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We recently sent out a surface mailing of the Survey of Computational Linguistics courses for the Association for Computational Linguistics. Much to my dismay, I just discovered that some of the questionnaires were collated and stapled incorrectly. (In the incorrect versions, the order of pages in the stapled copy was 214365 instead of 123456.) I apologize for this error. Here is the on-line version of the survey: [---------------------------------------------------------------------- To: Instructors of Classes in Computational Linguistics As a follow-on to the Directory of Graduate Programs recently compiled by Martha Evens, the Association for Computational Linguistics will publish a new edition of the Survey of Computational Linguistics Courses. This is a revised version of the 1986 survey, published in Computational Linguistics (vol. 12) by Robin Cohen, which is intended to be a systematic compilation of syllabi from individual classes that teach computational linguistics (i.e., it is not an enumeration of classes taught in CL programs as in the Directory of Graduate Programs). The new version of the survey will be published in the Computational Linguistics journal in 1993. We are eager to include two types of classes: those that teach computational linguistics as the sole topic and those that teach computational linguistics as one of several topics. The survey will allow us to share with colleagues ideas on how to teach computational linguistics. It will also provide an idea of how the field of computational linguistics is being portrayed to potential new researchers. Our listing will include the name and address of the University and Department(s) offering the class, the name and number of the class, the type of class, and information about the syllabus (e.g., topics, texts used, software used, format, workload, enrollment, duration, frequency, and assistance). In addition it will include some statistics on the responses (i.e., total number of classes having particular characteristics) and a bibliography of the most frequently cited references. We would appreciate your response to the survey as soon as possible. The intention is to complete the report by early 1993. You may send information electronically to: cl-surveyMail to author|Respond to list|Read more issues|LINGUIST home page|Top of issueumiacs.umd.edu or by mail: Ms. Sandy Tsue CL-SURVEY Institute for Advanced Computer Studies A.V. Williams Building University of Maryland College Park, MD 20742 USA (Electronic transmission is preferred.) Thank you very much for your time. Sincerely, Bonnie J. Dorr [---------------------------------------------------------------------- SURVEY OF COMPUTATIONAL LINGUISTICS COURSES INSTRUCTIONS This survey, originally designed by Robin Cohen, and now revised by Bonnie Dorr, attempts to gather information as painlessly as possible for both respondents and surveyor. The primary change that has been made since this survey was last conducted is that it now incorporates questions about different types of software that people use in their CL courses. Brief answers are solicited to the questions that follow. For multiple choice questions, simply type in the appropriate answer(s) from the list. For open-ended questions, use sentence fragments separated by semicolons. For illustration, a sample response is provided after the questionnaire. If possible, return your response electronically as one file of question numbers and answers, using the message header "ACL Survey Response." Hardcopy is acceptable as well. Feel free to include a copy of course description handouts, if available, for filing with the ACL. Regrettably, we will not be able to transcribe syllabi for the journal survey, but these could serve as the basis for a more extended treatment later. Note: If you have taught your course a number of times, respond according to the latest version of the course. In Q12, you may allude to topics covered and techniques used in previous versions. [ ---------------------------------------------------------------------- CONTROL INFORMATION Name: Department: Institution: Address: Net address: Name and number of course: LEVEL A. Is the course - undergraduate? - graduate? - cross-listed, undergraduate and graduate? CL STATUS B. In any given year that you teach this course, is it a course in computational linguistics (CL) or is CL just one of several topics covered? - only CL - topics other than CL Note: Respond to the remainder of the questionnaire with respect to the computational linguistics part of the course, only. ACL SURVEY QUESTIONS TOPICS Q1. What topics are covered in the course? Suggestion: list the topics, one per line, in the order they are addressed in the course. Use brief summaries of the topic name, followed by names of researchers used as references for each topic in parentheses, where appropriate e.g., lexical acquisition and use of corpora (Boguraev & Briscoe, 1987; Zernik, 1990). REFERENCES Q2. What kinds of reference materials are used in the course? - course text(s); specify author & name (publisher & year, if known) - recommended reading texts; specify as above - papers on various topics; specify if different from those in Q1 Note: If your texts are not written in English, please provide a brief English translation of the title. FORMAT Q3. What format of teaching is used? - formal lectures - paper presentations by professor - paper presentations by students - guest lectures - open discussions - other; please specify WORKLOAD Q4. What workload/method of assessment is used in the course? - midterm exam(s) - final exam - assignments with programming - assignments without programming? - course project - class presentations - other; please specify Note: You may provide further details--e.g., midterm exam: take-home, no programming; class presentations: including one on project topic. SOFTWARE WRITTEN BY STUDENTS Q5. Which of the following do students write? - parsers - generators - morphological processors - tagging programs - discourse processors - language translators - ATNs - semantic network processors - lexical-semantic processors - knowledge-based processors - parallel processors - connectionist processors - statistical processors - other; please specify - none SOFTWARE PROVIDED TO STUDENTS Q6. Which of the following are provided for