Acun Sener, A. C., & Nasraoui , O., & Hieb, J. L. (2019, June), Work in Progress: Finding the Right Questions: Using Data Science to  Close the Loop with Classroom Response Systems  Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--33619

\bibitem{asee_peer_33619}
  Acun Sener, A. C., \& Nasraoui , O., \& Hieb, J. L. (2019, June), \emph{Work in Progress: Finding the Right Questions: Using Data Science to  Close the Loop with Classroom Response Systems}
  Paper presented at 2019 ASEE Annual Conference \& Exposition , Tampa, Florida.
  10.18260/1-2--33619

Asuman Cagla Acun Sener, Olfa Nasraoui , and Jeffrey Lloyd Hieb.  "Work in Progress: Finding the Right Questions: Using Data Science to  Close the Loop with Classroom Response Systems".  2019 ASEE Annual Conference & Exposition , Tampa, Florida, 2019, June.  ASEE Conferences, 2019.  https://strategy.asee.org/33619 Internet.  07 Jun, 2024

\bibitem{asee_peer_33619}
  Asuman Cagla Acun Sener, Olfa Nasraoui , and Jeffrey Lloyd Hieb.
  "Work in Progress: Finding the Right Questions: Using Data Science to  Close the Loop with Classroom Response Systems".
  \emph{2019 ASEE Annual Conference \& Exposition , Tampa, Florida, 2019, June}.
  ASEE Conferences, 2019.
  https://strategy.asee.org/33619 Internet.  07 Jun, 2024

@INPROCEEDINGS{asee_peer_33619
author = "Asuman Cagla Acun Sener, Olfa Nasraoui , and Jeffrey Lloyd Hieb"
title = "Work in Progress: Finding the Right Questions: Using Data Science to  Close the Loop with Classroom Response Systems"
booktitle = "2019 ASEE Annual Conference \& Exposition "
year = "2019"
month = "June"
address = "Tampa, Florida"
publisher = "ASEE Conferences"
note = {https://strategy.asee.org/33619}
number = {10.18260/1-2--33619}
}

TY  - CPAPER
AB  - This is a work in progress paper.  Classroom response systems (CRS) are educational technology tools that when paired with an appropriate pedagogy, provide increased classroom engagement in support improved teaching and learning.  They do this by leveraging technology to allow every student to respond to instructor posed questions. Many of these systems, such as Learning Catalytics and clickers, collect and store a wealth of individual student response data that is aggregated to provide instructors with real time student response data. One open challenge in this setting is how to glean insights from all of the the collected response data to identify activities, specific questions, and combinations of questions that associate with student performance. A data driven analysis of student response data collected by a CRS combined with student performance data will enable individual instructors to refine and adapt their use of a CRS, thus closing the loop from an instructional design perspective.  This paper presents a data science methodology and preliminary results of analyzing CRS data accumulated from daily activities in two sections of an engineering mathematics course.  The data is collected from the CRS Learning Catalytics where students respond to questions in two rounds following the team-based learning model. In the first round, students answer questions individual; in the second round, they answer the same questions as a team after reviewing each other’s answers from round 1. The CRS stores each student’s responses from both rounds along with a timestamp. This study serves two purposes, 1) examine the effect of disagreement between individual responses on student performance  and 2)  identify which activity question scores, individual versus team-based,  are associated with better exam performance, thus allowing the reduction of the number of questions. Using a  methodology based on data mining and data exploration, we found three trends between round 1 and round 2 scores: students who have no score change in both rounds, students who increase their scores, and student who decrease their scores after the team-based collaboration. Our plan is  to cluster class activity questions depending on the predicted performance, thus paving the way toward an improved data driven design of in class activities. 
AU  - Asuman Cagla Acun Sener
AU  - Olfa Nasraoui 
AU  - Jeffrey Lloyd Hieb
CY  - Tampa, Florida
DA  - 2019/06/15
PB  - ASEE Conferences
TI  - Work in Progress: Finding the Right Questions: Using Data Science to  Close the Loop with Classroom Response Systems
UR  - https://strategy.asee.org/33619
DO  - 10.18260/1-2--33619
ER  -