Assessing learning programs: advantages and disadvantages of the pre-test design

When choosing to integrate the retrospective pre-test design method into your learning program evaluation and measurement methodology, the selection must take place in the after very carefully evaluating arguments both for and against its utility. The method has many advantages for the practitioner-researcher (see Table 1) but one must be cognisant of the threats to validity. However, in the context of the case study method, triangulation of data from other sources (questionnaires, surveys, quantitative analysis of access logs, LMS records, summative assessments and so on) can be used to counteract or balance such threats.

Table 1 Advantages and disadvantages of the retrospective pre-test model

Advantages	Disadvantages
Simple and cost-effective	Possibility that results were due to history in the job or organisation
Reduces costs and time for data collection and analysis	Possible distortions in retrospective reports because of response shift bias
Gathers data as part of the learning intervention
Compares post-intervention data with retrospective pre-data
Avoids attrition from the sample being measured
Decreases likelihood of testing effects

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Evaluating learning initatives: the Retrospective Pretest Design

The Retrospective Pre-test method is an interesting if controversial data collection design. I will examine its advantages and negative aspects here, as well as an argument for including this strategy in in assessing organisational learning initiatives. The retrospective pre-test method (see Table 1 is an extension of the one-shot case study design where data are gathered from participants following the learning intervention (for example, a series of non-formal Information Sessions).

Table 1 Retrospective Pre-test Design

Retrospective Pre-test Design
Groups		Non-equivalent	Intervention	Observation
Locally-based		N	X	O1	O2
Remotely-based		N	X	O1	O2
<- Time ->

However, participants (N) report on their knowledge, understanding or skills (Observation O1) after the intervention (X), and then also reflect and answer (O2) what they believe their understanding or skill was before the intervention. Rockwell & Kohn (1989) applied this method to testing the effectiveness of achieving program outcomes when interventions such as training programs are implemented and concluded that “using a post-then-pre design [retrospective pre-test] to identify self-reported behavioural changes can provide substantial evidence for program impact”. The retrospective pre-test enables researchers to reduce the response shift bias - defined by Klatt & Taylor-Powell in their 2005 paper Synthesis of Literature relative to Retrospective Pretest Design as

the change in the participant’s metric for answering questions from the pre-test to the post-test due to a new understanding of a concept being taught

- because the participants are able to give pre-test responses which are based on a post-intervention frame of reference.

Using the retrospective pre-test, response shift bias can be reduced increasing the likelihood that the observable results are due to intended intervention effects (Pratt, McGuigan & Katzev, 2001). This proposition is complicated and not without its critics – Theodore Lamb (2005), an advocate of the retrospective pre-test method, describes it as “an imperfect but useful tool.” Robson (2002, p.139-141) expresses concerns that used purely as a quasi-experimental method, this strategy could lead to an internal validity threat through regression to the mean.

References:

Klatt, J. and Taylor-Powell, E. (2005) Synthesis of Literature relative to RetrospectivePretest Design. Presentation to the 2005 Joint CES/AEA Conference, Toronto [Internet] Available from: http://www.citra.org/Assets/documents/evaluation%20design.pdf [Accessed 5th August 2007]

Lamb, T. (2005) The Retrospective Pretest: An Imperfect but Useful Tool. Evaluation Exchange. [Internet] 11(2). Available from: http://www.gse.harvard.edu/hfrp/eval/issue30/spotlight.html [Accessed 21st March 2007]

Pratt, C.C., McGuigan, W.M., & Katzev, A.R. (2000). Measuring program outcomes: Using retrospective pretest methodology. American Journal of Evaluation, 21(3). 341-349.

Robson, C. (2002) Real World Research. 2nd ed. Oxford: Blackwell Publishing.

Rockwell, S. K. & Kohn, H. (1989) Post-Then-Pre Evaluation. Journal of Extension. [Internet] 27(2). Available from: http://www.joe.org/joe/1989summer/a5.html [Accessed 21st March 2007]

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Learning Circuits Blog Big Question for April: Do Better

This month's Learning Circuits Blog Big Question is:

"What would you like to do better as a Learning Professional?"

I would like to do two things:

1. Really improve my "elevator pitch" to really convince sceptical behind-the-curve C-level executives that learning and development initiatives are actually going to grow their business, not send it into a Hindenburg-like crash and burn.
   
2. Bridge the gap between digital immigrants and digital natives

...we might all do better if we dared classify ourselves as developing.

(Seymour Papert, 1992)

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Evaluating Non-formal e-learning initatives: Case Study Techniques

As I asserted in a previous post, case studies allow naturalistic methods of enquiry such as individual interviews to be carried out, side-by-side with quantitative data gathering from surveys, archival records, server access logs and so on.

Interestingly in discussing the flexibility of the case study design, Yin (1994, p.285) contends that in the future, researchers will focus not on the case study method, but rather on the specifi case study data collection techniques (see Table 1) and we will increasingly see these techniques used in other “non-case study” forms of research.

Table 1 Case Study Techniques

Case Study Techniques

The use of multiple sources of evidence, in a converging manner

The explicit specification and testing of hypotheses and rival hypotheses, especially in lieu of control or comparison groups

The dominance of deductive strategies, whereby research starts with theorizing

Program logic models as a standard way of initiating a program evaluation

Pattern-matching as a common strategy for data analysis

Portfolio analysis, using qualitative criteria to differentially weigh the outcomes from a project or the projects within a program

The use of replication logic, rather than aggregating data, when comparing the results from multiple sites or cases.

This approach of modularising (to coin a term) the methodologies used in a case study may potentially enable future researchers to generalise from results attained through a case study approach to a broader context: this concept is outside the scope of this blog, but is something in my view that would have benefits in future social sciences research and evaluation of learning initiatives.

References:

Yin, R. K. (1994). Discovering the future of the case study method in evaluation research. Evaluation Practice [Internet] 15. Available from: http://aje.sagepub.com/cgi/reprint/15/3/283 [Accessed 15th January 2008 subscription required]

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