Difference between revisions of "Team:Valencia UPV/Human Practices"

Kano Model

Kano model is a methodology, which supports the development of products taking into account the needs of the customer. It helps you to understand the importance of functions or features to a customer[1]. We have used it to improve Printeria and we want it to be a guide for future iGEM teams, thats why we are going to present our work as an example of using it.

Kano model is made up of three stages:

1. Pick up the user's voice

   In this phase you have to present your project to an audience and then ask them for criticisms or suggestions. We did it in the Mustang Art Gallery (MAG) in Elche (Alicante). After showing them Printeria we gathered all the students and teachers and we asked them for demands, improvements or criticisms.

2. Create your paired questions quiz

   With those demands that we will call necessities you have to make a questionaire based on paired questions. This questions have the next grammar: ¿How do you feel if (a necessity exists on your device)? and ¿How do you feel if (that necessity did not exist on your device)? As you can observe, it is the same necessity but expressed positively or negatively. Check out our questionnaire to see an example:

   QUESTIONNAIRE

3. Classify your demands

   Once you have all the answers, you have to complete a series of tables to conclude if that necessity is really important or not. If it is, you should include it in your design because that will increase the satisfaction rate of the user. If it is not, do not waste time and money implementing something no one will appreciate!

Study case: Kano model in Printeria

When using the Kano model you can easily combine public engagement with integrated human. Taking advantage of the fact that we went to MAG (Mustang Art Gallery) in Elche (Alicante) to present our project in front of students and teachers, we decided to demand feedback. The most important necessities were included in the questionnaire we described above, and then we sent it to the students and teachers who filled it. The questionnaire and the results are available by clicking in the button "questionnaire".

Once we had the answers (more than 20 to be representative), we filled the different tables which compose Kano model to obtain the results. Here you can download the document with the tables and what is most important, the conclusions we extracted from them:

Overall conclusions

Last but not least, a table summarizing why Kano model is important and should be implemented in future iGEM projects.

Table 1. Conclusions of Kano model use in Printeria.

Kano model results conclusions
Kano model is an strong tool to include feedback in your project
Kano model rank needs by customer/user satisfaction
Kano model prevents wasting money and time implementing unnecessary needs
Kano model allows you to combine public engagement and integrated practices
Kano model allows you to explain why something was designed or not

Expert feedback

A very good way to enrich the project through feedback is to do so by consulting experts in the field of study as has been done previously in iGEM. Their opinion is really relevant because of the reputation that precedes them, and that adds value to the product/project.

That is why we have decided to contact renowned artists and sciencists from the world of bioart and biotecnology to present them our project and seek advice. Next section describes who we have reached out and how their opinions have changed Printeria.

María Peñil & Mehmet Berkmen

María Peñil Cobo is a Spanish mixed media artist born in San Vicente de la Barquera. She studied fine arts and has a master in art education. To do her masterpieces she works with natural media like bacteria.

Dr. Mehmet Berkmen is a Turkish-born international microbiologist. Nowadays he is a Senior sciencist at NEB working on genetically engineering bacteria to produce proteins.

As you can see above María Peñil and Mehmet Berkmen are coworkers in NEB Biolabs Boston. Together, they are dedicated to making bioart with bacteria grown in agar, which fascinated us. They are what printeria represents, art and science connected, so we wanted to contact them and expose our project as well as ask for advice. The results of the interview can be seen in this document:

Interview conclusions were:

• It is difficult for artists to get in touch with scientists. Maria and Memo met by coincidence.

  In this aspect, Printeria could help to approach artists to scientists.

• Presevation of bioart plates is one of the biggest problems. The best way to preserve them is leaving the plates in the fridge. But using epoxy or other resins can help preservation.

  We leave them on the fridge and we are trying to fix them by using transparent nail polish.

• Consider working by layers when working with different types of bacteria. The slow growers should go first and after growing them, fast growers should be added.

  As we are only working with E. coli, we are having no problems. But this piece of advice should be taken into account if Printeria ends up using other different chassis than just E. coli strains.

