Empirical Modelling and Educational Learning

Your choice of theme is an interesting one. There surely are dependencies between what we eat and our health. At the same time, these dependencies may be very hard to identify precisely. For instance, it is well-recognised that different individuals respond to particular foods in different ways e.g. showing different levels of tolerance, and the controversies surrounding special diets - notably for slimmers - are well-known. In principle, applying Empirical Modelling to the science in this context would have to mean engaging with empirical research on real human subjects - this is perhaps the only way in which we could get a really nuanced picture of how diet impacts on health.

What you have in mind concerns more general commonsense understanding of nutrition. Though we don't know precisely what represents excessive consumption for a specific individual, we do know that there are implications and risks to health that stem from excesses and deficiencies in particular nutrients. Your choice of the word 'information' here is probably appropriate - it suggests knowledge for which the empirical basis is established, and is not to be explored in your project. The role of EM in this context will be to convey this information by generating interactive experiences. And because the knowledge is "commonsense" knowledge, I think it's entirely appropriate to target the non-specialist audience you've identified. The EM interest in your study then derives from the different ways in which you can make use of interactive models to enhance learners' construals where nutrition is concerned. The spirit of this enhancement is particularly well-expressed in the first sentence of your abstract.

The core resources here would be information about how consumption of nutrients affects growth and probability of contracting diseases. But it would be good to go beyond a standard spreadsheet-style correspondence between consumption levels and probable outcomes to consider broader aspects of the EM agenda. For instance: advice is often framed in terms of 'sophisticated' observables, such as body-mass index, that can be expressed as dependencies, it is also often contingent on factors such as whether the subject suffers with chronic conditions, is ill or pregnant or takes medication or drugs etc. There are also conditions such as anorexia that can be (at least naively) interpreted with reference to self-perception - whether someone thinks they are fat being more important than whether they are objectively overweight etc. This might argue for making several relatively small construals, each illustrating different ways in which EM principles might be used to communicate information about nutrition and health, rather than a single monolithic construal. In this connection, you may find it interesting to look at Sarah Marshall's WEB-EM-9 submission on EM and problem-solving, where the quality of the submission primarily derives from the way in which practical examples of construals are used to investigate and expose concepts and thought-processes rather than the sophistication of the construals themselves. Should you use JS-EDEN, you might also consider to what extent existing web resources might be adapted to be more interactive (as is illustrated in a rudimentary way in the JS-EDEN enhancement of the depiction of the cycle of malaria infection - the "animated diagram" referred to at http://www.dcs.warwick.ac.uk/~wmb/malaria/).

In their present form, the title and abstract are somewhat too vague. To some extent, this is natural, as you are uncertain about the details. Your eventual title should be more explicit about the actual content of the paper - consider for instance under which keywords you would like your paper to be retrievable by another researcher. The phrase 'educational learning' is also slightly odd - is there such a thing as non-educational learning? Finally, to conclude, by way of further comment, there's something rather uninformative about a "boiler-plate" sentence such as: "Finally, to conclude the paper, any further work will be explained". It's important to be aware of writing sentences of this nature - they take up space but don't communicate too much to the reader. It's particularly important in an abstract to make sure that your words really count.

Empirical modelling → Empirical Modelling