Abstract

In this chapter, we apply the expectancy-value model of motivation, particularly the family socialization aspect of the model (Eccles (Parsons) et al., 1983; Eccles, 1994, 2007; Wigfield & Eccles, 2002) to address a number of key questions regarding gender differences in adult attainment, in particular educational attainment. When some individuals in the work force of today were children, what kinds of expectations did they have for themselves? What expectations did their parents have for them? Did these expectations vary for girls and boys? Were parents’ expectations about their children’s future education related to the actual education that these adolescents later attained in midlife? How did the child’s academic ability and characteristics of the family figure into this picture? We present original empirical findings, drawing on data collected for a Swedish longitudinal study that spans from childhood to middle adulthood. In line with the expectancy-value model of motivation, the family’s socioeconomic status (SES) was identified as an important predictor of several outcomes. Consistent with the model, for both genders, the family’s SES and parental educational expectations in middle adolescence predicted middle adult educational attainment. The importance of grades differed by gender in that the mathematics grade was a statistically significant predictor of middle adult educational attainment for males, while for females grades in Swedish were a statistically significant predictor of middle adult educational attainment. In this chapter, we situated these study findings in the wider pertinent scholarly literature and discussed the implications of our results as they might relate to efforts to promote equitable and optimal life chances for the current generation of European girls and boys.

The purpose of this chapter is to discuss different approaches for studying processes. Since methods are – or at least should be – intimately related to the theory guiding the research it is natural to start from a meta theoretical perspective. A powerful general theoretical framework for studying personality in a life-course perspective is provided by the holistic-interactionistic research paradigm as incorporated in the new developmental science. Therefore, the chapter starts with a brief introduction of this framework and how it leads to an interest in studying processes. A very thought-provoking and potentially attractive approach to studying processes is given by emerging methods for studying nonlinear dynamical systems (NOLIDS). Some general ideas in NOLIDS are indicated and a few examples given of key concepts that seem relevant in relation to the study of personality. Against this background, the emphasis in current research on what will here be called static statistical methods is questioned and a number of approaches are discussed which stay closer to the process characteristics of the phenomena under study.

The issues treated in this chapter, although methodological and apart from the substantive issues treated elsewhere in this book, may be useful to consider in conjunction with the rest of the book.

THE NEED FOR A LONGITUDINAL APPROACH

Longitudinal studies are vital for studying individual development and cannot normally for this purpose be replaced by other kinds of studies. This has been asserted many times (see Chapter 1 in this volume; Magnusson, 1988; Mednick, Harway & Finello, 1984). The main reason for using a longitudinal approach is really common-sense: If you want to understand how an individual develops over time, you have to study the individual over time. All other approaches are more indirect and have to make questionable assumptions for the results to be applicable for statements about individual development. For overviews of longitudinal versus other designs, the reader is referred to Bakes (1968) and Bakes and Nesselroade (1979).

The above should not be interpreted to mean that a longitudinal study always is necessary when development or change is to be studied. For instance, within epidemiology, a case-control study can be faster, cheaper, and more efficient than a longitudinal study for the (preliminary) study of the aetiology of a certain decease.

THE RESEARCH PROCESS

The research process can be described as having the following components:

1. 1 The process starts from the specific aspect of reality that is at the focus of enquiry.

2. 2 By some kind of data collection procedure, the raw data are produced.

3. 3 The raw data are often further processed to give the variable values used in the analyses (transformed, summed to form indices and so on).

4. 4 Statistical analyses are performed.

5. 5 The results are interpreted in relation to the theoretical formulations.

6. […]

Longitudinal research is the main road to fundamental and valid knowledge of living organisms' development. Because the longitudinal approach implies collecting data about the same subjects across time, the demands on the researchers to be accurate and scrupulous are high for several reasons. First, a mistake made at one assessment occasion can seldom be satisfactorily remedied at a later stage. Second, the complexity of information makes it necessary to treat and analyze data with special care.

The importance of issues of methodology and research strategy in longitudinal research is evident from the fact that two of the eight workshops organized by the European Science Foundation's Network on Longitudinal Studies on Individual Development have exclusively dealt with methodology. The first of these was concerned with data quality and resulted in one of the volumes that have come out of the workshop series (see page iv).

This volume emanates from the second methodology workshop, which was held at Soria Moria conference center in Oslo, Norway, April 2-5, 1989. It concentrates on issues that have to do with the intricate task of applying methodological tools which are appropriate to the problem at hand. Two overriding and related concepts are central to longitudinal research: stability and change. In this book these concepts subsume multiple aspects of the human condition: for example, depression, health development, cognitive development, behavior genetics, and adjustment problems. An array of statistical methods is introduced and discussed in relation to the content areas and the problems studied.

INTRODUCTION

Research on individual development has been strongly dominated by an interest in variables; in the characteristics of and interrelationships among person variables, and in the relationships between person variables and environmental variables (Thomae, 1988; Wohlwill, 1973). However, if the focus is on an analysis of the character of the structures and processes involved in the total functioning of an individual – in a current and in a developmental perspective – it is easy to see that this approach to the study of individual development has clear limitations (Magnusson, 1985, 1988).

Individual functioning can be described as a multidetermined stochastic process partly unique to the individual; a characteristic that is reflected in strong interactions and nonlinearity in data across individuals. This view leads to the conclusion that we have to complement the variable-oriented approach with one in which the person as a gestalt is the central object of interest. Operationally, such a person orientation implies that individuals are studied on the basis of their patterns of individual characteristics relevant for the study of the problem under consideration.

Several methodological approaches are possible for the study of individual development in terms of patterns. The aim of the present chapter is to illustrate the applicability of a cluster analysis oriented methodology to research on individual development, by presenting an empirical study concerned with the issue of early maladjustment behaviors as precursors of later adjustment problems.

INTRODUCTION

The ultimate goal for developmental research is to understand and explain the developmental process underlying an individual's way of thinking, feeling, acting and reacting at a certain stage of the life process.

In order for empirical research to contribute effectively to this goal there are three crucial aspects of the research strategy which are important:

1. the problem under consideration,

2. the data used to reflect the structures and processes involved, and

3. the methods applied for data treatment.

An important prerequisite for the formulation of relevant problems is a careful analysis of the phenomena, in this case the functioning of the individual at the appropriate level of the structures and processes relevant for the problem. Too often problems are formulated with reference to theories which have not been anchored in careful observation and analysis of the phenomena, a circumstance which has contributed to much artificial theorizing and meaningless empirical research.

The crucial importance of using data relevant to the character of the problem, with respect to reliability, validity, level of generalization, etc., was comprehensively dealt with in an earlier volume in this series (Magnusson & Bergman, 1990).

The focus of this volume is on methods for data treatment. The emphasis is on the importance of careful linking of methods for data treatment to the character of the substantive problem under consideration in the specific case. The choice of method for data treatment should always be made with reference to an analysis of the structures and processes relevant to the problem under consideration.