Metacognition as a Basis for Learning Support Software

In order to understand the task of instructional designers who produce learning support software, this paper reviews the influence of learning theory on instructional design, recent developments in computer technology, and the evolving role of the instructor as a facilitator of higher-order thinking. Constructivist principles of learning and an appreciation for the fact that the learner must become more independent and skilled in metacognitive self-assessment and self-management are fundamental to this changing role. Two cognitive tools that provide learner/user support for personal construction of knowledge systems are “MindMap” and “Learning FourMat Processor.” These tools are examined in the light of current learning theory and a recent study comparing the work of novice and expert writers using different forms of performance support. Recommendations are made for the development of a more complete set of cognitive tools that enables users to construct their own multimedia knowledge systems based on higher-order thinking and problem solving.     

Detecting potential hucksterism in meta-analysis using a follow-up fail-safe test

Meta-analysis is an analysis of analyses. It is a technique widely used by researchers and practitioners to aggregate and summarize statistically reported empirical educational research. In 10 years, meta-analysis appeared more than 600 times in research journals and dissertation abstracts. Although most meta-analyses were reported as significant, few of the findings determined how many unpublished “no-effect” studies, if sampled, would have invalidated significance. If significant meta-analysis results are over represented through selective sampling, hucksterism in the form of sampling bias exists. An explanation for using a follow-up test called the fail-safe N is provided with tables constructed to assist researchers and practitioners to estimate, without calculation, the relative stability of meta-analysis results. The implication is that failsafe N should routinely be used and reported in meta-analysis research.     

The retrograde motion of planets and children: Interpreting percentile rank

A common method used to interpret raw scores is to convert them into percentile rank. The broad application of percentile rank in almost all norm-referenced tests, and the exclusive use in some tests, requires the conversion of raw scores. Because percentile rank is not a linear transformation of raw scores, percentile-rank transformation in the lower and upper part of the raw-score distribution relates percentile rank and raw scores differently than in the center of the raw-score distribution. This paper describes the popularity of using percentile rank and offers an interpretation of the use of percentile rank with normal and skewed score distributions.