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Graduate Course Proposal Form Submission Detail - LIN7639
Tracking Number - 5200

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Current Status: Approved by SCNS - 2015-12-01
Campus: Tampa
Submission Type: New
Course Change Information (for course changes only):
Comments: GC Approved 10/12/15. To USF 10/12/15. To SCNS 10/28/15. Approved effective 12/1/15

Detail Information

  1. Date & Time Submitted: 2015-02-21
  2. Department: World Languages
  3. College: AS
  4. Budget Account Number: TPA 124100 10000 000000 0000000
  5. Contact Person: Amy Thompson
  6. Phone: 42548
  7. Email:
  8. Prefix: LIN
  9. Number: 7639
  10. Full Title: Quantitative Methods in Applied Linguistics
  11. Credit Hours: 3
  12. Section Type: C - Class Lecture (Primarily)
  13. Is the course title variable?: N
  14. Is a permit required for registration?: N
  15. Are the credit hours variable?: N
  16. Is this course repeatable?: N
  17. If repeatable, how many times?: 0
  18. Abbreviated Title (30 characters maximum): Quant. Mthd in Applied Ling.
  19. Course Online?: C - Face-to-face (0% online)
  20. Percentage Online: 0
  21. Grading Option: R - Regular
  22. Prerequisites:
  23. Corequisites:
  24. Course Description: This course is intended to help you develop as applied linguistics scholars with regards to quantitative analyses using SPSS.

  25. Please briefly explain why it is necessary and/or desirable to add this course: Needed for new program/concentration/certificate
  26. What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service? This will be a required course in the proposed Ph.D. in Applied Linguistics
  27. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times? Yes, 1 time
  28. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.) Course instructor would need to hold a Ph.D. in applied linguistics, second language studies, or closely related field.
  29. Objectives: This course is intended to help you develop as applied linguistics scholars with regards to quantitative analyses using SPSS. The classes are organized in a workshop style format, giving you opportunities for guidance and feedback on performing a variety of quantitative analyses commonly used in applied linguistics research. The topics covered include correlations, t-test, various ANOVA types (one-way, factorial, and repeated-measures), issues regarding power and effect size, multiple regression, and ANCOVA, among others. You are expected to be actively engaged with your peers inside and outside of the classroom. No research happens in isolation: as researchers, we always rely on help, support, and assistance from others. Thus, collegial collaboration is expected from all students in this class.
  30. Learning Outcomes: The objectives of this course are as follows:

    1) To become familiar with performing a variety of quantitative analyses in SPSS

    2) To become familiar with quantitative analyses, broadly construed

    3) To actively engage in research design using quantitative methods

    4) To be able to interpret, write about, and discuss a wide range of quantitative measures

  31. Major Topics: The topics covered include correlations, t-test, various ANOVA types (one-way, factorial, and repeated-measures), issues regarding power and effect size, multiple regression, and ANCOVA, among others.
  32. Textbooks: Larson-Hall, J. (2010). A guide to doing statistics in second language research using SPSS. New York, NY: Routledge.
  33. Course Readings, Online Resources, and Other Purchases: Loewen, S. & Gonulal, T. (forthcoming). Exploratory factor analysis and principal components analysis. In L. Plonsky (Ed.), Advancing quantitative methods in second language research. New York: Routledge.

    Plonsky, L., & Oswald, F. L. (in press). How big is ‘big’? Interpreting effect sizes in L2 research. Language Learning.

  34. Student Expectations/Requirements and Grading Policy: Course expectations: 2%

    Idea for final project: 3%

    Meeting to discuss final project: 5%

    Analyses run in class and discussion: 35% (10 content classes at 3.5% each)

    Homework: 35% (10 homework assignments at 3.5% each)

    Final project: 20%

  35. Assignments, Exams and Tests: Course expectations: 2%

    In lieu of meeting the first day of class, you will post a brief summary of what you perceive your strengths and weaknesses to be regarding quantitative analyses, and what you hope to learn from this class. I will check these from England and use this to count for your first day attendance.

    Idea for final project: 3%

    Before our regular meeting time on Week 9, October 22nd, you will need to write a brief summary of your final project and post it on Canvas. Please post as a Word document so that I can make comments directly on your paper.

    Meeting to discuss final project: 5%

    During Week 13 (replacing the typical November 19th class date), I will meet with each of you individually to discuss your final projects. To this meeting, you will need to bring a draft of what you have done for your project, as well as a list of specific questions that you have about your project. I anticipate that each of these meetings should take approximately 30-45 minutes, although the length may vary depending on the complexity of the specific project. Please book an appointment on my booking website. I will open additional time slots that week to be able to accommodate everyone.

    Analyses run in class and discussion: 35% (10 content classes at 3.5% each)

    This class is in a workshop format. Thus, attendance and participation are a large part of the class. If you do need to miss class for any reason (even excused absences), you are still responsible for completing the work done in class (to be turned in before the next class period). Each individual “workshop” (i.e. class) is worth 3.5% of your final grade.

