Resto Restaurant Menu Helper By: Shashank Ranjan, Amlan Pradhan, Rohit Kumar Malik Problem to be addressed: New international students face problems and.

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Presentation transcript:

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: – p-value <.0001 – given result is unlikely to change – t-value = – recommendation score for our app are higher Secondary Hypothesis: – p-value = – given result is unlikely to change – t-value = – embarrassment level of our app is lower Existing SystemsResto Mean Standard Deviation Existing SystemsResto Mean Standard Deviation

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.