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Scott Crossley

Associate Professor    
Education

May, 2006: The University of Memphis
Ph.D., English (Concentration in Applied Linguistics)

June, 2002: The University of Memphis
M.A., English (Concentrations in Linguistics and ESL)

June, 2001: California State University of Northridge
State of California Secondary Teaching Credential (Social Studies)

August, 1999: The University of Memphis
TEFL Certificate

June, 1999: California State University of Northridge
B.A., History

Specializations

Natural Language Processing
Application of Computational Tools
Educational Technology
Machine Learning
Second language literacy
Lexical development
Language assessment

Biography

Dr. Scott Crossley is an Associate Professor of Applied Linguistics at Georgia State University. Professor Crossley’s primary research focus is on natural language processing and the application of computational tools and machine learning algorithms in language learning, writing, and text comprehensibility. His main interest area is the development and use of natural language processing tools in assessing writing quality and text difficulty. He is also interested in the development of second language learner lexicons and the potential to examine lexical growth and lexical proficiency using computational algorithms. He has received external funding to support his research from Educational Testing Services (ETS), the National Institute of Health (NIH), and the National Science Foundation (NSF). His research has appeared in many prestigious journals in the field of discourse processing, language acquisition, composition studies, and reading including Studies in Second Language Acquisition, TESOL Quarterly, Language Learning, The Modern Language Journal, Second Language Research, Language Testing, Written Communication, Behavior Research Methods, Discourse Processing, and the Journal of Reading Research.

Natural Language Processing Tools developed (click on link for free download)

Constructed Response Analysis Tool (CRAT)

Sentiment Analysis and Cognition Engine (SEANCE)

Simple NLP (SiNLP)

Tool for the Automatic Analysis of Lexical Sophistication (TAALES)

Tool for the Automatic Analysis of Text Cohesion (TAACO)

Tool for the Automatic Analysis of Syntactic Sophistication and Complexity (TAASSC)

External Research Support

Investigator(s) Source Amount Period
Ocumpaugh, J., Baker, R., Crossley, S. A. (Co-PI), Kostyuk, V., & Mingle, L. National Science Foundation (NSF) $540,047 2016-2019
Kim, M., & Crossley, S. A. (Co-PI) Cambridge Michigan Language Assessment (CaMLA) Research Committee Research Program $3,000 2017
Karter, A. J., Schillinger, D. et al. National Institute of Health (NIH) $3,100,000 2015–2019
Skalicky, S., & Crossley, S. A. Qualtrics Behavioral Research Grant $3,000 2015
Yung, Y., Crossley, S. A. (Co-PI), & McNamara, D. S. Cambridge Michigan Language Assessment (CaMLA) Research Committee Research Program $3,000 2014-2015
Crossley, S. A. (PI) & Kim, Y. Educational Testing Service $100,000 2013-2016
Crossley, S. A. (PI) Office of English Language Programs, Bureau of Educational and Cultural Affairs, Public Diplomacy, US Department of State $6,000 2011

Publications

Books

Crossley, S. A., & McNamara, D. S. (2016). Adaptive Educational Technologies for Literacy Instruction. New York: Routledge. [link]

Jarvis, S., & Crossley, S. A. (2012). Approaching language transfer through text classification: Explorations in the detection-based approach. Bristol, UK: Multilingual Matters. [link]

Journal Articles

Berger, C. M., Crossley, S., & Kyle, K. (in press). Using native-speaker psycholinguistic response norms to predict lexical proficiency in second language learners. Applied Linguistics.

Crossley, S. A., Kyle, K., & McNamara, D. S. (in press). Sentiment Analysis and Social Cognition Engine (SEANCE): An automatic tool for sentiment, social cognition, and social order analysis. Behavior Research Methods.

Crossley, S. A., Russell, D., Kyle, K., & Römer, U. (in press). Applying natural language processing tools to a student academic writing corpus: How large are disciplinary differences across science and engineering fields? Journal of Writing Analytics.

Crossley, S. A., & Skalicky, S. (in press). Making sense of polysemy relations in first and second language speakers of English. International Journal of Bilingualism.

Kim, M., Crossley, S. A., & Kyle, K. (in press). Lexical sophistication as a multidimensional phenomenon: Relations to second language lexical proficiency, development, and writing quality. Modern Language Journal.

Kyle, K., & Crossley, S. A. (in press). Assessing syntactic sophistication in L2 writing: A usage-based approach. Language Testing.

Kyle, K., Crossley, S. A., & Berger, C. (in press). The Tool for the automatic analysis of lexical sophistication version 2.0 Behavior Research Methods.

Skalicky, S., Crossley, S. A. (in press). Examining satire processing of satirical Onion newspaper headlines. Discourse Processes.

Skalicky, S., Crossley, S.A., McNamara, D.S., & Muldner, K. (in press). Identifying creativity during problem solving using linguistic features. Creativity Research Journal.

Crossley, S. A., Skalicky, S., Dascalu, M., McNamara, D., & Kyle, K. (2017). Predicting text comprehension, processing, and familiarity in adult readers: New approaches to readability formulas. Discourse Processes, 54(5-6), 340-359.

Berger, C. M., Crossley, S., & Kyle, K. (2017). Using novel word context measures to predict human ratings of lexical proficiency. Journal of Educational Technology & Society, 20(2), 201-212.

Crossley, S. A., Francus Rose, D., Danekes, C., Rose, C. W. & McNamara, D. S. (2017). That noun phrase may be beneficial and this may not be: Discourse cohesion and text processing. Reading and Writing, 30 (3), 569-589.

