We report an experimental study on the effects of diagrams on deductive reasoning with double disjunctions, for example: Raphael is in Tacoma or Julia is in Atlanta, or both. Julia is in Atlanta or Paul is in Philadelphia, or both. What follows? We confirmed that subjects find it difficult to deduce a valid conclusion, such as Julia is in Atlanta, or both Raphael is in Tacoma and Paul is in Philadelphia. In a preliminary study, the format of the premises was either verbal or diagrammatic, and the diagrams used icons to distinguish between inclusive and exclusive disjunctions. The diagrams had no effect on performance. In the main experiment, the diagrams made the alternative possibilities more explicit. The subjects responded faster (about 35 s) and drew many more valid conclusions (nearly 30%) from the diagrams than from the verbal premises. These results corroborate the theory of mental models and have implications for the role of diagrams in reasoning.

Extracting information efficiently from game/simulation‐based assessment (G/SBA) logs requires two things: a well‐structured log file and a set of analysis methods. In this report, we propose a generic data model specified as an extensible markup language (XML) schema for the log files of G/SBAs. We also propose a set of analysis methods for identifying useful information from the log files and implement the methods in a package in the Python programming language, glassPy. We demonstrate the data model and glassPy with logs from a game‐based assessment, SimCityEDU.

In this paper we describe WITT, a computational model of categorization and conceptual clustering that has been motivated and guided by research on human categorization. Properties of categories to which humans are sensitive include best or prototypieal members, relative contrasts between categories, and polymorphy (neither necessary nor sufficient feature rules). The system uses pairwise feature correlations to determine the "similarity" between objects and clusters of objects, allowing the system a flexible representation scheme that can model common-feature categories and polymorphous categories. This intercorrelation measure is cast in terms of an information-theoretic evaluation function that directs WITT'S search through the space of clusterings. This information-theoretic similarity metric also can be used to explain basic~level and typicality effects that occur in humans. WITT has been tested on both artificial domains and on data from the 1985 World Almanac, and we have examined the effect of various system parameters on the quality of the model's behavior.

In computer-based interactive environments meant to support learning, students must bring a wide range of relevant knowledge, skills, and abilities to bear jointly as they solve meaningful problems in a learning domain. To function effectively as an assessment, a computer system must additionally be able to evoke and interpret observable evidence about targeted knowledge in a manner that is principled, defensible, and suited to the purpose at hand (e.g., licensure, achievement testing, coached practice). This article describes the foundations for the design of an interactive computer-based assessment of design, implementation, and troubleshooting in the domain of computer networking. The application is a prototype for assessing these skills as part of an instructional program, as interim practice tests and as chapter or end-of-course assessments. An Evidence Centered Design (ECD)

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