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Adaptation is a desirable feature in on-line courses which allows for the consideration of students particular characteristics and needs. However, it is not common for teachers to embrace technologies related to this feature. This phenomenon may be mainly attributed to: a) unawareness of appropriate authoring tools, and/or b) resistance to their use. Regarding this panorama, this research has two purposes. The first purpose is to present a web platform to create adaptive on-line courses that considers three adaptive functionalities: curriculum sequencing, content presentation and assessment. The second purpose is to present a validation for such platform with real users, more specifically, 51 teachers of K-12. The obtained results show that even if there was general distrust while using the platform, there was also an overall interest in rely on a tool that grants teachers in providing an individualized learning experience. [ABSTRACT FROM AUTHOR]

Learning objects (LOs) repositories are important in building educational content and should allow search, retrieval and composition processes to be successfully developed to reach educational goals. However, such processes require so much time-consuming and not always provide the desired results. Thus, the aim of this paper is to propose a model for the semiautomatic composition of LOs, which are automatically recovered from open repositories. For the development of model, various text similarity measures are discussed, while for calibration and validation some comparison experiments were performed using the results obtained by teachers. Experimental results show that when using a value of k (number of LOs selected) of at least 3, the percentage of similarities between the model and such made by experts exceeds 75%. To conclude, it can be established that the model proposed allows teachers to save time and effort for LOs selection by performing a pre-filter process. [ABSTRACT FROM AUTHOR]