Team:Marburg:Policy Practices:iGEM Quiz
From 2014.igem.org
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- | + | Policy and Practices is an important part of the iGEM competition and we want to expand the world's knowledge of Synthetic Biology. | |
- | During | + | During discussion with people visiting our booth at <html><a href="https://2014.igem.org/Team:Marburg:Policy_Practices:Hessentag"> |
- | "Drei-Tage-Marburg" and "Hessentag"</a></html> we discovered a | + | "Drei-Tage-Marburg" and "Hessentag"</a></html> we discovered a significant lack of knowledge in this field. In particular, gene technology is not |
- | part of the common knowledge | + | part of the common knowledge; however, we were able to answer a lot of questions about it. We strongly believe in the importance of spreading knowledge |
- | + | of Synthetic Biology, as this relatively young area of research will have impact on our lives, and much remains to be discovered. Since we could only reach a small number of people during these events, we decided to go online and create an application available to all common platforms. We are thereby able to reach a much wider audience, including a variety of ages to fill those gaps in common knowledge. | |
- | + | ||
- | application available | + | |
- | gaps in common knowledge. | + | |
- | + | To present the information in a playful way we chose a quiz style app instead of just a non-interactive learning platform. | |
- | This quiz enables us | + | This quiz enables us to precisely check for knowledge in specific areas. In order to get an overview of the users’ level |
- | of knowledge we integrated an interaction between our app and our server by collecting the users answers anonymously. With the | + | of knowledge we integrated an interaction between our app and our server by collecting the users' answers anonymously. With the |
help of the collected data we are not only able to adapt our quiz depending on the given answers but also to perform statistical | help of the collected data we are not only able to adapt our quiz depending on the given answers but also to perform statistical | ||
analyses. Our system is completely extendible by submitting new questions at any time. | analyses. Our system is completely extendible by submitting new questions at any time. | ||
- | In addition to the regular quiz we integrated the “Game of | + | In addition to the regular quiz we integrated the “Game of GenEthics”. This part of the app is not about wrong or right answers |
- | but how the users | + | but about how the users react to controversial decisions of real biotechnological applications. Because biotechnology works by altering the genetic code of organisms, bioethics is an important topic to consider when discussing ethical boundaries. |
- | by altering | + | |
- | By | + | By integrating an online high-score system for every participant, we aimed to draw more attention towards the game and to |
- | add a competitive aspect. Depending on the difficulty of | + | add a competitive aspect. Depending on the difficulty and amount of time the user needs to answer the questions, he earns more or less points. These points will be added to points gained from the quiz in order to calculate one total high score. The best players will be able to win a |
- | earns more or less points. | + | |
special price in the end. | special price in the end. | ||
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<img src="https://static.igem.org/mediawiki/2014/b/b5/MR_app_01.png" alt="" /> | <img src="https://static.igem.org/mediawiki/2014/b/b5/MR_app_01.png" alt="" /> | ||
<span class="caption"> | <span class="caption"> | ||
- | Screenshots of the home screen and some example questions from the "greenhorn" category. | + | <b>Screenshots of the home screen and some example questions from the "greenhorn" category.</b> |
</span> | </span> | ||
<br /> | <br /> | ||
<img src="https://static.igem.org/mediawiki/2014/9/93/MR_app_02.png" alt="" /> | <img src="https://static.igem.org/mediawiki/2014/9/93/MR_app_02.png" alt="" /> | ||
<span class="caption"> | <span class="caption"> | ||
- | Screetshots from the "Game of Genethics" | + | <b>Screetshots from the "Game of Genethics".</b> |
</span> | </span> | ||
</div> | </div> | ||
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<html><h2><a name="results">Results</a></h2></html> | <html><h2><a name="results">Results</a></h2></html> | ||
- | The following results are based on data collected during a period of two months. We | + | The following results are based on data collected during a period of two months. We analyzed over 13.000 responses given by users |
- | from around the globe. We are able to correlate the datasets with gender, age, relation to the field of | + | from around the globe. We are able to correlate the datasets with gender, age, relation to the field of Synthetic Biology and |
participation in the iGEM competition, assuming that every user entered honest information. | participation in the iGEM competition, assuming that every user entered honest information. | ||
- | Besides expected outcomes like correlation between contact with synthetic biology and right answers in the first round, we found | + | Besides expected outcomes, like correlation between contact with synthetic biology and right answers in the first round, we found |
- | some surprising results. | + | some surprising results. The most encouraging unexpected result was the strong increase in the learning curve of users without iGEM participation compared |
- | + | ||
