Thesis Proposal VARUN GUPTA 1. Thesis Proposal VARUN GUPTA 2.
P.D.A.T. (Piazza Data Analysis Tool) by Varun Agarwal and...
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P.D.A.T. (Piazza Data Analysis Tool) by Varun Agarwal and Aashish Lalani Co-Advised By Swapneel Sheth, Arvind Bhusnurmath, Benedict Brown Introduction P.D.A.T is a tool to be used to analyze student/TA behavior in classes with available piazza data. Our objective was to create an application that can be used by professors and teachers to improve class experience in the future. We developed a set of hypothesis to study and research with the available data. We analyzed CIS110 data with certain statistical models in mind. P.D.A.T can take raw piazza data and produce datasets that helped us in our study and can be used in the future by others. . • Perform statistical evaluations on more hypothesis which involve more data sources such as “Higher Attendance in Office Hours leads to higher grades”. • Tool can be used by students and teachers for improvement of classes since it is generic to any class with available Piazza data. Future Work Initial User Interface The XML Format The CSV Database Sample Output Graphs New TAs answer more questions on average! However certain returning TAs answer more than everyone! (Head TAs?) Solution? Engage old TAs! Do New TAs answer more posts than old TAs? Does number of posts spike during class milestones (exams and homework deadlines)? Yes! Posts spike 150% or more on milestone days! Solution? Give more TAs piazza duty on these days! Do a few students answer all the questions? Inequality between number of answers is greater than income inequality in the country! By when can you expect an answer? A day at most? 0 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 Number of TAs who Answered X Questions Number of Questions Answered by Y TAs Answering Behavior Between Old and New TAs Returning TAs New TAs Gamma-Poisson distribution used to account for heterogeneity in TA Behavior Mid term d ate Homework Due Number of piazza posts on given day D ates o f semester in Ch ro n o lo g ical o rd er Acquire piazza data in CSV and xml format Choose appropriate hypothesis from the UI Provide data dump to selected option App will produce database in the background and export it as CSV file App performs statistical evaluation Output is printed to screen and graphs are displayed Time for response Cumulative % of students/TA’s ;, =) () ,-.//-0(1) 2 , 1− 56776 : ;
Transcript of P.D.A.T. (Piazza Data Analysis Tool) by Varun Agarwal and...
P.D.A.T. (Piazza Data Analysis Tool)by Varun Agarwal and Aashish Lalani
Co-Advised By Swapneel Sheth, Arvind Bhusnurmath, Benedict BrownIntroduction
P.D.A.T is a tool to be used to analyze student/TA behavior in classes with available piazza data. Our objective was to create an application that can be used by professors and teachers to improve class experience in the future. We developed a set of hypothesis to study and research with the available data.We analyzed CIS110 data with certain statistical models in mind. P.D.A.T can take raw piazza data and produce datasets that helped us in our study and can be used in the future by others..
• Perform statistical evaluations on more hypothesis which involve more data sources such as “Higher Attendance in Office Hours leads to higher grades”.
• Tool can be used by students and teachers for improvement of classes since it is generic to any class with available Piazza data.
Future Work
Initial User Interface
The XML Format
The CSV Database
Sample Output Graphs
New TAs answer more questions on average! However certain returning TAs answer more than everyone! (Head TAs?) Solution?
Engage old TAs!
Do New TAs answer more posts than old TAs?
Does number of posts spike during class milestones (exams and homework deadlines)?
Yes! Posts spike 150% or more on milestone days! Solution? Give more TAs piazza duty on these days!
Do a few students answer all the questions?
Inequality between number of answers is greater than income inequality in the country!
By when can you expect an answer?
A day at most?
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Num
ber o
f TA
s w
ho A
nsw
ered
X Q
uest
ions
Number of Questions Answered by Y TAs
Answering Behavior Between Old and New TAs
Returning TAs New TAs
Gamma-Poisson distribution used to account for heterogeneity in TA Behavior
Midterm dateHomework Due
Num
ber o
f piaz
za p
osts
on g
iven
day
Dates of semester in Chronological order
Acquire piazza data in CSV and xml format
Choose appropriate hypothesis from the UI
Provide data dump to selected option
App will produce database in the background and export it as CSV file
App performs statistical evaluation
Output is printed to screen and graphs are displayed
Time for response
Cumulative % of students/TA’s
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1 − 𝑝𝑝56776
𝜆 𝑑𝜆
:
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