Adaptive e-learning system based on accumulative digital activities in revised Bloom's taxonomy

Adaptive e-learning systems enhance efficiency in education by providing personalized e-course content (e.g., learning materials and activities) that changes with respect to learners' needs and achievements. An adaptive approach is presented in this paper, which is based upon accumulative digital activities and which is ordered according to pre-established demarcations of cognitive skills with components of the dimension of knowledge within Revised Bloom's Taxonomy. Utilizing the adaptive approach allows for a dynamic selection of different assignments for these activities in accordance with learners' resultant scores that are established after working on previous assignments. This type of selection ensures that individualized curricular content is determined by the level of knowledge of each learner and educational objectives. In order to be implemented the adaptive approach creates workflow that describes logical and meaningful connections between assignments of the digital activities. The implementation of the approach is made within the Moodle e-learning system by means of Bonita software in order to provide workflow modelling.