Schillinger, D., McNamara, D. S., Crossley, S. A., Moffet, H., Sarkar, U., Duran, N., Allen, J., Liu, J., Oryn, D., & Karter, A. J. (2017). The next frontier in communication and the ECLIPPSE Study: Bridging the digital divide in secure messaging. Journal of Diabetes Research. doi:10.1155/2017/1348242

Crossley, S. A., Allen, L., Snow, E., & McNamara, D. S. (2016). Incorporating learning characteristics into automatic essay scoring models: What individual differences and linguistic features tell us about writing quality. Journal of Educational Data Mining, 8(2), 1-19. [PDF]

Crossley, S. A., Kyle, K., & McNamara, D. S. (2016). The development and use of cohesive devices in L2 writing and their relations to judgments of essay quality. The Journal of Second Language Writing, 32, 1-16. [PDF]

Crossley, S. A., Kyle, K., & McNamara, D. S. (2016). The Tool for the Automatic Analysis of Text Cohesion (TAACO): Automatic assessment of local, global, and text cohesion. Behavior Research Methods, 48 (4), 1227-1237. [PDF]

Crossley, S. A., Kyle, K., & Salsbury, T. (2016). A usage-based investigation of L2 lexical acquisition: The role of input and output. The Modern Language Journal, 100(3), 702-715. [PDF]

Crossley, S. A., & McNamara, D. S. (2016). Say more and be more coherent: How text elaboration and cohesion can increase writing quality. Journal of Writing Research, 7 (3), 351-370. [PDF]

Crossley, S. A., & McNamara, D. S. (2016). Text-based recall and extra-textual generations resulting from simplified and authentic texts. Reading in a Foreign Language, 28(1), 1-19. [PDF]

Crossley, S. A., Muldner, K., & McNamara, D. S. (2016). Idea generation in student writing: Computational assessments and links to successful writing. Written Communication, 33(3), 328-354. [PDF]

Frishkoff, G. A., Collins-Thompson, K., Hodges, L., & Crossley, S. (2016). Accuracy feedback improves word learning from context: Evidence from a meaning-generation task. Reading and Writing, 29(4), 609-632. [PDF]

Kyle, K., & Crossley, S. A. (2016). The relationship between lexical sophistication and independent and source-based writing. Journal of Second Language Writing, 34(4), 12-24. [PDF]

Kyle, K., Crossley, S.A., & McNamara, D. S. (2016). Construct validity in TOEFL iBT speaking tasks: Insights from natural language processing. Language Testing, 33(3), 319-340. [PDF]

Skalicky, S., Berger, C. M., Crossley, S. A., & McNamara, D. S. (2016). Linguistic features of humor in academic writing. Advances in Language and Literary Studies, 7 (3), 248-259. [PDF]

Crossley, S. A., Kyle, K., & McNamara, D. S. (2015). To aggregate or not? Linguistic features in automatic essay scoring and feedback systems. Journal of Writing Assessment, 8(1), 1-16. [PDF]

Crossley, S. A., Salsbury, T., & McNamara, D. S. (2015). Assessing lexical proficiency using analytic ratings: A case for collocation accuracy. Applied Linguistics, 36(5), 570-590. [PDF]

Kyle, K., & Crossley, S. A. (2015). Automatically assessing lexical sophistication: Indices, tools, findings, and application. TESOL Quarterly, 49(4), 757-786.
[PDF]

Kyle, K., Crossley, S.A., & Kim, Y. (2015). Native language identification and writing proficiency. International Journal of Learner Corpus Research, 1(2), 187-209. [PDF]

McNamara, D. S., Crossley, S. A., Roscoe, R., Allen, L., Dai, J. (2015). A hierarchical classification approach to automated essay scoring. Assessing Writing, 23(1), 35-59. [PDF]

Skalicky, S., & Crossley, S. A. (2015). A statistical analysis of satirical Amazon.com product reviews. The European Journal of Humor Research, 2(3), 66-85. [PDF]

Snow, E., Allen, L. K., Jacovina, M. E., Crossley, S. A., Perret, C., & McNamara, D. S. (2015). Keys to detecting writing flexibility over time: Entropy and natural language processing. Journal of Learning Analytics, 2(3), 40-54. [PDF]

Allen, L., Crossley, S. A., & McNamara, D. S. (2014). L2 writing practice: Game enjoyment as a key to engagement. Language Learning & Technology, 18(2), 124-150. [PDF]

Allen, L. K., Snow, E. L., Jackson, G. T., Crossley, S. A., & McNamara, D. S. (2014). Reading comprehension components and their relation to writing. L’Année psychologique/Topics in Cognitive Psychology, 114(4), 663-691. [PDF]

Crossley, S. A., Allen, L. K., Kyle, K., & McNamara, D.S. (2014). Analyzing discourse processing using the Simple Natural Language Processing Tool (SiNLP). Discourse Processes, 51(5-6), 511-534. [PDF]

Crossley, S. A., Clevinger, A., & Kim, Y. (2014). The role of lexical properties and cohesive devices in text integration and their effect on human ratings of speaking proficiency. Language Assessment Quarterly, 11(3), 250-270. [PDF]

Crossley, S. A., Roscoe, R., & McNamara, D. S. (2014). What is successful writing? An investigation into the multiple ways writers can write successful essays. Written Communication, 31(2), 184-215. (Winner of the 2014 John R. Hayes Award for Excellence in Research). [PDF]

Crossley, S. A., Kyle, K., Varner, L., Gou, L., & McNamara, D. S. (2014). Linguistic microfeatures to predict L2 writing proficiency: A case study in automated writing evaluation. Journal of Writing Assessment, 7(1), 1-16.
[PDF]

Crossley, S. A., & McNamara, D. S. (2014). Does writing development equal writing quality? A computational investigation of syntactic complexity in L2 learners. Journal of Second Language Writing, 26(4), 66-79. [PDF]

Crossley, S. A., Salsbury, T., Titak, A., & McNamara, D. S., (2014). Frequency effects and second language lexical acquisition: Word types, word tokens, and word production. International Journal of Corpus Linguistics, 19(3), 301-332. [PDF]

Crossley, S. A., Yang, H. S., & McNamara, D. S. (2014). What’s so simple about simplified texts? A computational and psycholinguistic investigation of text comprehension and text processing. Reading in a Foreign Language, 26(1), 92-113. [PDF]

Roscoe, R. D., Allen, L. K., Weston, J. L., Crossley, S. A., & McNamara, D. S. (2014). The Writing Pal Intelligent Tutoring System: Usability testing and development. Computers and Composition, 34, 39-59. [PDF]

Crossley, S. A., Cobb, T., & McNamara, D. S. (2013). Comparing count-based and band-based indices of word frequency: Implications for active vocabulary research and pedagogical applications. System, 41(4), 965-981. [PDF]

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. [PDF]

Crossley, S. A. (2013). Advancing research in second language writing through computational tools and machine learning techniques: A research agenda. Language Teaching, 46 (2), 256-271. [PDF]

Crossley, S. A. (2013). Automatic processing of hypernymic relations in first language speakers and advanced second language learners: A semantic priming approach. Mental Lexicon, 8(1), 96-116. [PDF]

Crossley, S. A., & McNamara, D. S. (2013). Applications of text analysis tools for spoken response grading. Language Learning & Technology, 17(2), 171-192. [PDF]

Crossley, S. A., Subtirelu, N., Salsbury, T. (2013). Frequency effects or context effects in second language word learning: What predicts early lexical production? Studies in Second Language Acquisition, 35(4), 727-755. [PDF]

Guo, L. Crossley, S. A., & McNamara, D. S. (2013). Predicting human judgments of essay quality in both integrated and independent second language writing samples: A comparison study. Writing Assessment, 18(3), 218-238. [PDF]

McNamara, D. S., Crossley, S. A., & Roscoe, R. (2013). Natural Language Processing in an Intelligent Writing Strategy Tutoring System. Behavior Research Methods, 45 (2), 499-515. [PDF]

Crossley, S. A., Allen, D., & McNamara, D. S. (2012). Text simplification and comprehensible input: A case for an intuitive approach. Language Teaching Research, 16(1), 89-108. [PDF]

Crossley, S. A., & McNamara, D. S. (2012). Predicting second language writing proficiency: The roles of cohesion and linguistic sophistication. Journal of Research in Reading, 35(2), 115-135. [PDF]

Crossley, S. A., Salsbury, T., & McNamara, D. S. (2012). Predicting the proficiency level of language learners using lexical indices. Language Testing, 29(2), 240-260. [PDF]

Bell, N. D., Crossley, S. A., & Hempelmann, C. F. (2011). Wordplay in church marquees. HUMOR, 24(2), 167-185. [PDF]

Crossley, S. A. (2011). Metaphors and the reclamation of blackness in Derek Walcott’s Dream on Monkey Mountain. Journal of Caribbean Literatures, 7(1), 15-32. [PDF]

Crossley, S. A., Allen, D., & McNamara, D. S. (2011). Text readability and intuitive simplification: A comparison of readability formulas. Reading in a Foreign Language, 23(1), 84-102. [PDF]

Crossley, S. A., Dempsey, K., & McNamara, D. S. (2011). Classifying paragraph types using linguistic features: Is paragraph positioning important? Journal of Writing Research, 3(2), 119-143. (Finalist for the John R. Hayes Award, 2010-2012). [PDF]

Crossley, S. A., & McNamara, D. S. (2011). Shared features of L2 writing: Intergroup homogeneity and text classification. Journal of Second Language Writing, 20(4), 271-285. [PDF]

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(2/3), 170-191. [PDF]

Crossley, S. A., Weston, J., McLain Sullivan, S. T., & McNamara, D. S. (2011). The development of writing proficiency as a function of grade level: A linguistic analysis. Written Communication, 28(3), 282-311. [PDF]

Crossley, S. A., & Salsbury, T. (2011). The development of lexical bundle accuracy and production in English second language speakers. IRAL: International Review of Applied Linguistics in Language Teaching, 49(1), 1-26. [PDF]

Crossley, S. A., Salsbury, T., McNamara, D. S., & Jarvis, S. (2011). Predicting lexical proficiency in language learners using computational indices. Language Testing, 28(4), 561-580. [PDF]

Crossley, S. A., Salsbury, T., McNamara, D. S., & Jarvis, S. (2011). What is lexical proficiency? Some answers from computational models of speech data. TESOL Quarterly, 45(1), 182-193. [PDF]

Salsbury, T., Crossley, S. A, & McNamara, D. S. (2011). Psycholinguistic word information in second language oral discourse. Second Language Research, 27(3), 343-360. [PDF]

Crossley, S. A., Salsbury, T., & McNamara, D. S. (2010). The role of lexical cohesive devices in triggering negotiations for meaning. Issues in Applied Linguistics, 18(1), 55-80. [PDF]

Crossley, S. A., & Salsbury, T. (2010). Using lexical indices to predict produced and not produced words in second language learners. The Mental Lexicon, 5(1), 115-147. [PDF]

Crossley, S. A., Salsbury, T., & McNamara, D. S. (2010). The development of polysemy and frequency use in English second language speakers. Language Learning, 60(3), 573-605. (Language Learning Outstanding Article of the Year, 2010). [PDF]

Crossley, S. A., Salsbury, T., & McNamara, D. S. (2010). The development of semantic relations in second language speakers: A case for Latent Semantic Analysis. Vigo International Journal of Applied Linguistics, 7, 55-74. [PDF]

McNamara, D. S., Crossley, S. A., & McCarthy, P. M. (2010). Linguistic features of writing quality. Written Communication, 27(1), 57-86. [PDF]

Crossley, S. A., Louwerse, M., & McNamara, D. S. (2009). Identifying linguistic cues that distinguish text types: A comparison of first and second language speakers. Language Research, 44(2), 361-381. [PDF]

