Erin Shaw

Pedagogical agents on the Web

Animated pedagogical agents are lifelike animated characters that facilitate the learning process. This paper describes Adele, a pedagogical agent that is designed to work with Web-based educational simulations. The Adele architecture implements key pedagogical functions: presentation, student monitoring and feedback, probing questions, hints, and explanations. These capabilities are coupled with an animated persona that supports continuous multi-modal interaction with a student. The architecture supports client-side execution in a Web browser environment, and is able to inter-operate with simulations created by off-the-shelf authoring tools.

The politeness effect: Pedagogical agents and learning outcomes

Pedagogical agent research seeks to exploit Reeves and Nasss media equation theory, which holds that users respond to interactive media as if they were social actors. Investigations have tended to focus on the media used to realize the pedagogical agent, e.g., the use of animated talking heads and voices, and the results have been mixed. This paper focuses instead on the manner in which a pedagogical agent communicates with learners, i.e., on the extent to which it exhibits social intelligence. A model of socially intelligent tutorial dialog was developed based on politeness theory, and implemented in an agent interface within an online learning system called virtual factory teaching system. A series of Wizard-of-Oz studies was conducted in which subjects either received polite tutorial feedback that promotes learner face and mitigates face threat, or received direct feedback that disregards learner face. The polite version yielded better learning outcomes, and the effect was amplified in learners who expressed a preference for indirect feedback, who had less computer experience, and who lacked engineering backgrounds. These results confirm the hypothesis that learners tend to respond to pedagogical agents as social actors, and suggest that research should focus less on the media in which agents are realized, and place more emphasis on the agents social intelligence.

Learning to Detect Conversation Focus of Threaded Discussions

In this paper we present a novel feature-enriched approach that learns to detect the conversation focus of threaded discussions by combining NLP analysis and IR techniques. Using the graph-based algorithm HITS, we integrate different features such as lexical similarity, poster trustworthiness, and speech act analysis of human conversations with feature-oriented link generation functions. It is the first quantitative study to analyze human conversation focus in the context of online discussions that takes into account heterogeneous sources of evidence. Experimental results using a threaded discussion corpus from an undergraduate class show that it achieves significant performance improvements compared with the baseline system.

Evolution of user interaction: the case of agent adele

Animated pedagogical agents offer promise as a means of making computer-aided learning more engaging and effective. To achieve this, an agent must be able to interact with the learner in a manner that appears believable, and that furthers the pedagogical goals of the learning environment. In this paper we describe how the user interaction model of one pedagogical agent evolved through an iterative process of design and user testing. The pedagogical agent Adele assists students as they assess and diagnose medical and dental patients in clinical settings. We describe the results of, and our responses to, three studies of Adele, involving over two hundred and fifty medical and dental students over five years, that have led to an improved tutoring strategy, and discuss the interaction possibilities of two different reasoning engines. With the benefit of hindsight, the paper articulates the principles that govern effective user-agent interaction in educational contexts, and describes how the agents interaction design in its current form embodies those principles

Tutoring Diagnostic Problem Solving

This paper presents an approach to intelligent tutoring for diagnostic problem solving that uses knowledge about causal relationships between symptoms and disease states to conduct a pedagogically useful dialogue with the student. An animated pedagogical agent, Adele, uses the causal knowledge, represented as a Bayesian network, to dynamically generate a diagnostic process that is consistent with the best practice approach to medical diagnosis. Using a combination of hints and other interactions based on multiple choice questions, Adele guides the student through a reasoning process that exposes her to the underlying knowledge, i.e., the patho-physiological processes, while being sensitive to the problem solving state and the students current level of knowledge. Although the main focus of this paper is on tutoring medical diagnosis, the methods described here are applicable to tutoring diagnostic skills in any domain with uncertain knowledge.

Scaffolding On-Line Discussions with Past Discussions: An Analysis and Pilot Study of PedaBot

PedaBot is a new discussion scaffolding application designed to aid student knowledge acquisition, promote reflection about course topics and encourage student participation in discussions. It dynamically processes student discussions and presents related discussions from a knowledge base of past discussions. This paper describes the system and presents a comparative analysis of the information retrieval techniques used to respond to free-form student discussions, a combination of topic profiling, term frequency-inverse document frequency, and latent semantic analysis. Responses are presented as annotated links that students can follow and rate. We report a pilot study of PedaBot based on student viewings, student ratings, and a small survey. Initial results indicate that there is a high level of student interest in the feature and that its responses are moderately relevant to student discussions.

Computational workflows for assessing student learning

The use of technology for instruction, and the enormous amount of information available for consumption, places a considerable burden on instructors who must learn to integrate appropriate student practices and learning assessment The Pedagogical Workflows project is developing a novel workflow environment that supports efficient assessment of student learning through interactive generation and execution of various assessment workflows We focus especially on how student discussion use can be combined with more traditional assessment data In this paper, we present our initial assessment workflows, the initial feedback from instructors, and the user portal that is being developed for running the workflows Inherent in the development of the workflows is an examination of what teachers think is important to learn about their students, a question that is central to every intelligent tutoring system We anticipate that assessment workflows will become an important tool for instructors, researchers, and ITS development.

Animating 2D Digital Puppets with Limited Autonomy

Digital puppets are animated personas that augment online educational materials with commentary and summaries. Their animations are generated dynamically based on user-authored text, contextual hints, and domain goals, allowing the puppet to act with limited autonomy within specific domains. In this paper we describe the graphical realization and authoring of a 2D digital puppet. We present a build-once, use-forever production path that allows us to quickly create new character behaviors, and makes the production of 2D personas feasible. We describe two digital puppet applications and explain how the animation capability is supported across domains.

A semi-automated wizard of oz interface for modeling tutorial strategies

Human teaching strategies are usually inferred from transcripts of face-to-face conversations or computer-mediated dialogs between learner and tutor. However, during natural interactions there are no constraints on the human tutors behavior and thus tutorial strategies are difficult to analyze and reproduce in a computational model. To overcome this problem, we have realized a Wizard of Oz interface, which by constraining the tutors interaction makes explicit his decisions about why, how, and when to assist the student in a computer-based learning environment. These decisions automatically generate natural language utterances of different types according to two “politeness” strategies. We have successfully used the interface to model tutorial strategies.

An Agent That Helps Children to Author Rhetorically-Structured Digital Puppet Presentations

This paper describes a pedagogical agent that helps children to learn to author structured presentations about explanations of concepts. Using a Rhetorical Structure Theory analysis of a source Web page, the agent performs pedagogical tasks to support the users understanding of rhetorical relations, stimulates reflection about the relations between the structure of the original text and the structure of the presentations, and suggests ways to improve the users performance. Upon completion of the authoring, the presentations are organized into coherent structures that can be performed by animated characters, or Digital Puppets, in a learning-by-teaching classroom context.