Book review

Philosophy of Educational Research Richard Pring (2000), London and New York: Continuum.     

THE GENETIC ASPECTS OF HIGH INTELLIGENCE

A cohort of 71 pairs of twins was studied in a project which started within the decade 1965 to 1975. The total level of intelligence (global IQ) and the level of particular intellectual components have been examined annually since the twins were two years of age. The data were analysed by comparing monozygotic and dizygotic twins. The results revealed that high intelligence is influenced much more by hereditary than exogenous factors. Furthermore, there is an irregularity in the development of intellectual level from childhood to adulthood. Consequently, decision making about children cannot be carried out on the basis of a single IQ evaluation. A cluster analysis demonstrated the importance of hereditary factors not only on intellectual level, but also on the pattern of intellectual development.     

Analysis of performance in orienteering with treadmill tests and physiological field tests using a differential global positioning system

The aim of this study was to determine the physiological responses to orienteering by examining the interrelationships between the information provided by a differential global positioning system (dGPS) about an orienteer's route, speed and orienteering mistakes, portable metabolic gas analyser data during orienteering and data from incremental treadmill tests. Ten male orienteers completed a treadmill threshold test and a field test; the latter was performed on a 4.3 km course on mixed terrain with nine checkpoints. The anaerobic threshold, threshold of decompensated metabolic acidosis, respiratory exchange ratio, onset of blood lactate accumulation and peak oxygen uptake (VO2peak) were determined from the treadmill test. Time to complete the course, total distance covered, mean speed, distance and timing of orienteering mistakes, mean oxygen uptake, mean relative heart rate, mean respiratory exchange ratio and mean running economy were computed from the dGPS data and metabolic gas analyser data. Correlation analyses showed a relationship between a high anaerobic threshold and few orienteering mistakes (r = - 0.64, P < 0.05). A high threshold of decompensated metabolic acidosis and VO2peak were related to a fast overall time (r = -0.70 to -0.72, P < 0.05) and high running speed (r = 0.64 to 0.79, P < 0.05 and P < 0.01, respectively), and were thus the best predictors of performance.     

Impact of question-answering tasks on search processes and reading comprehension

This study examined the effect of (a) high- and low-level questions and (b) reading the text before the questions asked on performance, delayed text recall, and deep text comprehension, as well as on specific text-inspection patterns. Participants were 37 undergraduate students who answered either high- or low-level questions using the software Read&Answer to read and answer questions on the computer screen. Additionally, half of the sample read first a text and then answered the questions (reading-first condition), whereas the other half answered the questions without having read the text in advance (no-reading-first condition). All participants had the text available to search for the answer. Results indicated that high-level questions facilitated deep comprehension but not immediate performance or delayed recall of text, independently of the reading condition, and that high- and low-level questions differentially affected text-inspection patterns.     

HPS: High precision stemmer

Research into unsupervised ways of stemming has resulted, in the past few years, in the development of methods that are reliable and perform well. Our approach further shifts the boundaries of the state of the art by providing more accurate stemming results. The idea of the approach consists in building a stemmer in two stages. In the first stage, a stemming algorithm based upon clustering, which exploits the lexical and semantic information of words, is used to prepare large-scale training data for the second-stage algorithm. The second-stage algorithm uses a maximum entropy classifier. The stemming-specific features help the classifier decide when and how to stem a particular word.