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This report reviews the use of loans for learning in 33 European countries and analyses the schemes in eight selected Member States: France, Hungary, the Netherlands, Austria, Poland, Finland, Sweden and the UK. The analysis shows that loan schemes vary considerably across Europe in terms of types and levels of learning covered, conditions of access, repayment and governance. Some loans aim to increase participation in learning in general, while others are designed to promote equity. The report attempts to assess the selected loans and discusses their strengths and weaknesses and determinants of performance, while considering if a given scheme operates on a large scale or targets niche groups. The evaluation results provide a basis for identifying good practice principles for designing and implementing loans. Policy recommendations are formulated based on these findings. Annexed are: (1) Methodology; (2) Key terms and definitions; (3) Information on countries/schemes selected for in-depth analysis; (4) Proposed typologies of VET loan schemes; (5) Tables and figures; (6) Tosmana truth tables; (7) Questionnaires; (8) Basic characteristics of non-European loan schemes. (Contains 37 tables, 5 figures, 20 boxes and 33 footnotes.)

This examination of data selection preceding multivariate analysis compares results grained with "gentle" and "draconian" variable elimination. To acquire comparable results, two stages of statistical exploration into an integrated model of motivation, learning strategies, and quality of teaching were used. The goal of the paper was to select variables that were as powerful as possible and to use them to produce a new factor model, applying both standard linear (Statistical Package for the Social Sciences [SPSS]) and Bayesian (BAYDA) statistical software. The second stage of the research, planned for the future, will involve efforts to produce sensible path models related to the theory. The study of motivation, learning strategies, and teaching used research in a Finnish telecommunications company in which 156 respondents answered a questionnaire with 135 items. The statistical analyses used for variable selection are described. Research results indicate that both teaching style and subject material can influence study motivation and the use of learning strategies. Learning material can be described with respect to the degree that broad theoretical perspectives are developed, and the personal meaningfulness of the subject material or the drawing of logical conclusions from detailed evidence is emphasized. The new statistical methods described, especially the nonlinear approaches based on Bayesian networks, enable the application of statistical analysis to the study of student motivation and self-regulated learning. The SPSS syntax is attached. (Contains 19 tables, 6 figures, and 87 references.) (SLD)

This paper reports findings from a study of Finnish academic Olympians of different ages who participated in Olympiad Studies in mathematics, physics, or chemistry during the years 1965-1997. The study focused special interest on the influences of home and school in contributing to the development of academic talent. The results of the Finnish study are compared to an earlier U.S. study using the same instruments. The Finnish Olympians were mailed a 14-page questionnaire and the self-confidence attitude attribute scales; their parents received a shorter version of the same questionnaire and the inventory of parental influence. Data included 150 males and 7 females. More than half of the Olympians were first-born children; parents had either a very high educational level or a very low educational level; and parents had good incomes. Olympians and their parents were asked to rate the importance of family/school influences in development of academic talent, and parents rated these influences as more important than did the Olympians. Finnish Olympians emphasized their own interests and efforts as key factors to their talent development, as well as good teachers. They noted few hindrances to their talent development. More than half expressed the view that they would not have accomplished as much without the Olympiad program. Data are going to be compared with similar data from the United States, Germany, and Taiwan. (Contains 21 figures, 7 tables, and 11 references.) (BT)

Bayesian and classical approaches to classification of vocational data were compared using an educational data set from a longitudinal study of professional growth and development in organizations (P. Ruohotie et al., 1994). Data were from 2,430 workers in companies in Finland who completed a questionnaire with behavior and background statements. The main purpose of this study was to look for new possibilities in analyzing multiform vocational data starting from the level at which traditional linear methods become too complex to apply. After describing the data and the theory of professional growth, the paper discusses linear discrimination and its use in the social sciences. Bayesian modeling with the BAYDA software package is described. It is concluded that linear and nonlinear methods support each other depending on the subject of the study. The Bayesian approach, in the form of the BAYDA program, is still under rapid development, but it appears to provide a valuable tool for analysis. (Contains 10 figures, 21 tables, and 12 references.) (SLD)