Measuring student knowledge and skills
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measuring students\' knowledge
Mathematical Literacy
49 OECD 1999 Change and growth Every natural phenomenon is a manifestation of change. Examples are: organisms changing as they grow, the cycle of seasons, the ebb and flow of tides, cycles of unemployment, weather changes and the Dow-Jones index. Some of these growth processes can be described or modelled by straightforward mathematical functions: linear, exponential, periodic, logistic, either discrete or continuous. But many processes fall into different categories and data analysis is quite often essential. The use of computer technology has resulted in more powerful approximation techniques and more sophisticated ways for visualising data. The patterns of change in nature and in mathematics do not follow the traditional content strands. In order to be sensitive to the patterns of change, Stuart (1990) states that we need to: – represent changes in a comprehensible form; – understand the fundamental types of change; – recognise particular types of change when they occur; – apply these techniques to the outside world; and – control a changing universe to our best advantage. These competencies relate closely to both our definition of mathematical literacy and the compe- tencies defined earlier in this framework. Many different sub-strands of traditional content strands emerge in this big idea of change and growth. The obvious ones are relationships and functions, and their graphical representations. Series and gradients are closely intertwined with functions. An examination of rates of growth for different growth phenomena leads to linear, exponential, logarithmic, periodic and logistic growth curves, and to their properties and relationships. These, in turn, lead to aspects of number theory, such as Fibonacci numbers and the Golden Ratio. The connections between these ideas and geometrical representations can also play a role here. Geometry can also be used to explore patterns in nature, art and architecture. Similarity and congruence might play a role, as would the growth of an area in relation to the growth of the perimeter or circumference. Growth patterns can be expressed in algebraic forms, which in turn can be represented by graphs. Growth can also be measured empirically, and questions arise as to what inferences can be drawn from the growth data, how the growth data may be represented, and so on. Aspects of data analysis and statistics are other content strands that come to light in this context. Space and shape Patterns are not only encountered in growth and change processes, but everywhere around us: spo- ken words, music, video, traffic, constructions and art. Shapes are patterns: houses, churches, bridges, starfish, snowflakes, town plans, clover leaves, crystals and shadows. Geometric patterns can serve as rel- atively simple models of many kinds of phenomena, and their study is possible and desirable at all lev- els (Grünbaum, 1985). Shape is a vital, growing, and fascinating theme in mathematics, with deep ties to traditional geometry (although relatively few to school geometry) but going far beyond it in content, meaning and method (Senechal, 1990). In the study of shape and constructions, we are looking for similarities and differences as we analyse the components of form and recognise shapes in different representations and different dimensions. The study of shapes is closely connected to the concept of “grasping space” (Freudenthal, 1973). This means learning to know, explore and conquer, in order to live, breathe and move more easily in the space in which we live. To achieve this, we must be able to understand the relative positions of objects. We must be aware of how we see things and why we see them as we do. We must learn to navigate through space and through constructions and shapes. This means that students should be able to understand the relation- ship between shapes and images or visual representations, such as that between a real city and |
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