Boumi, S., & Vela, A. E. (2022, May), Impacts of Students' Academic-Performance Trajectories on their Final Academic Success  Paper presented at 2022 ASEE Zone IV Conference, Vancouver. 10.18260/1-2--44740

\bibitem{asee_peer_44740}
  Boumi, S., \& Vela, A. E. (2022, May), \emph{Impacts of Students' Academic-Performance Trajectories on their Final Academic Success}
  Paper presented at 2022 ASEE Zone IV Conference, Vancouver.
  10.18260/1-2--44740

Shahab Boumi and Adan Ernesto Vela.  "Impacts of Students' Academic-Performance Trajectories on their Final Academic Success".  2022 ASEE Zone IV Conference, Vancouver, 2022, May.  ASEE Conferences, 2022.  https://peer.asee.org/44740 Internet.  14 May, 2024

\bibitem{asee_peer_44740}
  Shahab Boumi and Adan Ernesto Vela.
  "Impacts of Students' Academic-Performance Trajectories on their Final Academic Success".
  \emph{2022 ASEE Zone IV Conference, Vancouver, 2022, May}.
  ASEE Conferences, 2022.
  https://peer.asee.org/44740 Internet.  14 May, 2024

@INPROCEEDINGS{asee_peer_44740
author = "Shahab Boumi and Adan Ernesto Vela"
title = "Impacts of Students' Academic-Performance Trajectories on their Final Academic Success"
booktitle = "2022 ASEE Zone IV Conference"
year = "2022"
month = "May"
address = "Vancouver"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/44740}
number = {10.18260/1-2--44740}
}

TY  - CPAPER
AB  - Many studies in the field of education analytics have identified student grade point averages (GPA) as an important indicator and predictor of students' final academic outcomes (graduate or halt). And while semester-to-semester fluctuations in GPA are considered normal, significant changes in academic performance may warrant more thorough investigation and consideration, particularly with regards to final academic outcomes. However, such an approach is challenging due to the difficulties of representing complex academic trajectories over an academic career. In this full paper, we apply a Hidden Markov Model (HMM) to provide a standard and intuitive classification over students' academic-performance levels, which leads to a compact representation of academic-performance trajectories. Next, we explore the relationship between different academic-performance trajectories and their correspondence to final academic success. Based on student transcript data from University of Central XXX, our proposed HMM is trained using sequences of students' course grades for each semester.  Through the HMM, our analysis follows the expected finding that higher academic performance levels correlate with lower halt rates. However, in this paper, we identify that there exist many scenarios in which both improving or worsening academic-performance trajectories actually correlate to higher graduation rates.  This counter-intuitive finding is made possible through the proposed and developed HMM model.
AU  - Shahab Boumi
AU  - Adan Ernesto Vela
CY  - Vancouver
DA  - 2022/05/12
PB  - ASEE Conferences
TI  - Impacts of Students' Academic-Performance Trajectories on their Final Academic Success
UR  - https://peer.asee.org/44740
DO  - 10.18260/1-2--44740
ER  -