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This study is being conducted by the Intelligent Interactive Systems Group at Harvard University.
How good is your nutrition knowledge?
Can you tell just by looking at a meal whether it is a significant source of protein, fat, or carbohydrates?
Find out for yourself and compare your performance to others!
This test typically takes 6 minutes to complete.
This study is being conducted by the Intelligent Interactive Systems Group at Harvard University.
Please read the following information carefully before proceeding.
Why we are doing this research: We are trying to understand how to design online quizzes such that they help people learn useful knowledge in the process.
What you will be asked to do: You will be presented with a series of pictures of meals. For each you will be asked a nutrition-related question. At the end of the study you will be able to compare your performance to that of others. Your participation in this study is completely voluntary, and you may refuse to participate or withdraw from the study without penalty or loss of benefits to which you may otherwise be entitled.
Potential risks: There are no risks anticipated in taking part in this study and you are free to leave at any time without penalty or loss of benefits to which you are otherwise entitled.
Privacy: Your responses will be kept anonymous. We do not collect any information that could be used to directly establish your identity.
Duration: Approximately 10 minutes.
To contact the researcher: If you have questions or concerns about this research, please contact Prof. Krzysztof Gajos, kgajos@seas.harvard.edu.
Whom to contact about your rights in this research, for questions, concerns, suggestions, or complaints that are not being addressed by the researcher, or research-related harm: Committee on the Use of Human Subjects in Research at Harvard University, phone: 617-496-2847. Email: cuhs@harvard.edu
Please print or save a copy of this page for your records.
We want to understand how to design short (less than 30 minutes) online activities such that they are simultaneously intrinsically interesting to people and educationally valuable. For example, can we design online questionnaires such that they are scientifically valuable to the researchers, entertaining to the participants, and result in participants learning something valuable in the process?
The main aim of this study is to design and evaluate a series of micro-learning interventions and measure whether they result in at least short-term learning gains.
We are building on two strands of prior work. 1) Education research on feedback during instruction (e.g., Hattie, J., & Gan, M. (2011). Instruction based on feedback.) and 2) Recent research on pedagogical interventions in crowdsourcing tasks (e.g., Zhu, H., Dow, S. P., Kraut, R. E., & Kittur, A. (2014). Reviewing versus doing: learning and performance in crowd assessment. Presented at the CSCW '14: Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing, ACM Press).
We will not record a link between your Amazon Mechanical Turk ID and any information that you provide during the study. We will, however, have a record indicating that your Amazon Mechanical Turk ID participated in this study.
Efforts will be made to limit the use and disclosure of your Personal Information, including the fact that you participated in this study, to people who have a need to review this information. We cannot promise complete secrecy. Organizations that may inspect and copy your information include the IRB and other representatives of this organization.
The anonymous data collected during this study could be used for future research studies, distributed to another investigator for future research studies, or shared in public research data repositories without your additional informed consent.
By clicking the "I agree" button you confirm that you have read and understood the above and agree to take part in this research. Your participation is voluntary and you are free to leave the experiment at any time by simply closing the web browser.
You will be presented with pairs of photographs of meals. For each, we will ask you a nutrition-related question like this:
Please pay attention to the description below each image. It is often hard to see all the ingredients in the photograph. The descriptions will help you figure out what the main ingredients of the meal are.
Your job is to answer the questions as accurately as possible. For some of them (but not all), we will give you immediate feedback on your answer. At the end of the study, we will tell you how well you did and how your score compared to others.
Sometimes, you will see a recommendation from a Meal Assistant, which is an experimental computer system that can analyze the nutritional content of meals. The Meal Assistant is right most of the time but not always. You are welcome to consider its recommendations, but you should make whatever decision you think is best.
Sometimes, after you make your initial choice you will see a recommendation from a Meal Assistant, which is an experimental computer system that can analyze the nutritional content of meals. You will have the option to revise your decision. The Meal Assistant is right most of the time but not always. You are welcome to consider its recommendations, but you should make whatever decision you think is best.
Sometimes, you will see a recommendation from a Meal Assistant, which is an experimental computer system that can analyze the nutritional content of meals. The Meal Assistant is right most of the time but not always. You are welcome to consider its recommendations, but you should make whatever decision you think is best.
If you you click the "View Meal Assistant's recommendation" button, a recommendation like this will be shown:
Sometimes, you will see relevant information from a Meal Assistant, which is an experimental computer system that can analyze the nutritional content of meals. The Meal Assistant is right most of the time but not always. You are welcome to consider the information it provides, but you should make whatever decision you think is best.
Sometimes, you will see relevant information or a recommendation from a Meal Assistant, which is an experimental computer system that can analyze the nutritional content of meals. The Meal Assistant is right most of the time but not always. You are welcome to consider the information it provides, but you should make whatever decision you think is best.
I am confident this is the right answer
I am confident this is the right answer
Please enter it on the Amazon Mechanical Turk form as a proof that you completed this study.
According to our expert nutritionist, you got questions correct. Others, on average, got questions correct.
Here are your results presented separately for each macronutrient:
| Carbohydrates | |
|---|---|
| Protein | |
| Fat | |
| Fiber |
If so...
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If you have any additional thoughts you'd like to share about this test, please email kgajos@eecs.harvard.edu.
Thank you for your participation!
Before we continue to the results, please answer the following two questions: