Automatic scoring of short handwritten essays in reading comprehension tests

Artificial Intelligence

Volumn 172, Issue 2-3, 2008, Pages 300-324

  Srihari, Sargur ^a   Collins, Jim ^a   Srihari, Rohini ^a   Srinivasan, Harish ^a   Shetty, Shravya ^a   Brutt Griffler, Janina ^a  

^a UNIVERSITY AT BUFFALO   (United States)

Author keywords

Artificial neural networks; Automatic essay scoring; Contextual handwriting recognition; Latent semantic analysis; Reading comprehension

Indexed keywords

COMPUTATIONAL METHODS; PATTERN RECOGNITION; SEMANTICS; STUDENTS;

AUTOMATIC ESSAY SCORING; CONTEXTUAL HANDWRITING RECOGNITION; LATENT SEMANTIC ANALYSIS; READING COMPREHENSION; SHORT HANDWRITTEN ESSAYS; TRANSCRIPTION ERROR RATES;

ARTIFICIAL INTELLIGENCE;

EID: 37149030059     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artint.2007.06.005     Document Type: Article

References (35)

1. M. Arivazhagan, H. Srinivasan, S.N. Srihari, A statistical approach to segmentation of scanned handwritten documents, in: Document Recognition and Retrieval XIV: Proceedings of SPIE, San Jose, vol. 6500, 2007, pp. 6500T-1-6500T-11
2. Baeza-Yates R., and Ribeiro-Neto B. Modern Information Retrieval (1999), New York, Addison-Wesley
3. Bozinovic R., and Srihari S.N. A multi-resolution perception approach to cursive script recognition. Artificial Intelligence 33 2 (1987) 217-255
4. Burstein J. The E-rater scoring engine: Automated essay scoring with natural language processing. In: Shermis M.D., and Burstein Y. (Eds). Automated Essay Scoring: A Cross-Disciplinary Perspective (2003), Lawrence Erlbaum Associates, Inc., Hillsdale, NJ
5. Chen S.F., and Goodman J. An empirical study of smoothing techniques for language modeling. In: Joshi A., and Palmer M. (Eds). Proceedings Thirty-Fourth Annual Meeting of the Association for Computational Linguistics (1996), Morgan Kaufmann Publishers, San Francisco 310-318
6. Collins J. Strategies for Struggling Writers (1998), Guilford, New York
7. Collins J., and Godinho G.V. Help for struggling writers. Learning Disabilities Research and Practice 11 (1996) 177-182
8. J.L. Collins, J. Lee, J. Brutt-Gifler, J. Fox, T. Madigan, E. Vosburgh, The writing intensive reading comprehension study, Technical Report, University at Buffalo, June 2006
9. Duda R.O., and Hart P.E. Use of the Hough transform to detect lines and curves in pictures. Communications of the ACM 15 (1972) 11-15
10. Englert C.S. Teaching written language skills. In: Cigilka P., and Berdine W. (Eds). Effective Instruction for Students with Learning Difficulties (1995), Allyn and Bacon, Boston, MA 304-343
11. Graesser A.C., McNamara D.S., Louwerse M.M., and Cai Z. Coh-metrix: Analysis of text on cohesion and language. Behavior Research Methods, Instruments, and Computers 36 (2004) 193-202
12. Huang C., and Srihari S.N. Mapping transcripts to handwritten text. Proceedings of the 10th International Workshop on Frontiers in Handwriting Recognition. LaBaule, France (2006), Universite de Rennes 15-20
13. J.J. Hull, Incorporation of a Markov model of syntax in a text recognition algorithm, in: Proceedings Symposium on Document Analysis and Information Retrieval, 1992, pp. 174-183
14. T. Ishioka, M. Kameda, Automated Japanese essay scoring system: Jess, in: Proceedings 15th International Workshop on Database and Expert Systems Applications, 2004
15. Kim G., and Srihari S.N. A segmentation and recognition strategy for handwritten phrases. Proceedings International Conference on Pattern Recognition. Vienna, Austria (1996), IEEE Computer Society Press D510-D514
16. Kintsch W. Comprehension: A Paradigm for Cognition (1998), Cambridge University Press, Cambridge, England