Crossley, S. A. & McNamara, D. S. (2009). Computationally assessing lexical differences in L1 and L2 writing. Journal of Second Language Writing, 17(2), 119-135. [PDF]

Crossley, S. A, Salsbury, T., & McNamara, D. S. (2009). Measuring second language lexical growth using hypernymic relationships. Language Learning, 59(2), 307-334. [PDF]

Crossley, S. A. (2008). The effects of genre analysis pedagogy: A corpus-based and situational analysis. Foreign Languages for Specific Purposes, 7, 20-35.
[PDF]

Crossley, S. A., Greenfield, J., & McNamara, D. S. (2008). Assessing text readability using cognitively based indices. TESOL Quarterly, 42 (3), 475-493. [PDF]

Crossley, S. A. & McNamara, D. S. (2008). Assessing Second Language Reading Texts at the Intermediate Level: An approximate replication of Crossley, Louwerse, McCarthy, and McNamara (2007). Language Teaching, 41(3), 409-429. [PDF]

Louwerse, M. M., Crossley, S. A., & Jeuniaux, P. (2008). What if? Conditionals in educational registers. Linguistics and Education, 19, 56-69. [PDF]

Crossley, S. A. (2007). A chronotopic approach to genre analysis: An exploratory study. English for Specific Purposes, 26(1) 4-24. [PDF]

Crossley, S. A. & Louwerse, M. M. (2007). Multi-dimensional register classification using bi-grams. International Journal of Corpus Linguistics, 12(4), 453-478. [PDF]

Crossley, S. A., Louwerse, M. M., McCarthy, P. M. & McNamara, D. S. (2007). A linguistic analysis of simplified and authentic texts. The Modern Language Journal, 91(2) 15-30. [PDF]

Crossley, S. A. (2005). Metaphorical considerations in hip-hop music: Toward a better understanding of the hip-hop generation. African American Review, 9(4) 501-512. [PDF]

Refereed Book Chapters

Kim, Y., Crossley, S., Jung, Y., Kyle, K., & Kang, S. (in press). The effects of task repetition and task  complexity on L2 lexicon use. In M. Bygate (Ed). Learning language through task repetition. Amsterdam: John Benjamins.

Crossley, S. A., & Kyle, K. (in press). Analyzing spoken and written discourse: A role for natural language processing tools. The Palgrave handbook of applied linguistics research methodology.

McNamara, D. S., Allen, L. K., Crossley, S. A., Dascalu, M., & Perret, C. A. (2017). Natural language processing and learning analytics. In G. Siemens & C. Lang (Eds.) Handbook of learning analytics and educational data mining. (pp. 93-104). Society for Learning Analytics Research (SOLAR).

Baker, R.S. Wang, Y., Paquette, L., Aleven, V., Popsecu, O., Sewall, J., Rose, C., Tomar, G., Ferschke, O., Zhang, J., Cennamo, M., Ogden, S., Condit, T., Diaz, J., Crossley, S., McNamara, D., Comer, D., Lynch, C., Brown, R., Barnes, T., Bergner, Y. (2016) A MOOC on Educational Data Mining. To appear in ElAtia, S., Zaiane, O.R., Ipperciel, D. (Eds.) Handbook of Data Mining and Learning Analytics. (pp. 55-66). Hoboken, NJ: Wiley.

Crossley, S. A. & McNamara, D. S. (2016). Educational technologies and literacy development. In S. A. Crossley and D. S. McNamara (Eds.), Adaptive Educational Technologies for Literacy Instruction. (pp. 1-12). New York: Routledge.

Crossley, S. A., Allen, L. K., & McNamara, D. S. (2016). Writing Pal: A writing strategy tutor. In S. A. Crossley and D. S. McNamara (Eds.), Adaptive Educational Technologies for Literacy Instruction. (pp. 204-224). New York: Routledge.

Frishkoff, G., Collins-Thompson, K., Nam, S., Hodges, L., & Crossley, S. A. (2016). Dynamic Support of Contextual Vocabulary Acquisition for Reading (DSCoVAR): An intelligent tutor for contextual word learning. In S. A. Crossley and D. S. McNamara (Eds.), Adaptive Educational Technologies for Literacy Instruction. (pp. 69-81).  New York: Routledge.

Crossley, S. A., Allen, L., & McNamara, D. S. (2014). A multidimensional analysis of essay writing: What linguistic features tell us about situational parameters and the effects of language functions on judgments of quality. In T. B. Sardinha and M. V. Pinto (Eds.), Multi-Dimensional Analysis, 25 years on: A Tribute to Douglas Biber. (pp. 197-238). Philadelphia, PA: John Benjamins.

Crossley, S. A., Feng, S., Cai, Z., & McNamara, D. S. (2013). Computer simulations of MRC Psycholinguistics Database word properties: Concreteness, familiarity, and imagability. In M. Daller and S. Jarvis (Eds.), Vocabulary Knowledge: Human Ratings and Automated Measures. (pp. 135-156). Philadelphia, PA: John Benjamins.

Crossley, S. A., Salsbury, T., & McNamara, D. S. (2013). Validating lexical measures using human scores of lexical proficiency. In M. Daller and S. Jarvis (Eds.), Vocabulary Knowledge: Human Ratings and Automated Measures. (pp. 105-134) Philadelphia, PA: John Benjamins.

Crossley, S. A. (2012). Detection-based approaches: Methods, theories, and applications.  In S. Jarvis and S. A. Crossley (Eds.),Approaching Language Transfer through Text Classification: Explorations in the Detection-Based Approach. (pp. 178-189). Bristol, UK: Multilingual Matters.

Crossley, S. A., & McNamara, D. S. (2012). A computational analysis of interlanguage talk: New approaches and applications. In P. M. McCarthy and C. Boonthum (Eds.), Applied natural language processing and content analysis: Identification, investigation, and resolution. (pp. 425-437). Hershey, PA: IGI Global.

