Loughborough University
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Automated email systems for submission and marking of course work

conference contribution
posted on 2006-05-23, 17:08 authored by Andrew Rosenthal
Many science subjects have the need for students to learn laboratory skills, such techniques as titrations, extractions, digestions, gravimetric determinations, to name but a few. Within my own discipline of food science it is desirable that the students are aware of the techniques required to determine the basic composition of foods through chemical analysis. The term Proximate Composition refers to the percentage of the five macronutrient components present in our foods, namely: protein, fat, carbohydrate, moisture and total minerals. The analytical procedures which are used to determine these proteins, fat, moisture and minerals can be carried out in a three hour practical session (carbohydrates can be determined by difference from 100%). Working with about 20 students in a laboratory session, I run a demonstration/practical in which we carry out the analysis of peanuts. I start the session with a preamble along the lines: “There are two reasons that students undertake practical work, the first is to gain marks which help them to get a degree and the second is learn laboratory techniques. In this session I am only interested in the second.” We then get started on the fat extraction, the protein digestion, the moisture and ash determinations. There is then a ½ hour gap during which they go for a coffee break. After this we carry out titrations on the protein digest and distil off the solvent which has been used to extract the fat. All this fits into a 2½ hour period. I tell the students that to complete the procedures they will need to return the next morning to obtain their moisture and mineral results (these take about 12 hours in an oven or furnace). Towards the end of the practical session I inform the students that they are required to complete a report. For their report, I tell them that they each have a unique set of data which is within the expected variation for analysis of peanuts, but includes a random element to ensure that each student has a unique set of figures. I go on to tell them how to access the data using the program which I developed. Despite the students not actually working with the laboratory data, I suggest that they return the following day for the final moisture, ash and fat results, if only to see the analytical part of the practical to completion....



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ROSENTHAL, A., 2001. Automated email systems for submission and marking of course work. IN: Proceedings of the 5th CAA Conference, Loughborough: Loughborough University


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