Preliminary Evaluation of a Negotiable Student Model in a Constraint-Based Its

Thomson, David; Mitrović, Antonija

doi:10.1142/s1793206810000797

Cited by 23 publications

(22 citation statements)

References 4 publications

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“…The plant (column 2) demonstrates the tutor's assessment of student effort, while the mastery bar (column 3) records presumed knowledge (according to Bayesian Knowledge Tracing). The tutor comments on its assessment of the student's behavior (column 4) and offers students the choice to continue, review or challenge themselves and make informed decisions about future choices (column 5) the relation between metacognition, student learning (Zimmerman 2000), and supporting students' self-regulation (Aleven et al 2010;Roll et al 2007) shows that open student models promote metacognitive activities by encouraging students to reflect on their progress, to take greater control and responsibility over their learning, and to increase their trust in an adaptive environment through increased transparency (Bull 2012;Kay 2012;Long and Aleven 2013;Mathews et al 2012;Thomson and Mitrovic 2010). The open student model in Wayang allows students to inspect their progress and the tutor's assessment of their work, see Fig.…”

Section: Open Student Models To Enhance Self-regulationmentioning

confidence: 99%

A Multimedia Adaptive Tutoring System for Mathematics that Addresses Cognition, Metacognition and Affect

Arroyo

Woolf

Burelson

et al. 2014

Int J Artif Intell Educ

179

103

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This article describes research results based on multiple years of experimentation and real-world experience with an adaptive tutoring system named Wayang Outpost. The system represents a novel adaptive learning technology that has shown successful outcomes with thousands of students, and provided teachers with valuable information about students' mathematics performance. We define progress in three areas: improved student cognition, engagement, and affect, and we attribute this improvement to specific components and interventions that are inherently affective, cognitive, and metacognitive in nature. For instance, improved student cognitive outcomes have been measured with pre-post tests and state standardized tests, and achieved due to personalization of content and math fluency training. Improved student engagement was achieved by supporting students' metacognition and motivation via affective learning companions and progress reports, measured via records of student gaming of the system. Student affect within the tutor was measured through sensors and

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Section: Open Student Models To Enhance Self-regulationmentioning

confidence: 99%

A Multimedia Adaptive Tutoring System for Mathematics that Addresses Cognition, Metacognition and Affect

Arroyo

Woolf

Burelson

et al. 2014

Int J Artif Intell Educ

179

103

View full text Add to dashboard Cite

show abstract

“…Mathews et al (2012) embedded open student models in constraint-based tutors allowing students to see their own student model to facilitate the development of metacognitive strategies. Thomson and Mitrovic (2010) adopted negotiable student models in an established constraintbased tutoring system, and showed that the approach was both useful for learning and enjoyable to use. The suitability of open learner models in web-based testing and assessment was also illustrated by Lazarinis and Retalis (2007).…”

Section: Developing Enhanced Methods For Interaction and Lm Inspectionmentioning

confidence: 99%

From Interactive Open Learner Modelling to Intelligent Mentoring: STyLE-OLM and Beyond

Dimitrova

Brna

2015

Int J Artif Intell Educ

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STyLE-OLM (Dimitrova 2003 International Journal of Artificial Intelligence in Education, 13, 35-78) presented a framework for interactive open learner modelling which entails the development of the means by which learners can inspect, discuss and alter the learner model that has been jointly constructed by themselves and the system. This paper outlines the STyLE-OLM framework and reflects on the key challenges it addressed: (a) the design of an appropriate communication medium; this was addressed by proposing a structured language using diagrammatic representations of conceptual graphs; (b) the management of the interaction with the learner; this was addressed by designing a framework for interactive open learner modelling dialogue utilising dialogue games; (c) the accommodation of different beliefs about the learner's domain model; this was addressed with a mechanism for maintaining different views about the learner beliefs which adapted belief modal logic operators; and (d) the assessment of any resulting improvements in learner model accuracy and learner reflection; this was addressed in a user study with an instantiation of STyLE-OLM for diagnosing a learner's knowledge of finance concept, as part of a larger project that developed an intelligent system to assist with learning domain terminology in a foreign language. Reviewing follow on work, we refer to projects by the authors' students and colleagues leading to further extension and adoption of STyLE-OLM, as well as relevant approaches in open learner modelling which have cited the STyLE-OLM framework. The paper points at outstanding research challenges and outlines future a research direction to extend interactive open learner modelling towards mentor-like intelligent learning systems.

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“…In addition to the initial studies with SQL-Tutor, we conducted a number of studies involving open student models (Hartley and Mitrovic 2002) and negotiable student models (Thomson and Mitrovic 2010) in EER-Tutor, with similar results: students report being interested in examining their models, and believe that OSMs are helpful for reflecting on their knowledge. OSMs help students be better at self-assessment and also positively impact students' motivation to persist with learning.…”

Section: Supporting Self-assessment With Open Student Modelsmentioning

confidence: 99%

Fifteen years of constraint-based tutors: what we have achieved and where we are going

Mitrović

2011

User Model User-Adap Inter

Self Cite

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Fifteen years ago, research started on SQL-Tutor, the first constraintbased tutor. The initial efforts were focused on evaluating Constraint-Based Modeling (CBM), its effectiveness and applicability to various instructional domains. Since then, we extended CBM in a number of ways, and developed many constraint-based tutors. Our tutors teach both well-and ill-defined domains and tasks, and deal with domain-and meta-level skills. We have supported mainly individual learning, but also the acquisition of collaborative skills. Authoring support for constraint-based tutors is now available, as well as mature, well-tested deployment environments. Our current research focuses on building affect-sensitive and motivational tutors. Over the period of fifteen years, CBM has progressed from a theoretical idea to a mature, reliable and effective methodology for developing effective tutors.

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Preliminary Evaluation of a Negotiable Student Model in a Constraint-Based Its

Cited by 23 publications

References 4 publications

A Multimedia Adaptive Tutoring System for Mathematics that Addresses Cognition, Metacognition and Affect

A Multimedia Adaptive Tutoring System for Mathematics that Addresses Cognition, Metacognition and Affect

From Interactive Open Learner Modelling to Intelligent Mentoring: STyLE-OLM and Beyond

Fifteen years of constraint-based tutors: what we have achieved and where we are going

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