Semi-Adaptive Testing Strategies in a Web-based Generic Tutoring System

2004 ◽  
pp. 141-164
Author(s):  
Matthias R. Brust
Keyword(s):  
Adaptive Testing ◽  
Tutoring System ◽  
Student Model ◽  
Web Based ◽  
Tutoring Systems ◽  
Human Tutor ◽  
Testing Strategies ◽  
Fully Adaptive

Adaptive testing is an important component of most tutoring systems. This component normally interacts with the student model to determine students’ abilities and students’ knowledge. For this, fully adaptive testing strategies are used. However, this kind of strategy needs training for estimating specific values before they can be applied. Furthermore, the human tutor does not have any influence on the testing process. In this chapter, semi-adaptive testing strategies are introduced to deal with these problems. It is shown how a generic tutoring system can be designed to apply semi-adaptive testing strategies. The meta-language XML is used as approach for implementing these results in a Web-based application.

MAKING DECISIONS IN AN INTELLIGENT TUTORING SYSTEM

2005 ◽  
Vol 04 (02) ◽  
pp. 207-233 ◽  
Author(s):  
PENG-KIAT PEK ◽  
KIM-LENG POH
Keyword(s):  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
Learning Objectives ◽  
Tutoring System ◽  
Web Based ◽  
Tutoring Systems ◽  
Test Items ◽  
Optimal Policies ◽  
Separability Condition ◽  
Engineering Mechanics

In computerized tutoring, the pace of instruction is related to the student's mastery levels of the learning objectives. The observable student's behavior that can be used to measure his knowledge is usually his responses to test items. Unobservable variables that are related to learner's motivation can affect learning but are difficult to quantify. In comparison with other decision-theoretic tutoring systems, the novelties of this research are: (1) the efficiency-centric approach to develop the Bayesian networks; (2) the formulation of utility values for different tutoring outcomes that are independent of past actions and to satisfy the separability condition; (3) the development of a common measure for student's mastery levels and item difficulties; and (4) the generation of optimal policies in polynomial time. A prototype web-based tutoring system, known as iTutor, incorporating the novelties has been developed for engineering mechanics. Formative evaluations of iTutor have shown encouraging results.

Developing an Intelligent Tutoring System that has Automatically Generated Hints and Summarization for Algebra and Geometry

2015 ◽  
Vol 11 (2) ◽  
pp. 14-31 ◽  
Author(s):  
Yatao Li ◽  
Ke Zhao ◽  
Wei Xu
Keyword(s):  
Problem Solving ◽  
Natural Language ◽  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
After School ◽  
Tutoring System ◽  
Learning Gain ◽  
Web Based ◽  
Tutoring Systems ◽  
Natural Language Interface

Intelligent tutoring systems (ITSs), which provide step-by-step guidance to students in problem-solving activities, have been shown to enhance student learning in a range of domains. However, they tend to be preestablished and cannot supply the tutoring function immediately from the diverse mathematical questions. The MITSAS (multiagent intelligent tutoring system after school) is a web-based ITS in algebra and geometry with a natural language interface which is designed to extract the hint and summarization from the detailed solving answer automatically. In this paper, its Design principles and functionality is analysed firstly. Then, the framework including the natural language understanding agent, automatic modelling agent and automatic problem-solving agent are discussed in the following in order to support the real-time problems solution. Next, the methods for automatically extracting tutoring function such as hint and summarization is given based on the difficulty of knowledge components and the type of problem acquired from the detailed answer. Finally, the effectiveness of MITSAS at improving the Chinese Students' learning gain is shown by an experiment conducted in junior school.

Error-specific and individualised feedback in a Web-based language tutoring system: Do they read it?

ReCALL ◽  
2001 ◽  
Vol 13 (1) ◽  
pp. 99-109 ◽  
Author(s):  
TRUDE HEIFT
Keyword(s):  
Error Correction ◽  
Tutoring System ◽  
Student Model ◽  
Web Based ◽  
Metalinguistic Feedback ◽  
Specific Feedback ◽  
Student Input

This paper discusses learners’ responses to metalinguistic feedback and their strategies in error correction in a Web-based Intelligent Language Tutoring System (ILTS) for German. The system consists of a grammar and a parser which analyses student input and provides error-specific feedback to grammar and vocabulary exercises. Furthermore, the ILTS employs a Student Model that matches feedback messages to learner expertise and provides remedial exercises. Two beginner German classes, 33 students in all, used the ILTS for grammar practice, submitting a total of 4405 sentences for analysis. The results indicate that for the vast majority of sentences (79.5%) students read and attended to system feedback. Moreover, as iterations increased students paid more attention to the feedback messages.

Web-Based Music Intelligent Tutoring Systems

2011 ◽  
pp. 231-248
Author(s):  
Somnuk Phon-Amnuaisuk ◽  
Chee Keh Siong
Keyword(s):  
Teaching And Learning ◽  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
Learning Technologies ◽  
Tutoring System ◽  
Web Based ◽  
Tutoring Systems ◽  
Pedagogical Aspect ◽  
Teaching Music ◽  
Inference Techniques

Our work bridges two interesting topics: the research in the area of web-based applications and the area of learning technologies. We give an overall picture of the current development in web-based music intelligent tutoring system (WMITS). The term WMITS is coined by us to describe the two main areas in our focus. In this chapter, we address the following issues: (i) the pedagogical aspect of teaching and learning music, (ii) the background of music intelligent tutoring system and (iii) our WMITS system for teaching music theories. A web-based environment offers strengths in terms of accessibility and self-paced learning. However, the environment has a great drawback in terms of inter-activities between the users and the system. Our design addresses this issue by developing a specialised client tool. The client tool provides an interactive environment for score editing which is crucial for learning music theories. The system incorporates three major inference techniques (i.e. Deductive, Inductive, and Bayesian Inference) in dealing with music theories and uncertain knowledge such as students’ understanding.

Live-action mass-casualty training and virtual world training

2016 ◽  
Vol 60 (1) ◽  
pp. 2103-2107 ◽  
Author(s):  
Keith T. Shubeck ◽  
Scotty D. Craig ◽  
Xiangen Hu
Keyword(s):  
Virtual World ◽  
Domain Knowledge ◽  
Mass Casualty ◽  
Learning Technologies ◽  
Learning Needs ◽  
Web Based ◽  
Tutoring Systems ◽  
Aeromedical Evacuation ◽  
User Input ◽  
Live Action

Live-action training simulations with expert facilitators are considered by many to be the gold-standard in training environments. However, these training environments are expensive, provide many logistical challenges, and may not address the individual’s learning needs. Fortunately, advances in distance-based learning technologies have provided the foundation for inexpensive and effective learning environments that can simultaneously train and educate students on a much broader scale than live-action training environments. Specifically, intelligent tutoring systems (ITSs) have been proven to be very effective in improving learning outcomes. The Virtual Civilian Aeromedical Evacuation Sustainment Training (VCAEST) interface takes advantage of both of these technologies by enhancing a virtual world with a web-based ITS, AutoTutor LITE (Learning in Interactive Training Environments). AutoTutor LITE acts as a facilitator in the virtual world by providing just-in-time feedback, presenting essential domain knowledge, and by utilizing tutoring dialogues that automatically assess user input. This paper will discuss the results of an experimental evaluation of the VCAEST environment compared to an expert-led live-action training simulation.

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