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Analyzing Discourse Processing Using a Simple Natural Language Processing Tool

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REFERENCES

  • Attali, Y., & Burstein, J. (2006). Automated essay scoring with e-rater® v.2.0. Journal of Technology, Learning and Assessment, 4, 1–31.
  • Baayen, R. H., Piepenbrock, R., & Gulikers, L. (1995). The CELEX lexical database (CD-ROM). Philadelphia, PA: Linguistic Data Consortium, University of Pennsylvania.
  • Balota, D. A., Cortese, M. J., Sergent-Marshall, S. D., Spieler, D. H., & Yap, M. (2004). Visual word recognition of single-syllable words. Journal of Experimental Psychology: General, 133, 283–316.
  • Biber, D. (1988). Variation across speech and writing. Cambridge, UK: Cambridge University Press.
  • Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python. O'Reilly Media. Retrieved from http://nltk.org/book.
  • Bormuth, J. R. (1969). Development of readability analyses(Final Report, Project No. 7-0052, Contract No. 1, OEC-3-7-070052-0326). Washington, DC: U.S. Office of Education.
  • Brill, E. (1995). Transformation-based error-driven learning and natural language processing: A case study in part-of-speech tagging. Computational Linguistics, 21, 543–566.
  • Chafe, W. (1975). Givenness, contrastiveness, definiteness, subjects, topics, and point of view in subject and topic. In C.Li (Ed.), Subject and topic (pp. 25–55). New York, NY: Academic Press.
  • Chall, J., & Dale, E. (1995). Readability revisited: The new DaleChall Readability. Cambridge, MA: Brookline Books.
  • Charniak, E. (2000). A maximum-entropy-inspired parser. In Proceedings of the First Conference on North American Chapter of the Association for Computational Linguistics (pp. 132–139). San Francisco, CA: Morgan Kaufmann.
  • Chomsky, N. (1957). Syntactic structures. The Hague, The Netherlands/Paris, France: Mouton.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
  • Coxhead, A. (2000). A new academic word list. TESOL Quarterly, 34(2), 213–238.
  • Crossley, S. A. (2013). Advancing research in second language writing through computational tools and machine learning techniques: A research agenda. Language Teaching, 46, 256–271.
  • Crossley, S. A., Greenfield, J., & McNamara, D. S. (2008). Assessing text readability using cognitively based indices. TESOL Quarterly, 42, 475–493.
  • Crossley, S. A., & McNamara, D. S. (2010). Cohesion, coherence, and expert evaluations of writing proficiency. In S.Ohlsson & R.Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 984–989). Austin, TX: Cognitive Science Society.
  • Crossley, S. A., & McNamara, D. S. (2011). Understanding expert ratings of essay quality: Coh-Metrix analyses of first and second language writing. International Journal of Continuing Engineering Education and Life-Long Learning, 21, 170–191.
  • Crossley, S. A., & McNamara, D. S. (2012). Predicting second language writing proficiency: The role of cohesion, readability, and lexical difficulty. Journal of Research in Reading, 35, 115–135.
  • Crossley, S. A., & McNamara, D. S. (2013). Text analysis tools for spoken response grading. Language Learning & Technology, 17, 171–192.
  • Crossley, S. A., Roscoe, R. D., & McNamara, D. S. (2013). Using automatic scoring models to detect changes in student writing in an intelligent tutoring system. In P. M.McCarthy & G. M.Youngblood (Eds.), Proceedings of the 26th International Florida Artificial Intelligence Research Society (FLAIRS) Conference (pp. 208–213). Menlo Park, CA: The AAAI Press.
  • Deane, P. (2013). On the relation between automated essay scoring and modern views of the writing construct. Assessing Writing, 18, 7–24.
  • Dell, G. S., McKoon, G., & Ratcliff, R. (1983). The activation of antecedent information during the processing of anaphoric reference in reading. Journal of Verbal Learning and Verbal Learning and Verbal Behavior, 22, 121–132.
  • D'Mello, S. K., & Graesser, A. C. (2012). Language and discourse are powerful signals of student emotions during tutoring. IEEE Transactions on Learning Technologies, 5, 304–317.
  • Duran, N. D., McCarthy, P. M., Graesser, A. C., & McNamara, D. S. (2007). Using temporal cohesion to predict temporal coherence in narrative and expository texts. Behavior Research Methods, 39, 212–223.
  • Flesch, R. (1948). A new readability yardstick. Journal of Applied Psychology, 32, 221–233.
  • Forster, K. I., & Chambers, S. M. (1973). Lexical access and naming time. Journal of Verbal Learning and Verbal Behavior, 12, 627–635.
  • Frederiksen, J. R., & Kroll, J. F. (1976). Spelling and sound: Approaches to the internal lexicon. Journal of Experimental Psychology: Human Perception and Performance, 2, 361–379.
