Web-Based Intelligent Tutoring Systems Using the SCORM 2004 Specification - A Conceptual Framework for Implementing SCORM Compliant Intelligent Web-Based Learning Environments

2010 ◽  
Author(s):  
Gustavo Santos ◽  
Álvaro Figueira
Keyword(s):  
Conceptual Framework ◽  
Learning Environments ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Web Based ◽  
Tutoring Systems ◽  
Web Based Learning

Recent Advances in Intelligent Tutoring Systems

2013 ◽  
pp. 631-647
Author(s):  
Joel J. P. C. Rodrigues ◽  
Pedro F. N. João ◽  
Isabel de la Torre Díez
Keyword(s):  
Learning Process ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Field Tests ◽  
Study Guide ◽  
Web Based ◽  
Tutoring Systems ◽  
Recent Advances ◽  
The Web

Intelligent Tutoring Systems (ITS) include interactive applications with some intelligence that supports the learning process. Some of ITS have had a very large impact on educational outcomes in field tests, and they have provided an important ground for artificial intelligence research. This chapter elaborates on recent advances in ITS and includes a case study presenting an ITS called EduTutor. This system was created for the Web-Based Aulanet Learning Management System (LMS). It focuses on subjects for the first cycle of studies of the Portuguese primary education system, between the first and the fourth year. It facilitates the perception of the learning process of each student, individually, in a virtual environment, as a study guide. Moreover, EduTutor has been designed and its architecture prepared for being easily integrated into higher levels of studies, different subjects, and several languages. Currently, it is used in the Aulanet LMS platform.

Intelligent Tutoring and Games (ITaG)

2010 ◽  
pp. 44-65 ◽  
Author(s):  
Danielle S. McNamara ◽  
G. Tanner Jackson ◽  
Art Graesser
Keyword(s):  
Conceptual Framework ◽  
Learning Environments ◽  
Functional Groups ◽  
Intelligent Tutoring ◽  
Learning Systems ◽  
Potential Solution ◽  
Learning Gains ◽  
Tutoring Systems ◽  
System A ◽  
Insight Into

Intelligent Tutoring Systems (ITSs) have been producing consistent learning gains for decades. The authors describe here a conceptual framework that provides a guide to how adding game-based features and components may improve the effectiveness of ITS learning environments by improving students’ motivation to engage with the system. A problem consistently faced by ITS researchers is the gap between liking and learning. ITSs effectively produce learning gains, but students often dislike interacting with the system. A potential solution to this problem lies in games. ITS researchers have begun to incorporate game-based elements within learning systems. This chapter aims to describe some of those elements, categorize them within functional groups, and provide insight into how elements within each category may affect various types of motivation.

Using Intelligent Tutoring Technologies to Enhance Online Learning Environments

2011 ◽  
pp. 2246-2251
Author(s):  
Kausalai Kay Wijekumar
Keyword(s):  
Online Learning ◽  
Distance Learning ◽  
Learning Environments ◽  
Intelligent Tutoring Systems ◽  
Interactive Learning ◽  
Intelligent Tutoring ◽  
Interactive Learning Environments ◽  
Group Instruction ◽  
Tutoring Systems ◽  
Human Tutoring

Online and distance learning environments have changed dramatically over the last 20 years and are now sophisticated interactive learning environments. However, much more improvement is possible, and some of that improvement might come from mining some of the technologies developed as part of intelligent tutoring systems. Intelligent tutoring systems combine the best of human tutoring by capturing one on one tutoring interactions between a teacher and student on all topics for a learning module and converting them to a computerized version. The computerized version is designed to gauge the understanding of the student and adapt the instruction, modeling, hints, interactions, and activities to particular students. The systems are usually designed to assess the student’s learning continuously and scaffold the learning of the student. Ideally, these interactions will mimic human tutoring that has been shown to significantly improve learning beyond large group instruction.

Toward a Feature-Driven Understanding of Students' Emotions during Interactions with Agent-Based Learning Environments

Gamification ◽  
2015 ◽  
pp. 2148-2166
Author(s):  
Jason M. Harley ◽  
Roger Azevedo
Keyword(s):  
Learning Environments ◽  
Intelligent Tutoring Systems ◽  
Affective Computing ◽  
Intelligent Tutoring ◽  
Relative Effectiveness ◽  
Specific System ◽  
Tutoring Systems ◽  
Agent Based ◽  
Selective Review

This selective review synthesizes and draws recommendations from the fields of affective computing, intelligent tutoring systems, and psychology to describe and discuss the emotions that learners report experiencing while interacting with agent-based learning environments (ABLEs). Theoretically driven explanations are provided that describe the relative effectiveness and ineffectiveness of different ABLE features to foster adaptive emotions (e.g., engagement, curiosity) vs. non-adaptive emotions (e.g., frustration, boredom) in six different environments. This review provides an analytical lens to evaluate and improve upon research with ABLEs by identifying specific system features and their relationship with learners' appraisals and emotions.

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