CA.SFU.FAS.UCC/Papers:2000-9

New Course Proposal - KIN 304 Inquiry and Measurement in Kinesiology

David Goodman and Richard Ward, School of Kinesiology

September 26, 2000

Calendar Information

Course Number: KIN 304

Course Title: Inquiry and Measurement in Kinesiology

Credit Hours: 3 Vector: 3-1-0

Course Description

This course covers the evaluation of measurement quality, test construction and assessment, and computer techniques for data capture and signal processing relevant to issues in Kinesiology. Prerequisite statistical knowledge will be put into practice when discussing typical research designs, modeling and hypothesis testing in Kinesiology.

Prerequisite: KIN 142, 201, 205, 207, and STAT 201.

Corequisite: None.

Special Instructions: None.

Course(s) to be dropped if this course is approved: Kin 203 (Computer Applications in Kinesiology) will be dropped in the same calendar that Kin 304 is added.

Rationale for Introduction of this Course

Measurement forms an important basis of information in kinesiology, and many of the career paths our students take require considerable knowledge of the measurement process and application. The material covered in Kin 203 (Computer Applications in Kinesiology) is obsolete because students now know more about computers when they enter the Kinesiology program. What is needed is a course that deals with issues related to data acquisition, treatment, evaluation and hypothesis testing.

Will this be a required or elective course in the curriculum; probable enrolment when offered?

Elective course with approximately 30-45 students for each of the offerings.

Scheduling and Registration Information

Indicate Semester and Year this course would be first offered and planned frequency of offering thereafter.

Fall 2001; once or twice a year.

Which of your present CFL faculty have the expertise to offer this course? Will the course be taught by sessional or limited term faculty?

Dr. Richard Ward, Dr. David Goodman, and Dr. Dan Weeks.

Are there any proposed student fees associated with this course other than tuition fees?

No.

Does this course duplicate the content of a previously approved course to such an extent that students should not receive credit for both courses. If so, please specifv.

No.

Resource Implications

Note: Senate has approved (S.93-11) that no new course should be approved by Senate until funding has been committed for necessary library materials. Each new course proposal must be accompanied by a library report and, if appropriate, confirmation that funding arrangements have been addressed.

Provide details on how existing instructional resources will be redistributed to accommodate this new course. For instance, will another course be eliminated or will the frequency of offering of other courses be reduced; are there changes in pedagogical style or class sizes that allow for this additional course offering.

Kin 203 is being dropped from the Calendar, thus freeing the required teaching resources.

Does the course require specialized space or equipment not readily available in the department or university, and if so, how will these resources be provided?

No.

Does this course require computing resources (e.g. hardware, software, network wiring, use of computer laboratory space) and if so, describe how they will be provided.

This course will be run with the only major resources required being a lecture theatre with computer projection and network connection and the resources of the University Computer Teaching and Assignment Labs. Thus, it is a matter of the scheduling of a lecture theater and PC Computer Teaching Lab and Assignment Lab Time. Existing departmental hardware resources are sufficient to meet the needs for those sections of the course in which demonstrations are required. There may be some need for additional software purchases.

Course Outline

Kin 304: Inquiry and Measurement in Kinesiology

Course Description

This course covers the evaluation of measurement quality, test construction and assessment, and computer techniques for data capture and signal processing relevant to issues in Kinesiology. Prerequisite statistical knowledge will be put into practice when discussing typical research designs, modeling and hypothesis testing in Kinesiology.

Prerequisites

KIN 142, 201, 205, 207, and STAT 201.

Lectures and Tutorials

The course will have three hours of lecture each week plus a one hour tutorial in a computer teaching lab. In addition University Assignment Lab time will be reserved for each student.

Text

Due to the breadth of the course the required text will be a composite of documents downloadable from the course website and a custom courseware package purchased from the University bookstore.

Evaluation

Tutorials

Tutorials will be held in a University Computer Teaching Lab. The T.A. will address skills and evaluation procedures necessary for the completion of the marked assignments. Numerous example data sets and analyses will be used.

Assignments

These assignments will require manipulation of real data using speadsheet software, in the areas of quality assessment of data, treatment and conditioning of data, modeling and hypothesis testing. Assignments will also focus on skills required to critique research papers.

Lecture Topics

Philosophy of Science:
A brief discussion of the philosophy of science. Discussion of the primary writings of selected philosophers (e.g., Popper, Whitehead, Kuhn) giving students an appreciation for the history of science and how it proceeds. A section on inquiry in science will be included since “the question” precedes the need for measurement.
Principles of Measurement:
With a review of basic statistics essential to measurement theory, validity, reliabililty, issues in measurement and assessment, test construction and assessment, norms & scales.
Questionnaires:
Design, testing, administration and analysis of responses.
Computer Techniques for Data Capture and Signal Processing:
The computer is now ubiquitous in all phases of measurement and analysis. This section will focus on analogue to digital conversion and digital signal processing, and will include topics such as sampling rate and bits/conversion, filtering, and digital signal processing techniques. Examples will be drawn from different areas of kinesiology to illustrate the techniques.
Modeling:
Mathematical modeling is an important tool in kinesiology. This section will include a discussion of both deterministic models and probabilistic or stochastic models with specific examples from areas such as diabetes research, kinanthropometry, and motor control.
Design of Experiments & Hypothesis Testing:
The kind of science one is doing impacts on the nature of the appropriateness of the methodology and hypothesis testing. This section provides a unique opportunity to discuss some of the techniques used in the various kinesiology labs and the measurement problems they present. The students' task will be to examine research papers representative of many different areas in the school (e.g., cancer research, ergonomics, biomechanics, areo-space physiology, cellular biology) Discussion will centre around: the nature of the question, the appropriateness of the experimental design and analysis, and unique measurement issues encountered.

Building upon prerequisite statistical knowledge there will be a discussion of typical research designs in Kinesiology and the appropriate statistical analysis. This will entail putting into practice knowledge of descriptive vs inferential statistics, parametric vs non parametric statistics, univariate vs multivariate statistics, in application to analysis of real data. Although the majority of this course can be completed using only MS EXCEL, this section will require other student accessible statistics packages (SPSS, Minitab).

Library Resources for New Courses

KIN 304 – Inquiry and Measurement in Kinesiology

Are the current SFU library resources adequate for this course?

Yes.

What additional library resources are essential for the offering of this course?

None.

What additional library resources, if any, would be desirable but not essential for the offering of this course?

None.