17. Landauer T., Laham D., and Foltz P. Automated scoring and annotation of essays with the Intelligent Essay Assessor. Automated Essay Scoring: A Cross-Disciplinary Perspective (2003), Lawrence Erlbaum Associates, Inc., Hillsdale, NJ
18. Landauer T.K., Foltz P.W., and Laham D. An introduction to latent semantic analysis. Discourse Processes 25 (1998) 259-284
19. Leacock C., and Chodorow M. C-rater: Scoring of short-answer questions. Computers and the Humanities 37 4 (2003) 389-405
20. Mahadevan U., and Srihari S.N. Parsing and recognition of city, state and ZIP codes in handwritten addresses. Proceedings of Fifth International Conference on Document Analysis and Recognition (ICDAR). Bangalore, India (1999), IEEE Computer Society Press 325-328
21. Nicolas S., Paquet T., and Heutte L. Complex handwritten page segmentation using contextual models. Proceedings of International Workshop on Document Image Analysis for Libraries (DIAL). Lyons, France (2006), IEEE Computer Society Press 46-57
22. Page E.B. Computer grading of student prose using modern concepts and software. Journal of Experimental Education 62 (1961) 127-142
23. Palmer J., Williams R., and Dreher H. Automated essay grading system applied to a first year university subject-how can we do better?. Informing Science (June 2002) 1221-1229
24. Plamondon R., and Srihari S.N. On-line and off-line handwriting recognition: A comprehensive survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 22 1 (2000) 63-84
25. Porter M.F. An algorithm for suffix stripping. Program 14 3 (1980) 130-137
26. T. Raphael, B.W. Kirschner, C.S. Englert, Acquisition of expository writing skills, in: J. Mason (Ed.), Reading and Writing Connections, 1988
27. Reddy R. Three open problems in Artificial Intelligence. Journal of the ACM 50 1 (2003)
28. Sanjosé V., Vidal-Abarca E., and Padilla O.M. A connectionist extension to Kintsch's construction-integration model. Discourse Processes 42 (2006) 1-35
29. R.K. Srihari, S. Ng, C.M. Baltus, J. Kud, Use of language models in on-line sentence/phrase recognition, in: Proceedings of International Workshop on Frontiers in Handwriting Recognition, Buffalo, 1993, pp. 284-294
30. Srihari R.K., Li W., Cornell T., and Niu C. InfoXtract: A customizable intermediate level information extraction engine. Journal of Natural Language Engineering (2006)
31. S.N. Srihari, G. Kim, PENMAN: A system for reading unconstrained handwritten page images, in: Proceedings of Symposium on Document Image Understanding Technology (SDIUT 97), Annapolis, MD, 1997, pp. 142-153
32. S.N. Srihari, B. Zhang, C. Tomai, S. Lee, Z. Shi, Y.C. Shin, A system for handwriting matching and recognition, in: Proceedings of Symposium on Document Image Understanding Technology (SDIUT 03), Greenbelt, MD, 2003, pp. 67-75
33. S.N. Srihari, E.J. Keubert, Integration of handwritten address interpretation technology into the United States Postal Service Remote Computer Reader System, in: Proceedings of Fourth International Conference on Document Analysis and Recognition (ICDAR 97), Ulm, Germany, 1997, pp. 892-896
34. S.N. Srihari, J. Collins, R.K. Srihari, P. Babu, H. Srinivasan, Automatic scoring of handwritten essays based on latent semantic analysis, in: H. Bunke and A. L. Spitz (Eds.), Document Analysis Systems VII, Proceedings of Seventh International Workshop on Document Analysis Systems, Nelson, New Zealand, Springer-Verlag, February 2006, pp. 71-83
35. B. Zhang, S.N. Srihari, Word image retrieval using binary features, in: Proceedings of Document Recognition and Retrieval XI, E.H. Smith, J. Hu, J. Allen (Eds.), Proceedings of SPIE, vol. 5296, 2004, pp. 45-53