Background: Because of approaches to learning in every place and at any time, ubiquitous learning with knowledge of the context and framework, and due to the development of wireless technologies and sensors, the learning process has changed. Mobile learning and ubiquitous learning as models of e-learning that refer to the acquisition of knowledge, attitudes and skills through wireless technolog...

because of approaches to learning in every place and at any time, ubiquitous learning with knowledge of the context and framework, and due to the development of wireless technologies and sensors, the learning process has changed. mobile learning and ubiquitous learning as models of e-learning that refer to the acquisition of knowledge, attitudes and skills through wireless technologies. the eff...

introduction: in this study, the authors aimed to examine the effects of cooperative learning methods using web quest and team-based learning on students’ self-direction, self-regulation, and academic achievement. methods: this is a comparative study of students taking a course in mental health and psychiatric disorders. in two consecutive years, a group of students were trained using the web q...

There has been a dramatic growth of research concerned about the ubiquitous learning (u-learning) in recent years. It has an urgent need that U-learning systems have to be continuously evaluated and improved for ensuring the system reliability. However, there are only few or none of existent u-learning system evaluation researches. Therefore, this study develops a u-learning evaluation method s...

U-shaped learning is a learning behaviour in which the learner first learns something, then unlearns it and finally relearns it. Such a behaviour, observed by psychologists, for example, in the learning of past-tenses of English verbs, has been widely discussed among psychologists and cognitive scientists as a fundamental example of the non-monotonicity of learning. Previous theory literature h...

The paper deals with the following problem: is returning to wrong conjectures necessary to achieve full power of algorithmic learning? Returning to wrong conjectures complements the paradigm of U-shaped learning [3,7,9,24,29] when a learner returns to old correct conjectures. We explore our problem for classical models of learning in the limit from positive data: explanatory learning (when a le...

A decision list is an ordered list of conjunctive rules (Rivest 1987). Inductive algorithms such as AQ and CN2 learn decision lists incrementally, one rule at a time. Such algorithms face the rule overlap problem -the classification accuracy of the decision list depends on the overlap between the learned rules. Thus, even though the rules are learned in isolation, they can only be evaluated in ...