- | The most encouraging unexpected result was the strong increase in the learning curve of users without iGEM participation compared | + | |
to participants. | to participants. | ||
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<img src="https://static.igem.org/mediawiki/2014/0/0d/Mr_igem_quiz.png" alt="" /> | <img src="https://static.igem.org/mediawiki/2014/0/0d/Mr_igem_quiz.png" alt="" /> | ||
<span class="caption"> | <span class="caption"> | ||
- | + | <b>Right answers after two attempts.</b> | |
</span> | </span> | ||
</div> | </div> | ||
</html> | </html> | ||
- | In the second attempt the users without an iGEM background were able to memorize most of the questions, increasing their | + | In the second attempt the users without an iGEM background were able to memorize most of the questions, increasing their percentage of right answers from 65.8% to fantastic 90.7%, while the participants’ learning curve just increased by 2.6% (from 70.2% to 72.8%). |
- | Altogether we can confirm a strong increase of right answers in the second approach. | + | Altogether, we can confirm a strong increase of right answers in the second approach. Therefore, we are able to verify the success of our app towards our goal to teach synthetic biology to a broad audience. |
- | The following questions are the top five | + | The following questions are the top five correctly answered ones, with rates of positive answers over 90%... |
# What are the components of proteins? | # What are the components of proteins? | ||
- | # What is Escherichia coli? | + | # What is <i>Escherichia coli</i>? |
# What is a Dalton? | # What is a Dalton? | ||
# What is green Biotechnology? | # What is green Biotechnology? | ||
# What does PCR stand for? | # What does PCR stand for? | ||
- | ...do you also know the | + | ...do you also know the answers? |
<html><center> | <html><center> |
Latest revision as of 02:45, 18 October 2014
iGEM Quiz Marburg
Policy and Practices is an important part of the iGEM competition and we want to expand the world's knowledge of Synthetic Biology. During discussion with people visiting our booth at "Drei-Tage-Marburg" and "Hessentag" we discovered a significant lack of knowledge in this field. In particular, gene technology is not part of the common knowledge; however, we were able to answer a lot of questions about it. We strongly believe in the importance of spreading knowledge of Synthetic Biology, as this relatively young area of research will have impact on our lives, and much remains to be discovered. Since we could only reach a small number of people during these events, we decided to go online and create an application available to all common platforms. We are thereby able to reach a much wider audience, including a variety of ages to fill those gaps in common knowledge.
To present the information in a playful way we chose a quiz style app instead of just a non-interactive learning platform. This quiz enables us to precisely check for knowledge in specific areas. In order to get an overview of the users’ level of knowledge we integrated an interaction between our app and our server by collecting the users' answers anonymously. With the help of the collected data we are not only able to adapt our quiz depending on the given answers but also to perform statistical analyses. Our system is completely extendible by submitting new questions at any time.
In addition to the regular quiz we integrated the “Game of GenEthics”. This part of the app is not about wrong or right answers but about how the users react to controversial decisions of real biotechnological applications. Because biotechnology works by altering the genetic code of organisms, bioethics is an important topic to consider when discussing ethical boundaries.
By integrating an online high-score system for every participant, we aimed to draw more attention towards the game and to add a competitive aspect. Depending on the difficulty and amount of time the user needs to answer the questions, he earns more or less points. These points will be added to points gained from the quiz in order to calculate one total high score. The best players will be able to win a special price in the end.
Results
The following results are based on data collected during a period of two months. We analyzed over 13.000 responses given by users from around the globe. We are able to correlate the datasets with gender, age, relation to the field of Synthetic Biology and participation in the iGEM competition, assuming that every user entered honest information.
Besides expected outcomes, like correlation between contact with synthetic biology and right answers in the first round, we found some surprising results. The most encouraging unexpected result was the strong increase in the learning curve of users without iGEM participation compared to participants.
In the second attempt the users without an iGEM background were able to memorize most of the questions, increasing their percentage of right answers from 65.8% to fantastic 90.7%, while the participants’ learning curve just increased by 2.6% (from 70.2% to 72.8%).
Altogether, we can confirm a strong increase of right answers in the second approach. Therefore, we are able to verify the success of our app towards our goal to teach synthetic biology to a broad audience.
The following questions are the top five correctly answered ones, with rates of positive answers over 90%...
- What are the components of proteins?
- What is Escherichia coli?
- What is a Dalton?
- What is green Biotechnology?
- What does PCR stand for?
...do you also know the answers?