John R. Frederiksen

Assessment of Perceptual, Decoding, and Lexical Skills and Their Relation to Reading Proficiency

A central problem in evaluation research is the assessment of effects of instructional strategies on specific information processing skills. The goal of the research project on which I shall report is to develop and validate techniques for measuring perceptual and cognitive skills that are related to reading proficiency, and to investigate how deficiencies in particular skills may limit an individual’s ability to read with speed and comprehension. The measures to be developed are chosen to represent five skill domains or levels of processing, as illustrated in Figure 1.

Mental Models and Understanding: A Problem for Science Education

Science, particularly physics, is a difficult, and apparently inaccessible subject, to a majority of American students. According to a recent report of the Educational TestingService referred to in Science [12], “only 7% of 17-year-olds are adequately prepared for college-level science courses,” and “more than half have so little scientific understanding that they cannot hold down jobs that require technical skills, benefit from specialized on-the-job training, or make informed decisions as citizens.” Even students who have been interested in science and technology -- who, for example, enjoy tinkering with mechanics or electronics -- are often “put off” by physics as it is currently taught. The high school physics course is regarded by many students as perhaps the most difficult one offered. We are interested in why this is the case.

A Componential Approach to Training Reading Skills: Part 2. Decoding and Use of Context

This is the second of two articles that describe the development and evaluation of three component-specific instructional systems for improving critical reading skills. The skill components that were the focus of training have been shown in prior research to represent particular sources of processing difficulty for young adult, poor readers and, based on a model of component interaction, were predicted to have a potentially strong impact on the performance of other component processes. Part 1 presented the evaluation of SPEED, a system designed to develop automaticity in the ability to perceptually encode multiletter units that appear in words. Part 2 describes the evaluation of the RACER and SKI JUMP systems, which focus respectively on developing automaticity in phonological decoding of orthographic information in words and the use of context frames in retrieving and integrating word meanings. In both the RACER and SKI JUMP training studies, all subjects achieved highly accurate and efficient levels of ...

Causal models as intelligent learning environments for science and engineering education

AI research in qualitative physics and causal models suggests new approaches to teaching people about science and engineering. We have been investigating the form that such models need to take to be effective within intelligent learning environments. The subject matter we have focused on is understanding how electrical circuits work, but the approach can be generalized to other subjects. Two key hypotheses have emerged from our research. The first is that in order to understand a physical system, students need to acquire causal mental models for how the system works. Further, it is not enough to have just a single mental model; students need alternative mental models that represent the systems behavior from different but related perspectives, such as at the macroscopic and microscopic levels. The second hypothesis is that in order to make causal understanding feasible in the initial stages of learning, students have to be introduced to simplified models. These models are then gradually refined into more s...