This paper considers learner misconceptions information which is presented to the learner in an open learner model. We suggest that specific information about misconceptions may be of benefit to the learner, to help them reflect on their knowledge and understanding. We investigate acceptance of their misconceptions presented as animations and step-by-step text descriptions by two groups of user...

The significance of the study of the theoretical and practical properties of AdaBoost is unquestionable, given its simplicity, wide practical use, and effectiveness on real-world datasets. Here we present a few open problems regarding the behavior of “Optimal AdaBoost,” a term coined by Rudin, Daubechies, and Schapire in 2004 to label the simple version of the standard AdaBoost algorithm in whi...

Class binarizations are effective methods that break multi-class problem down into several 2class or binary problems to improve weak learners. This paper analyzes which effects these methods have if we choose a Naive Bayes learner for the base classifier. We consider the known unordered and pairwise class binarizations and propose an alternative approach for a pairwise calculation of a modified...

Nowadays, instructional technologies are the enabler for educators to have more choices in course planning, course design, and lecturing. These technologies not only strengthen the communication between instructors and learners, but also let the learners get an easily access their course materials at anytime and from anywhere. As a result, many educational institutes, including formal universit...

We have implemented ubiquitous computing technology in a primary school setting to support rich classroom activities particularly in the field of early literacy. After initial tests have corroborated the benefit of this technology with respect to attaining curricular goals and to better supporting learner-centred classroom methodologies, we are now exploring specific intelligent support mechani...

We extend a recently proposed 1-nearest-neighbor based multiclass learning algorithm and prove that our modification is universally strongly Bayes consistent in all metric spaces admitting any such learner, making it an “optimistically universal” Bayes-consistent learner. This the first known to enjoy this property; by comparison, k-NN classifier its variants are not generally consistent, excep...

An extensive analysis of the college teaching literature (over 350 items) suggests that the perspective of perhaps the most highly effective college teachers has yet to be conceptualized, at least within a comprehensive developmental framework. This paper articulates that perspective-called here Systemocentrism (or teacher/learner-centeredness). The perspective b two distinctive elements-attent...

A learner corpus is a useful resource for developing automatic assessment techniques for implementation in a computer-assisted language learning system. However, presently, learner corpora are only helpful in terms of evaluating the accuracy of learner output (speaking and writing). Therefore, the present study proposes a learner corpus annotated with evaluation results regarding the accuracy a...