    Homework: 35% (10 homework assignments at 3.5% each)

    Each content class will have a homework assignment to reinforce the content learned. These assignments will mostly be in the form of using an additional data set to perform the analysis done in class, as well as to do a write-up of the analysis as if you were going to publish the results. However, other types of homework will be assigned as needed. The homework is always due at the beginning of the following class.

    Final project: 20%

    We will discuss the final project together in class. Essentially, I would like you all to do a final project that would specifically benefit your program of study in some way. If you have data to analyze, it would be a good idea to pick a project revolving around that. If you need more practice with a specific type of analysis but don’t have data, we can find you some data to analyze. If you would like to do a research design based on quantitative methods, this would also be an option. One requirement, however, is that you may not work on a project that you are doing for another class. Start thinking about what type of project you would like to do, and we can have class and individual discussions as the semester progresses. You will lead a discussion of your final project during the last day of class (December 3rd).

  36. Attendance Policy: All students are expected to attend and actively participate in class. Additionally, students are expected to come to class on time and stay for the whole class. You are expected to do all of the readings before class, and to make every effort to contribute meaningfully to class discussions. Absence from class, arriving late, or leaving early from class significantly affects your opportunities for learning. If you miss more than two classes, I reserve the right to lower your grade, and arriving more than 10 minutes late or leaving more than 10 minutes early will count as missing half of the class. For emergencies that require you to miss class, please provide documentation for your absence. The following is the USF policy on absences: “Acceptable reasons for scheduled absences include observation of religious holy days, court-imposed legal obligations (e.g., jury duty), special requirements of other courses and university-sponsored events (e.g., performances, athletic events), and requirements of military service. Employment schedules, athletic training and practice schedules, and personal appointments are not valid reasons for scheduled absences.”

    Course Attendance at First Class Meeting – Policy for Graduate Students: For structured courses, 6000 and above, the College/Campus Dean will set the first-day class attendance requirement. Check with the College for specific information. This policy is not applicable to courses in the following categories: Educational Outreach, Open University (TV), FEEDS Program, Community Experiential Learning (CEL), Cooperative Education Training, and courses that do not have regularly scheduled meeting days/times (such as, directed reading/research or study, individual research, thesis, dissertation, internship, practica, etc.). Students are responsible for dropping undesired courses in these categories by the 5th day of classes to avoid fee liability and academic penalty. (See USF Regulation – Registration - 4.0101,

    Attendance Policy for the Observance of Religious Days by Students: In accordance with Sections 1006.53 and 1001.74(10)(g) Florida Statutes and Board of Governors Regulation 6C-6.0115, the University of South Florida (University/USF) has established the following policy regarding religious observances: (

    In the event of an emergency, it may be necessary for USF to suspend normal operations. During this time, USF may opt to continue delivery of instruction through methods that include but are not limited to: Blackboard, Elluminate, Skype, and email messaging and/or an alternate schedule. It’s the responsibility of the student to monitor Blackboard site for each class for course specific communication, and the main USF, College, and department websites, emails, and MoBull messages for important general information.

  37. Policy on Make-up Work: Late work policy

    I don’t expect work to be turned in late. That being said, learning from experience, there are a few times each semester when students ask to turn in an assignment late. In order to standardize the late work consequences, the following guidelines will apply: 1. Work turned in from 1 minute to 24 hours late can receive a maximum score of 85% of the possible points. 2. Work turned in 24 hours after the due date can receive a maximum score of 50% of the possible points. 3. No late work will be accepted after two weeks.

    USF policies

    Plagiarism is intentionally or carelessly presenting the work of another as one’s own. It includes submitting an assignment purporting to be the student’s original work which has wholly or in part been created by another person. It also includes the presentation of the work, ideas, representations, or words of another person without customary and proper acknowledgment of sources. Students must consult with their instructors for clarification in any situation in which the need for documentation is an issue, and will have plagiarized in any situation in which their work is not properly documented.


    1. Every direct quotation must be identified by quotation marks or appropriate indentation and must be properly acknowledged by parenthetical citation in the text or in a footnote or endnote.

    2. When material from another source is paraphrased or summarized in whole or in part in one’s own words, that source must be acknowledged in a footnote or endnote, or by parenthetical citation in the text.

    3. Information gained in reading or research that is not common professional knowledge must be acknowledged in a parenthetical citation in the text or in a footnote or endnote.

    4. This prohibition includes, but is not limited to, the use of papers, reports, projects, and other such materials prepared by someone else. (from

    Assignments that are submitted online are subject to being submitted to the Turnitin system. Punishment for Academic Dishonesty will depend on the seriousness of the offense and may include receipt of an “F” with a numerical value of zero on the item submitted, and the “F” shall be used to determine the final course grade. It is the option of the instructor to assign the student a grade of F or FF (the latter indicating dishonesty) in the course.

  38. Program This Course Supports: Proposed program for a Ph.D. in applied linguistics
  39. Course Concurrence Information: MA in Linguistics: ESL in WLE

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