Mobile English Teaching System Based on Adaptive Algorithm

To improve the students’ individualized and autonomous learning ability in English teaching, a mobile English learning system is designed on the basis of adaptive algorithm. The students’ need for the adaptive mobile English teaching system is analyzed through researches on students and questionnaires. According to the needs analysis, the main functional modules of the adaptive mobile English learning system are designed, including the creation module, personalized learning module, evaluation and feedback module, and management module. Then, the improved XAHM (XML adaptive hypermedia model) is applied to the mobile English learning system. The three-layer architecture of the English mobile learning system is revised into four layers of composition layer, data layer, business logic layer and presentation layer. At the same time, more attention is diverted to the terminal and the situation. Finally, the system is tested. The test results showed that the mobile English learning system realized the self-adaptive and intelligent navigation of learning space in the course of teaching. It is concluded that the new adaptive algorithm had a good performance for college English learning.

Information Imperfection as an Inherent Characteristic of Adaptive Hypermedia

daptive hypermedia applications are aimed at tailoring hypermedia structures according to some form of user model, in an attempt to increase the usability and utility of the application for each individual or group. Existing research in the field has resulted in many systems, techniques, and paradigms, both for modelling user data and for the subsequent exploitation of such model for the sake of personalisation. As a matter of fact, the majority of adaptive hypermedia systems work with user models that are imperfect in some way, and the theories or hypotheses that guide adaptation are also often of a heuristic or approximate nature. Although some existing systems provide explicit means for dealing with imperfection in one or several of its multiple facets, there exists a lack of support for information imperfection in adaptive hypermedia models and architectures. In an attempt to provide such conceptual support, the MAZE model was proposed as a generalisation of an existing abstract hypermedia model, providing built-in support for fuzzy set-theoretic notions. This chapter provides an overall account of the MAZE model, along with its rationale, and an overview of a possible instance of a MAZE-based architecture. In addition, the use of MAZE to model common adaptive hypermedia technologies is illustrated through a concrete case study.