Learning processes

The first step in an inductive learning process is always to order the observations to group those objects together that have essential features in common and to separate objects that are distinctly different. Thus, in learning from individual reactions we have to classify reactions - we have to define reaction types that encompass a series of reactions with essential common characteristics. Clearly, the definition of what are essential common features is subjective and thus a variety of different classification schemes have been proposed. 

Thus, when a large set of chemical reactions has to be investigated, an inductive learning process, deriving knowledge on chemical reactions and reactivity from a series of reactions, still has many merits. Such chemical knowledge can be put into models that then allow one to predict the course of new reactions. 

We learn from data. Therefore, the way we prepare the data for the learning process will crucially condition the quality of learning and the reliability of the extracted knowledge. 

The quality and the relationship of the data to the information and knowledge are crucial points in the learning process... 

To understand the machine learning process and learning concepts... 

The underlying learning process can follow different concepts. The two major learning strategies are unsupervised learning and supervised learning. 

Just like humans, ANNs learn from examples. The examples are delivered as input data. The learning process of an ANN is called training. In the human brain, the synaptic connections, and thus the connections between the neurons. 

Classification describes the process of assigning an instance or property to one of several given classes. The classes are defined beforehand and this class assignment is used in the learning process, which is therefore supervised. Statistical methods and decision trees (cf. Section 9.3) are also widely used for classification tasks. 

Before posing the problem for this computer project, we shall introduce another vei y useful piece of microcomputer software by repeating the integration of Eq. (l-36a) with Mathcad (Appendix A). Like other software of this kind, there is a short learning process before mathcad can be used with ease. Once one has entered the equation of interest, mathcad solves it with a click on the = sign. In the present example, the constants of (Eq. l-36a) are entered followed by the desired integral... 

In unsupervised learning, the outcome is usually a hypothesis to then be tested, often usiag classification or prediction methods. If the unsupervised learning process suggests the presence of distinct clusters, the hypothesis can be tested by applyiag a classification method to the data. A low number of misclassified samples would tend to reinforce the hypothesis. 

Provided that no learning process is involved (so that the value of Pi is not influenced by previous results), the probabihty of x successes in n trials is given by the term containing pf in the expansion of the binomial ... 

The structure of a neural network forms the basis for information storage and governs the learning process. The type of neural network used in this work is known as a feed-forward network the information flows only in the forward direction, i.e., from input to output in the testing mode. A general structure of a feed-forward network is shown in Fig. I. Connections are made be-... 

The following questions are still to be answered to what extent can an EDSS be modified directly by any user Who should decide that an EDSS has to start a learning process Who has to validate the results of such process Why should an EDSS start a learning process Who is legally responsible for the decisions made by... 

The experiential curriculum the actual learning processes that the students undertake. 

Fig. 9.5 Sequence of activities to develop the conceptualisation of porosity and structure in the unit about unbreakable crockery (Example of expanding the meaning of the concepts by activities that are meaningful for students at every step of the teaching and learning process)...

In this last part of the chapter we present - as far as possible - a summarising overview about the development of micro-macro thinking in the history of chemistry. Where no investigations concerning students development of micro-macro-thinking over the time in school were available, we have formulated possible links to historic developments. Further studies, e.g. in the maimer of learning process studies would be helpful. 

In different places in the outlines of teachers reflective diaries there are statements indicating that students interest in learning about chemical reactions has increased in comparison to previous years. Teachers mentioned the increase of students interest in the context of all three main factors that are incorporated in the LON approach, i.e. (1) Eveiyday life situations as the foundation of the learning process. (2) The learning process involves many students activities. (3) Chemical reactions are consistently presented in all three types of representation. Consequently, we assnme that those three factors are the main reasons for the increased interest of students in learning about chemical reactions. Each of the listed factors is described in detail below ... 

Everyday life situations are the foundation of the learning process Stndents understood that chemical reaction go on in everyday life and are therefore of interest to them. That point seemed to be important to all of the participating teachers since in many places in their reflective diaries they made statements like e.g. ... 

The learning process involves many students"activities Students interest increased because they liked playing an active role in the learning process (e.g. hands on experiments, constraction of representations of chemical reactions with the use of models). Those who were not used to such an approach from earlier teaching also improved their experimental skills and gained experiences through the work with models. In the reflective diaries of all the teachers, statements to support this point could be found as follows ... 

Some tasks in the Test of Gained Knowledge required students to connect observations about the macro course of chemical reactions with their notations in the submicro and/or symbolic types of representation. The results indicate that most students were able to rearticulate the information about reactants and products of a chemical reaction from the textual description of chemical reaction into the form of word chemical equation (textual description of macros word equation of macro Task 8.2, f(o/ )=89.82% Task 9.1, f(o/ )=87.61%). This action corresponds to the first step in learning to write down chemical equation in the LON approach. It can easily be explained, because teachers described the learning process to be very efficient to this point, as is illustrated below ... 

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