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psych 2080 ch 18.docx

4 Pages

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Psychology 2080A/B
Patrick Brown

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Industrial/organizational Psychology  2 major areas:  Personnel Psychology; study and practice of job analysis, recruitment, employee selection and evaluation of employee performance  Organizational Psychology; leadership, job satisfaction, and employee motivation Employment Interview  Most research supports a structured format for employment interview – this enables interviewers to reach agreement  Loss of flexibility increases reliability  Mean validity coefficients twice as high  Search for negative or unfavourable evidence – if it is found, the person will probably not be hired  As few as 1 unfavourable impression was followed by final rejection in 90% of the cases  Caution against employment interviewers against forming an early bias  Negative factors: poor communication skills, lack of confidence, low enthusiasm, nervousness, and failure to make eye contact  Positive factors: ability to express oneself, self-confidence, enthusiasm, ability to sell oneself, and aggressiveness  Most important factor: good first impression – professional attire, good grooming, aura of competence and expertise, friendliness or personal warmth through nonverbal cues  Female – perfume and nonverbal behaviours – when used alone, enhanced ratings for the applications – when used together, negative reactions  Interviews are the primary tool for selecting employees Base Rates and Hit Rates  Test results place individuals in one of two categories  Dichotomous (two-choice) decision – a cutoff score is usually used  Values above the cutoff are in the plus category (e.g. person is suitable for a job) and values below the cutoff are in the minus category (e.g. person may be turned away)  Cutting score; score marking the point of decision – does not ensure correct decisions  Tests can be evaluated by how well they sort people into the right categories  4 cell table – 2 are labeled “hit”, 2 are labeled “miss”  Hit; test has made the correct prediction (e.g. predicted that person will be unacceptable and they are, or predicted that person will be acceptable and they are)  Misses; tests make inaccurate prediction  Hit rate = % of cases in which a test accurately predicts success or failure (produces the correct result)  Base rate = proportion of people expected to succeed on a criterion if they are chosen at random  Real value of a test comes from a comparison of the hit rate with the base rate  False negatives = test suggests a negative classification, when really it is positive  Consider relative cost (e.g. basis that a tumour is benign when really it is malignant – patients life is endangered)  False positives = test suggests a positive classification, when really it is negative  Someone is selected for a job, does poorly, and gets fired (costs; time and money invested in training a person)  A and D = hit cells  A + D / sum of all cells = accuracy rate  B = false negative  C = false positive  A / A + B = detection rate Taylor-Russell Tables  Evaluating the validity of a test in relation to the amount of information it contributes beyond the base rates  Likelihood that a person selected on the basis of the test score will actually succeed  Requires that criterion be a dichotomous variable 1. Definition of success – success on the outcome must be defined (e.g. the person succeeded on the job) 2. Determination of base rate - % of people who would succeed if there was no testing or screening procedure must be determined 3. Definition of selection ratio – selection ratio (% of applicants selected/admitted) must be defined 4. Definition of Validity Coefficient – a validity coefficient for the test is required (usually the correlation)  Find the row that represents the validity of the test that would be used for selection  Find the column associated with the proportion of people who can be selected  The number in the body of the table gives an estimate of the % of people who could be expected to succeed when selected on the basis of a test  When validity is low and selection ratio is high, the test will be of little value  When the test has no validity, using the test will be no better than selecting applicants by chance  When nearly everyone is selected (last column) there is little reason to use test  Pages 508-511 provide examples of using a Taylor-Russell Tables Utility Theory and Decision Analysis  Attempts to define levels beside success and failure – based on utility theory  Equations are complex – require information that is hard to estimate  Raju; value of each individual can be estimated from the total value of his or her compensation package – does not solve estimation problem  Managers perceive use of utility information as an attempt to manipulate them to invest in a personnel intervention  Used occasionally in personnel selection – as well as education, and medicine  False positives – costing money – may lead to other painful and unnecessary medical procedures Value-Added Employee Assessments  Challenges in determining which employees should be retained and which should be promoted – decisions are usually made on the basis of a supervisor’s appraisal  Should judge work performance on the basis of achieving long term goals  Controversy has erupted over teachers on the basis of student performance  Promote teachers who perform better than expected and deny appointment for teachers whose students perform poorly  Challenge; students come to the classroom with different levels of ability (use quantitative methods – value-ad
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