Please make sure that you bring the following documents with you when you come to attend the
National Fair:

• Project Data Book – all the data that you have collected during your project research.
• Log book
• Project Synopsis
• Research Paper (if any)
• This letter with your project code on it.

Feedback from the Scientific Review Committee (SRC)

The SRC has gone through each submission carefully. We hope that the information will help you highlight the important aspects of your project, and also make the evaluation process easier for both you as well as the judging team at IRIS 2007.
Further, we would also like to inform you about the judging process at the National Fair, and what judges are looking for when they see your project and interview you. Do go through this list as well, as it will help you understand how we evaluate research-based projects, and the importance of having the appropriate supporting materials with you.

The SRC feedback is as follows:

Do check to see if your project contains any of these common misconception/ errors and discuss them with your guide as well.

1. “Internet science”: While the internet is a great resource for all sorts of information, and science project related information in particular, one has to be cautious of the veracity of what’s available on the web. In particular, there is a trend of “I saw this on the net, and hence this must be correct”. Further, there is also clearly a widespread use of the copy-and-paste method of writing reports, without understanding what is really been copied, or without bothering to change the context, grammar, etc. of the paragraph! Judges are usually smart enough to figure out if you have copied something!
2. “Significant digits”: There is poor appreciation of the importance and relevance of significant digits, experimental accuracy and errors, and the correct treatment of data. This includes
• Having results with too many digits beyond the decimal point (often upto the 9th decimal place because the calculator said so!) For example, if you are making measurements using a ruler where the least count is a millimeter, and have reading of 5.3, 5.5 and 5.2, the average is 5.3, and not 5.3333333 etc. Similarly, when using software like Microsoft Excel, be sure that you do not have extra digits which are not meaningful
• Making unwarranted conclusions based on such data (eg. if the average values of some quantities A, B, C are say 185.4, 186.7 and 120.5, it is perhaps OK to say that A and B were better than C, but one can’t say B is better than A, especially if the individual variations in data points are more than the difference between A&B)
3. “Be scientific”: The use of proper (preferably SI) units is a must! (Please note that the symbol for grams is g, not gm or gms!), similarly, please use scientific units - weights in g, not in teaspoons, etc., saying things like ‘I stirred it for “some time,”’ is not acceptable.
4. “V, not I”: For many of the electricity generation / conservation / use experiments there are measurements only of voltage, with no consideration for current. It is very easy to generate (even large) voltages, particular in open circuit conditions, but the key parameter is how much current can be generated (even the measurement of short circuit current, if not under load). Many projects particularly those with solar cells, or other electricity generation methods are in this category.
5. “Statistics and controls”: In many cases, just doing an experiment once is not sufficient to draw solid conclusions; you may need to repeat your experiments. Also, in most cases, appropriate positive and negative control experiments are necessary – e.g., if you have used an alcohol extract of some plant as a (say) insecticide, then you must see if alcohol alone has the same effect. Also, in many cases one needs to perform appropriate statistical tests to see if the data is meaningful.
6. “Practicality”: some ideas sound nice, but a good reality check on how practical (feasibility, costs, efficiency, etc.) will it be, particularly if it has to be useful under life-like conditions. E.g., if you are generating electricity from potatoes – how much would you need to generate say at least a few amperes of current at 12V.
7. “Know your instruments”: If you are using any instruments to gather data – e.g. a lactometer to check milk quality or a device to measure wind speed, you must have some basic idea of how it works, and the limits to which it can be used. Otherwise it just gives a number, which means nothing.
8. “References”: Usually similar work would have been carried out earlier in related areas, and it is important that you show that you have made efforts to find out about such earlier work, and reference it. This way it is easier to show what the novel aspect of your work is!

1. What YOU, the student or team did in the project;
2. How well you followed the scientific methodologies;
3. The detail and accuracy of research as documented in the data book;
4. Whether experimental procedures were used in the best possible way. We are always looking out for innovative ideas, original work, well thought-out research and scientific or engineering skill.

Remember that most people read from left to right and from top to bottom. Design what the "center" of your display will be. This is where everyone will look first. Group topics that go together like question, research, and hypothesis; materials and procedures; analysis and conclusion. Make a small sketch of where everything will go and lay it out before you glue anything down to make sure it looks good. (If needed, please number your panels, so that the logical sequence of going through the panels is clear even if you are not physically present to guide the viewer.)

Do make sure that all items that are displayed are permissible as per the display guidelines in the IRIS handbook. Basically, anything that is or could be hazardous to other participants or the public is prohibited and cannot be displayed. NO HEATERS or STOVES will be allowed. ALL electrical appliances MUST have plugs; projects having bare wires inserted into sockets will be disqualified.

If your work involves working with human subjects, consent forms must have been obtained prior to experimentation, and should be available in case needed. Similarly, any work involving living organisms, human/animal tissues, DNA etc. must have the appropriate documentation if required.

In most cases, similar work would have been carried out earlier in related areas, and it is important that these be appropriately referenced. Ideally, paper or electronic copies of some key references should be available in case these are needed to be referred to.

PRACTICE your presentation! Remember that most judges will spend only about 5-10 minutes with you, where they would like to focus mostly on what you have done, rather than the background of the problem, and have enough time to ask you questions and have a discussion. So do not come with a “memorized speech”, with a long introduction, but be prepared to explain what you have done in your project in as short or long as a time that may be available. Practice with your friends and encourage them to ask questions.

Maybe it will help to give some ideas of what judges look for while going through a project:

1. Clearly defined objectives – what did you want to do, and how did you go about doing it? (Presenting original ideas, stating the problem clearly, defining the variables and using controls, relating background reading to the problem)

2. Skill in performing the project – (knowledgeable about equipment used, Performing the experiments with little or no assistance except as required for safety/special equipment/data collection, Demonstrating the skills required to do all the work necessary to obtain the data reported… )

3. Appropriate data collection – (using a log-book and journal to collect data and document research, Repeating experiment to verify the results, Spending an appropriate amount of time to complete the project, Having measurable results, appropriate control experiments etc.)

4. Correct data interpretation – (collecting enough data to make a conclusion, Using research to interpret data collected, Using only data collected to make a conclusion, Using tables, graphs etc. to visualize the data easily…)

5. Project Presentation – (Written Materials, Interviews, Displays) (Having a complete and comprehensive report, Answering questions accurately, Using the display during oral presentation, Justifying conclusions on the basis of experimental data, Summarizing what was learned, Presenting an attractive and interesting display…)