Daniel M. Belenky

Using an Intelligent Tutoring System to Support Collaborative as well as Individual Learning

Collaborative learning has been shown to be beneficial for older students, but there has not been much research to show if these results transfer to elementary school students. In addition, collaborative and individual modes of instruction may be better for acquiring different types of knowledge. Collaborative Intelligent Tutoring Systems (ITS) provide a platform that may be able to provide both the cognitive and collaborative support that students need. This paper presents a study comparing collaborative and individual methods while receiving instruction on either procedural or conceptual knowledge. The collaborative groups had the same learning gains as the individual groups in both the procedural and conceptual learning conditions but were able to do so with fewer problems. This work indicates that by embedding collaboration scripts in ITSs, collaborative learning can be an effective instructional method even with young children.

Authoring Tools for Collaborative Intelligent Tutoring System Environments.

Authoring tools have been shown to decrease the amount of time and resources needed for the development of Intelligent Tutoring Systems (ITSs). Although collaborative learning has been shown to be beneficial to learning, most of the current authoring tools do not support the development of collaborative ITSs. In this paper, we discuss an extension to the Cognitive Tutor Authoring Tools to allow for development of collaborative ITSs through multiple synchronized tutor engines. Using this tool, an author can combine collaboration with the type of problem solving support typically offered by an ITS. Different phases of collaboration scripts can be tied to particular problem states in a flexible, problem-specific way. We illustrate the tool’s capabilities by presenting examples of collaborative tutors used in recent studies that showed learning gains. The work is a step forward in blending computer-supported collaborative learning and ITS technologies in an effort to combine their strengths.

Science diaries: a brief writing intervention to improve motivation to learn science

This study investigated the hypothesis that prompting students to self-assess their interest and understanding of science concepts and activities would increase their motivation in science classes. Students were randomly assigned to an experimental condition that wrote self-assessments of their competence and interest in science lessons or a control condition that wrote summaries of those same lessons. Writing activities were 10 min long and were given approximately once a week for eighteen weeks. Student motivation was assessed via self-report surveys for achievement goals and interest in science before and after the intervention. Students in the experimental condition showed higher endorsement of mastery goals and reported greater situational interest in science topics after the intervention compared to students who summarised the lessons. Increases in situational interest predicted higher individual interest in the domain. Results indicate an instructional practice requiring just 3 hours out of a semester of instruction was sufficient to achieve these effects on motivation in science classes.

Chapter Four - Incorporating Motivation into a Theoretical Framework for Knowledge Transfer

Abstract Knowledge transfer is critical to successfully solving novel problems and performing new tasks. Several theories have been proposed to account for how, when, and why transfer occurs. These include both classical cognitive theories such as identical rules, analogy, and schemas, as well as more recent views such as situated transfer and preparation for future learning. Although much progress has been made in understanding specific aspects of transfer phenomena, important challenges remain in developing a framework that can account for both transfer successes and failures. Surprisingly, few of these approaches have integrated motivational constructs into their theories to address these challenges. In this chapter, we propose a theoretical framework that builds on the classical cognitive approaches and incorporates aspects of competence motivation. In the first part of the chapter we review the classical and alternative views of transfer and discuss their successes and limitations. We then describe our transfer framework that begins to address some of the issues and questions that are raised by the alternative views. In the second part, we describe how our proposed framework can incorporate aspects of competence motivation—specifically, students’ achievement goals. We then describe an initial test of the framework and the implications for both psychological theory and educational practice.

Intelligent Tutoring Systems for Collaborative Learning: Enhancements to Authoring Tools

Collaborative and individual instruction may support different types of knowledge. Optimal instruction for a subject domain may therefore need to combine these two modes of instruction. There has not been much research, however, on combining individual and collaborative learning with Intelligent Tutoring Systems (ITSs). A first step is to expand ITSs for collaborative learning. This paper investigates the expansion of the Cognitive Tutor Authoring Tools to include collaborative components for example-tracing tutors. The tools were enhanced to support flexible use of collaboration scripts so different learning goals can be supported. We introduce the collaboration features supported and describe an initial pilot study using the new features in a fractions ITS.