MENON : automating a Socratic teaching model for mathematical proofs

This thesis presents an approach to adaptive pedagogical feedback for arbitrary domains as an alternative to resource-intensive pre-compiled feedback, which represents the state-of-the-art in intelligent tutoring systems today. A consequence of automatic adaptive feedback is that the number of tasks with pedagogical feedback that can be offered to the student increases, and with it the opportunity for practice. We focus on automating different aspects of teaching that together are primarily responsible for learning and can be integrated in a unified natural-language output. The automatic production and natural-language generation of feedback enables its personalisation both at the pedagogical and the natural-language dialogue level. We propose a method for automating the production of domain-independent adaptive feedback. The proof- of-concept implementation of the tutorial manager Menon is carried out for the domain of set-theory proofs. More specifically, we define a pedagogical model that abides by schema and cognitive load theory, and by the synergistic approach to learning. We implement this model in a Socratic teaching strategy whose basic units of feedback are dialogue moves. We use empirical data from two domains to derive a taxonomy of tutorial-dialogue moves, and define the most central and sophisticated move hint. The formalisation of the cognitive content of hints is inspired by schema theory and is facilitated by a domain ontology.Die vorliegende Arbeit präsentiert eine Annäherung an adaptives pädagogisches Feedback für beliebige Domäne. Diese Herangehensweise bietet eine Alternative zu ressource-intensivem, vorübersetztem Feedback, dass das heutige "state-of-the-art'; in intelligenten tutoriellen Systemen ist. Als Folge können zahlreiche Aufgaben mit pädagogischem Feedback für die Praxis angeboten werden. Der Schwerpunkt der Arbeit liegt auf der Automatisierung verschiedener Aspekte des Lehrprozesses, die in ihrer Gesamtheit wesentlich den Lernprozess beeinflussen, und in einer einheitlichen Systemausgabe Natürlicher Sprache integriert werden können. Die automatische Produktion und die Systemgenerierung von Feedback in Natürlicher Sprache ermöglichen eine Individualisierung des Feedback auf zwei Ebenen: einer pädagogischen und einer dialogischen Ebene. Dazu schlagen wir eine Methode vor, durch die adaptives Feedback automatisiert werden kann, und implementieren den tutoriellen Manager Menon als "proof-of-concept'; beispielhaft für die Domäne von Beweisen in der Mengentheorie. Konkret definieren wir ein pädagogisches Modell, das sich auf Schema- und Kognitionstheorie sowie auf die synergetische Herangehensweise an Lernen stützt. Dieses Modell wird in einer Sokratischen Lehrmethode implementiert, deren basale Feedback-Elemente aus Dialogakten bestehen. Zur Bestimmung einer Taxonomie Tutorielle-Dialogakte sowie des zentralen und komplexen Dialogakts hint (Hinweis) wenden wir empirische Daten aus zwei Domänen an. Die Formalisierung des kognitiven Inhaltes von Hinweisen folgt der Schematheorie und basiert auf einer Domänenontologie

Towards social embodied cobots: The integration of an industrial cobot with a social virtual agent

The integration of the physical capabilities of an industrial collaborative robot with a social virtual character may represent a viable solution to enhance the workers' perception of the system as an embodied social entity and increase social engagement and well-being at the workplace. An online study was setup using prerecorded video interactions in order to pilot potential advantages of different embodied configurations of the cobot-avatar system in terms of perceptions of Social Presence, cobot-avatar Unity and Social Role of the system, and explore the relation of these. In particular, two different configurations were explored and compared: the virtual character was displayed either on a tablet strapped onto the base of the cobot or on a large TV screen positioned at the back of the workcell. The results imply that participants showed no clear preference based on the constructs, and both configurations fulfill these basic criteria. In terms of the relations between the constructs, there were strong correlations between perception of Social Presence, Unity and Social Role (Collegiality). This gives a valuable insight into the role of these constructs in the perception of cobots as embodied social entities, and towards building cobots that support well-being at the workplace

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

Domain-Knowledge Manipulation for Dialogue-Adaptive Hinting

Empirical evidence has shown that natural language (NL) dialogue capabilities are a crucial factor to making human explanations effective [6]. Moreover, the use of teaching strategies is an important ingredient for intelligent tutoring systems. Such strategies, normally called dialectic or socratic, have been demonstrated to be superior to pure explanations

A Multi-dimensional Taxonomy for Automating Hinting

Hints are an important ingredient of natural language tutorial dialogues. Existing models of hints, however, are limited in capturing their various underlying functions, since hints are typically treated as a unit directly associated with some problem solving script or discourse situation. Putting emphasis on making cognitive functions of hints explicit, we present a multi-dimensional hint taxonomy where each dimension defines a decision point for the associated function. Hint categories are then conceived as convergent points of the dimensions. So far, we have elaborated five dimensions: (1) domain knowledge reference, (2) inferential role, (3) elicitation status, (4) discourse dynamics, and (5) problem solving perspective. These fine-grained distinctions support the constructive generation of hint specifications from modular knowledge sources

Building Hint Specifications in an NL Tutorial System for Mathematics

NL interaction and skillful hinting are known as cornerstones for successful tutoring. Despite these insights, a combination of these two factors is widely under-represented in the field. Building a tutorial system for teaching mathematical proof techniques, we aim at an elaborate hinting algorithm which integrates problem solving, discourse contexts and accurate domain knowledge into a socratic hinting strategy

Building Hint Specifications in an NL Tutorial System for Mathematics

NL interaction and skillful hinting are known as cornerstones for successful tutoring. Despite these insights, a combination of these two factors is widely under-represented in the field. Building a tutorial system for teaching mathematical proof techniques, we aim at an elaborate hinting algorithm which integrates problem solving, discourse contexts and accurate domain knowledge into a socratic hinting strategy