Toby Dragon

Affect-aware tutors: recognising and responding to student affect

Theories and technologies are needed to understand and integrate the knowledge of student affect (e.g., frustration, motivation and self-confidence) into learning models. Our goals are to redress the cognitive versus affective imbalance in teaching systems, develop tools that model student affect and build tutors that elicit, measure and respond to student affect. This article describes our broad approach towards this goal and our three main objectives: develop tools for affect recognition, interventions in response to student affect, and emotionally animated agents.

Coaching within a domain independent inquiry environment

We describe a portable coaching environment used within a domain-independent inquiry-learning infrastructure. This coach reasons about a students knowledge and offers pertinent, domain-specific feedback. It promotes good inquiry behavior by critiquing the students hypotheses and supporting data and relationships among propositions. Four inquiry tutors in separate disciplines have been developed that use embedded expert knowledge bases and reusable domain-independent rules. We describe the functionality of the coach within an art history domain, discuss the implementation of the coach, and elaborate on the options given to domain authors for customization.

Objects: visualization of behavior and state

Animated program visualization can be used to support innovative instructional methods for teaching beginners about objects, their behavior, and state. In this paper, we present a discussion of methods that define object behavior and character (class)-level state variables that track state changes for 3D animated objects in small virtual worlds. We have found that character-level methods provide a means to demonstrate inheritance. Examples of worlds and program code used in instructional materials are provided.

Recognizing dialogue content in student collaborative conversation

This paper describes efforts to both promote and recognize student dialogue in free-entry text discussion within an inquiry-learning environment First, we discuss collaborative tools that enable students to work together and how these tools can potentially focus student effort on subject matter We then show how our tutor uses an expert knowledge base to recognize (with 88% success rate) when students are discussing content relevant to the problem and to correctly link (with 70% success) that content with an actual topic Subsets of the data indicate that even better results are possible This research provides solid support for the concept of using a knowledge base to recognize content in free-entry text discussion The paper concludes by demonstrating how this content recognition can be used to support students engaged in problem-solving activities.

Learning to learn together with CSCL tools

In this paper, we identify Learning to Learn Together (L2L2) as a new and important educational goal. Our view of L2L2 is a substantial extension of Learning to Learn (L2L): L2L2 consists of learning to collaborate to successfully face L2L challenges. It is inseparable from L2L, as it emerges when individuals face problems that are too difficult for them. The togetherness becomes a necessity then. We describe the first cycle of a design-based research study aimed at promoting L2L2. We rely on previous research to identify collective reflection, mutual engagement and peer assessment as possible directions for desirable L2L2 practices. We describe a CSCL tool: the Metafora system that we designed to provide affordances for L2L2. Through three cases in which Metafora was used in classrooms, we describe the practices and mini-culture that actually developed. In all contexts, groups of students engaged either in mathematical problem solving or in scientific inquiry and argumentation. These cases show that L2L2 is a tangible educational goal, and that it was partially attained. We show how the experiments we undertook refined our view of L2L2 and may help in improving further educational practice.

Argument diagrams in facebook: facilitating the formation of scientifically sound opinions

Students use Facebook to organize their classroom experiences [1], but hardly to share and form opinions on subject matters. We explore the benefits of argument diagrams for the formation of scientific opinion on behaviorism in Facebook. We aim at raising awareness of opinion conflict and structuring the argumentation with scripts [2]. A lab study with University students (ten dyads per condition) compared the influence of argument structuring (students built individual argument diagrams before discussing in Facebook) vs. no argument structuring (only Facebook discussion) on opinion formation, measured through opinion change. The argumentation script was implemented in the web-based system LASAD to support sound argumentation [3].

Recognizing and Responding to Student Affect

This paper describes the use of wireless sensors to recognize student emotion and the use of pedagogical agents to respond to students with these emotions. Minimally invasive sensor technology has reached such a maturity level that students engaged in classroom work can us sensors while using a computer-based tutor. The sensors, located on each of 25 students chair, mouse, monitor, and wrist, provide data about posture, movement, grip tension, facially expressed mental states and arousal. This data has demonstrated that intelligent tutoring systems can provide adaptive feedback based on an individual students affective state. We also describe the evaluation of emotional embodied animated pedagogical agents and their impact on student motivation and achievement. Empirical studies show that students using the agents increased their math value, self-concept and mastery orientation.

Who Needs Help? Automating Student Assessment Within Exploratory Learning Environments

This article describes efforts to offer automated assessment of students within an exploratory learning environment. We present a regression model that estimates student assessments in an ill-defined medical diagnosis tutor called Rashi. We were pleased to find that basic features of a student’s solution predicted expert assessment well, particularly when detecting low-achieving students. We also discuss how expert knowledge bases might be leveraged to improve this process. We suggest that developers of exploratory learning environments can leverage this technique with relatively few extensions to a mature system. Finally, we describe the potential to utilize this information to direct teachers’ attention towards students in need of help.

Improving Course Content and Providing Intelligent Support Simultaneously: (Abstract Only)

This lightning talk describes our current effort to create a system that helps teachers organize the content of their computer science courses while simultaneously providing a basis for intelligent support. This work blends the disciplines of computer science education, artificial intelligence in education, and instructional design to create a holistic system that helps teachers create a unified vision of their course from diverse learning resources and assessment techniques. The vision is created in the form of a concept map with links to external materials and assessments (including traditional materials like textbooks and exams, and more advanced technology like online interactive practice environments). We are creating these concept maps for our computer science curriculum at Ithaca College and we have found clear benefits to organization and content. Beyond these improvements to courses, we seek to use the resulting concept map to offer intelligent support for students and instructors. Students can benefit by seeing their assessment automatically summarized by concept rather than by assignment, and receive suggestions of materials crucial to their understanding. Instructors can benefit from assessment summaries about individuals/ or entire classes/ understanding of specific concepts. The system can also make recommendations for dynamic groups to be formed for short-term in-class collaboration. Currently we have basic prototypes of this functionality and we/re seeking feedback from others who may have engaged (even informally) in similar techniques, as well as any collaborators who are interested in trying this technique in their courses or integrating their materials with our system.

Turning the Tables: Authoring as an Asset Rather than a Burden.

We argue that authoring of Intelligent Tutoring Systems can be beneficial for instructors that choose to author content, rather than a time-consuming burden as it is often seen. In order to make this a reality, the authoring process must be easy to understand, must provide immediate benefit to the instructor doing the authoring, and must allow for incremental development and improvement. We describe a methodology that meets all of these needs using concept maps as a basis for authoring. The methodology creates a basis for intelligent support that helps authors improve their course organization and content as they work on the authoring task. We also present details of the rapid prototype being developed to apply the methodology and the initial experiences