Crossley, S. A., & McNamara, D. S. (2012). Detecting the first language of second language writers using automated indices of cohesion, lexical sophistication, syntactic complexity, and conceptual knowledge. In S. Jarvis and S. A. Crossley (Eds.),Approaching Language Transfer through Text Classification: Explorations in the Detection-Based Approach. (pp. 106-126). Bristol, UK: Multilingual Matters.

Jarvis, S., Bestgen, Y., Crossley, S. A., Granger, S., Paquot, M. Thewissen, J. (2012). The comparative and combined contributions of N-grams, Coh-Metrix indices, and error types in the L1 classification of learner texts. In S. Jarvis and S. A. Crossley (Eds.), Approaching language transfer through text classification: Approaching Language Transfer through Text Classification: Explorations in the Detection-Based Approach. (pp. 154-157). Bristol, UK: Multilingual Matters.

McNamara, D. S., Raine, R., Roscoe, R., Crossley, S., Jackson, T., Dai, J., Cai, Z., Renner, A., Brandon, R., Weston, J., Dempsey, K., Lam, D., Kim, L., Rus, V., Floyd, R., McCarthy, P. M., Graesser, A. C. (2012). The Writing-Pal: Natural language algorithms to support intelligent tutoring on writing strategies. In P. M. McCarthy and C. Boonthum (Eds.),Applied natural language processing and content analysis: Identification, investigation, and resolution. (pp. 298-311). Hershey, PA: IGI Global.

Weston, J. L., Crossley, S. A., & McNamara, D. S. (2012). Computational assessing human judgments of freewriting. In P. M. McCarthy and C. Boonthum (Eds.), Applied natural language processing and content analysis: Identification, investigation, and resolution.(pp. 365-382). Hershey, PA: IGI Global.

Anderson, T., & Crossley, S. A. (2011). Rue with a difference: A stylistic analysis of the rhetoric of suicide in Hamlet. In M. Ravassat & J. Culpeper (eds.), Shakespeare’s Language: Stylistic and Linguistic Approaches. (pp. 192-214). New York, NY: Continuum Press.

Refereed Conference Proceedings

Dascalu, M., Gutu, G., Ruseti, S., Paraschiv, I. C., Dessus, P., McNamara, D .S., Crossley, S., & Trausan-Matu, S. (in press). ReaderBench: A Multi-Lingual Framework for Analyzing Text Complexity. In 12th European Conference on Technology Enhanced Learning (EC-TEL 2017). Tallinn, Estonia: Springer.

Andres, J. M., Baker, R., Siemens, G., Gašević, D., Spann, C. & Crossley, S. (2017). Studying MOOC completion at scale using the MOOC Replication Framework. Proceedings of the 10th International Conference on Educational Data Mining. (pp. 338-339). [PDF]

Crossley, S.A., Barnes, T., Lynch, C., & McNamara, D.S. (2017). Linking language to math success in a blended course. Proceedings of the 10th International Conference on Educational Data Mining. (pp 180-185). [PDF]

Crossley, S., Dascalu, M., Baker, M., McNamara, D. S., & Trausan-Matu, S. (2017). Predicting success in Massive Open Online Courses (MOOC) using cohesion network analysis. In Proceeding of the 12th International Conference on Computer Supported Collaborative Learning (CSCL). (pp. 103-110). [PDF]

Crossley, S. A., & Kostyuk, V. (2017). Letting the Genie out of the lamp: Using natural language processing tools to predict math performance. In Gracia J., Bond F., McCrae J., Buitelaar P., Chiarcos C., Hellmann S. (Eds.) In Language, Data, and Knowledge (LDK 2017). Lecture Notes in Computer Science, vol 10318. Cham, Switzerland: Springer. [link]

Dascalu, M., Allen, K. A., McNamara, D. S., Trausan-Matu, S., & Crossley, S. A. (2017). Modeling comprehension processes via automated analyses of dialogism. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Proceeding of the 39th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society. (pp 1884-1889). [PDF]

Kopp, K. J., Johnson, A. M., Crossley, S. A, & McNamara, D. S. (2017). Assessing question quality using natural language processing. Proceedings of the 18th International Conference on Artificial Intelligence in Education. (pp 523-527). [link]

Crossley, S. A., Dascalu, M., & McNamara, D. S. (2017). How important is size? An investigation of corpus size and meaning in both Latent Semantic Analysis and Latent Dirichlet Allocation. In Proceedings of the 30th International Florida Artificial Intelligence Research Society (FLAIRS) Conference, (pp. 293-296). Menlo Park, CA: The AAAI Press.[PDF]

Heidari, A., D’Arienzo, M., Crossley, S.A., & Duran, N. (2017). Computational analysis of lexical and cohesion differences in deceptive language: The role of accordance. In Proceedings of the 30th International Florida Artificial Intelligence Research Society (FLAIRS) Conference, (pp. 270-275). Menlo Park, CA: The AAAI Press. [PDF]

Skalicky, S., Crossley, S.A., McNamara, D.S., and Muldner, K. (2017). Automatically identifying humorous and persuasive language produced during a creative problem-solving task. In Proceedings of the 30th International Florida Artificial Intelligence Society Conference (FLAIRS 2017), (pp. 282-287). Menlo Park, CA: The AAAI Press. [PDF]

Crossley, S. A., Liu, R., & McNamara, D. S. (2017) Predicting math performance using natural language processing tools. Proceedings of the 7th International Learning Analytics and Knowledge (LAK) Conference. (pp. 339-347).  New York, NY: ACM. [PDF]

