The Programme for International Student Assessment (PISA) has drawn attention to the role of mathematical literacy as an important prerequisite for lifelong learning and active participation in society and culture. Many everyday situations require mathematical abilities for sound judgements or important decisions. The aim of this study is to find out how often adults use mathematics in their work and daily life and how this is connected to their mathematical competence. The sample comprises N = 461 adults from Germany (age: M = 44.2 years, SD = 12.2 years). The testing took place by individual sessions in the adults' personal home environment. A Latent-Class-Analysis identified three classes of adults which differ in their profiles of using mathematics in work and daily life. Regression analyses on the adults' mathematical competence showed statistically significant effects for age (beta = -0.19), socio-economic status (beta = 0.26), educational attainment (beta = 0.18) and the interaction between gender and educational attainment (beta = 0.57). Adding the variable "use of mathematics" to the regression model resulted in an additional effect mathematics user profile classes. The findings showed that the use of mathematics in work and daily life is a strong predictor for mathematical competence. This effect is stable even when characteristics of the social background are controlled. Further implications for the life-long learning in mathematics with regard to limitations of the study (sample bias and cross sectional design) will be discussed.
The Programme for International Student Assessment (PISA; OECD, 2003) has drawn attention to the role of mathematical literacy as an important prerequisite for lifelong learning and active participation in society and culture. Many everyday situations require mathematical abilities for sound judgements or important decisions. Mathematical literacy thereby emphasizes the knowledgeable use of mathematics as a tool for solving problems in real-world situations.
The aim of this study is to find out how often adults use mathematics in their work and daily life and how this is connected to their mathematical competence. More concrete we follow two research questions:
(1) Which profiles can be identified concerning the use of different mathematical concepts in work and daily life?
(2) Of what kind is the relationship between the adults' use of mathematics in work and daily life, their social status and their mathematical competence?
The sample comprises N = 461 adults from Germany (age: M = 44.2 years, SD = 12.2 years; gender: 55 percent women and 45 percent men). It was taken within a pilot study of the National Educational Panel Study (NEPS) in Germany (Blossfeld, Schneider & Doll, 2009). The testing took place by individual sessions in the adults' personal home environment. Test administrators who had been trained in advance conducted the test according to standardized guidelines. Each session took 90 minutes, and the participating adults were rewarded with a sum of 20 Euros. The test time was divided into 60 minutes for a paper-and-pencil mathematics test and 30 minutes for a questionnaire. The mathematics test consists of 40 items (Cronbachs' alpha = 0.90) (Ehmke, Duchhardt, Geiser, Grýþing, Heinze, & Marschick, 2009). The questionnaire asks for standard sociodemographics (age, gender, socio-economic status, educational attainment) and also includes a scale on the use of different mathematical concepts in work and daily life (12 items, cronbachs' alpha = 0.86).
A Latent-Class-Analysis identified three classes of adults which differ in their profiles of using mathematics in work and daily life. The adults in the first class (63 percent of the sample) represent the "normal users". They apply elementary mathematics (e.g. fractions) in their work and daily life on average at least once per month. They almost do not use higher mathematical concepts (e.g. trigonometry). The second class (14 percent) comprises "advanced users". They use elementary mathematics as regularly as the first class. Additionally, they use advanced mathematics quite frequently. The third class (23 percent) can be described as "non-users". They report that they very seldom apply mathematics in their work and daily life.
Regression analyses on the adults' mathematical competence showed statistically significant effects for age (beta = -0.19), socio-economic status (beta = 0.26), educational attainment (beta = 0.18) and the interaction between gender and educational attainment (beta = 0.57). Adding the variable "use of mathematics" to the regression model shows an additional effect mathematics user profile classes. Also, this results in a reduction of the effects for the characteristics of social status. This can be interpreted as a mediation effect. In the final model, 35 percent of the variance in the adults' mathematical competence is explained by the characteristics of social status and their use of mathematics in work and daily life.
The findings showed that the use of mathematics in work and daily life is a strong predictor for mathematical competence. This effect is stable even when characteristics of the social background are controlled. Further implications for the life-long learning in mathematics with regard to limitations of the study (sample bias and cross sectional design) will be discussed.

References:
Blossfeld, H.-P., Schneider, T. & Doll, J. (2009). Methodological Advantages of Panel Studies: Designing the New National Educational Panel Study (NEPS) in Germany. Journal for Educational Research online, 1 (2), 10-32.

Ehmke, T., Duchhardt, C., Geiser, H., Grýþing, M., Heinze, A. & Marschick, F. (2009): Kompetenzentwicklung über die Lebensspanne - Erhebung von mathematischer Kompetenz im Nationalen Bildungspanel. In: A. Heinze & M. Grýþing (Hrsg.): Mathematiklernen vom Kindergarten bis zum Studium. Kontinuität und Kohärenz als Herausforderung für den Mathematikunterricht. Münster: Waxmann, S. 313-327.

OECD. (2003). The PISA 2003 assessment framework – mathematics, reading, science and problem solving knowledge and skills. Paris: OECD.