Using artificial neural nets to predict academic performance

Proceedings of the ACM Symposium on Applied Computing

Volumn Part F128723, Issue , 1996, Pages 33-37

  Cripps, Al ^a  

^a MIDDLE TENNESSEE STATE UNIVERSITY   (United States)

Author keywords

Academic; Neural networks; Prediction

Indexed keywords

BACKPROPAGATION; EDUCATION; FORECASTING; STUDENTS;

ACADEMIC; ACADEMIC PERFORMANCE; ACTIVATION FUNCTIONS; ARTIFICIAL NEURAL NET; BACKPROPAGATION LEARNING; COLLEGE STUDENTS; DEGREE PROGRAM; NET ARCHITECTURE;

NEURAL NETWORKS;

EID: 85002129924     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/331119.331137     Document Type: Conference Paper

References (26)

1. Allen, D., February 1995, "Persistence patterns of those students who drop out of ASU," Recruitment & Retention in Higher Education, 9(2), pages 4-6
2. Boylan, H.R. & Bonham, B.S., 1992, "The impact of developmental education programs," Research in Developmental Education, 9(5)
3. Cotter, N. E. and Mian, O. N., March 1992, "A pulsed neural network capable of universal approximation," 1EEE Transactions on Neural Networks, 3:308-314
4. Dishner, D., December 1994, "Faculty 'Culture' and Student Success," Recruitment & Retention in Higher Education, 8(12), pages 4-5
5. Dole, A., 1963, "Prediction of academic success upon readmission to college," Journal of Counseling Psychology, 10(2), pages 169-175
6. Foster, W.R., Collopy, F., & Ungar, L.H., 1992, "Neural network forecasting of short noisy time series," Computers and Chemical Engineering, 16(4),pages 293-297
7. Hall, K.M. and Gahn, S.W., Spring 1994, "Predictors of success for academically dismissed students following readmission," NACADA Journal, 14(1), page 8
8. Hansmeier, T. W., 1965, "Factors related to success of college students academically dismissed," College and University, 40(1), pages 194-202
9. Hartman, E. J., Keeler, J. D., and Kowalski, J. M., 1990, "Layered neural networks with Gaussian hidden units as universal approximations," Neural Computation, 2:210-215
10. Lapedes, A. and Farber, R., 1988, "How neural nets work," Evolution, Learning, and Cognition, pages 331-345, World Scientific, Singapore
11. Lautz, R., MacLean, D., Vaughn, A. T., & Oliver, T. C., 1970, "Characteristics of successful students readmitted following academic suspension," College and University, 45(2), pages 192-202
12. Lavin, D. E., 1965, "The prediction of academic performance," New York: Russell Sage Foundation
13. Montes, A., February 1994, "Retention Concepts," Recruitment & Retention in Higher Education, 8(2)page 6
14. Moody, J., 1989, "Fast learning in multi-resolution hierarchies," Advances in Neural Information Processing Systems, volume 1, pages 29-39, Denver, Morgan Kaufmann, San Mateo
15. Ott, M. D., 1988, "An analysis of predictors of early academic dismissal," Research in Higher Education, 28(1), pages 34-48
16. Schreiner, L., September 1993, "Identifying and Advising the 'At Risk' Student," Recruitment & Retention in Higher Education, 7(9), page 5
17. Sharda, R., & Patil, R.B., 1992; "A connectionist approach to time series prediction: an empirical test," Journal of Intelligent Manufacturing
18. Tang, Z., Almeida, C., & Fishwick, P., 199l, "Time series forecasting using neural networks vs. Box-Jenkins methodology," Simulation, 57(5), pages 303-310
19. Tennessee Board of Regents, 1991, "Evaluation of remedial/developmental programs," Available from TBR, 1415 Murfreesboro Rd, Suite 350, Nashville, TN 27217
20. Tinto, V., 1975, "Dropout from high education: A theoretical synthesis of recent research," Review of Educational Research, 45(1), pages 89-125
21. Weigend, A.S., Rumdhart, D.E., & Huberman, B.A., 1990, "Backpropagation, weight-elimination and time series prediction" Connectionist Models: Proceedings of the 1990 Summer School, pages 105-116
22. Wieberg, S., May 20, 1993, "NCAA: New grad rates reveal status quo," USA Today, page 1C.
23. Werbos, P.J, 1989, "Generalization of backpropagation with application to recurrent gas market model," Neural Networks, 1, pages 339-356
24. Werbos, PJ., October 1990, "Backpropagation through time: What it does and. how to do it," Proceedings of the IEEE, volume 78, pages 1550-1560
25. White, H., 1988, "Economic prediction using neural networks: the case of IBM daily stock returns," IJCNN, Volume lI, pages 451-458
26. Wishart, M. E., 1990, "Making rational reinstatement decisions," NACADA Journal, 10(1), pages 18-21