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IE 486 Work Analysis & Design II

IE 486 Work Analysis & Design II. Exam 2 Review Dr. Vincent G. Duffy Friday, March 23, 2007. IE486 – Material on Exam 2. You’ll be asked to answer somewhere between 30 and 35 questions (M.C. and short answer). Lecture 15 Work Physiology (ch.12)

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IE 486 Work Analysis & Design II

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  1. IE 486 Work Analysis & Design II Exam 2 Review Dr. Vincent G. Duffy Friday, March 23, 2007

  2. IE486 – Material on Exam 2 • You’ll be asked to answer somewhere between 30 and 35 questions (M.C. and short answer). • Lecture 15 Work Physiology (ch.12) • Lecture 14 Anthropometry & Workspace Design (finish) (ch.10) • Lecture 13 Biomechanics (ch.11) • Lecture 12 Exam Review & Anthropometry (start) (ch.10) • Lecture 11 Design Evaluation & Methods (ch.2, 3) • Lecture10 Structured questionnaires: more examples (Lab 3) • Lecture 9: Selection & Training (Ch.18) • Lecture 8: Human-Computer Interaction (Ch.15) • Began before exam 2 material, but due during exam 2 time period between exam 1 & 2 – Lab 2 • Emphasizing the notes and text materials that include parts of • Ch. 2, 3 Design & Evaluation Methods, Ch. 10 Anthropometry & Workspace Design, Ch.11 Biomechanics, Ch. 12 Work Physiology, Ch. 15 Human-Computer Interaction, Ch. 18 Selection & Training • Also includes issues in Lab 2 related to the IRB training module and Lab 3 on Data Analysis & Interpretation. • There will be no questions on the readings during exam 2.

  3. A mix of short answer and fill in; possibly some quantitative; expect 6-8 sides of a page, depending on size of figures; any necessary equations would be given; Closed book, no calculators. • For multiple choice: circle the best answer. • For all questions, be sure to read the question carefully. • If you are not clear on the meaning or how to interpret the question, please ask.

  4. Lecture 8 Human Computer Interaction • Q. What is the purpose of a GOMS model? • A. It is used to explain the users mental model • B. It is used to predict performance. • C. It is used for improved training and selection for HCI related tasks. • D. All of the above. • E. None of the above • Q. Give an example of a ‘selection rule’ in a GOMS model.

  5. Lecture 8 Human-Computer Interaction • Q. Briefly explain what this below figure is showing. • Q. If the total number of keystrokes is reduced, why might productivity not be lowered in this specific application?

  6. Lecture 9 Selection & Training • L. Consider ways to quantify the benefits of ‘selection tests’ or ‘transfer of training’ based on likelihood of success (see notes, fig. 18.1 and p.486 in text).

  7. Lecture 10-11 on Design Evaluation & Methods Q. A measure can be valid if it is not reliable. • True • False Q. A factor analysis would be used before an ANOVA when analyzing continuous data. • True • False Briefly explain your answer_________________.

  8. Lecture 10-11 on Design Evaluation & Methods Lecture on research methods Q. Cronbach’s alpha is used as • a measure of validity • a measure of reliability • in a chi squared analysis • all of the above • none of the above Q. If q1 and q2 comprised a variable ‘feature’ with alpha 0.75, then the value for ‘score’ in the ANOVA would be the mean of q1 and q2. True or False? If you wrote False, briefly explain your answer.__________________

  9. Lecture 10-11 on Design Evaluation & Methods Lecture on Methods The values shown below are after a factor analysis with rotation. Which questions would you include in the measure for factor 1? Factor 1 Factor 2 Ques. 1 Feel blue - 0.898 0.047 Ques. 2 People stare at me - 0.165 0.935 Ques. 3 People follow me - 0.222 0.926 Ques. 4 Basically happy 0.905 - 0.279 Ques. 5 People want to hurt me - 0.549 0.544 Ques. 6 Enjoy going to parties 0.647 - 0.302

  10. Lecture 10-11 on Design Evaluation & Methods Lecture on methods The values shown below are after a factor analysis with rotation. Which questions would you include in the measure for factor 1? Factor 1 Factor 2 Ques. 1 Feel blue - 0.898 0.047 Ques. 2 People stare at me - 0.165 0.935 Ques. 3 People follow me - 0.222 0.926 Ques. 4 Basically happy 0.905 - 0.279 Ques. 5 People want to hurt me - 0.549 0.544 Ques. 6 Enjoy going to parties 0.647 - 0.302 How much of the variance is explained by the first factor? (show work)

  11. Lab 2 • Q1. Why is it acceptable to proceed with IE 486 project II data analysis without specific approval from Purdue’s IRB for protection of human subjects in research? Briefly explain. • Q2. Under what conditions would project II efforts need prior approval from Purdue’s IRB? • if the work could be classified as research • if the work was intended for publication, thesis or dissertation • if any of the students intended to sell the results to a company • if the data were collected for discovering generalizable knowledge

  12. Lecture 10-11 on Statistical Analysis for Lab 3 Q. The following is an example of SAS output from what analysis? Q. What is your interpretation of the results shown below? 2 Variables: p1 p2 Simple Statistics Variable N Mean Std Dev Sum Min Max p1 30 3.76667 1.92414 113.0 1.00 7.00 p2 30 3.76667 1.63335 113.0 1.00 6.00 Variables Alpha Raw 0.948786 Standardized 0.955452

  13. Lecture 12 Anthropometry • Is it reasonable to expect that the ‘whole’ is equivalent to the ‘sum of the parts’? Yes or No. Why?

  14. Lecture 13 – Intro to Biomechanics • Which is more costly, low back injury or CTD/upper limb? When, or under what conditions? • Find the moment about the elbow for a single segment biomechanical model of the forearm in which the hand is holding a load of x kg. • Show the individual coefficients to determine the recommended weight limit for lifting in the given example.

  15. Lecture 14 Anthropometry • Briefly describe the difference between design for standing or seated work. • What may be changed when accommodating for differences in Precision work, Light work, and heavy work?

  16. Lecture 15 – Work Physiology The figure 12.7 is based on an article from the journal Ergonomics and shows work capacity as a function of a. time b. performance c. heart rate d. all of the above e. none of the above

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