mEASURING

MASTER OF SOCIAL WORK II YR

PRESENTATION

ON

MEASURING INTERVENTION & CHANGE.

SYNOPSISINTRODUCTION

MEASUREMENT OF OD INTERVENTIONS:

SELECTING VARIABLE

DESIGNING GOOD MEASURE

RELIABILITY

VALIDITY

RESEARCH DESIGN

OD CHANGES

INTRODUCTION

Assessing OD Interventions involves judgments about whether an intervention has been implemented as intended & if so, whether it is having desired results. Managers investing resources in OD efforts increasingly are being held accountable for results

being asked to justify in terms of bottom-line outcomes. Measurement of Organizational Interventions provides development of useful implementation &

evaluation feedback.

MEASUREMENT OF OD INTERVENTIONS

Selecting Appropriate Variable.

Selecting Appropriate Variable

Ideally, the variables measured in OD evaluation should derive from the theory or conceptual model underlying the intervention. The model should incorporate the key features of the intervention as well as its expected results.

For example, the joblevel diagnostic model proposes several major features of work: task variety, feedback, and autonomy. The theory argues that high levels of these elements can be expected to result in high levels of work quality and satisfaction.

Whether the intervention is being implemented could be assessed by determining how many job descriptions have been rewritten to include more responsibility or how many organization members have received cross-training in other job skills. Again, these measures would likely be included in the initial diagnosis, when the company’s problems or areas for improvement are discovered.

OPERATIONAL DEFINITION FOR DESIGNING GOOD MEASURE

A good measure is operationally defined; that is, it specifies the empirical data needed how they will be collected and, most important, how they will be converted from data to information. These measures consist of specific computational rules that can be used to construct measures for each of the behaviour. They provide precise guidelines about what characteristics of the situation are to be observed and how they are to be used.

RELIABILITY

Reliability concerns the extent to which a measure represents the “true” value of a variable; that is, how accurately the operational definition translates data into information. The 1 st source of

reliability is by or through measurement, rigorously & operationally defining the chosen variables. Clearly specified operational definitions contribute to reliability by explicitly describing how

collected data will be converted into information about a variable. Second, use multiple methods to measure a particular variable through use of questionnaire, interviews, observation.Third, use

multiple items to measure the same variable on a questionnaire.Fourth, use of standard questionnaire.

Validity

Validity concerns the extent to which, a measure actually reflects the variable it is intended to reflect.On a measure of happiness of employees, for e.g., the test would be said to have face validity if it appeared to actually measure levels of happiness.In other

words, a test can be said to have face validity if it ‘looks like ’ it measures what it is supposed to measure. If the experts agree that the measure appears valid it is called

Content Validity.If measures of similar variables correlate highly with each other, it is called Criterion/Convergent validity. If measures of non similar variables show no

association, it is called Discriminant Validity

RESEARCH DESIGN In assessing OD Interventions, practitioners have turned to quasi-

experimental Research design with the following features:

Longitudinal measurement:

This involves measuring results repeatedly over relatively long time periods. Ideally, the data collection should start before the change program is implemented and continue for a period considered reasonable for producing expected results.

Comparison unit: It is always desirable to compare results in the intervention situation with those in another situation where no such change has taken place. Although it is never possible to get a matching group identical to tile intervention group, most organizations include a number of similar work units that can be used for comparison purposes.

Statistical analysis Whenever possible, statistical methods should be used to rule out the possibility that the results are caused by random error or chance. Various statistical techniques are applicable to quasi experimental designs, and OD practitioners should apply these methods or seek help from those who can apply them.

Assessing OD Changes

The use of multiple measures also is important in assessing perceptual changes resulting from intervention. Considerable research has identified three types of change

Alpha, Beta, and Gamma change.

OD CHANGESAlpha Change:It concerns a difference that occurs along some relatively stable dimension of reality. . For example, comparative measures of perceived employee discretion might show an increase after a job enrichment program. If this increase represents alpha change, it can be assumed that the job enrichment program actually increased employee perceptions of discretion.

Beta Change:

It refers to recalibration of units of measure in a stable dimension.

Gamma change:

It involves fundamental redefinition of dimension.