Driven: It \"Collects Numerical Data

¶ … driven: it "collects numerical data in order to explain, predict and/or control phenomena of interest" (Ouyang 2009). It is mainly statistical in nature, and can compile data through descriptive research, correlational research, causal-comparative research and experimental research methods (Ouyang 2009). For example, to determine the attitude of counselors regarding changes in the procedure of determining eligibility for vocational rehabilitation services, counselors might fill in a survey assessing different attitudes about the changes, expressing their agreement or disagreement on a 1-5 scale, or through true and false statements. Correlational research might seek to determine if length of service in the profession or the area where the counselor was located was correlated to strong support or a lack of support for the plan, based upon a data-driven demographic and attitudinal questionnaire. Causal-comparative research might hypothesize that 'counselors in high-crime areas are more likely to support the reforms,' because the reforms make good behavior in prison contingent upon participation in the program, and thus improve the experience and outcome of the counseling. Experimental research "establishes the cause-effect relationship and does the comparison, but the cause is manipulated" as in 'counselors have a more positive view of the reformed program if they receive specialized training beforehand' (Ouyang 2009). In such a design, one group of counselors would receive additional training to address the needs of the new population while a control group would not.