4,327 research outputs found
A Comparative Analysis of Cognitive Tutoring and Constraint-Based Modeling
Numerous approaches to student modeling have been proposed since
the inception of the field more than three decades ago. hat the field is lacking
completely is comparative analyses of different student modeling approaches.
Such analyses are sorely needed, as they can identify the most promising
approaches and provide guidelines for future research. In this paper we
compare Cognitive Tutoring to Constraint-Based Modeling (CBM). We present
our experiences in implementing a database design tutor using both
methodologies and highlight their strengths and weaknesses. We compare their
characteristics and argue the differences are often more apparent than real. For
specific domains, one approach may be favoured over the other, making them
viable complementary methods for supporting learning
Intelligent tutoring systems for systems engineering methodologies
The general goal is to provide the technology required to build systems that can provide intelligent tutoring in IDEF (Integrated Computer Aided Manufacturing Definition Method) modeling. The following subject areas are covered: intelligent tutoring systems for systems analysis methodologies; IDEF tutor architecture and components; developing cognitive skills for IDEF modeling; experimental software; and PC based prototype
On empirical methodology, constraints, and hierarchy in artificial grammar learning
This paper considers the AGL literature from a psycholinguistic perspective. It first presents a taxonomy of the experimental familiarization test procedures used, which is followed by a consideration of shortcomings and potential improvements of the empirical methodology. It then turns to reconsidering the issue of grammar learning from the point of view of acquiring constraints, instead of the traditional AGL approach in terms of acquiring sets of rewrite rules. This is, in particular, a natural way of handling long‐distance dependences. The final section addresses an underdeveloped issue in the AGL literature, namely how to detect latent hierarchical structure in AGL response patterns
Towards an Intelligent Tutor for Mathematical Proofs
Computer-supported learning is an increasingly important form of study since
it allows for independent learning and individualized instruction. In this
paper, we discuss a novel approach to developing an intelligent tutoring system
for teaching textbook-style mathematical proofs. We characterize the
particularities of the domain and discuss common ITS design models. Our
approach is motivated by phenomena found in a corpus of tutorial dialogs that
were collected in a Wizard-of-Oz experiment. We show how an intelligent tutor
for textbook-style mathematical proofs can be built on top of an adapted
assertion-level proof assistant by reusing representations and proof search
strategies originally developed for automated and interactive theorem proving.
The resulting prototype was successfully evaluated on a corpus of tutorial
dialogs and yields good results.Comment: In Proceedings THedu'11, arXiv:1202.453
A Causal-Comparative Study on the Efficacy of Intelligent Tutoring Systems on Middle-Grade Math Achievement
This study is a quantitative examination of intelligent tutoring systems in two similar suburban middle schools (grades 6-8) in the Southeastern United States. More specifically, it is a causal-comparative study purposed with examining the efficacy of intelligent tutoring systems as they relate to math achievement for students at two similar middle schools in the Midlands of South Carolina. The independent variable, use of an intelligent tutoring system in math instruction, is defined as the supplementary use of two intelligent tutoring systems, Pearson’s Math Digits and IXL, for math instruction. The dependent variable is math achievement as determined by the Measures of Academic Progress (MAP) SC 6+Math test. The student data examined is archived MAP SC 6+ Math scores from the 2017-2018 school year. A one-way ANCOVA was used to compare the mean achievement gain scores of both groups, students whose math instruction included intelligent tutoring systems and students whose math instruction did not include intelligent tutoring systems, to establish whether or not there was any statistically significant difference between the adjusted population means of the two independent groups. The results showed that the adjusted mean of posttest scores of students who did not receive math instruction that involved an intelligent tutoring system were significantly higher than those who did
Intelligent training in control centres based on an ambient intelligence paradigm
This article describes a new approach in the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances
Large-Scale Deployment of Three Intelligent Web-Based Database Tutors
We present our experiences with DatabasePlace, a Web portal aimed at university-level students enrolled in database courses. The portal was established by Addison-Wesley in January 2003. Besides presenting information about the textbooks, the portal also provides additional domain information, online quizzes and three Intelligent Tutoring Systems developed by the Intelligent Computer Tutoring Group (ICTG). We briefly present the three systems, and then discuss our experiences. We also compare the DatabasePlace students to our local students using the three ITSs
Authoring Example-based Tutors for Procedural Tasks
Researchers who have worked on authoring systems for intelligent tutoring systems (ITSs) have examined how examples may form the basis for authoring. In this chapter, we describe several such systems, consider their commonalities and differences, and reflect on the merit of such an approach. It is not surprising perhaps that several tutor developers have explored how examples can be used in the authoring process. In a broader context, educators and researchers have long known the power of examples in learning new material. Students can gather much information by poring over a worked example, applying what they learn to novel problems. Often these worked examples prove more powerful than direct instruction in the domain. For example, Reed and Bolstad (1991) found that students learning solely by worked examples exhibited much greater learning than those learning instruction based on procedures. By extension then, since tutor authoring can be considered to be teaching a tabula rasa tutor, tutor authoring by use of examples may be as powerful as directly programming the instruction, while being easier to do
Learner Modelled Environments
Learner modelled environments (LMEs) are digital environments that are capable of
automatically detecting learner’s behaviours in relation to a specific knowledge
domain, to reason about those behaviours in order to asses learner’s performance,
skills, socio-emotional and cognitive needs, and to act accordingly in a pedagogically
appropriate manner. Digital environments that possess such capabilities are typically
referred to as Intelligent Learning Environments, or more traditionally – as Intelligent
Tutoring Systems (ITSs)
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