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Article
Publication date: 31 August 2004

Mircea Gh. Negoita and David Pritchard

Education is increasingly using Intelligent Tutoring Systems (ITS), both for modelling instructional and teaching strategies and for enhancing educational programs. The…

Abstract

Education is increasingly using Intelligent Tutoring Systems (ITS), both for modelling instructional and teaching strategies and for enhancing educational programs. The first part of the paper introduces the basic structure of an ITS as well as common problems being experienced within the ITS community. The second part describes WITNeSS ‐ an original hybrid intelligent system using Fuzzy‐Neural‐GA techniques for optimising the presentation of learning material to a student. The original work in this paper is related to the concept of a “virtual student”. This student model, modelled using fuzzy technologies, will be useful for any ITS, providing it with an optimal learning strategy for fitting the ITS itself to the unique needs of each individual student. In the third part, experiments focus on problems developing a “virtual student” model, which simulates, in a rudimentary way, human learning behaviour. Part four finishes with concluding remarks.

Details

Interactive Technology and Smart Education, vol. 1 no. 3
Type: Research Article
ISSN: 1741-5659

Keywords

Open Access
Article
Publication date: 28 July 2020

Julián Monsalve-Pulido, Jose Aguilar, Edwin Montoya and Camilo Salazar

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of…

Abstract

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

Book part
Publication date: 20 September 2018

Stephen B. Gilbert, Michael C. Dorneich, Jamiahus Walton and Eliot Winer

This chapter describes five disciplinary domains of research or lenses that contribute to the design of a team tutor. We focus on four significant challenges in developing…

Abstract

This chapter describes five disciplinary domains of research or lenses that contribute to the design of a team tutor. We focus on four significant challenges in developing Intelligent Team Tutoring Systems (ITTSs), and explore how the five lenses can offer guidance for these challenges. The four challenges arise in the design of team member interactions, performance metrics and skill development, feedback, and tutor authoring. The five lenses or research domains that we apply to these four challenges are Tutor Engineering, Learning Sciences, Science of Teams, Data Analyst, and Human–Computer Interaction. This matrix of applications from each perspective offers a framework to guide designers in creating ITTSs.

Details

Building Intelligent Tutoring Systems for Teams
Type: Book
ISBN: 978-1-78754-474-1

Keywords

Article
Publication date: 25 April 2022

Huixiao Le and Jiyou Jia

In intelligent tutoring systems (ITS), learners were often granted limited authority and are forced to obey the decision of the system which might not satisfy their needs…

Abstract

Purpose

In intelligent tutoring systems (ITS), learners were often granted limited authority and are forced to obey the decision of the system which might not satisfy their needs. Failure to grant learners sufficient autonomy could yield unexpected effects that hinder learning, including undermining learners’ motivation, priming learners’ aversion to the algorithm. On the contrary, granting learners overwhelming autonomy could also be harmful as the absence of learning support would also have a negative impact on learning. As such, this study aims to design and implement an intelligent tutoring system that offers learners proper autonomy.

Design/methodology/approach

The main learning activity in the system is doing exercises, and by finishing exercises learners could earn virtual coins. Based on item response theory, exercises are administered to learners with proper difficulty. Based on a recommended difficulty parameter predicted by the system, learners could manually modify the difficulty of the exercises, they could earn more credits by finishing more challenging exercises. Meanwhile, a pedagogical agent is embedded. Learners could customize the agent’s personality jointly with the system to create the learning context they prefer.

Findings

A intelligent tutoring system with proper learner autonomy (LA) is designed and implemented.

Originality/value

Few previous researches have noticed the potentially important role that LA plays in ITS. Learning might be facilitated using such a design.

Details

Interactive Technology and Smart Education, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-5659

Keywords

Article
Publication date: 1 September 1995

V. Venugopal and W. Baets

In the current global competitive environment, if an organizationis to be successful, it has to be a learning organization. Organizationslearn from their assertive and…

1815

Abstract

In the current global competitive environment, if an organization is to be successful, it has to be a learning organization. Organizations learn from their assertive and adaptive interaction with the environment and from their internal dynamics. Organizational learning needs to be supported as external environments and internal dynamics of organizations become more complex. Discusses different learning processes and the different intelligent systems which can support and enhance organizational learning. Finally, presents a conceptual framework of an integrated intelligent system for supporting organizational learning. Intends to be useful to both organizational theorists/ practitioners and IT managers, who are involved in the development and implementation of learning organizations.

Details

The Learning Organization, vol. 2 no. 3
Type: Research Article
ISSN: 0969-6474

Keywords

Article
Publication date: 31 August 2004

E. Kukla, N.T. Nguyen, C. Danilowicz, J. Sobecki and M. Lenar

In this paper a conception of the model for learning scenario determination is presented. We define the learning scenario as a sequence of the hypermedia pages…

Abstract

In this paper a conception of the model for learning scenario determination is presented. We define the learning scenario as a sequence of the hypermedia pages, representing particular knowledge units, and tests related to them. The scenario determination is a dynamic process that begins when a new student takes up a course. The opening scenario for this student is chosen as the consensus of the final scenarios of the students, who have already finished this course, and who belong to a class of the learners similar to the new one. We have elaborated the consensus‐based procedure for the scenario determination. Since this procedure operates on a set of similar learners, we have developed the conceptions of learner’s profile and students’ classification. The learner’s profile is proposed to include the attributes describing students’ personal data (as name, birthday etc.), their cognitive and learning styles as well as their usage data (represented by the learning scenarios). The students’ classification is based on a set of the basic attributes that seem to influence the learning effects. Their significance is verified during the learning process. We have also elaborated the procedure of reducing undistinguishable values of the attribute and removing useless attributes from the set of basic attributes. A learning procedure proposed, describes generally the situations when the scenario is modified, and the methods used for its modification.