students? (Label them C if commercial source, N if non-commercial outside source, H if built in house; also specify type, e.g., unification parser, chart parser, etc.) - parsers - generators - morphological processors - tagging programs - discourse processors - language translators - ATNs - semantic network processors - lexical-semantic processors - knowledge-based processors - parallel processors - connectionist processors - statistical processors - grammars - lexicons - corpora - semantic networks - data bases - knowledge bases - other; please specify - none SOFTWARE AVAILABLE FOR DISTRIBUTION Q7. If you've developed software and distribute it, please specify type (e.g., grammars, lexicons, parsers, generators, etc.) and mode (e.g., by diskette, tape, cdrom, anonymous ftp (give addresses), etc.). ENROLLMENT Q8. About how many people take the course each time it is offered? DURATION Q9. Does the course last one term or a full year? - one term - full year FREQUENCY Q10. How often is the course offered? - more than once per year - once per year - every other year - occasionally ASSISTANCE Q11. Are there teaching assistants/markers assigned to the course? - yes; conduct tutorial sessions - yes; only mark and hold office hours - no - other; please specify COMMENTS Q12. Include here any other comments about the course--what you would have liked to do ideally, what you plan for the future, what lessons you've learned. [ ------------------------- Sample response ------------------------ Name: Bonnie J. Dorr Department: Computer Science Institution: University of Maryland Address: A.V. Williams Building, College Park, MD 20742 Net Address: bonnie
cs.umd.edu Course: Computational Linguistics (CMSC 828) Level(A): graduate, cross-listed in linguistics Status(B): CL only Q1. TOPICS The course is divided into 3 sections: (1) Syntax, (2) Lexicon, and (3) Machine Translation and Generation. The course outline is as follows: - Introduction to CL: techniques and analytical tools for comparing linguistic theories and comparing computational practice; levels of representation and their importance in a computational theory. - Syntax: introduction to basic concepts and theories; bottom-up vs. top-down parsing; Earley algorithm; Tomita's algorithm; ATN's. (Sells, 1985; Kay in "Readings," 1986; Earley, 1970; Tomita, 1987; Woods, 1970; Kaplan, 1972.) - Contemporary syntactic models: government-binding theory; principle-based parsing; deterministic parsing; unification-based approaches; GPSG; LFG. (Berwick & Fong, 1990; Marcus in "Readings," 1986; Berwick & Weinberg, 1984; Sells, 1985; Shieber, 1986; Kaplan & Bresnan, 1982.) - Lexicon: lexical representations; semantic roles; primitives; case frames; thematic relations; predicate-argument structure; conceptual dependencies; spatial fields; nonspatial fields; compositionality; linking routines. (Gruber, 1967; Fillmore, 1968; Jackendoff, 1972, 1983; Schank, 1973; Dorr, 1991.) - Lexical Acquisition: non-representational vs. representational approaches; statistical methods; use of corpora; acquisition of syntactic information; bootstrapping semantics from syntax. (Boguraev & Briscoe, 1987; Klavans & Tzoukermann, 1990; Church & Hanks, 1990; Zernik, 1990; Pustejovsky, 1987; Hindle, 1990; Brent, 1991.) - Machine translation and generation: basic theory and technology; major characteristics and tradeoffs; mapping techniques; problems in MT and generation; divergences; mismatches; lexical selection; syntactic realization; parameterization. (Slocum, 1988; Thurmair, 1990; Kaplan et al., 1989; Abeille et al., 1990; Arnold & Sadler, 1990; Lindop & Tsujii, 1991; Barnett et al., 1991; Dorr, 1991.) Q2. REFERENCES No required texts. Papers on various topics (see Q1) are assigned on a weekly basis. Some reading texts are recommended: - Allen, J., Natural Language Understanding, Benjamin-Cummings, New York, NY, 1987. - Berwick, R., and Weinberg, A., The Grammatical Basis of Linguistic Performance, MIT Press, Cambridge, MA, 1984. - Grosz, B., K. Sparck-Jones, and B. Webber, Readings in Natural Language Processing, Morgan-Kaufman, Los Altos, CA, 1986. - Hutchins, W., Machine Translation: Past, Present, Future, Ellis Horwood, Chichester, England, 1986. - Sells, P., Lectures on Contemporary Syntactic Theories, University of Chicago Press, CLSI, Chicago, IL, 1985. - Zernik, U. (ed.), Lexical Acquisition: Using on-line Resources to Build a Lexicon, Lawrence Erlbaum, Hillsdale, NJ, 1987. Q3. FORMAT - formal lectures - open discussions - paper presentations by students - two guest lectures Q4. WORKLOAD - 2-4 assigned readings per week - One written assignment - One programming lab - Class presentation - Final term paper Q5. SOFTWARE WRITTEN BY STUDENTS - simple generator and lexical-semantic processor for a language translation program - small grammar and lexicon Q6. SOFTWARE PROVIDED TO STUDENTS - parser (N; Marcus Parser) - grammar (N; Marcus style rules) Q7. SOFTWARE AVAILABLE FOR DISTRIBUTION - none Q8. ENROLLMENT - 20 Q9. DURATION - one semester (14 weeks, 2-1/2 hours/week) with one semester follow-on taught in the linguistics department (LING 819). Q10. FREQUENCY - every other year Q11: ASSISTANCE - none. Q12: COMMENTS - The goal of the course is to introduce topics, issues, and theories in computational linguistics, to relate the field to linguistics and AI, and to provide the background necessary for analysis and evaluation of computational models of natural language understanding, generation, and translation. - The distribution of students is approximately 60% computer science, 30% linguistics, and 10% engineering. - Students work in groups of 4 for the laboratory. The goal is to allow linguists and computer scientists to be able to benefit from each other's knowledge while also giving students a chance to have hands-on experience with some of the concepts that are presented in class at a more abstract level. A minimal amount of programming in Lisp is expected. - Sample topics chosen by the students for final papers include syntactic models of parsing, logic programming approaches to generation, connectionist processing models, speech processing models, knowledge representation, lexical semantics, and machine translation. Students are expected to compare and critique different approaches to natural language processing and to give a 20 minute in-class presentation of their paper.