Design coursework

Thus the degree of isomorphy between the Stimulus (the text) and the response (its retention) has been the chief Interest of learning researchers. If a similar text were to be used in an educational setting, the measurement of the learning outcome would probably be of the same kind. Consider, however, the following excerpts from an undergraduate textbook: If all farmers work hard and nature cooperates in producing a bumper crop, total farm income may fall, and probably will. A question of that kind would not enable a teacher to judge which ItUuents had really understood the meaning of the examples.

By using materials with little or no inherent meaning, such poriments describe and explain only how students set about learning )9n the task has been drained of meaning. Yet most human learning ptndl on meaning and it is directed towards it. To learn is to strive for 24 25 THE EXPERIENCE OF LEARNING meaning, and design coursework to have learned something is to have grasped its meaning. In spite of this dominant interest in learning defined as a quantitative phenomenon, since the time of Bartlett (1932) there has also been a concern with learning defined in qualitative terms. Bartlett investigated the ways in which students recounted a story they had read. The differences in the form of these responses led Bartlett to abandon the conception of memory as a reproductive storage mechanism, where every impression with all its specific characteristics is stored in a defined, neural region.

It rejects the description of knowledge as discrete pieces of knowledge passed passively from teacher to learner, and tested in terms of whether or not the student can reproduce verbatim those elements. Necessarily this qualitative type of research is concerned with the learning of realistically complex passages which contain a description or an explanation of a phenomenon. The next step in the research process depends on generating data about how the subjects have understood the content of the text. The need for intensive and deep information places limitations on the choice of methods. The general research strategy has been to use semi-structured or thematic interviews which are tape-recorded. Identical introductory questions on each topic are followed by questions aimed at eliciting answers in more depth. Depending on the structure design coursework and comprehensive- ness of an initial answer the interviewer may have to ask for clarification, elaboration or examples. The interviewer must, however, avoid giving any clues about the desired direction which the process should lead. The tape recordings are then typed up and the resulting protocols — once they have been checked by the researcher — constitute the data on which analysis is carried out.

The aim of the analysis is to yield descriptive categories of the qualitative variation found in the empirical data. The process involves the reduction of unimportant dissimilarities e. Some examples of this kind of analysis will be presented below. Thus in one investigation (Marton, 1975b: Marton et al. The article (which was written by Urban Dahllof, a Swedish professor of education) was a contribution to a debate about a reform in the Swedish system of higher education.

By reanalysing the empirical data used in an investigation initiated by the National Board of design coursework Universities and Colleges, Dahllof arrives at a conclusion which differs from that drawn in the original study.

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In that study the pass rate of students was found to be very low in the faculties of liberal arts and social science. The pass rate was however considerably higher in more vocationally oriented fields such as medicine, civil engineering, etc. In his re-analysis, of the data, Dahllof makes the assumption that many students who enter the system of higher education do so without the intention of graduating, but only to study a particular subject over a design coursework number of terms. Dahllof excludes from the empirical material students older than twenty-five on the assumption that, at that age, they have probably already gone through some kind of post-secondary education and want to complete that education with a few terms of university studies. Although this group of students are officially defined as drop-outs, that definition does not match their own intentions. Further- more, Dahllof splits the data into sub-groups according to university, sex, subject area, and grade point average from upper secondary school. He thus finds that there are large differences between the different sub-groups. Some have a very low pass rate and some have a pass rate which is similar to that found in the medical or engineering faculties. Dahllof draws the conclusion that if the purpose of the reform is to raise the pass rate in the faculties of humanities and social science, selective rather than general measures should be taken. The grounds on which he therefore challenges the wisdom of the reform are that a closer look at the empirical data shows that the situation is satisfactory as far as many groups of students are concerned, and very problematic in the case of others. In the learning experiment students were invited, individually, to read Dahllof s article carefully at their own pace. They were asked to read it in their usual way, but they were told that they would be asked questions about it afterwards.

Here we are concerned only with the analysis of the extent to which the main point of the article could be recounted.

This means that the protocols have to be studied with the intention of understanding what the students are expressing, THE EXPERIENCE OF LEARNING irrespective of what words or examples they may use, which may show a considerable variation even between answers belonging design coursework to the same category. Starting with a comparatively large number of categories the researcher will gradually refine these, arriving at a smaller set of categor- ies that may finally be difficult or impossible to collapse further. There are differences between different groups of students. What then differentiates these categories one from another? Clearly there is a hierarchical relationship between A, B and C with regard to their degree of specificity, in that selective measures (A) are a special case of differential measures (B) while the same relation is applicable also for B in relation to C. Category D, on the other hand deviates from the others by expressing only an aspect of the empirical data.

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