  • Gernsbacher, M. A. (1990). Language comprehension as structure building. Hillsdale, NJ: Erlbaum.
  • Givon, T. (1992). The grammar of referential coherence as mental processing instructions. Linguistics, 30, 5–55.
  • Graesser, A. C., & McNamara, D. S. (2012a). Automated analysis of essays and open-ended verbal responses. In H.Cooper, P.Camic, R.Gonzalez, D.Long, & A.Panter (Eds.), APA handbook of research methods in psychology: Foundations, planning, measures, and psychometrics (pp. 307–325). Washington, DC: American Psychological Association.
  • Graesser, A. C., & McNamara, D. S. (2012b). Reading instruction: Technology-based supports for classroom instruction. In C.Dede & J.Richards (Eds.), Digital teaching platforms: Customizing classroom learning for each student (pp. 71–87). New York, NY: Teachers College Press.
  • Graesser, A. C., McNamara, D. S., Louwerse, M. M., & Cai, Z. (2004). Coh-Metrix: Analysis of text on cohesion and language. Behavioral Research Methods, Instruments, and Computers, 36, 193–202.
  • Graesser, A. C., McNamara, D. S., & VanLehn, K. (2005). Scaffolding deep comprehension strategies through Point&Query, AutoTutor, and iSTART. Educational Psychologist, 40, 225–234.
  • Gundel, J. K., Hedberg, N., & Zacharski, R. (1993). Cognitive status and the form of referring expressions in discourse. Language, 69, 274–307.
  • Halliday, M. A. K. (1967). Notes on transitivity and theme in English. Journal of Linguistics, 3, 199–244.
  • Halliday, M. A. K., & Hasan, R. (1976). Cohesion in English. London, UK: Longman.
  • Haviland, S. E., & Clark, H. H. (1974). What's new? Acquiring new information as a process in comprehension. Journal of Verbal Learning and Verbal Behavior, 13, 512–521.
  • Hempelmann, C. F., Dufty, D., McCarthy, P., Graesser, A. C., Cai, Z., & McNamara, D. S. (2005). Using LSA to automatically identify givenness and newness of noun-phrases in written discourse. In B.Bara (Ed.), Proceedings of the 27th Annual Meetings of the Cognitive Science Society (pp. 941–946). Mahwah, NJ: Erlbaum.
  • Jurafsky, D., & Martin, J. (2008). Speech and language processing. Englewood, NJ: Prentice Hall.
  • Just, M. A., & Carpenter, P. A. (1987). The psychology of reading and language comprehension. Boston, MA: Allyn & Bacon.
  • Kellogg, R. T. (1988). Attentional overload and writing performance: Effects of rough draft and outline strategies. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14, 355–365.
  • Kintsch, W., & Keenan, J. (1973). Reading rate and retention as a function of the number of propositions in the base structure of sentences. Cognitive Psychology, 5, 257–274.
  • Kintsch, W., & van Dijk, T. A. (1978). Toward a model of text comprehension and production. Psychological Review, 85, 363–394.
  • Kirsner, K. (1994). Implicit processes in second language learning. In N.Ellis (Ed.), Implicit and explicit learning of languages (pp. 283–312). San Diego, CA: Academic Press.
  • Klein, A., & Badia, T. (2014). The usual and the unusual: Solving remote associates test tasks using simple statistical natural language processing based on language use. Journal of Creative Behavior. Advance online publication. 10.1002/jocb.57.
  • Kogut, P., & Holmes, W. (2001). AeroDAML: Applying information extraction to generate DAML annotations from web pages. In S.Handschuh, R.Dieng, & S.Stabb (Eds.), Proceedings of the K-CAP 2001 Workshop on Knowledge Markup and Semantic Annotation. Aachen, Germany: CEUR-WS.
  • Korbin, J. L., Patterson, B. F., Shaw, E. J., Mattern, K. D., & Barbuti, S. M. (2008). Validity of the SAT for predicting first-year college grade point average. New York, NY: The College Board.
  • Landauer, T., McNamara, D. S., Dennis, S., & Kintsch, W. (Eds.). (2007). Handbook of latent semantic analysis. Mahwah, NJ: Erlbaum.
  • Lecocke, M., & Hess, K. (2006). An empirical study of univariate and genetic algorithm-based feature selection in binary classification with microarray data. Cancer Informatics, 2, 313–327.
  • Lintean, M., Rus, V., & Azevedo, R. (2012). Automatic detection of student mental models based on natural language student input during metacognitive skill training. International Journal of Artificial Intelligence in Education, 21, 169–190.
  • Louwerse, M. M. (2001). An analytic and cognitive parameterization of coherence relations. Cognitive Linguistics, 12, 291–315.
  • Malvern, D., Richards, B., Chipere, N., & Durán, P. (2004). Lexical diversity and language development: Quantification and assessment. Basingstoke, UK: Palgrave Macmillan.
