ONE OF THE WAYS OF PROCESSING AND ANALYSIS OF RESULTS OF THE PEDAGOGICAL EXPERIMENT

Provide statistical processing and analysis of results of pedagogical experiment on introduction of innovative methods based on the matrix model of cognitive activity carried out in Samara state University of railway engineering teachers of the Department "Higher mathematics". To confirm the effectiveness of the proposed method investigates four stochastic variables that characterize the coefficient of mastering of educational material by the individual student resulting from two control tests in experimental and control groups. As the result of an experiment, data is a set of numbers, which are difficult to capture any pattern of change (variation), they are subjected to statistical processing. Built for this interval variational series; the calculated basic numerical characteristics: sample average (arithmetic average value of the attribute of the sample), sample variance (average of squared deviations of observed values from their average values) and sample standard deviation (square root of sample variance). Determined the observed value of goodness-of-fit Pearson that allows you to install, after comparing them with critical values that all of the investigated random variable subject to normal distribution law. Built line of empirical densities of the results obtained in control and experimental groups after the first and after the second test, allowing, to estimate dynamics of process of mastering of educational material. The calculated coefficients of variation characterizing the dispersion of the variational series. Thus it is shown that in the experimental group by the end of training not only increased the average (10% compared with the control group), but decreased the dispersion of results about the mean (16,55 to 13,67 %), which undoubtedly confirms the effectiveness of the proposed method.

Pedagogical experiment, self-educational activity, the coefficient of mastering of educational information, random variable, sample average, sample variance, sample standard deviation, goodness-of-fit, empirical density function, the coefficient of variation