Name
Abstract | ||
|---|---|---|
This paper investigates the different attributes used in evaluating faculty performance to come up with a regression model that predicts faculty performance. The main objective of this paper is to develop a model for predicting faculty performance and design a framework of data mining implementing ETL. The outcome of this research could be used as basis in improving the instruction in an academic institution. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/SERA.2011.29 | SERA |
Keywords | Field | DocType |
data mining,predicting faculty performance,faculty performance,regression model,main objective,academic institution,different attribute,prediction algorithms,database,clustering,clustering algorithms,regression analysis,predictive models,algorithm design and analysis | Data mining,Predictive Model Markup Language,Algorithm design,Computer science,Regression analysis,Prediction algorithms,Artificial intelligence,Cluster analysis,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Raymond S. Bermudez | 1 | 0 | 0.34 |
| Joseph O. Manalang | 2 | 0 | 0.34 |
| Bobby D. Gerardo | 3 | 27 | 13.79 |
| Bartolome T. Tanguilig III | 4 | 0 | 1.35 |