Name
Title | ||
|---|---|---|
Understanding the evolution of mathematics performance in primary education and the implications for STEM learning: A Markovian approach. |
Abstract | ||
|---|---|---|
•Model students’ performance in mathematics over time as a stochastic process.•Create longitudinal datasets linking student scores on end-of-grade math exams.•Analyze longitudinal datasets based on a variety of demographic factors.•Use Markov chains to probabilistically characterize movement of students’ scores. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.chb.2014.09.037 | Computers in Human Behavior |
Keywords | DocType | Volume |
Mathematics education,Longitudinal student data,Markov chain,Educational data mining | Journal | 47 |
Issue | ISSN | Citations |
C | 0747-5632 | 0 |
PageRank | References | Authors |
0.34 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amy Craig Reamer | 1 | 0 | 0.34 |
| Julie S. Ivy | 2 | 33 | 9.12 |
| Anita R. Vila-Parrish | 3 | 0 | 1.35 |
| Robert E. Young | 4 | 209 | 31.20 |