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Tutoring and Intelligent Tutoring Systems

Editor: Scotty D. Craig (Arizona State University)

Nova Science Publishers

Tutoring and Intelligent Tutoring Systems-small

 Brief Description

This book explores the intersection of tutoring and intelligent tutoring systems. The process of tutoring has a long history within learning settings. This effective method led to attempts to automate the process and the Intelligent Tutoring System research area. Intelligent Tutoring Systems (ITS) are increasingly being used in a wide range of educational settings to enhance student learning. They are also used frequently as platforms for research on educational psychology and artificial intelligence. ITS can assess a wide variety of learner characteristics and adapt instruction according to principles of learning. Their effectiveness allegedly derives from their ability to provide detailed guidance to learners and to adapt promptly to individual learner’s needs that are tracked at a fine grained level. Examples of such tutoring technologies included writing (but are not limited to) environments for guided inquiry learning, environments for collaborative problem solving or discussion, natural language processing and dialogue in tutoring systems, modeling and shaping affective states, interactive simulations of complex systems, ill-defined domains, and adaptive educational games. At their core, these systems rely on our basic knowledge of effective human tutoring. The book starts with a presentation of learning frameworks related to tutoring and ITS. This is followed by examples of best practices of tutoring and learning strategies implementing within specific ITS. Finally, it presents examples of evaluating effectiveness of tutoring systems. It is available in print and eBook format from the publisher and also on Amazon and Barnes & Noble.

 

 Target Audience

The target audience of this book spans researchers, practitioners, developers, and professionals. This multidisciplinary area synthesizes diverse contributions from education, psychology, learning science, computer science, software engineering, artificial intelligence, human factors, and user-experience design.

 

Table of Contents

Preface  (link to Preface on Research gate)

Frameworks

Chapter 1

What is Tutoring? On the Nature and Origin of Human Pedagogy

Donald M. Morrison

pp. 3-40 (Summary PDF)

Chapter 2

Facilitating Peer Tutoring and Assessment in Intelligent Learning Systems

Rod D. Roscoe, Erin A. Walker, and

Melissa M. Patchan

pp. 41-68 (Summary PDF)

Chapter 3

Framework for the Design of Accessible Intelligent Tutoring Systems

Eric G. Hansen, Diego Zapata-Rivera, and

Jason White

pp. 69-100 (Summary PDF)

Best Practices and ITS Technologies

Chapter 4

Intelligent Tutoring Systems that Adapt to Learner Motivation

Benedict du Boulay

pp. 103-128 (Summary PDF)

Chapter 5

Embedding Effective Teaching Strategies in Intelligent Tutoring Systems

Keith T. Shubeck, Ying Fang, Andrew J. Hampton, Brent Morgan, Xiangen Hu, and Arthur C. Graesser

pp. 129- 156 (Summary PDF)

Chapter 6

MetaMentor: An Interactive System That Uses Visualizations of Students’ Real-Time Cognitive, Affective, Metacognitive, and Motivational Self-Regulatory Processes to Study Human Tutors’ Decision Making

Nicholas V. Mudrick, Michelle Taub, and Roger Azevedo

pp. 157-186 (Summary PDF)

Chapter 7

Operationalizing the Contingent Scaffolding of Human Tutors in an Intelligent Tutoring System

Sandra Katz, Patricia Albacete, Pamela Jordan, Dennis Lusetich, Irene-Angelica Chounta, and Bruce M. McLaren

pp. 187-220 (Summary PDF)

Chapter 8

Adaptive Literacy Instruction in iSTART and W-Pal: Implementing the Inner and Outer Loop

Amy M. Johnson, Cecile A. Perret, Micah Watanabe, Kristopher J. Kopp, Kathryn S. McCarthy, and Danielle S. McNamara

pp.221-249 (Summary PDF)

Evaluations of Tutoring Systems

Chapter 9

Please ReaderBench this Text: A Multi-Dimensional Textual Complexity Assessment Framework

Mihai Dascalu, Scott A. Crossley, Danielle S. McNamara, Philippe Dessus, and

Stefan Trausan-Matu

pp. 251-272 (Summary PDF)

Chapter 10

Simulated Student Behaviors with Intelligent Tutoring Systems: Applications for Authoring and Evaluating Network-Based Tutors

Eric G. Poitras, Zachary Mayne, Lingyun Huang, Tenzin Doleck, Laurel Udy, and Susanne P. Lajoie

pp. 273-298 (Summary PDF)

Chapter 11

Impact of Argumentation Scripts on Socio-Cognitive Conflict Induction in Intelligent Tutoring System Environments

Zhou Long, Hongli Gao, Nia Dowell, and Xiangen Hu

pp. 299-320 (Summary PDF)

Chapter 12

Wizard’s Apprentice: Testing of an Advanced Conversational Intelligent Tutor

Jae-wook Ahn, Patrick Watson, Maria Chang, Sharad Sundararajan, Tengfei Ma, Nirmal Mukhi, Srijith Parabhu, and Bob Schloss

pp. 321-340 (Summary PDF)

Chapter 13

The Tale of Two Tutoring Interventions: Implications for Targeting Reading Fluency

Kristen Figas and Julie Q. Morrison

pp. 341-364 (Summary PDF)

 

Publisher

This book was published by Nova Science Publishers, Inc. This publication was released Fall 2018.  It is available in print and eBook format from the publisher and also on Amazon and Barnes & Noble.

 

Copyright CoBALT Lab 2014