Allen, L. K., Dascalu, M., McNamara, D.S., Crossley, S., & Trausan-Matu, S. (2016). Modeling individual differences among writers using ReaderBench. In Proceedings of the 8th annual International Conference on Education and New Learning Technologies (EduLearn) (pp. 5269–5279). Barcelona, Spain: IATED. [PDF]

Allen, L. K., Mills, C., Jacovina, M. E., Crossley, S. A., D’Mello, S. K., & McNamara, D. S. (2016). Investigating boredom and engagement during writing using multiple sources of information:  The essay, the writer, and keystrokes. Proceedings of the 6th International Learning Analytics and Knowledge (LAK) Conference. (pp. 114-123). New York, NY: ACM. [PDF]

Crossley, S. A., Dascalu, M., Trausan-Matu, S., Allen, L., & McNamara, D. S. (2016).  Document cohesion flow: Striving towards coherence. In Papafragou, A., Grodner, D., Mirman, D., & Trueswell, J.C. (Eds.) Proceedings of the 38th Annual Conference of the Cognitive Science Society. (pp. 764-769). Austin, TX: Cognitive Science Society. [PDF]

Crossley, S. A, Kyle, K., Davenport, J., & McNamara, D. S. (2016). Automatic assessment of constructed response data in a chemistry tutor. In Barnes, T., Chi, M., & Feng, M. (eds.). Proceedings of the 9th International Educational Data Mining (EDM) Society Conference. (pp. 336-340). Raleigh, NC. [PDF]

Crossley, S. A., Paquette, L., Dascalu, M., McNamara, D., & Baker, R. (2016). Combining click-stream data with NLP tools to better understand MOOC completion. Proceedings of the 6th International Learning Analytics and Knowledge (LAK) Conference. (pp. 6-14). New York, NY: ACM. [PDF]

Dascalu, M., McNamara, D.S., Crossley, S.A., & Trausan-Matu, S. (2016). Age of Exposure: A model of word learning. Proceedings of the Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI) Conference. (pp. 2928-2934) [PDF]

Dascalu, M., Popescu, E., Becheru, Alexandru, Crossley, S., & Trausan-Matu, S. (2016). Predicting academic performance based on students’ Blog and Microblog posts. Proceedings of the 11th European Conference on Technology Enhanced Learning (EC-TEL 2016) in Lecture Notes in Computer Science” (LNCS) Series. Lyon, France: Springer, (pp. 370-376). [PDF]

Popescu, Dascalu, M., & Crossley, S. A. (2016). Predicting student performance and differences in learning styles based on textual complexity indices applied on Blog and Microblog posts. A Preliminary Study. Proceedings of the 16th IEEE International Conference on Advanced Learning Technologies (ICALT), (pp. 184-188). [PDF]

Secui, A., Sirbu, D., Dascalu, M., Crossley, S., Ruseti, S., & Trausan-Matu, S. (2016) Expressing sentiments in game reviews. Proceedings of the 17th International Conference on Artificial Intelligence: Methodology, Systems, Applications, (pp. 352-355). [PDF]

Sirbu, M. D., Secui, A., Dascalu, M., Crossley, S. A., Ruseti, S., & Trausan-Matu, S. (2016). Extracting gamers’ opinions from reviews. Proceedings of the 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2016). Timisoara, Romania: IEEE, (pp. 227-232). [PDF]

Allen, L., Crossley, S. A., Snow, E., Jacovina, M., Perret, C., & McNamara, D. (2015). Am I wrong or am I right? Gains in monitoring accuracy in an intelligent tutoring system for writing. In Conati, C., Heffernan, N., Mitrovic, A., & Verdejo, M.F. (eds.). Proceedings of the Artificial Intelligence in Education (AIED) Conference, (pp. 533-536). Heidelberg, Germany: Springer. [PDF]

Allen, L., Crossley, S. A., & McNamara, D. S. (2015). Predicting misalignments between teachers’ and students’ essay scores using natural language processing tools. In Conati, C., Heffernan, N., Mitrovic, A., & Verdejo, M.F. (eds.). Proceedings of the Artificial Intelligence in Education (AIED) Conference, (pp. 529-532). Heidelberg, Germany: Springer. [PDF]

Crossley, S. A., Kim, Y., Lester, T., & Clark, S. (2015). Embodied cognition and passive processing: What hand-tracking tells us about syntactic processing in L1 and L2 speakers of English. In Dale, R., Jennings, C., Maglio, P., Matlock, T., Noelle, D., Warlaumony, A., & Yoshimi, J. (eds). Proceedings of the 37th Annual Cognitive Science Society Meeting, (pp. 495-500). [PDF]

Crossley, S. A., McNamara, D. S., Baker, R., Wang, Y., Paquette, L., Barnes, T., & Bergner, Y. (2015). Language to completion: Success in an educational data mining massive open online class. In Santos, O. C., Boticario, J. G., Romero, C., Pechenizkiy, M., Merceron, A., Mitros, P., Luna, J. M., Mihaescu, C., Moreno, P., Hershkovitz, A., Ventura, S., & Desmarais, M. (eds.) Proceedings of the 8th International Conference on Educational Data Mining, (pp. 388-392). [PDF]

Crossley, S.A., Varner, L., Snow, E., & McNamara, D. S. (2015). Pssst… Textual Features… There is more to automatic essay scoring than just you! In Baron, J., Lynch, G., & Maziarz, N. (Eds.) Proceedings of the 5th International Learning Analytics and Knowledge Conference. (pp. 203-207). New York, NY: Association for Computing Machinery. [PDF]

Crossley, S. A., Kyle, K., Allen, L, & McNamara, D. S. (2014). The importance of grammar and mechanics in writing assessment and instruction: Evidence from data mining. Stamper, J., Pardos, Z., Mavrikis, M., & McLaren, B.M. (Eds.). Proceedings of the 7th  Educational Data Mining (EDM) Conference. (pp. 300-303). Heidelberg, Berlin, Germany: Springer. [PDF]

