Andes: An Intelligent Tutor for Classical Physics

Schulze, Kay G.; Shelby, Robert; Treacy, D.J.; Wintersgill, M. C.; VanLehn, Kurt; Gertner, Abigail S.

doi:10.3998/3336451.0006.110

Cited by 25 publications

(12 citation statements)

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“…These can be used to represent both correct and incorrect knowledge and provide increased modularity (single rules instead of entire procedures) and decreased grain size (single problem solving steps versus entire paths). ANDES, physics tutor is one example of such a system and contains approximately 600 rules [Schulze, Shelby, Treacy, Wintersgill, Vanlehn and Gertner 2000]. Constraint-based modelling based on Ohlsson's theory of learning from performance errors [Ohlsson 1996] uses the notion of state constraints to represent knowledge.…”

Section: The Domain Modulementioning

confidence: 99%

Assessing the Impact of Positive Feedback in Constraint-Based Tutors

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Mitrović

Ohlsson

et al. 2008

Intelligent Tutoring Systems

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Across many domains, Intelligent Tutoring Systems (ITSs) are used to facilitate practice, providing a customized learning environment and personal tutoring experience for students to learn at their own pace through effective student modeling and feedback. queries. An evaluation study was conducted at the University of Canterbury involving a control group of students who used the original version of SQL-Tutor giving only negative feedback and an experimental group using the modified version of SQL-Tutor where both negative and positive feedback were given. Results of the study show that students learn quite similarly from one system to another, however those in the experimental group take significantly less time to solve the same number of problems, in fewer attempts compared to those in the control group. Students in the experimental group also learn approximately the same number of concepts as students in the control but in much less time. This indicates that positive feedback results in increased amount of learning over a shorter period of time and improves the effectiveness of learning in ITSs.

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Section: The Domain Modulementioning

confidence: 99%

Assessing the Impact of Positive Feedback in Constraint-Based Tutors

Barrow

Mitrović

Ohlsson

et al. 2008

Intelligent Tutoring Systems

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“…On one evaluation of Andes1, the mean posttest exam score of the students who did their homework on Andes1 was approximately one standard deviation higher than the mean exam score of students who did the same homework with pencil and paper (Schulze, Shelby, Treacy, Wintersgill, VanLehn, & Gertner, 2000, as reported in VanLehn et al, 2005. In addition, the Bayesian student modeling technique was found to be a highly accurate assessment of student mastery (VanLehn & Niu, 2001).…”

Section: Andes1mentioning

confidence: 75%

Evaluation of Automated Diagnosis and Instruction for Mathematics Problem‐solving

Underwood

2007

ETS Research Report Series

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ETS and the ETS logo are registered trademarks ofEducational Testing Service (ETS). AbstractThe past several decades have seen numerous approaches toward automated diagnosis and instructional support of students engaged in mathematics problem-solving. These approaches typically involve detailed analysis of potential solution paths for problems, formal representations of correct and incorrect answers, and support in the form of feedback or explanations to students during the process of solving a problem. The approaches of each of a number of representative systems (ACED, ALEKS, Cognitive Tutors, Andes, and Assistments)will be described through a critical evaluation of how they represent content knowledge, their approaches to diagnosis, and their approaches to instructional support. Finally, recommendations are made for new approaches to automated diagnosis and instructional support of mathematics problem-solving.

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“…Gertner et al 1998;A. S. Gertner and VanLehn 2000;Schulze et al 2000a;Schulze et al 2000b). Along with the CMU tutors, Andes assumed that mastery learning would cause large gains in either effectiveness or efficiency, so it was worth determining which rules a student had mastered.…”

Section: Lesson 3: Goal-free Interfaces Make Embedded Assessment Muchmentioning

confidence: 99%

Reflections on Andes’ Goal-free User Interface

VanLehn

2015

Int J Artif Intell Educ

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Although the Andes project produced many results over its 18 years of activity, this commentary focuses on its contributions to understanding how a goalfree user interface impacts the overall design and performance of a step-based tutoring system. Whereas a goal-aligned user interface displays relevant goals as blank boxes or empty locations that the student needs to fill with specific content, a goal-free user interface is essentially a blank canvas, with no visual indications of the goals that should be attempted next. This commentary also briefly mentions work that occurred after the Bfinal^report on Andes appeared in this journal in 2005. The newer work focused on getting students to ask for hints when they need them.

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Andes: An Intelligent Tutor for Classical Physics

Cited by 25 publications

References 0 publications

Assessing the Impact of Positive Feedback in Constraint-Based Tutors

Assessing the Impact of Positive Feedback in Constraint-Based Tutors

Evaluation of Automated Diagnosis and Instruction for Mathematics Problem‐solving

Reflections on Andes’ Goal-free User Interface

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