Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Please provide a short abstract of 100 to 250 words. The abstract should not contain any undefined abbreviations or unspecified references. Work planned but not completed should not appear in the abstract.

User Modeling and User-Adapted Interaction

Artificial Intelligence and Tutoring Systems

An Introduction to Probability Theory and Its Applications. Volume II By William Feller. Pp. xviii, 626. 90s. 1966. (Wiley)

In this special issue is to indicate foresight, innovation, and strategy for the future direction of e-learning, more than web-oriented teaching and multipoint videoconferencing, for collaborative, distributed, experiential learning and creation of new knowledge, with youngsters around the world, which hence promote mutual understanding for global peace. Emphasis will be on knowledgeable and inspiring papers (but not limited) on the use of GRID networking technology with distributed computer simulation for experiential (hands-on) learning through broadband Internet, across national, continental and oceanic boundaries. Subjects are in any fields of e-learning and e-healthcare/telemedicine, in research, case studies, project descriptions, implementation, reports from the field or book review. Preparing this special issue with Dr. Salmon, took 6 months, from the beginning to the arrival period to the on your screen. This period was shorter than the first special issue publishing in 2004. Of course this success belongs to this issue's guest editor who I will explain a bit details him belove and what did he do during in his period. During this process, Dr. Salmon served very healthy communication between the authors. In addition, she spared his valuable time, beside his other academic activities and responsibilities in the name of her university, her lectures, and researches, duties for distance education field and for TOJDE as well. Each article in this issue has therefore been read carefully by Gilly; me and Dr. Gokdag. This process has maximized the quality and rigour of the published articles. In addition to the articles, " notes for editor " books review and news, sections are still keeping in this issue too. "Anadolu University's Articles" and "TOJDE's links are getting more" columns are still keeping in this issue too. I would like to express my sincere thanks especially to Dr. Salmon in the name of my University and also for TOJDE she was the leader of the guest editorial team in this special issue. She will give detail info about structure of the articles in her " From Guest Editors " article. I strongly believe that experience gained on this third special issue would encourage us and other interested colleagues in the field in the near future. Below you will find short biodata about guest editors. He interested in heavily with the applications of distance education in Turkey, profile of the distance education students and graduates, additionally relationships of the distance education graduates and market. And last but not …

Encyclopedia of Distance Learning

Activity recognition using eye-gaze movements and traditional interactions

The article describes a recognition approach of undertaken activities of daily living (ADLs) performed by memory and/or cognitively impaired elders in smart homes. The proposed technique is materialized via a recognition module inserted in a modular generic architecture which aims to offer a framework to conceive intelligent ADLs assistance systems.

Intelligent Recognition of Activities of Daily Living for Assisting Memory and/or Cognitively Impaired Elders in Smart Homes

In the field of e-learning, a popular solution to make teaching material reusable is to represent it as learning object (LO). However, building better adaptive educational software also takes an explicit model of the learner’s cognitive process related to LOs. This paper presents a three layers model that explicitly connect the description of learners’ cognitive processes to LOs. The first layer describes the knowledge from a logical and ontological perspective. The second describes cognitive processes. The third builds LOs upon the two first layers. The proposed model has been successfully implemented in an intelligent tutoring system for teaching Boolean reduction that provides highly tailored instruction thanks to the model.

/pdf/a-cognitive-and-logic-based-model-for-building-glass-box-1zf8n5ncxb.pdf

A Cognitive and Logic Based Model for Building Glass-Box Learning Objects

Despite a growing development of virtual laboratories which use the advantages of multimedia and Internet for distance education, learning by means of such tutorial tools would be more effective if they were specifically tailored to each student needs. The virtual teaching process would be well adapted if an artificial tutor can identify the correct acquired knowledge, recognise the erroneous learner’s knowledge and suggest a suitable sequence of pedagogical activities to improve the level of the student. This paper proposes a knowledge representation model which judiciously serves the remediation process to students’ errors during e-learning activities. The model is inspired by recent researches on computational representation of the knowledge and by cognitive psychology theories that offer a refined modelling of the human learning processes. Experimental results, obtained via practical tests, show that the knowledge representation and remediation approach facilitates the planning of tailored sequences of feedbacks that considerably help the learner.

On Scaffolding Adaptive Teaching Prompts Within Virtual Labs

Encouraging results of the last few years in the field of knowledge representation within virtual learning environments confirm that artificial intelligence research in this topic finds it very beneficial to integrate the knowledge that psychological research has accumulated on understanding the cognitive mechanism of human learning and all the positive results obtained in computational modeling theories. This article introduces a novel cognitive and computational knowledge representation approach inspired by cognitive theories that explain the human cognitive activity in terms of memory subsystems and their processes, and whose aim is to suggest formal computational models of knowledge that offer efficient and expressive representation structures for virtual learning. Practical studies both contribute to validate the novel approach and permit to draw general conclusions.

Mehdi Najjar

Papers

Activity recognition using eye-gaze movements and traditional interactions

Intelligent Recognition of Activities of Daily Living for Assisting Memory and/or Cognitively Impaired Elders in Smart Homes

A Cognitive and Logic Based Model for Building Glass-Box Learning Objects

On Scaffolding Adaptive Teaching Prompts Within Virtual Labs

AURELLIO: A Cognitive Computational Knowledge Representation Theory