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Evaluation of C Turnover in Soils

Patricia Spence, The University of Aberdeen (Centre for Learning and Professional Development)

Introduction and Background to the Evaluation

C Turnover in Soils (CT) is a computer-assisted learning module comprising a tutorial and a simulation model. It is used as part of the Soil Microbiology and Biochemistry course (taken by honours and postgraduate students) in the Department of Plant and Soil Science. The tutorial provides students with access to the subject information necessary to work with the CT model. The use of a simulation aims to encourage a deeper level of understanding, and hence provides a deeper learning experience for the students.

In previous years the lecturer had observed a wider spread of marks in the courseware reports than in traditional laboratory reports completed in other parts of the course. Students fell into two distinct groups: those who did very well, and those who performed poorly. Although it was a smaller proportion (around 30%) who did badly, that proportion tended to perform less well than would have been expected. The aims of the evaluation were to establish why a relatively high proportion of students using the C Turnover courseware perform less well than would be expected and then to propose ways to help students with low marks improve their performance on the CT practical.

Evaluation Instruments

Preliminary results

1 Distribution of CT marks.


The students CT marks did not fall into two groups, as had been expected. This needs to be investigated further.

The evaluation should have resulted in recommendations to improve the situation for weaker students but more general recommendations can be made which should help support all students’ use of the CT model.

The evaluation was ambitious for the time available. Restricting the objectives to be tested would perhaps have made the exercise more manageable.

Some of the original objectives have not yet been investigated. Pre and post test data was obtained but has not yet been fully analysed; it was not possible to monitor the students’ use of the software, and data for previous years has not yet been obtained.

Preparation is essential: the use and purpose of the evaluation instruments must be fully thought out before they are implemented eg, the Approaches and Study Skills Inventory for Students is time consuming to implement and analyse and it could be suggested the results are very subjective

The student CT marks did not fall into the distinct high and low groups that were anticipated. The marks ranged from 13 to

20 with a mean of 17.4 and standard deviation of 1.76. This was similar to the distribution of marks in other courses and also the overall course marks.

2 Factors associated with CT marks:

IT skills. Overall there was no significant association between students IT skills and their CT scores. However, there was a relationship between IT and CT scores for the undergraduate population.

Previous Subject Knowledge. Having a previous subject knowledge as indicated by the students degree was not associated with CT score.

Individual Learning Styles. Initial analysis suggests that students with a deep/strategic approach are slightly more likely to get higher marks and that postgraduate students were significantly more likely to have a higher deep/strategic score.

Academic performance and CT practical marks. There was a strong association between the overall course marks and CT marks.

3 Problems students have in the CT practical.

Students used both the C Turnover tutorial and simulation model. They generally found the tutorial very straight forward but ran into difficulties with the simulation model. The most common comment was that they felt ‘thrown in at the deep end’ when using the simulation.

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