George, R. (2019, June), Predictors for Success in Calculus I  Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--33184

\bibitem{asee_peer_33184}
  George, R. (2019, June), \emph{Predictors for Success in Calculus I}
  Paper presented at 2019 ASEE Annual Conference \& Exposition , Tampa, Florida.
  10.18260/1-2--33184

Rebecca  George.  "Predictors for Success in Calculus I".  2019 ASEE Annual Conference & Exposition , Tampa, Florida, 2019, June.  ASEE Conferences, 2019.  https://peer.asee.org/33184 Internet.  05 Feb, 2025

\bibitem{asee_peer_33184}
  Rebecca  George.
  "Predictors for Success in Calculus I".
  \emph{2019 ASEE Annual Conference \& Exposition , Tampa, Florida, 2019, June}.
  ASEE Conferences, 2019.
  https://peer.asee.org/33184 Internet.  05 Feb, 2025

@INPROCEEDINGS{asee_peer_33184
author = "Rebecca  George"
title = "Predictors for Success in Calculus I"
booktitle = "2019 ASEE Annual Conference \& Exposition "
year = "2019"
month = "June"
address = "Tampa, Florida"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/33184}
number = {10.18260/1-2--33184}
}

TY  - CPAPER
AB  - 
Rebecca George

Abstract:
“What are the factors for success for students in calculus 1?” Because calculus 1 is considered a gateway course in most STEM majors, this is a common question among universities as attrition rates of students in these majors is considered high.
This paper explores the use of different statistical approaches to analyzing data on students who have taken calculus 1 at a large research extensive university. Hierarchal Linear Modeling (HLM) analysis will be used in determining if the class attributes of different sections determine the success of students in calculus 1 in college. HLM analyses will be used because students are nested within each class, or section. Another model involving the mediation variable of anxiety level will be explored. Lastly, a multivariate model will be used to examine relationships between all factors.
For all models, the dependent variable is student grade in calculus 1. In the HLM model, the level one factors are student academic level, gender, whether the student attended on cam- pus tutoring, and whether the student is a STEM major (or more specifically an Engineering major). The level two factors come from the students’ class section and include whether the section is online or face-to-face (mode of instruction), the semester (Fall vs. Spring), the size of the class, and the instructor’s gender.
Keywords: calculus, student success, statistical analysis

AU  - Rebecca  George
CY  - Tampa, Florida
DA  - 2019/06/15
PB  - ASEE Conferences
TI  - Predictors for Success in Calculus I
UR  - https://peer.asee.org/33184
DO  - 10.18260/1-2--33184
ER  -