Scaling the Student Journey from Course-Level Information to Program Level Progression and Graduation: A Model
| Autor: | Amelia Brennan, Pablo Munguia |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry 05 social sciences Learning analytics Psychological intervention 050301 education Context (language use) 02 engineering and technology Academic achievement Computer Science Applications Education Course (navigation) Analytics ComputingMilieux_COMPUTERSANDEDUCATION 0202 electrical engineering electronic engineering information engineering Mathematics education 020201 artificial intelligence & image processing Program Design Language business 0503 education Graduation |
| Zdroj: | Journal of Learning Analytics. 7:84-94 |
| ISSN: | 1929-7750 |
| Popis: | No course exists in isolation, so examining student progression through courses within a broader program context is an important step in integrating course-level and program-level analytics. Integration in this manner allows us to see the impact of course-level changes to the program, as well as identify points in the program structure where course interventions are most important. Here we highlight the significance of program-level learning analytics, where the relationships between courses become clear, and the impact of early-stage courses on program outcomes such as graduation or drop-out can be understood. We present a matrix model of student progression through a program as a tool to gain valuable insight into program continuity and design. We demonstrate its use in a real program and examine the impact upon progression and graduation rate if course-level changes were made early on. We also extend the model to more complex scenarios such as multiple program pathways and simultaneous courses. Importantly, this model also allows for integration with course-level models of student performance. |
| Databáze: | OpenAIRE |
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