This simulation provides the basis for introductory work on the theory and process of evolution by natural selection. Its aim is to develop a conceptual understanding of how selection controls fluctuations in gene frequencies of wild populations and so produces adaptations for the specific requirements of the environment. The work is based on a bead or computer model of a population and the process of natural selection can be simulated by the manipulation of the model. The model is not deterministic; it works on chance factors, random assortment and pairing of alleles, and so mirrors the natural process of random fertilization. The results can be predicted but not predetermined, thus emphasising the role of chance in the real world. The model can be used to illustrate the development and maintenance of a polymorphism and the occurrence of genetic drift in small populations and to introduce the process of speciation by isolation.

This simulation enables the student to investigate the factors affecting the changes which occur in the sizes of populations over periods of time in either conditions of intra-especific, where a populations of a single species grows on limited resources,or inter-specific competition, where two species are competing with each other for limited resources. This simulation seeks to answer such questions as: (i). Can two species coexist with one another over an extended period of time?; (ii)  if they cannot coexist, does one of the species inevitably oust the other?; and (iii) what are the factors which are significant in deciding the outcome of such competition? This simulation can be introduced into biology courses at two separate, but not mutually exclusive, levels. The first is as an exercise in population dynamics per se and the second is as a vehicle for reinforcing the need for a systematic approach in tackling any work in biology involving more than one variable.

Genetics is a part of biology in which it is sometimes difficult to arrange adequate practical work. Moreover, there are concepts within genetics which students often find difficult initially. Two of these are the related topics of linkage and crossing-over. Genetic mapping follows logically from these topics and, by involving students actively in the planning and execution of mapping experiments which would not normally be possible in schools and colleges, this simulation will help improve their comprehension of these important concepts.

The study of interactions between flowering plants is an important part of ecology and a considerable amount of experimental work has been carried out to investigate the factors which are involved. Some of the best studies are presented here. Since experimental work with real plants often takes a long time, it is not very suitable for students, but the computer simulation of plant growth enables students to plan an investigation and to carry it out without the long delay usually associated with growth experiments. This simulation thus describes investigations with both real and simulated plants, and presents background data in the form of graphs and tables. The simulation is based on a mathematical model of plant growth devised by Baeumer & De Wit. They grew barley, oats and tall and dwarf peas in rows on their own and in mixtures of two kinds in alternate rows. The dwarf peas were var. Pauli and the tall peas var. Mechelse Krombek.

This simulation is intended, primarily, for students of chemistry. There are two investigations which are possible. In the first, students can investigate the effect on the percentage yield of ammonia of varying temperature, pressure and the molar ratio of hydrogen to nitrogen. In this way students can engage in a quantitative exploration of Le Chatelier's Principle. In the second investigation students can investigate the kinetics in the process.
The objectives of this simulation are to give a further understanding of the Haber process, the effects on the equilibrium yield of ammonia of changing temperature, pressure and the initial hydrogen to nitrogen molar ratio; the effects on the reaction rate of changing temperature and pressure; the effects on the reaction rate of using various catalysts; some of the considerations which have to be taken into account in the design of chemical plant for the industrial production of ammonia; and the interpretation of results predicted by a model for conditions which the students are unable to create in the laboratory.

This simulation fits within the general philosophy of enabling students to extend their enquiry through questions such as "What would happen if...?". It enables them to design investigations of reactions which are normally beyond their experimental experience but within the range of their study of reaction kinetics. The rapid dialogue and the ease of repeating the investigation are used to establish an understanding of the topic that would take many hours through laboratory work alone. The simulation fulfills two basic objectives: (i) to extend students' laboratory experience by enabling them to carry out a wider range of investigations without taking up an excessive amount of time, and (ii) to assist students' understanding of the relationship between a mathematical model and reality. It is appropriate to use this simulation twice. First, after initial laboratory experiments have been performed, so that students can gain further experience of manipulating kinetic data; and second, after the effect of temperature has been discussed, when they can deal with more data and begin to appreciate the ideas behind this model.

A piece of experimental research requires at least three kinds of work: planning of experiments, performance of the experiments and interpretation of the results. Only the middle stage involves laboratory work, and it is on this that traditional biochemical practical teaching concentrates. This simulation permits the student to obtain realistic results very rapidly simulating the enzyme-catalysed reactions, and so allows many cycles of plan, experiment and interpretation over a short time. Its educational objectives are: (i) to enable the students to answer for themselves some of the fundamental questions of enzyme kinetics, (ii) to give students experience in dealing, step by step, with an initially, quite unknown system; (iii) to provide experience in the interpretation of data. The results from any investigation they have planned seem more real than tables of data from a book and the need to use the results in planning the next investigation encourages students to extract the meaning quickly; and optionally, (iv) to introduce students to some more complex situations in enzyme kinetics, such as substrate inhibition, co-operativity and the influence of the cofactor.

The aim of this simulation is to focus students' attention on the physical model used to 'explain' the observations in a way that, because of the mathematics involved, is not simple to do without a computer. The simulation focuses on some of the assumptions - nearly always made, but hardly ever mentioned - in one particular example: diffraction and interference of radiation. But it draws students' attention to some of the usually hidden features of the model used in this particular example encouraging a more thoughtful and critical awareness of the role of models in physics. The simulation calculates the intensity due to the superposition of radiation from two point sources or two slits. It does exactly what the superposition model requires: it adds the wave amplitudes due to each point source (or each element of each slit) without using trigonometrical relationships or approximations. This means that the simulation can be used for a wide range of geometries. It is not restricted, as is the familiar treatment of Young's experiment, to situations where small angle approximations can be made. The user can choose the complexity of the model being used, and is asked to compare the predictions of the model with experimental observations.

Most physics courses include some work on evidence for the nuclear atom, and reference to the 'Rutherford' scattering experiment. To compensate for the fact that the experiment cannot be done in schools or colleges various alternatives have been devised. This simulation can supplement the battery of teaching aids already available. Its educational objectives include some that are not possible in more traditional teaching. There are three options in the simulation: (i) 'Marbles' are scattered by hard, massive targets of regular shape. By the scattering produced students can infer the shape and size of the target; (ii) the particles are scattered by a hard object or by an 'inverse square scatterer'. In the latter case the particle's energy has an effect on the scattering produced and the 'size' of the scattering object depends on the energy of the probing particles; (iii) a simulation of the scattering of alpha particles by a thin foil based on a simple model of the nucleus. Students can vary parameters (metal, foil thickness, energy of alpha particles) and are asked to decide, on the basis of their own 'experiments', whether a hard sphere or inverse square scattering model of the nucleus was used.