Technological literacy for students aged 6–18: a new method for holistic measuring of knowledge,capabilities, critical thinking and decision-making

Technological literacy is identified as a vital achievement of technology- and engineering-intensive education. It guides the design of technology and technical components of educational systems and defines competitive employment in technological society. Existing methods for measuring technological literacy are incomplete or complicated, unreliable, unstable and imprecise, time-consuming, and require large expenditures on resources. This paper presents a new method for valid and reliable measuring of technological literacy. The method encompasses three main components—knowledge, capabilities, and critical thinking and decision-making. It is centred on the standards for technological literacy issued by the International Technology and Engineering Educators Association. It has three key features. (1) A construct-measure-result front-ended approach, where a construct consists of an object, attribute, and entity; which causes reduction of measure-induced distortion and error. (2) A broad test range definition that provides stable and accurate measuring of technological literacy for 6–18-year-old students. (3) A genuine design approach including a multiple choice test item form determination consisting of content, criterion and construct validity, item discrimination, difficulty index, and an intraclass correlation measure for time stability and scooping its heterogeneous nature. Only the method is described herein and its pilot test results are presented. It is moderately reliable over time (intraclass correlation coefficient = 0.68, p < 0.05), has high criterion-related validity (r _xy  < 0.4) and construct validity (h ² > 0.7). High content validity evidence was ensured through a two-stage validation method, while test item discrimination coefficient values are acceptable (r _pbis  > 0.1). The method is time-efficient (measuring lasts 45 min), valid, stable, and enables holistic investigation of large sample sizes.     

Dynamic multidimensional assessment of sustainability at the macro level: The case of Austria

This paper explores the issue of sustainability at the macro scale employing multi-criteria decision aid (MCDA) methods. The incommensurability of values and the essentially multi-dimensional and dynamic nature of sustainability challenge the use of composite measurement indices. This determined the choice of MCDA methods. Austria was chosen as a case study, due to the wide availability of data, especially on indicators of strong sustainability. The structure of the multi-criteria problem comprised the evolution of different sustainability dimensions over time. The process for selecting criteria included a critical assessment of institutional sustainability agendas (UN, EU and Austrian Government) and theoretical recommendations.After an assessment of MCDA methods, the NAIADE method demonstrated the most suitable properties for sustainability assessment. The application of this outranking approach was undertaken in three separate settings: long-term from 1960 to 2003, medium-term, 1970-1995, and short-term, 1995-2003 with varying numbers of criteria. The response of results to the addition of evaluating criteria and periods was tested. The degree of credibility for accepting preference relations was also employed for sensitivity analysis.According to the results of long-term and medium-term assessments, especially in the weak sustainability setting, sustainable progress is taking place in Austria. In the short term, in the stronger sustainability setting and, especially as the number of criteria increases, more incomparable periods appear and trends are less determined. Moreover, it is shown how results crucially depend on the methodological choices.This is one of the first applications of the multi-criteria tools to the dynamic analysis of sustainability at the macro scale.     

The role of permanent and transitory components in business cycle volatility moderation

The paper examines the processes underlying economic fluctuations by investigating the volatility moderation of U.S. economy in the early 1980s. We decompose the volatility decline using a dynamic factor framework into a common stochastic trend, common transitory component and idiosyncratic components. We find that the moderation of business cycle was a result of the moderation in transitory and idiosyncratic components. Our results suggest that important part of stochastic process that drives economy is transitory. The paper investigates the role of oil prices, monetary and financial market factors. Proposed economic factors do not have a significant relationship to either transitory or permanent components. In addition, we find that transitory shocks are as common during the 1980s and 1990s as they were during the 1960s and 1970s.

