PCF3 // Availability of advanced mobile technologies, such as high bandwidth infrastructure, wireless technologies, and handheld devices, have started to extend e-learning towards mobile learning (m-learning) (Sharples, 2000). This phenomenon fits well with the new paradigm “anytime, anywhere computing” (Lehner and Nösekabel, 2002). However, the development of m-learning is still at rather early stage and many issues have yet to be resolved. One of these issues is the potential of individualization of learning process for the learners. // This paper explores how to improve learning process by adapting course content presentation to student learning styles in multi-platform environments such as PC and PDA. A framework has been developed to comprehensively model student’s learning styles and present the appropriate subject matter, including the content, format, media type, and so on, to suit individual student. The work is based on the Felder-Silverman Learning Style Theory. The framework uses traditional web-based intelligent tutorial architecture, with two additional components: ‘learning style analysis module’ and ‘access device analysis module’. The learning style analysis module takes care of modeling student learning style and communicates with student model, whereas the access device analysis module identifies the access device profile and provides the information to tutorial module. The tutorial module creates the suitable content, based on the student model (including individual learning styles) and access device profile, and presents to the student. // Based on the framework, a prototype for the domain of PHP programming course has been developed. With this system, students are able to learning PHP programming with course content that matches their own learning style and the device used to access the content. A formative evaluation is planned to assess the student satisfaction, learning efficiency, and effectiveness of the system while providing various presentations of the same content to different users on different devices.