CALMsystem: A Conversational Agent for Learner Modelling

Kerly, Alice; Ellis, R. W. B.; Bull, Susan

doi:10.1016/j.knosys.2007.11.015

Cited by 65 publications

(30 citation statements)

References 8 publications

(11 reference statements)

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“…The conceptual model (defined as a set of interconnected concepts associated with an estimation value indicating how well these concepts were used by the students) shared similarities with the conceptual graphs based LM in STyLE-OLM. The interaction with the learner was further extended by Kerly et al (2008) to enable natural language negotiation of the open LM, which was inspired by research in chatbots and their potential for extending the interactive means in learning applications. A conversational agent, or Bchatbot^was developed to allow the learner to negotiate over the representations held about them using natural language.…”

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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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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“…Self-assessment is the ability for a learner to accurately assess their knowledge and skills in relation to their actual performance; this ability is very important in learning [52]. OLM, when used to support reflective self-assessment activities, can have a positive effect on self-assessment and on learning outcomes [24,32,36].…”

Section: Moving From External Regulation To Srlmentioning

confidence: 99%

Adaptive Robotic Tutors that Support Self-Regulated Learning: A Longer-Term Investigation with Primary School Children

Jones

Castellano

2018

Int J of Soc Robotics

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Robots are increasingly being used to provide motivating, engaging and personalised support to learners. These robotic tutors have been able to increase student learning gain by providing personalised hints or problem selection. However, they have never been used to assist children in developing self regulated learning (SRL) skills. SRL skills allow a learner to more effectively self-assess and guide their own learning; learners that engage these skills have been shown to perform better academically. This paper explores how personalised tutoring by a robot achieved using an open learner model (OLM) promotes SRL processes and how this can impact learning and SRL skills compared to personalised domain support alone. An OLM allows the learner to view the model that the system holds about them. We present a longer-term study where participants take part in a geography-based task on a touch screen with adaptive feedback provided by the robot. In addition to domain support the robotic tutor uses an OLM to prompt the learner to monitor their developing skills, set goals, and use appropriate tools. Results show that, when a robotic tutor personalises and adaptively scaffolds SRL behaviour based upon an OLM, greater indication of SRL behaviour can be observed over the control condition where the robotic tutor only provides domain support and not SRL scaffolding.

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“…Study of (Kerly & Ellis, 2008), where they have to build a system that integrates natural language techniques, to address the database and learning theories in light of the negotiated learner model of a Negotiated (Hear Men Model) and for the integration of the education system with intelligent system gives the learner the opportunity to compare the on and capacity to learn with those deduced by the system, the system provides also a conversation, or the so-called "Chat bot", which was developed to allow the speaker to negotiate or debate with the use of natural language, and it is the most important objectives of the system knowledge to support the objectives of the Meta Cognitive self-assessment reaction. The present report on the user's system and have found a natural language conversation, to increase the accuracy of self-evaluation of the students themselves, and reduce the number of discrepancies between the system and user beliefs negotiated learner model.…”

Section: Literature Review Of Intelligent Tutoring Systemmentioning

confidence: 99%

A Suggested E-Tutor Model as Dynamic Intelligent Tutoring System For Mathematics in Egyptian Language Schools

Mahmoud¹

2009

IJET

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Abstract-Current research aimed to construct an e-tutor according to Dynamic Math Intelligent Tutoring System (MD_ITS) to help mathematics teachers to develop their e-courses, and their Knowledge Base according to e-tutor algorithm and instructional design. A sample of teachers from Taha Hussein Language school, Yarmouk School, Mohammad Najibullah experimental language schools were chosen, The sample is divided into two equal groups: the first experimental group was taught Math Fractions units to fourth grade students of primary schools through the proposed e-tutor software designed in accordance with the intelligent tutoring system (MD_ITS), and the other experimental group was taught by the traditional software prepared by the Ministry of Education. Then the test measurements of Math teachers attitudes towards e-courses depended on ITS were applied. The proposed intelligent (MD_ITS) design, depended on some instructional models. Researcher adopted the model of the " Fogan Tai, 1994" including phases of: analysis phase, instructional design phase, Interaction design phase, production phase. Also addressed the study of the (Rezzaq, 2003) to design a system, based on smart dialogue, to improve the level of student performance as a tool to provide content.The suggested E-tutor MD-ITS depends on the four sub-models: 1) Expert Model, to extract knowledge and representation. 2) Student Model, to determine the student's knowledge to provide intelligent problem of the child. 3) Tutorial Model, to choose the appropriate lesson for the child, depending on the response model. ITS can offer the guidance, hints, help, and assistance. 4) User Interface, The interaction between the user (both teacher and students) and the system.The proposed E-Tutor MD_ITS activate the role of a teacher and involvement him in the development of lessons, questions, guidance, assistance generated for the responsibility towards the students, and created a kind of competition among teachers to try to access to the most basic formulas, which would simplify the subject and therefore it was to benefit from their experiences as experts in area of specialization, also encouraged teachers to enter data and information, which in turn directly to the dynamics of knowledge bases built by the researcher.

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CALMsystem: A Conversational Agent for Learner Modelling

Cited by 65 publications

References 8 publications

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

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

Adaptive Robotic Tutors that Support Self-Regulated Learning: A Longer-Term Investigation with Primary School Children

A Suggested E-Tutor Model as Dynamic Intelligent Tutoring System For Mathematics in Egyptian Language Schools

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