• They don’t create their own GM microorganisms, so they think Printeria could be a useful machine to do so. Memo encourages us to write a manuscript out of this, even if the machine does not totally work. This could make people start using it so that Printeria could evolve.

  The idea of doing a manuscript caught our eyes and we are planning to do so. It also made us think about creating the ‘Printeria user manual’ as well as an activity booklet for the user to learn even more about SynBio.

• Do not only focus on creating colourful bacteria but on stand-alone scent pathways.

  We achieved to create mint scented E.coli but we will continue doing some research in stand-alone scent pathways.

• For doing bioart, just try different techniques: using glass beads, pipetting liquid cultures, using sowing handles.

  We knew nothing about bioart and, thanks to Maria and Memo, we started developing our skills to quickly learn the basics about this type of art. We used the pipetting method to create Yturralde’s living art and the sowing handles for creating Printeria’s logo and for letting students create their own masterpieces in MAG.

• Memo thinks Printeria is a nice multidisciplinary project. He encourages us to show who we are, and the way we learnt to speak a common language in which biotechnologists, engineers, designers and informatics, understood each other.

  It is very important for people to know that Printeria is more than just a biotechnological project. It is a machine in which lots of different disciplines worked together with a single goal. And this piece of advice really helped us while creating our poster and while planning our Giant Jamboree’s presentation.

• It could be graeat for people to touch Printeria. Take it to Boston and try to do a live performance during the Jamboree. This will influence the judges a lot.

  Printeria was built to be as easy as a lego toy, so that anyone can assemble it. This fact will make Printeria perfect to travel to Boston and, of course, to perform public demonstrations there.

Francis Mojica

Dr. Francisco Juan Martínez Mojica is a microbiologist, researcher and professor at the University of Alicante. He is the discoverer of the CRISPR-Cas systems whose application would later be researched by Emmanuelle Charpentier and Jennifer Doudna among others.

In Spain, he is one of the most reputable researchers and as such, his opinion and advice are worth their price in gold. Mojica accepted our invitation for a personal interview in which we would present the project and ask him for advice. The interview was carried out by Carolina Ropero, member of the Printeria team. In the following button you will be able to read the whole interview:

Interview conclusions were:

• Mojica agrees that with Printeria the automation of Printeria decreases the experimental error. However, he warned us about the importance of being aware of the decisions to make, even if a device such Printeria is able to do all the process by itself.

  To avoid the user lack of awareness, we decided to develop a Simulation tool, so the user could simulate the experiments in silico. Thus, this functionality provides the user with a quantitative, mathematical description to ensure the rational decision making.

• He believes that, from the education point of view, the automation is detrimental to the observation. He also pointed out the necessity of training the teaching stuff, as they are not often used to SynBio.

  In order to ensure the students understanding of the biology that is behind each step, we decided to develop a Printeria basic user-guide. Moreover, we implemented recipes in our software tool. Recipes are already pre-defined experiments that include an easy ID name such as “pink colour”, so in this way the most basic user can understand what he/she is printing and so the biological reason of the final result.

• Biosafety measures are completely necessary to ensure Printeria introduction in non-scientific environments.

  We realized it was necessary to improve our safety measurements. Mojica advised us the use of UV light filters as bacterial-killer, which were positively integrated into Printeria final design.

• He advised us to be aware about the vocabulary used to divulgue science, as it needs to be technically correct but close and safe enough for the lay public to listen to you.

  This, along with the bioartist expert feedback, gave us the idea to use a non-usual approach to divulgue SynBio into the lay-public. As a consequence, Printeria promotion among society was carried out by including the BioArt as the main attraction to get to the public.

José María Yturralde

Yturralde has a bachelor's degree and a PhD in fine arts awarded by the Polytechnic University of Valencia (UPV). Furthermore he has been researcher in the MIT among other great things. Between 1968 and 1973 he developed his work "Impossible figures". These figures are really interesting because they show us how our space perception works, they seem coherent at first glance but when you observe them in more detail you see there are inconsistent details.