Transcript Resto – Restaurant Menu Helper

Resto
Restaurant Menu Helper
By: Shashank Ranjan, Amlan Pradhan, Rohit Kumar Malik
Problem to be addressed: New international students face
problems and embarrassment in conveying orders at
restaurants
• What is the food item?
• What is it called here?
• How to pronounce it correctly?
Existing Systems
Our Interface
User Study Conditions
• Number of Participants – 33
• Target population- Indian Students studying at
University of Florida
– Frequently visit fast food restaurants around the campus
– Face difficulty with names and pronunciations of food
items
• Comparison against multiple systems
– Users use varied systems to solve this problem
• Study Conditions
– Within subjects/repeated measures
– First explain and rate the existing methods used
– Then use application for a week as many times as desired.
Results and Analysis
• Statistical Test Performed: Correlated Samples T-test
• Primary Hypothesis:
Existing Systems
Resto
Mean
4.5455
8.1515
Standard Deviation
2.49
1.39
–p-value <.0001 – given result is unlikely to change
– t-value = +7.33 – recommendation score for our app are
higher
• Secondary Hypothesis:
Existing Systems
Resto
Mean
5.6364
2.8788
Standard Deviation
3.22
2.50
–p-value = 0.0003 – given result is unlikely to change
– t-value = -3.81 – embarrassment level of our app is lower
Conclusion
• We reject the null hypothesis of our primary
hypothesis
– Our app is as good or better than previous
employed methods for building or conveying
orders at restaurants.
• We reject the null hypothesis of our secondary
hypothesis
– Our app is as or more comfortable to use than
previous methods employed by the users.