Meta-analytic techniques were used to examine the effectiveness of Web-based instruction (WBI) relative to classroom instruction (CI) and to examine moderators of the comparative effectiveness of the two delivery media. Overall the results indicate WBI is 6% more effective than CI for teaching declarative knowledge, the two delivery media are equally effective for teaching procedural knowledge,...

This study evaluated the utility of generic teamwork skills training for enhancing the effectiveness of action teams. Results from 65 four-person action teams working on an interdependent command and control simulator revealed that generic teamwork skills training had a significant and positive impact on both cognitive and skill-based outcomes. Trained team members evidenced higher levels of de...

This paper describes the MATHESIS Ontology, which is part of the MATHESIS project that aims at the development of an intelligent authoring environment for reusable model-tracing math tutors. The purpose of the ontology is to provide a semantic and therefore inspectable and reusable representation of the declarative and procedural authoring knowledge necessary for the development of a model-trac...

Currently, most knowledge representation using logic programming with answer set semantics (AnsProlog) is ‘flat’. In this paper we elaborate on our thoughts about a modular structure for knowledge representation and declarative problem solving formalism using AnsProlog. We present language constructs that allow defining of modules and calling of such modules from programs. This allows one to wr...

This is a report on the aims of and the latest results from my Ph.D. research work. The aim of the work is to create a framework which allows a declarative representation of programs that interact with external processes and can adapt according to generalisations made from that interaction. Such systems are also described as adaptive agents. A new logic programming language, Eel, has been devel...

The challenge we address is to create autonomous , inductively learning agents that exploit and modify a knowledge base. Our general approach, embodied in a continuing research program (joint with Stuart Rus-sell), is declarative bias, i.e., to use declarative knowledge to constrain the hypothesis space in inductive learning. In previous work, we have shown that many kinds of declarative bias c...

Building military simulations requires bridging the gap between the knowledge of commanders and computer representations of that knowledge. A significant part of this knowledge concerns military tasks, their interactions, and an understanding of how to grade their achievement. Action Models describe the complex spacial and temporal dynamics of goal directed tasks with a graphical notation. Comm...

Building military simulations requires bridging the gap between the knowledge of commanders and computer representations of that knowledge. A significant part of this knowledge concerns military tasks, their interactions, and an understanding of how to grade their achievement. Action Models describe the complex spacial and temporal dynamics of goal directed tasks with a graphical notation. Comm...

The challenge we address is to create autonomous, inductively learning agents that exploit and modify a knowledge base. Our general approach, embodied in a continuing research program (joint with Stuart Russell), is declarative bias, i.e., to use declarative knowledge to constrain the hypothesis space in inductive learning. In previous work, we have shown that many kinds of declarative bias can...