Biographical Data (Biodata) Tests
Biographical Data (Biodata) Tests
Biodata measures are based on the measurement principle of behavioral consistency, that is, past behavior is
the best predictor of future behavior. Biodata measures include items
about past events and behaviors reflecting personality attributes, attitudes,
experiences, interests, skills and abilities validated as
predictors of overall performance for a given occupation.
Often, biodata test items are developed through behavioral
examples provided by subject matter experts (SMEs). These items specify
situations likely to have occurred in a person's life, and ask about the
person's typical behavior in the situation. In addition, biodata items reflect
external actions that may have involved, or were observable by, others and are
objective in the sense there is a factual basis for responding to each
item. An item might ask "How many books have you read in the last 6 months?"
or "How often have you put aside tasks to complete another, more difficult
assignment?" Test takers choose one of several predetermined alternatives to
best match their past behavior and experiences.
A response to a single biodata item is of little value.
Rather, it is the pattern of responses across several different situations that
give biographical data the power to predict future behavior on the job. For
this reason, biodata measures often contain between 10 and 30 items and some
wide-ranging instruments may contain a hundred or more items. Response options
commonly use a 5-point scale (1 = Strongly Disagree to 5 = Strongly Agree).
Once a group of biodata items is pre-tested on a sample of applicants, the
responses are used to group the items into categories or scales. Biodata items
grouped in this way are used to assess how effectively applicants performed in
the past in competency areas closely matched to those required by the job.
A more recent development is targeted biodata instruments.
In contrast to traditional biodata measures developed to predict overall job
performance, targeted biodata measures are developed to predict individual
differences in specific job-related behaviors of interest. Similar to the
developmental process used for traditional biodata, the content of a targeted
biodata measure is often driven by SME-generated behavioral examples relevant
to the specific behavior(s) of interest.
An example of a targeted biodata measure is a job
compatibility measure (sometimes referred to as a suitability measure) which
focuses on the prediction of counterproductive or deviant behaviors.
Counterproductive behavior is often defined as on-the-job behavior that is (a)
harmful to the mission of the organization, (b) does not stem from a lack of
intelligence, and (c) is willful or so seriously careless it takes on the
character of being willful. Previous criminal misconduct (e.g., theft),
employment misconduct (e.g., sexual harassment, offensiveness to customers, and
disclosure of confidential material), fraud, substance abuse, or efforts to
overthrow the Government are some major factors that may be relevant to
suitability determinations. A job compatibility index is typically used to
screen out applicants who are more likely to engage in counterproductive
behavior if they are hired. Job compatibility measures are less costly to implement
than other procedures typically used to detect counterproductive behaviors
(e.g., interviews, polygraphs) and are beneficial for positions requiring
employees to interact frequently with others or handle sensitive information or
valuable materials.
Considerations:
- Validity — Biodata measures
have been shown to be effective predictors of job success (i.e., they have
a moderate degree of criterion-related validity)
in numerous settings and for a wide range of criterion types (e.g.,
overall performance, customer service, team work); Biodata measures
also appear to add validity (i.e., incremental
validity) to selection systems employing traditional ability
measures
- Face
Validity/Applicant Reactions — Because some biodata items may not
appear to be job related (i.e., low face validity) applicants may react to
biodata tests as being unfair and invasive
- Administration Method —
Administered individually but can be administered to large numbers of
applicants via paper and pencil or electronically at one time
- Subgroup Differences —
Typically have less adverse impact on
minority groups than do many other types of selection measures; Items
should be carefully written to avoid stereotyping and should be based on
experiences under a person's control (i.e., what a person did rather than
what was done to the person)
- Development Costs — The development
of biodata items, scoring strategies, and validation procedures is a
difficult and time-consuming task requiring considerable expertise; Large
samples of applicants are needed to develop as well as validate the
scoring strategy and additional samples may be needed to monitor the validity of the items for future applicants
- Administration Costs — Can be
cost effective to administer and generally not time consuming to score if
an automated scoring system is implemented
- Utility/ROI — High predictive
ability can allow for the identification and selection of top performers;
Benefits (e.g., savings in training, high productivity, decreased
turnover) can outweigh developmental and administrative costs
- Common Uses — Commonly used in
addition to cognitive ability tests to
increase validity and lower adverse impact
References:
(See Section VI for a summary of each article)
Elkins, T., &
Phillips, J. (2000). Job context, selection decision outcome, and the perceived
fairness of selection tests: Biodata as an illustrative case. Journal of
Applied Psychology, 85(3), 479-484.
Hough, L. M., & Oswald, F. L. (2000).
Personnel selection: Looking toward the future — Remembering
the past. Annual Review of Psychology, 51, 631-664.
Mount, M. K.,
Witt, L. A., & Barrick, M. R. (2000). Incremental validity of empirically
keyed biodata scales over GMA and the five factor personality constructs. Personnel
Psychology, 53(2), 299-323.
Rothstein, H. R.,
Schmidt, F. L., Erwin, F. W., Owens, W. A., & Sparks, C. P. (1990).
Biographical data in employment selection: Can validities be made
generalizable? Journal of Applied Psychology, 75(2), 175-184.
Schmitt, N., Cortina,
J. M., Ingerick, M. J., & Wiechmann, D. (2003). Personnel selection and
employee performance. Handbook of Psychology: Industrial and Organizational
Psychology, 12, 77-105. New York, NY: John Wiley & Sons, Inc.
The following Society for Industrial and Organizational
Psychology (SIOP) website contains information on Biographical Data:
http://www.siop.org/workplace/employment%20testing/employment_testing_toc.aspx