Adaptive Intelligent Tutorial Dialogue in the BEETLE II System

Dzikovska, Myroslava O.; Isard, Amy; Bell, P. J.; Moore, Johanna D.; Steinhauser, Natalie B.; Campbell, Gwendolyn E.; Taylor, Leanne S.; Caine, Simon; Scott, Charlie

doi:10.1007/978-3-642-21869-9_122

Cited by 3 publications

(2 citation statements)

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“…Moreover, it has been highlighted that for effective learning students should be allothe authorsd to produce explanations and the agent should take that information into account and act accordingly (Nielsen et al 2009). For instance, using Autotutor (Graesser et al 2008), it has been found out that mixed-dialogue interaction, in which both the agent and the student can change the turn of the conversation, can improve the score of the student up to one point; the adaptive intelligent tutorial dialogue module in the BEETLE II (Dzikovska et al 2011) pedagogic agent system provided significant learning gains for students interacting with the system; and, Mike (Lane et al 2011) behaves differently depending on the students' feelings and some pedagogic choices with good results. Some agents that have been used in different domains are the following: Herman the Bug (Lester et al 1997), Steve (Rickel and Johnson, 1999), Guilly (Nunes et al 2002), Sam (Ryokai et al 2003), Baldi (Massaro et al 2005), Betty (Biswas et al 2009;Segedy et al 2013), Agents in Active Worlds (Holmes, 2007), SBEL agents (Reategui et al 2007), MyPet (Chen et al 2009), Fisca (Pérez-Marín andBoza, 2013), Pascall (Da Costa Pinho et al 2013), MentorChat (Tegos et al 2014), and Metabots (Griol et al 2014).…”

Section: Related Workmentioning

confidence: 99%

A Procedure to Engage Children in the Morphological and Syntax Analysis of Pedagogic Conversational Agent-Generated Sentences to Study Language

Marín

2015

International Journal of Online Pedagogy and Course Design

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Pedagogic Conversational Agents are computer applications that interact with the students in natural language. They usually focus the dialogue on a certain topic under study. In this paper, the authors propose the possibility of children studying morphology and syntax by using a Pedagogic Conversational Agent. The main benefit is that the agent is able to generate an infinite number of sentences and, it automatically generates the morphological and syntactical analysis from a given grammar. That way, students can practise with all the sentences they need, receive immediate feedback with automatic evaluation, at their own rhythm and, the level of difficulty can be adapted to their particular competence of analysis. Given the originality of this new computer assisted learning initiative, the authors have devised a procedure to engage the students in the dialogue with the agent to carry out the morphological and syntax analysis at five different levels of difficulty, and test the validity of the approach with a limited number of users according to the principles of User-Centered Design. The results gathered provide evidence of the goodness of the procedure and, they encourage us to keep working on this promising field of using pedagogic agents as computer teaching language assistants.

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Section: Related Workmentioning

confidence: 99%

A Procedure to Engage Children in the Morphological and Syntax Analysis of Pedagogic Conversational Agent-Generated Sentences to Study Language

Marín

2015

International Journal of Online Pedagogy and Course Design

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“…Today's tutorial dialogue systems engage in natural language dialogue in support of tasks such as solving qualitative physics problems (VanLehn et al, 2002), understanding computer architecture and physics (Graesser et al, 2004), and predicting behavior of electrical circuits (Dzikovska et al, 2011). Although these systems differ in many ways, they have an important commonality: in order to semantically interpret user dialogue utterances, these systems ground the utterances in a fixed domain description that is an integral part of the engineered system.…”

Section: Introductionmentioning

confidence: 99%

Semantic Grounding in Dialogue for Complex Problem Solving

Boyer

2015

Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Langua

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Dialogue systems that support users in complex problem solving must interpret user utterances within the context of a dynamically changing, user-created problem solving artifact. This paper presents a novel approach to semantic grounding of noun phrases within tutorial dialogue for computer programming. Our approach performs joint segmentation and labeling of the noun phrases to link them to attributes of entities within the problem-solving environment. Evaluation results on a corpus of tutorial dialogue for Java programming demonstrate that a Conditional Random Field model performs well, achieving an accuracy of 89.3% for linking semantic segments to the correct entity attributes. This work is a step toward enabling dialogue systems to support users in increasingly complex problem-solving tasks.

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A Methodology to Design and Evaluate Agents

Tamayo-Moreno

Marín

2018

Innovative Applications of Online Pedagogy and Course Design

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Pedagogic conversational agents are computer applications that interact with the students in natural language. They usually focus the dialogue on a certain topic under study. In this chapter, the authors propose the possibility of designing and evaluating agents according to a generic methodology. In particular, the methodology called MEDIE was applied to a study language agent. The main benefit of the study language agent called Lingu is that it is able to generate an infinite number of sentences, and it automatically generates the morphological and syntactical analysis from a given grammar. That way, students can practice with all the sentences they need, receive immediate feedback with automatic evaluation at their own rhythm, and the level of difficulty can be adapted to their particular competence of analysis. To be able to extend Lingu to different schools and needs, MEDIE has been applied as described in this chapter.

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Adaptive Intelligent Tutorial Dialogue in the BEETLE II System

Cited by 3 publications

References 1 publication

A Procedure to Engage Children in the Morphological and Syntax Analysis of Pedagogic Conversational Agent-Generated Sentences to Study Language

A Procedure to Engage Children in the Morphological and Syntax Analysis of Pedagogic Conversational Agent-Generated Sentences to Study Language

Semantic Grounding in Dialogue for Complex Problem Solving

A Methodology to Design and Evaluate Agents

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