Stephen B. Blessing

CONTENT EFFECTS IN PROBLEM CATEGORIZATION AND PROBLEM SOLVING

The goal of this article is to examine how the specific content of a problem may affect the problem solving of experienced solvers. In most domains, there is an empirical correlation between problem types and problem contents. We argue that experienced problem solvers learn to make use of these formally irrelevant, but empirically predictive, contents in accessing and applying their relevant knowledge. Understanding these content effects is important not only because content affects performance, but also because these effects provide clues as to how experienced solvers represent and use this relevant knowledge. We first provide some background on problem content and expertise and then return to this issue.

How People Learn to Skip Steps

Novices often explicitly apply in a domain each necessary operator while solving a problem, whereas experts often skip steps, and as a result, the solution procedures they use are often organized differently from those of novices. Using an algebra analog, the authors examined this change in process. In 2 experiments, people learned the rules of the task and then solved many problems. Their solution procedures were monitored, and concurrent verbal protocols were taken. When participants started overtly skipping steps, they appeared to be performing them mentally but later started to use new transformations, thereby covertly skipping steps as well. An adaptive control of thought—rational model (J. R. Anderson, 1993) of problem-solver behavior within this task was developed and evaluated with respect to existing theories of skill acquisition. As people solve the same type of problem again and again, not only do they get faster at doing that type of problem, but very often the process they use to solve the problems changes as well, often resulting in skipped steps (Koedinger & Anderson, 1990). This reorganization and skipping of steps allow people to solve problems more quickly, efficiently, and easily. One might expect this change in process to result in performance discontinuities in a persons acquisition of a skill because the person is undergoing what may be a radical reorganization of how that skill is performed. However, Newell and Rosenbloom (1981) showed that a variety of skills are acquired at a steady rate, one that follows a power function (an equation of the form y = a + bxc, where a, b, and c are constants). In this article we examine the step-skipping phenomenon and its apparent relationship to the power law of learning. Step skipping is often thought of as a compositional process, in which a person who used to take two or more steps to do a task now takes only one. Intuitively then, if a person does a problem in fewer steps in completing a task, he or she should take less time in performing that task. Research by Charness and Campbell (1988) showed that compositional processes account for about 70% of the speedup associated with acquiring a new skill, with the rest of the speedup accounted for by becoming faster at the operations themselves. Work done by Frensch and Geary (1993; Frensch, 1991) also indicated the importance of compositional processes, as distinct from a general speedup in performance, in learning a task. It is evident from this research that composition is an important component to acquiring a skill.

Using Twitter to Reinforce Classroom Concepts

Social networking sites like Twitter and Facebook have become very popular among college students. These sites enable people to be in constant contact and communication. Their value in meeting educational objectives is less clear. We use Twitter “tweets” to remind students of psychology topics while they are outside of class. The intervention itself was straightforward: Students received an informative tweet about once per day. Students remembered these topics significantly better in a test situation. The Twitter intervention appears to be an effective way to increase memory for important class concepts.

Authoring Tools for Component-Based Learning Environments

We argue that a focus on building an authoring tool for a complete learning environment is misplaced. An analysis of the task of authoring a commercial educational system reveals it to be best accomplished through authoring separate components. For some of these components, authoring tools already exist and need not be duplicated for use in educational systems. Connecting the various components together is a separate authoring task, and parts of this task are different for educational systems than for typical component-based software. The last part of this paper describes the current way in which our model—tracing ITSs are constructed .

PsychBusters: A Means of Fostering Critical Thinking in the Introductory Course

We discuss a project given to introductory psychology students that increased their critical thinking regarding psychological findings, such as those that might appear in news reports (e.g., “listening to Mozart makes you smarter”) or everyday life (e.g., “birds of a feather flock together”). Relative to students who did not do the project, students improved in their ability to take a psychological issue and decide how best to analyze it. Given these results and the positive student attitude toward it, this project seems to be an effective way to get students to engage critically with psychological issues.

Authoring Effective Embedded Tutors: An Overview of the Extensible Problem Specific Tutor (xPST) System.

The Extensible Problem Specific Tutor (xPST) allows authors who are not cognitive scientists and not programmers to quickly create an intelligent tutoring system that provides instruction akin to a model-tracing tutor. Furthermore, this instruction is overlaid on existing software, so that the learner’s interface does not have to be made from scratch. The xPST architecture allows for extending its capabilities by the addition of plug-ins that communicate with additional third-party software. After reviewing this general architecture, we describe three major implementations that we have created using the xPST system, each using different third-party software as the learner’s interface. We have conducted three evaluations of authors using xPST to create tutoring content, and these are considered in turn. These evaluations show that xPST authors can quickly learn the system, and can efficiently produce successful embedded instruction.

Evaluating an Authoring Tool for Model-Tracing Intelligent Tutoring Systems

We have been creating an authoring tool, the Cognitive Model SDK, which allows non-cognitive scientists and non-programmers to produce a cognitive model for model-tracing tutors [1, 2]. The SDK is in use by developers at Carnegie Learning to produce their commercial Cognitive Tutors for math. However, it has never been evaluated with regards to the strong claim that non-cognitive scientists and non-programmers could, without much effort, produce useful cognitive models with it. The research presented here shows that this can be done, using a task that past researchers have used [3]. The models are evaluated across several metrics to see what characteristics of either them or their creators may distinguish better models from worse models. The goal of this work is to establish a baseline for future work examining how cognitive modeling can be opened up to a wider class of people.

Using a Movie as a Capstone Activity for the Introductory Course.

A capstone experience serves as a culminating exercise for students to assimilate the information learned in a course and to realize how to use the material and skills in different contexts. Both majors and nonmajors benefit from having the material in the introductory course consolidated in such a way, for later study in the field and to more firmly establish its main themes in their memory. For such an experience in the introductory course, we used the classic film 12 Angry Men as the basis for discussion and an assignment. The film contains many scenes that highlight various psychological phenomena from across the curriculum that can be used to integrate those phenomena. We tested the experience in a classroom setting and found that students accessed and integrated material from across the semester significantly better than those who did not have the capstone assignment.

Lattice-based approach to building templates for natural language understanding in intelligent tutoring systems

We describe a domain-independent authoring tool, ConceptGrid, that helps non-programmers develop intelligent tutoring systems (ITSs) that perform natural language processing. The approach involves the use of a lattice-style table-driven interface to build templates that describe a set of required concepts that are meant to be a part of a students response to a question, and a set of incorrect concepts that reflect incorrect understanding by the student. The tool also helps provide customized just-in-time feedback based on the concepts present or absent in the students response. This tool has been integrated and tested with a browser-based ITS authoring tool called xPST.

Expansion of the xPST framework to enable non-programmers to create intelligent tutoring systems in 3d game environments

Our previous work has demonstrated that the Extensible Problem Specific Tutor (xPST) framework lowers the bar for non- programmers to author model tracing intelligent tutoring systems (ITSs) on top of existing software and websites In this work we extend xPST to enable authoring of tutors in 3D games This process differs substantially from authoring tutors for traditional GUI software in terms of the inherent domain complexity involved, different types of feedback required and interactions generated by various entities apart from the student A tutor for a village evacuation task has been constructed in order to demonstrate the capabilities of using the extended xPST system to create a game-based tutor.