  • McCarthy, P., & Jarvis, S. (2010). MTLD, vocd-D, and HD-D: A validation study of sophisticated approaches to lexical diversity assessment. Behavior Research Methods, 42, 381–392.
  • McCutchen, D. (1996). A capacity theory of writing: Working memory in composition. Educational Psychology Review, 8, 299–325.
  • McCutchen, D. (2000). Knowledge processing and working memory: Implications for a theory of writing. Educational Psychologist, 35, 13–23.
  • McKevitt, P., Partridge, D., & Wilks, Y. (1992). Approaches to natural language discourse processing. Artificial Intelligence Review, 6, 333–364.
  • McNamara, D. S., Crossley, S. A., & McCarthy, P. M. (2010). Linguistic features of writing quality. Written Communication, 27, 57–86.
  • McNamara, D. S., Crossley, S. A., & Roscoe, R. D. (2013). Natural language processing in an intelligent writing strategy tutoring system. Behavior Research Methods, 45, 499–515.
  • McNamara, D. S., & Graesser, A. C. (2012). Coh-Metrix: An automated tool for theoretical and applied natural language processing. In P. M.McCarthy & C.Boonthum-Denecke (Eds.), Applied natural language processing and content analysis: Identification, investigation, and resolution (pp. 188–205). Hershey, PA: IGI Global.
  • McNamara, D. S., Graesser, A. C., McCarthy, P., & Cai, Z. (2014). Automated evaluation of text and discourse with Coh-Metrix. Cambridge, UK: Cambridge University Press.
  • McNamara, D. S., Raine, R., Roscoe, R., Crossley, S., Jackson, G. T., Dai, J., … Graesser, A. C. (2012). The Writing-Pal: Natural language algorithms to support intelligent tutoring on writing strategies. In P. M.McCarthy & C.Boonthum (Eds.), Applied natural language processing and content analysis: Identification, investigation, and resolution (pp. 298–311). Hershey, PA: IGI Global.
  • Molinaro, A. M., Simon, R., & Pfeiffer, R. M. (2005). Prediction error estimation: A comparison of resampling methods. Bioinformatics, 21, 3301–3307.
  • Pennebaker, J. W. (2011). The secret life of pronouns. New York, NY: Bloomsbury Press.
  • Pennebaker, J. W., Booth, R. J., & Francis, M. E. (2007). LIWC2007: Linguistic inquiry and word count. Austin, TX: LIWC.net.
  • Ramineni, C., Trapani, C. S., Williamson, D. M. W., Davey, T., & Bridgeman, B. (2012). Evaluation of the e-rater® scoring engine for the TOEFL® independent and integrated prompts(ETS Research Report No. RR-12-06). Princeton, NJ: ETS.
  • Rayner, K., & Pollatsek, A. (1994). The psychology of reading. Englewood Cliffs, NJ: Prentice Hall.
  • Roscoe, R. D., Varner, L. K., Crossley, S. A., & McNamara, D. S. (2013). Developing pedagogically-guided algorithms for intelligent writing feedback. International Journal of Learning Technology, 8(4), 362–381.
  • Rudner, L., Garcia, V., & Welch, C. (2005). An evaluation of IntellimetricTM essay scoring system using responses to GMAT® AWA prompts. McLean, VA: GMAC.
  • Rudner, L. M., Garcia, V., & Welch, C. (2006). An evaluation of the IntelliMetricTM essay scoring system. Journal of Technology, Learning, and Assessment, 4(4), 1–22.
  • Sanders, T. J. M., & Noordman, L. G. M. (2000). The role of coherence relations and their linguistic markers in text processing. Discourse Processes, 29, 37–60.
  • Simpson-Vlach, R., & Ellis, N. C. (2010). An academic formulas list: New methods in phraseology research. Applied Linguistics (Oxford), 31, 487–512.
  • Sparks, J. R., & Rapp, D. N. (2010). Discourse processing—Examining our everyday language experiences. WIREs Cognitive Science, 1, 371–381.
  • Templin, M. (1957). Certain language skills in children: Their development and interrelationships. Minneapolis, MN: University of Minnesota Press.
  • Tomasello, M. (1992). First verbs: A case study of early lexical development. Cambridge, UK: Cambridge University Press.
  • Varner, L. K., Roscoe, R. D., & McNamara, D. S. (2013). Evaluative misalignment of 10th-grade student and teacher criteria for essay quality: An automated textual analysis. Journal of Writing Research, 5, 35–59.
  • Witten, I. H., & Frank, E. (2005). Data mining: Practical machine learning tools and techniques. San Francisco, CA: Elsevier.
  • Zelle, J. M. (2004). Python programming: An introduction to computer science. Wilsonville, OR: Franklin Beedle.
  • Zwaan, R. A., Langston, M. C., & Graesser, A. C. (1995). The construction of situation models in narrative comprehension: An event-indexing model. Psychological Science, 6, 292–297.

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