Danielle E. Kaplan

The Development of Cognitive Skills To Support Inquiry Learning

Establishing the value of inquiry learning as an educational method, it is argued, rests on thorough, detailed knowledge of the cognitive skills it is intended to promote. Mental models, as representations of the reality being investigated in inquiry learning, stand to influence strategies applied to the task. In the research described here, the hypothesis is investigated that students at the middle school level, and sometimes well beyond, may have an incorrect mental model of multivariable causality (one in which effects of individual features on an outcome are neither consistent nor additive) that impedes the causal analysis involved in most forms of inquiry learning. An extended intervention with 6th to 8th graders was targeted to promote (a) at the metalevel, a correct mental model based on additive effects of individual features (indicated by identification of effects of individual features as the task objective); (b) also at the metalevel, metastrategic understanding of the need to control the influences of other features; and (c) at the performance level, consistent use of the controlled comparison strategy. Both metalevel advancements were observed, in addition to transfer to a new task at the performance level, among many (though not all) students. Findings support the claim that a developmental hierarchy of skills and understanding underlies, and should be identified as an objective of, inquiry learning.

Mental Models and Computer-Based Scientific Inquiry Learning: Effects of Mechanistic Cues on Adolescent Representation and Reasoning About Causal Systems

This research applies cognitive science to the development and study of computer-based scientific inquiry learning. A scientific inquiry software program designed in the domain of elementary hydrology was adapted for mental model reasoning research, and tested in two middle school science classes. The study explores how qualitative mechanistic cues about system factors influence mental animation of system mechanisms and reasoning about causality. Middle school groups were compared on model development, inquiry, prediction, and learning. Students provided with mechanistic cues during inquiry developed more complex models with significantly more animated explanations of how and why causality exists. When not provided with mechanistic information, students reduced the level of complexity and animation in models during inquiry. Girls started with more complex and animated models than boys and reduced the level of complexity and animation in models during inquiry, whereas boys increased the level of complexity and animation in models. Students provided with mechanistic cues had more accurate theories after inquiry than students not provided with mechanistic cues. There was a trend toward use of better inquiry strategies and more accurate prediction in girls provided with mechanistic cues. Level of animation in model descriptions was a significant predictor of developing accurate theories.

Computer-Based Graphical Displays for Enhancing Mental Animation and Improving Reasoning in Novice Learning of Probability

OUR RESEARCH SUGGESTS static and animated graphics can lead to more animated thinking and more correct problem solving in computer-based probability learning. Pilot software modules were developed for graduate online statistics courses and representation research. A study with novice graduate student statisticians compared problem solving in five graphic versions: text, static visual, static motion cues, computer animated, and interactive computer animated. Groups were also compared on transfer problems with static graphics without motion cues. Level of animation in thinking was assessed as number of images and movement symbols in notes. All groups provided with graphic maps had more correct solutions than the text group. Displaying static motion cues, computer animated, and interactive animated maps resulted in more correct solutions and animation in notes than just text or static visuals without motion cues. Graphic maps with static motion cues or computer animated overlay resulted in equally more correct solutions and greater animation in notes. Graphic maps with static motion cues better prepared learners for solving less animated and more difficult problems. Imagery and movement in notes were significant predictors of correct training and transfer problem solutions.

Facts, Procedures, and Visual Models in Novices' Learning of Coding Skills.

A Study with students enrolled at an urban technical college compared learning of HTML coding across three Web-based program versions. One group received examples providing factual information about the source code (Facts group). A second group was presented with a step-by-step description of the source code (Procedures group). The third group was shown a visual model, including a diagram and arrows denoting the source code and the associated outcome (Visual Model group). A comparison of coding activity revealed that the Visual Model group constructed more correct code, with fewer trials, in the same amount of time. The Visual Model group also more accurately debugged flawed code. The Procedures group coded more correctly than the Facts group but differences decreased as problem complexity increased.