The Achievement Benefits of Standardized Testing (c) Richard P. Phelps (c) 2003, by Richard P. Phelps.

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Presentation transcript:

The Achievement Benefits of Standardized Testing (c) Richard P. Phelps (c) 2003, by Richard P. Phelps

The achievement benefits of standardized testing: outline 1) Main benefits 2) Why tests? 3) Why high-stakes tests? 4) The lost world of testing achievement benefit research 5) The lost art of literature searching 6) Why a keyword search is inadequate to this (and most) topics 7) Methodologies used in studies of testing achievement benefits 8) Check back later for updates

Main types of benefits associated with standardized testing (1) Information: information is used for diagnosis (of students, teachers, schools) information is used for alignment (of standards, instruction, across schools or districts, “what is tested is what is taught” focuses student and teacher efforts on what counts

Main types of benefits associated with standardized testing (2) Motivation: students, teachers, schools are motivated to demonstrate their competence (to themselves and to others) they are motivated to know more, now that they know where to concentrate their efforts they may be motivated by positive or negative consequences tied to their performance (e.g., promotion or retention, pay raise)

Why tests? ● Students tend to study more, and learn more, when it is: ● not known in advance exactly what will be tested ● (e.g.) Experiment comparing gains of students with “take-home tests” to those with “in class tests” -- the latter learned substantially more. ● when there is reinforcement of material already studied ● Mastery learning experiments of 19602—1980s: ● Students learn more when asked to recall what they have learned. ● Up to a point, the more students are made to actively process information, and describe it to others, the better they learn.

Why high- stakes tests? Most of us respond to both intrinsic and extrinsic motivators and the proportion varies from individual to individual. High- stakes tests provide both forms of inducement. The “Lake Wobegon Effect” occurred with “no stakes,” “internal” tests. Too many local educators manipulated

The lost world of testing achievement benefit research ● Repetitive, insistent claims by testing opponents (e.g., CRESST, FairTest) ● Even some folks who could not be labeled as testing opponents (e.g., Bill Mehrens, Greg Cizek) claim no evidence ● Even the Bush Administration's advisors on education research have claimed no evidence

The lost art of literature searching ● A computer search is a “black box” providing a false sense of security ● Computer keyword searches have made researchers lazy and myopic. ● Computer searches not adequate for finding most of the literature on a topic, much less a representative sample of it. ● Relying on a computer search alone introduces bias to a study.

Why keyword searches are inadequate to the study of testing benefits Most data bases only attach several keywords to each document Keywords tend to be academic discipline specific Most research studies uncovering testing benefits were focused on some other topic, and the keywords attached reflect that other focus.

More reasons why keyword searches are inadequate to the study of testing benefits Many, if not most, studies finding testing benefits are not stored in any data bases – they are government program evaluations, proprietary studies conducted by testing firms, or research conducted by testing practitioners, who have little incentive to publish in the academic literature.

Still more reasons why keyword searches are inadequate to the study of testing benefits Some studies uncovering testing benefits also uncover testing drawbacks, and the overall result given in the summary focuses on the negative. Some studies conducted by education professors simply disregard the positive evidence in their summaries. Some studies are fraudulent (e.g., data were doctored)

Methodologies used in testing achievement benefit studies Conceptual or analytical models Controlled experiments Quasi-experiments Multivariate analysis (manova, multiple regression) Interrupted time series with shadow measure Pre-post studies Program evaluations and surveys Case studies Benefit-cost studies

For more, see: Phelps, R.P., Ed. (2005). Defending standardized testing, Mahwah, N.J.: Lawrence Erlbaum. [ISBN: cloth: , paper: ]