Details

Interactive Technology and Smart Education, vol. 1 no. 3
Type: Research Article
ISSN: 1741-5659

Keywords

Book part
Publication date: 20 September 2018

Robert Sottilare and Eduardo Salas

This chapter examines some of the challenges and emerging strategies for authoring, distributing, managing, and evaluating Intelligent Tutoring Systems (ITSs) to support…

Abstract

This chapter examines some of the challenges and emerging strategies for authoring, distributing, managing, and evaluating Intelligent Tutoring Systems (ITSs) to support computer-based adaptive instruction for teams of learners. Several concepts related to team tutoring are defined along with team processes, and fundamental tutoring concepts are provided including a description of the learning effect model (LEM), an exemplar describing interaction between learners and ITSs with the goal of realizing optimal tutor decisions. The challenges noted herein are closely related to the LEM and range from acquisition of learner data, synthesis of individual learner and team state models based on available data, and tutor decisions which center on optimizing strategies (recommendations) and tactics (actions) given the state of the learner, the team, and the conditions under which they are being instructed, the environment. Finally, we end this chapter with recommendations on how to use this book to understand and design effective ITSs for teams.

Details

Building Intelligent Tutoring Systems for Teams
Type: Book
ISBN: 978-1-78754-474-1

Keywords

Book part
Publication date: 18 January 2022

Brian McBreen, John Silson and Denise Bedford

This chapter introduces the concept of an intelligent organization in the context of the twenty-first-century knowledge economy. An intelligent organization is one in…

Abstract

Chapter Summary

This chapter introduces the concept of an intelligent organization in the context of the twenty-first-century knowledge economy. An intelligent organization is one in which individuals behave intelligently, work is grounded in intelligent methods and choices, and rich stocks of intelligence in the form of knowledge capital to support intelligence work and choices. Intelligence is defined as both a thing and attribute and behavior and way of working. The chapter also highlights examples of intelligent behaviors and or organizational pathologies. The chapter also highlights the importance of becoming aware of intelligent and unintelligent choices.

Details

Organizational Intelligence and Knowledge Analytics
Type: Book
ISBN: 978-1-80262-177-8

Article
Publication date: 9 January 2007

Jason Watson, Pervaiz K. Ahmed and Glenn Hardaker

This research aims to investigate how a generic web‐based ITS can be created which will adapt the training content in real time, to the needs of the individual trainee…

1100

Abstract

Purpose

This research aims to investigate how a generic web‐based ITS can be created which will adapt the training content in real time, to the needs of the individual trainee across any domain.

Design/methodology/approach

After examining the various alternatives SCORM was adopted in this project because it provided an infrastructure that makes it possible to deliver personalised learning dynamically using re‐usable learning objects.

Findings

The results show that a system which presents a student with content that is supplementary to an authored course should be accompanied by a tool to help the trainee's navigation. For such a tool, key functionality would be: first, to identify learning objects that would take the student towards the ultimate learning goals; second, to suggest a pathway through the authored course structure and additional learning objects to the student; and finally, to present the student with different choices of pathway, such as fastest, most comprehensive and most popular routes.

Originality/value

This investigation has taken another approach of adapting the course by displaying an adapted set of learning objects to the trainee, instead of using a linear course structure.

Details

Campus-Wide Information Systems, vol. 24 no. 1
Type: Research Article
ISSN: 1065-0741

Keywords

Article
Publication date: 5 June 2007

Dawn G. Gregg

The purpose of this paper is to illustrate the advantages of using intelligent agents to facilitate the location and customization of appropriate e‐learning resources and…

3232

Abstract

Purpose

The purpose of this paper is to illustrate the advantages of using intelligent agents to facilitate the location and customization of appropriate e‐learning resources and to foster collaboration in e‐learning environments.

Design/methodology/approach

This paper proposes an e‐learning environment that can be used to provide customized learning. It utilizes a set of interacting agents that can personalize instruction based on an individual's prior knowledge as well as their cognitive and learning needs. The e‐learning agents monitor the e‐learning environment and improve learning and collaboration based on learners' prior knowledge, social characteristics and learning style.

Findings

E‐learning agents should allow the discovery of new learning objects more easily, allow learners to customize materials presented to improve learning outcomes, and improve collaboration in the e‐learning environment.

Originality/value

Little prior research has been done on the use of agents in e‐learning environments. This paper proposes a set of e‐learning agents that, if implemented in online education or training environments, should provide tangible benefits to organizations.

Details

The Learning Organization, vol. 14 no. 4
Type: Research Article
ISSN: 0969-6474

Keywords

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