Soviet society: Current trends and forecast scenarios

As perestroika drives the USSR towards free market socialism, the country's socioeconomic development depends on a number of factors that are only now taking shape. The transition is inconsistent and painful because there is no clear concept of the overall process. In order to overcome current difficulties the Soviet leadership must adopt a coherent transitional model. This article looks at the underlying trends of the current situation in the USSR and presents three scenarios for the development of Soviet society. Focusing on the dynamics of internal factors, the scenarios differ in terms of social orientation, degree of radicalism, approach to problems and proposed relationship between central power and the republics and regions. The extent of political support for each scenario is examined, and their potential for realization is assessed.     

Research on the Credit Cycle and Business Cycle with a Focus on Ten States from Central,Eastern, and Southeastern Europe

By performing an econometric analysis of the credit cycle and business cycle from an individual as well as a comparative perspective, with a focus on ten relevant economies from the areas of Central, Eastern, and Southeastern Europe, this research offers a fresh view regarding the importance of banks in promoting long-term economic growth through their lending capacity. The purpose is to better understand the behavior (the short- and medium-term dynamics) of the credit cycle and business cycle and the effects of the interactions between them. The results of this study offer valuable insights for both academics and policymakers and provide a warning to regulators not to overregulate or put too much pressure on banking activity.     

A 10-year retrospective on the determinants of Russian stock returns

We study factors influencing returns at the Russian stock market from 1995 to 2004, putting emphasis on how these evolved over time. We find that the relationship is highly unstable and this instability is not confined to financial crises alone. Most computed statistics exhibit constant ups and downs, but there has been recently a sharp rise in explainability of stock returns. Domestic factors have been playing a gradually diminishing role, while the importance of international factors has been increasing. In recent years, the effect of oil prices and foreign exchange rates has diminished, the impact of US stock prices and international and domestic interest rates has increased, while the influence of monetary aggregates such as gold reserves and credit balances has fallen to practically zero.     

Size (and competition) among organizations: modeling scale‐based selection among automobile producers in four major countries, 1885–1981

Based on previous empirical research, size is perhaps the most powerful explanatory organizational covariate in strategic analysis. We suggest that theoretical arguments about size be examined carefully to specify models with explicit comparison sets and with mechanisms linking size and underlying processes to outcomes. We illustrate the approach here by advancing arguments about scale competition within an organizational population. In this effort, we feature a theoretical model of scale‐based selection, which posits that a firm's chances of survival decrease with its aggregate distance from larger competitors on a transformed size gradient. The model assumes that the appropriate comparison set consists of all contemporaneous similar organizations competing on the basis of scale and operating in a localized geographic setting. We argue that aggregate distance of a focal firm from larger other firms (a specific form of relative position in the size distribution) reflects the extent to which it can capitalize on potential competitive advantages of scale emanating from economic, political, and social processes. Analyzing the mortality rates of large organizations across the entire histories of automobile industries in four major countries provides support for the theory. We discuss the general implications of our findings for strategic and organizational analysis. Copyright © 2003 John Wiley & Sons, Ltd.     

SOCIOECONOMIC STATUS MEASUREMENT WITH DISCRETE PROXY VARIABLES: IS PRINCIPAL COMPONENT ANALYSIS A RELIABLE ANSWER?

The last several years have seen a growth in the number of publications in economics that use principal component analysis (PCA) in the area of welfare studies. This paper explores the ways discrete data can be incorporated into PCA. The effects of discreteness of the observed variables on the PCA are reviewed. The statistical properties of the popular Filmer and Pritchett (2001 ) procedure are analyzed. The concepts of polychoric and polyserial correlations are introduced with appropriate references to the existing literature demonstrating their statistical properties. A large simulation study is carried out to compare various implementations of discrete data PCA. The simulation results show that the currently used method of running PCA on a set of dummy variables as proposed by Filmer and Pritchett (2001 ) can be improved upon by using procedures appropriate for discrete data, such as retaining the ordinal variables without breaking them into a set of dummy variables or using polychoric correlations. An empirical example using Bangladesh 2000 Demographic and Health Survey data helps in explaining the differences between procedures.