General models for automated essay scoring: Exploring an alternative to the status quo

Journal of Educational Computing Research

Volumn 33, Issue 1, 2005, Pages 101-113

  Kelly, P Adam ^a,b  

^a BAYLOR COLLEGE OF MEDICINE   (United States)

^b MICHAEL E DEBAKEY VETERANS AFFAIRS MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 33646414786     PISSN: 07356331     EISSN: None     Source Type: Journal    
DOI: 10.2190/19JK-UMP5-12EE-4XWE     Document Type: Article

References (13)

1. Burstein, J. C. (2003). The e-rater® scoring engine: Automated essay scoring with natural language processing. In M. D. Shermis & J. C. Burstein (Eds.), Automated essay scoring: A cross-disciplinary perspective (pp. 113-121). Mahwah, NJ: Erlbaum.
2. Burstein, J. C., Braden-Harder, L., Chodorow, M. C., Hua, S., Kaplan, B. A., Kukich, K., Lu, C., Nolan, J., Rock, D. A., & Wolff, S. E. (1998). Computer analysis of essay content for automated score prediction: A prototype automated scoring system for GMAT Analytical Writing Assessment essays (ETS Research Report 98-15). Princeton, NJ: Educational Testing Service. Retrieved January 25, 2005, from http://www.ets.org/research/dload/burstein_9815.pdf.
3. Cizek, G. J., & Page, B. A. (2003). The concept of reliability in the context of automated essay scoring. In M. D. Shermis & J. C. Burstein (Eds.), Automated essay scoring: A cross-disciplinary perspective (pp. 125-146). Mahwah, NJ: Erlbaum.
4. Clauser, B. E., Kane, M. T., & Swanson, D. B. (20020. Validity issues for performance-based tests scored with computer-automated scoring systems. Applied Measurement in Education, 75(4), 413-432.
5. Elliott, S. (2003). IntelliMetric™: From here to validity. In M. D. Shermis & J. C. Burstein (Eds.), Automated essay scoring: A cross-disciplinary perspective (pp. 71-86). Mahwah, NJ: Erlbaum.
6. nd ed.). New York: Wiley.
7. Keith, T. Z. (2003). Validity of automated essay scoring systems. In M. D. Shermis & J. C. Burstein (Eds.), Automated essay scoring: A cross-disciplinary perspective (pp. 147-168). Mahwah, NJ: Erlbaum.
8. Landis, J. D., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159-174.
9. Page, E. B. (2003). Project Essay Grade: PEG. In M. D. Shermis & J. C. Burstein (Eds.), Automated essay scoring: A cross-disciplinary perspective (pp. 71-86). Mahwah, NJ: Erlbaum.
10. Page, E. B., & Petersen, N. S. (1995). The computer moves into essay grading: Updating the ancient test. Phi Delta Kappan, 76((1), 561-565.
11. Powers, D. E. Burstein, J. C., Chodorow, M. C., Fowles, M. E., & Kukich, K. (2002). Comparing the validity of automated and human scoring of essays. Journal of Educational Computing Research, 26(4), 407-425.
12. Powers, D. E., Burstein, J. C., Chodorow, M. C., Fowles, M. E., & Kukich, K. (2001). Stumping e-rater®: Challenging the validity of automated essay scoring. (ETS Research Report 01-03). Princeton, NJ: Educational Testing Service. Retrieved January 25, 2005, from http://www.ets.org/research/dload/ powers_0103.pdf.
13. Yang, Y., Buckendahl, C. W., Juszkiewicz, P. J., & Bhola, D. S. (2002). A review of strategies for validating computer-automated scoring. Applied Measurement in Education, 75(4), 391-412.