This research was designed to explore the learning experiences of state college students using mobile electronic textbook (e-book) readers. The purpose of the study was to build a rich description of how students used e-books delivered on mobile computing devices for college-level, introductory sociology courses at a public state college in the southeastern United States. This research employed...

The paper presents a technique of interrogation, in mobile technology, of a knowledge base contained in an e-Learning platform. The query is done through the integrated use of an adaptive search engine (ASE) and QR codes. The QR-Code are used to label objects in real environments of cultural matter (eg: museums, art galleries, archaeological sites, etc.). These objects can then be analyzed in m...

This paper discusses why traditional reinforce ment learning methods and algorithms applied to those models result in poor performance in dynamic situated multi agent domains char acterized by multiple goals noisy perception and action and inconsistent reinforcement We propose a methodology for designing the repre sentation and the forcement functions that take advantage of implicit domain know...

The objective of this paper is to inform the design of information systems that support competence development in a work context. The paper builds on an action research study which followed the logic of (1) developing a general design framework mainly based on situated learning theory, (2) developing design concepts based on the design framework, and (3) evaluating the design concepts, and thus...

This paper describes a qualitative study into students’ use of higher-order thinking as they use an interactive multimedia program based on a situated learning framework. The analysis of types of talk used by students as they worked with the program clearly shows that the majority of their thinking was higher order, as defined by Resnick (1987) and other theorists. Social, procedural and lower-...

We present a computational model that uses intention recognition as a basis for situated word learning. In an initial experiment, the model acquired a lexicon from situated natural language collected from human participants interacting in a virtual game environment. Similar to child language learning, the model learns nouns faster than verbs. In the model, this is due to inherent ambiguities in...