English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Many studies in the field of education analytics have identified studentgrade point averages (GPA) as an important indicator and predictor of students'final academic outcomes (graduate or halt). And while semester-to-semesterfluctuations in GPA are considered normal, significant changes in academicperformance may warrant more thorough investigation and consideration,particularly with regards to final academic outcomes. However, such an approachis challenging due to the difficulties of representing complex academictrajectories over an academic career. In this study, we apply a Hidden MarkovModel (HMM) to provide a standard and intuitive classification over students'academic-performance levels, which leads to a compact representation ofacademic-performance trajectories. Next, we explore the relationship betweendifferent academic-performance trajectories and their correspondence to finalacademic success. Based on student transcript data from University of CentralFlorida, our proposed HMM is trained using sequences of students' course gradesfor each semester. Through the HMM, our analysis follows the expected findingthat higher academic performance levels correlate with lower halt rates.However, in this paper, we identify that there exist many scenarios in whichboth improving or worsening academic-performance trajectories actuallycorrelate to higher graduation rates. This counter-intuitive finding is madepossible through the proposed and developed HMM model.

Impacts of Students Academic Performance Trajectories on Final Academic Success