Crossley, S. A., & McNamara, D. S. (2014). Developing component scores from natural language processing tools to assess human ratings of essay quality. Eberle, W., & Boonthum-Denecke, C. (Eds.). Proceedings of the 27th International Florida Artificial Intelligence Research Society (FLAIRS) Conference. (pp. 381-386). Menlo Park, CA: The AAAI Press. [PDF]

Roscoe, R., Crossley, S. A., Snow, E., Varner, L., & McNamara, D. S. (2014). Writing quality, knowledge, and comprehension correlates of human and automated essay scoring. Eberle, W., & Boonthum-Denecke, C. (Eds.). Proceedings of the 27th International Florida Artificial Intelligence Research Society (FLAIRS) Conference. (pp. 393-398). Menlo Park, CA: The AAAI Press. [PDF]

Crossley, S. A., Defore, C., Kyle, K, Dai, J., & McNamara, D. S. (2013). Paragraph specific N-Gram approaches to automatically assessing essay quality. In D’Mello, S. K., Calvo, R. A., & Olney, A. (Eds.) Proceedings of the 6th Educational Data Mining (EDM) Conference. (pp. 216-220). Heidelberg, Berlin, Germany: Springer. [PDF]

Crossley, S. A., Roscoe, R., & McNamara, D. S. (2013). Using automatic scoring models to detect changes in student writing in an intelligent tutoring system. In McCarthy, P. M. & Youngblood G. M., (Eds.). Proceedings of the 26th International Florida Artificial Intelligence Research Society (FLAIRS) Conference. (pp. 208-213). Menlo Park, CA: The AAAI Press. [PDF]

Crossley, S. A., Varner, L., Roscoe, R., & McNamara, D. S. (2013). Using automated indices of cohesion to evaluate an intelligent tutoring system and an automated writing evaluation system. In Lane, H. C., Yacef, K., Mostow, J., & Pavlik, P. (Eds.). Proceedings of the Artificial Intelligence in Education (AIED) Conference. (pp. 269-278). Heidelberg, Germany: Springer. [PDF]

Crossley, S. A., Varner, L., & McNamara, D. S. (2013). Cohesion-based prompt effects in argumentative writing. In McCarthy, P. M. & Youngblood G. M., (Eds.). Proceedings of the 26th International Florida Artificial Intelligence Research Society (FLAIRS) Conference. (pp. 202-207). Menlo Park, CA: The AAAI Press. [PDF]

Kyle, K., Crossley, S.A., Dai, J., & McNamara, D.S. (2013). Native language identification: A key n-gram category approach. In J. Tetreault, J. Bursteain, & C. Leacock (Eds.), Proceedings of the North American Association for Computational Linguistics (pp. 242-250). The Association for Computational Linguistics. [PDF]

Collins-Thompson, K., Frishkoff, G., & Crossley, S. A. (2012). Definition response scoring with probabilistic ordinal regression. In B. Chang, S. Tan, T. Matsui, G. Biswas, LH Wong, T. Hirashima, & W. Chen (Eds).Proceedings of the 20th International Conference on Computers in Education (ICCE). National Institute of Education, Nanyang Technological University, Singapore. [PDF]

Brandon, R., Crossley, S. A., & McNamara, D. S. (2012). A linguistic analysis of expert-generated paraphrases. In McCarthy, P. M. & Youngblood G. M., (Eds.). Proceedings of the 25th International Florida Artificial Intelligence Research Society (FLAIRS) Conference. (pp. 268-271). Menlo Park, CA: The AAAI Press. [PDF]

Crossley, S. A., Cai, Z., & McNamara, D. S. (2012). Syntagmatic, paradigmatic, and automatic n-gram approaches to assessing essay quality. In McCarthy, P. M. & Youngblood G. M., (Eds.). Proceedings of the 25th International Florida Artificial Intelligence Research Society (FLAIRS) Conference. (pp. 214-219) Menlo Park, CA: The AAAI Press. [PDF]

Roscoe, R., Kugler, D., Crossley, S. A., Weston, J., & McNamara, D. S. (2012). Developing pedagogically-guided threshold algorithms for intelligent automated essay feedback. In McCarthy, P. M. & Youngblood G. M., (Eds.). Proceedings of the 25th International Florida Artificial Intelligence Research Society (FLAIRS) Conference (pp. 466-471). Menlo Park, CA: The AAAI Press. [PDF]

Crossley, S. A., & McNamara, D. S. (2011). Text coherence and judgments of essay quality: Models of quality and coherence. In L. Carlson, C. Hoelscher, & T. F. Shipley (Eds.), Proceedings of the 29th Annual Conference of the Cognitive Science Society. (pp. 1236-1241). Austin, TX: Cognitive Science Society.
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Crossley, S. A., Roscoe, R. D., & McNamara, D. S. (2011) Predicting human scores of essay quality using computational indices of linguistic and textual features. Proceedings of the 15th International Conference on Artificial Intelligence in Education. [PDF]

Feng, S., Cai, Z., Crossley, S. A., & McNamara, D. S. (2011). Simulating human ratings on word concreteness. In R. C. Murray & P. M. McCarthy (Eds.), Proceedings of the 24thInternational Florida Artificial Intelligence Research Society (FLAIRS) Conference (pp. 245-250). Menlo Park, CA: AAAI Press.
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Raine, R. B., Mintz, L., Crossley, S. A., Dai, J., & McNamara, D. S. (2011). Text box size, skill, and iterative practice in a writing task. In R. C. Murray & P. M. McCarthy (Eds.),Proceedings of the 24th International Florida Artificial Intelligence Research Society (FLAIRS) Conference (pp. 537-542). Menlo Park, CA: AAAI Press. [PDF]

