Educational materials represent a domain model of Adaptive Web-based Educational System (AWBES). However, these materials should be designed to cover the differences of learners’ preferences. Herrmann Whole Brain Model (HWBM) is a reliable Learning Style (LS) model which can be used to extract the learner’s preferences in educational environment according to brain structure of learner. In this paper, the learning materials of an essential programming language course (C++) are organized to cover all learners’ differences according to their brain dominance. The learning materials were described and classified by instructional metadata to fit the preferences of four brain quadrants (rational, organizational, interpersonal and intuitive) within diverse learning objects. The main advantage of this approach is that it is not related to particular type of learners, but it covers the different learners according to their brain-structure. The system which could apply this model can be used to detect the learner preferences dynamically and thus personalize the learning materials within Web-based Educational System (WBES)
