Abstract
Handwritten essays are widely used in educational assessments, particularly in classroom instruction. This paper concerns the design of an automated system for performing the task of taking as input scanned images of handwritten student essays in reading comprehension tests and to produce as output scores for the answers which are analogous to those provided by human scorers. The system is based on integrating the two technologies of optical handwriting recognition (OHR) and automated essay scoring (AES). The OHR system performs several pre-processing steps such as forms removal, rule-line removal and segmentation of text lines and words. The final recognition step, which is tuned to the task of reading comprehension evaluation in a primary education setting, is performed using a lexicon derived from the passage to be read. The AES system is based on the approach of latent semantic analysis where a set of human-scored answers are used to determine scoring system parameters using a machine learning approach. System performance is compared to scoring done by human raters. Testing on a small set of handwritten answers indicate that system performance is comparable to that of automatic scoring based on manual transcription.
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References
Baeza-Yates, R., Ribeiro-Neto, B.: Modern information retrieval. Addison-Wesley, New York (1999)
Burstein, J.: The E-rater Scoring Engine: Automated essay scoring with natural language processing. In: Automated Essay Scoring (2003)
Hull, J.J.: Incorporation of a Markov model of syntax in a text recognition algorithm. In: Proceedings of the Symposium on Document Analysis and Information Retrieval, pp. 174–183 (1992)
Landauer, T., Laham, D., Foltz, P.: Automated scoring and annotation of essays with the Intelligent Essay Assessor. In: Automated Essay Scoring (2003)
Landauer, T.K., Foltz, P.W., Laham, D.: An introduction to latent semantic analysis. Discourse Processes 25, 259–284
Larkey, L.S.: Automatic essay grading using text categorization techniques. In: Proceedings ACM-SIGIR Conference on Research and Development in Information Retrieval, Melbourne, Australia, pp. 90–95
Mahadevan, U., Srihari, S.N.: Parsing and recognition of city, state and ZIP Codes in handwritten addresses. In: Proceedings of Fifth International Conference on Document Analysis and Recognition (ICDAR), Bangalore, India, pp. 325–328 (1999)
Page, E.B.: Computer grading of student prose using modern concepts and software. Journal of Experimental Education 62, 127–142
Palmer, J., Williams, R., Dreher, H.: Automated essay grading system applied to a first year university subject - how can we do better? Informing Science, 1221–1229 (June 2002)
Plamondon, R., Srihari, S.N.: On-line and off-line handwriting recognition: A comprehensive survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(1), 63–84 (2000)
Porter, M.F.: An Algorithm for Suffix Stripping. Program 14(3), 130–137 (1980)
Srihari, R.K., Ng, S., Baltus, C.M., Kud, J.: Use of language models in on-line sentence/phrase recognition. In: Proceedings of the International Workshop on Frontiers in Handwriting Recognition, Buffalo, pp. 284–294 (1993)
Srihari, S.N., Kim, G.: PENMAN: A system for reading unconstrained handwritten page images. In: Proceedings of the Symposium on Document Image Understanding Technology (SDIUT 1997), Annapolis, MD, pp. 142–153 (1997)
Srihari, S.N., Zhang, B., Tomai, C., Lee, S., Shi, Z., Shin, Y.C.: A system for handwriting matching and recognition. In: Proceedings of the Symposium on Document Image Understanding Technology (SDIUT 2003), Greenbelt, MD, pp. 67–75 (2003)
Srihari, S.N., Keubert, E.J.: Integration of handwritten address interpretation technology into the United States Postal Service Remote Computer Reader System. In: Proceedings of the Fourth International Conference on Document Analysis and Recognition (ICDAR 1997), Ulm, Germany, pp. 892–896 (1997)
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Srihari, S., Collins, J., Srihari, R., Babu, P., Srinivasan, H. (2006). Automated Scoring of Handwritten Essays Based on Latent Semantic Analysis. In: Bunke, H., Spitz, A.L. (eds) Document Analysis Systems VII. DAS 2006. Lecture Notes in Computer Science, vol 3872. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11669487_7
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DOI: https://doi.org/10.1007/11669487_7
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