligence but neglects the subjective initiative in the learning process, and personalized features of the students are not complete and accurate enough; the recommended learning path is not precise; the system lacks scientific and reasonable domain knowledge model, and the resources of different systems are not shared adequately; successful cases of adaptive learning path recommendation systems are scarce; evaluation studies of the system application effect are not comprehensive and profound enough. In view of the above problems, this paper presents a deep research on the key issues of the adaptive learning path recommendation system. The preliminary research results are as follows:First, based on the ontology technology we constructed the ontology database of junior middle school physics. Firstly, through the comparison and analysis of different methods of constructing domain knowledge model, this research adopted ontology technology to construct the domain knowledge model. We chose the seven-step method and took the prototype model of domain ontology construction as a reference. Considering the characteristics of physics in junior middle school, we put forward the scheme of constructing domain ontology. Then, through the analysis of the physics textbook for junior middle school published by People’s Education Press, Junior Middle School Knowledge List:Physics, Physics Curriculum Standard for Compulsory Education (2011 Edition), and teaching resources for junior middle school physics from authoritative websites, we obtained ontology terms and the relationship between them via both automatic extraction and artificial extraction, and constructed the domain ontology library of junior middle school physics. For the extraction of ontology terms, this study focused on the method of automatic extraction based on word frequency distribution change and the information entropy, and verified the efficacy of this method through experiment. For marking ontology relationship, the study adopted different methods for different terms. Lastly, the ontology terms were stored by encoding tools and the ontology library was established completely. The ontology library is the key component of the adaptive learning path recommendation system, which is an important basis for generating adaptive learning paths.Second, based on context awareness, a learner model was constructed, based upon which mechanisms of adaptive learning path recommendation were explored and the application cases were designed. In this study, we analyzed the contextual factors of the adaptive learning path recommendation system, and constructed the learner model based on context awareness (CALM) and learning context ontology model. Furthermore, the framework and recommended mechanisms of the adaptive learning path recommendation model were described in detail. Finally, we designed an application case of the adaptive learning path recommendation system based on CALM.Third,an adaptive learning path recommendation system was designed and implemented. In this study, we designed and implemented an adaptive learning path recommendation system based on junior middle school physics. This system can recommend learning paths and learning resources for each knowledge point in the learning path based on the personalized features of learners. The core functions of the system include adaptive learning path recommendation, learning resource recommendation, adaptive testing, learning data analysis, learning behavior recording, etc. In addition to providing students with personalized learning services, the system also adds a teacher intervention modular whose function is reflected in two aspects. On the one hand, teachers in the system play a role of artificial intervention and they can adjust the recommended learning path and learning resources to better meet the personalized learning needs of students, so as to further improve the accuracy and service quality of the system. On the other hand, teachers can better understand the learning situation of students by systematic data.Finally, Evaluation research on the application effect of the adaptive learning path recommendation system was conducted. Based on the technology acceptance model (TAM) and through theoretical exploration, this research proposed an evaluation index system for design and implementation of adaptive learning path recommendation systems. In order to evaluate the effect comprehensively and objectively, user process and user experience were both considered from the perspectives of subjective evaluation and objective evaluation. The results showed that the system had a good overall effect, and the conclusions of the two evaluation methods could be confirmed by each other. Through variance analysis, correlation analysis and regression analysis of the data, this study explored the key factors and their mutual influence on each factor, which provided a reference for improving the application of the system and the construction of other adaptive learning support systems.This research was to provide the learning support service for learners and improve the quality and level of the personalized service recommendation system, which could effectively promote the learners’ individualized education. Its innovations lie in the following aspects. First, based on context awareness, a learner model was constructed, based upon which mechanisms of adaptive learning path recommendation were explored. Second, it designed and implemented a two-way adaptive learning path recommendation system and added the teacher intervention modular. Third, it proposed an application effect evaluation index system for the system and studied the application effect of the adaptive learning system based on the evaluation index system.