Roscoe, R. D., Crossley, S. A., Weston, J. L., & McNamara, D. S. (2011). Automated assessment of paragraph quality: Introductions, body, and conclusion paragraphs. In R. C. Murray & P. M. McCarthy (Eds.), Proceedings of the 24thInternational Florida Artificial Intelligence Research Society (FLAIRS) Conference (pp. 281-286). Menlo Park, CA: AAAI Press. [PDF]

Roscoe, R. D., Varner, L. K., Cai, Z., Weston, J. L., Crossley, S. A., & McNamara, D. S. (2011). Internal usability testing of automated essay feedback in an intelligent writing tutor. In R. C. Murray & P. M. McCarthy (Eds.),Proceedings of the 24th International Florida Artificial Intelligence Research Society (FLAIRS) Conference (pp. 543-548). Menlo Park, CA: AAAI Press. [PDF]

Rus, V., Feng, S., Brandon, R., Crossley, S. A., & McNamara, D. S. (2011). A linguistic analysis of student-generated paraphrases. In R. C. Murray & P. M. McCarthy (Eds.),Proceedings of the 24th International Florida Artificial Intelligence Research Society (FLAIRS) Conference (pp. 293-298). Menlo Park, CA: AAAI Press. [PDF]

Weston, J. L., Crossley, S. A., McCarthy, P. M., & McNamara, D. S. (2011). Number of words versus number of ideas: Finding a better predictor of writing quality. In R. C. Murray & P. M. McCarthy (Eds.), Proceedings of the 24th International Florida Artificial Intelligence Research Society (FLAIRS) Conference (pp. 335-340). Menlo Park, CA: AAAI Press. [PDF]

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. [PDF]

Crossley, S. A., & McNamara, D. S. (2010). Interlanguage talk: What can breadth of knowledge features tell us about input and output differences? In H.W. Guesgen and C. Murray (Eds.).  Proceedings of the 23rd International Florida Artificial Intelligence Research Society (229-235). Menlo Park, CA: The AAAI Press. [PDF]

Weston, J. L., Crossley, S. A., & McNamara, D. S. (2010). Towards a computational assessment of freewriting quality.  In H.W. Guesgen and C. Murray (Eds.). Proceedings of the 23rd International Florida Artificial Intelligence Research Society (FLAIRS) Conference (pp. 283-288). Menlo Park, CA: The AAAI Press. [PDF]

Crossley, S. A., Boggess, G., & Salsbury, T. (2009). Exploring Lexical Network Development in Second Language Learners. . In C.H. Lane & H.W. Guesgen (Eds.), Proceedings of the 22nd International Florida Artificial Intelligence Research Society (pp. 225-230).Menlo Park, CA: The AAAI Press. [PDF]

Duran, N. D., Crossley, S.A., Hall, C., McCarthy, P.M., & McNamara, D.S. (2009). Expanding a catalogue of deceptive linguistic features with NLP technologies. In C.H. Lane & H.W. Guesgen (Eds.), Proceedings of the 22ndInternational Florida Artificial Intelligence Research Society (pp. 243-248). Menlo Park, CA: The AAAI Press. [PDF]

Crossley, S. A., Salsbury, T. McCarthy, P. M. & McNamara, D. S. (2008). Using Latent Semantic Analysis to explore second language lexical development. In D. Wilson & G. Sutcliffe (Eds.), Proceedings of the 21stInternational Florida Artificial Intelligence Research Society (pp. 136-141). Menlo Park, California: AAAI Press. [PDF]

Crossley, S. A., Salsbury, T., McCarthy, P. M., & McNamara, D. S. (2008) LSA as a measure of second language natural discourse. In V. Sloutsky, B. Love, and K. McRae (Eds.), Proceedings of the 30th annual conference of the Cognitive Science Society (pp. 1906-1911). Washington, D.C.: Cognitive Science Society.
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McCarthy, P. M., Rus, V., Crossley, S. A., Graesser, A. C., & McNamara, D. S. (2008). Assessing forward-, reverse-, and average entailment indices on natural language input from the intelligent tutoring system, iSTART. In D. Wilson & G. Sutcliffe (Eds.), Proceedings of the 21st International Florida Artificial Intelligence Research Society (pp. 165-170). Menlo Park, California: AAAI Press. [PDF]

Crossley, S. A., Dufty, D. F., McCarthy, P. M., & McNamara, D. S. (2007). Toward a new readability: A mixed model approach. In D.S. McNamara and G. Trafton (Eds.), Proceedings of the 29th annual conference of the Cognitive Science Society (pp. 197-202). Austin, TX: Cognitive Science Society. [PDF]

Crossley, S. A., McCarthy, P. M. & McNamara, D. S. (2007). Discriminating between second language learning text-types. In D. Wilson & G. Sutcliffe (Eds.), Proceedings of the 20th International Florida Artificial Intelligence Research Society (pp. 205-210). Menlo Park, California: AAAI Press. [PDF]

McCarthy, P. M., Rus, V., Crossley, S. A., Bigham, S. C., Graesser, A. C. & McNamara, D. S. (2007). Assessing entailer with a corpus of natural language from an intelligent tutoring system. In D. Wilson & G. Sutcliffe (Eds.),Proceedings of the 20th International Florida Artificial Intelligence Research Society (pp. 247-252). Menlo Park, California: AAAI Press. [PDF]

Crossley, S. A., McCarthy, P. M., Lewis, G. A., Dufty, D. F., Louwerse, M. M. & McNamara, D. S. (2006). Detecting manipulated second language learning texts. In R. Sun & N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 2463). Mahwah, New Jersey: Lawrence Erlbaum Associates, Inc. [PDF]

Louwerse, M. M. & Crossley, S. A. (2006). Dialog act classification using N-Gram algorithms.  In G. Sutcliffe & R. Goebel (Eds.), Proceedings of the International Florida Artificial Intelligence Research Society (pp. 758-763). Menlo Park, California: AAAI Press. [PDF]