Five Lenses on Team Tutor Challenges: A Multidisciplinary Approach

This chapter describes five disciplinary domains of research or lenses that contribute to the design of a team tutor. We focus on four significant challenges in developing Intelligent Team Tutoring Systems (ITTSs), and explore how the five lenses can offer guidance for these challenges. The four challenges arise in the design of team member interactions, performance metrics and skill development, feedback, and tutor authoring. The five lenses or research domains that we apply to these four challenges are Tutor Engineering, Learning Sciences, Science of Teams, Data Analyst, and Human–Computer Interaction. This matrix of applications from each perspective offers a framework to guide designers in creating ITTSs

Building a Generic Feedback System for Rule-Based Problems

We present a generic framework that provides hints on how to achieve a goal to users of software supporting rule-based problem solving from different domains. Our approach consists of two parts. First, we present a DSL that relates and unifies different rule-based problems. Second, we use generic search algorithms to solve various kinds of problems. This solution can then be used to calculate a hint for the user. We present three rule-based problem frameworks to illustrate our approach: the Ideas framework, PuzzleScript and iTasks. By taking real world examples from these three example frameworks and instantiating feedback systems for them, we validate our approach

Fine-Grained Cognitive Assessment Based on Free-Form Input for Math Story Problems.

International audienc

EC-TEL 2020

Producción CientíficaThe use of Conversational Agents (CAs) in computer-supported collaborative learning (CSCL) has shown promising results regarding students' productive dialogue and learning. Yet, limited work has explored the connection between the configuration of the CA behavior, the nature of the learning task, and the student behavior in authentic educational settings. In this work, we describe a pedagogical design space of CAs for collaborative learning composed of three dimensions: task design, domain model, and agent intervention strategies. We conduct an initial field study in a university classroom comparing two types of agent intervention strategies based on student participation, dialogue, and satisfaction. 54 university students worked in pairs in the same collaborative brainstorming task with a CA tool and were randomly assigned in two CA conditions with a) knowledge-based prompts to connect two domain concepts, b) social prompts to link their partners' contributions. The results show that students who received knowledge-based prompts significantly exchanged more messages with evidence of explicit reasoning and were more satisfied with the agent and their discussion during the task. Students from both conditions reported problems like the lack of context-awareness and timely interventions by the agent. We discuss the relation between the agent intervention strategies and the task design towards seeking design recommendations for CAs in CSCL.European Commission under project grant 588438-EPP-1-2017-1-EL-EPPKA2-KAMinisterio de Ciencia, Innovación y Univerisades (project grant TIN2017-85179-C3-2-R and TIN2014-53199-C3-2-R)Junta de Castilla y León (programa de apoyo a proyectos de investigación - Ref. Project VA257P18