individual administration gives them detailed information on what particular areas need to be reinforced for each student. This requires comparable alternate forms of testing sensitive to change in performance over short periods of time. Also, when reporting to parents, teachers need some idea of what constitutes “grade-level performance” using references in the form of gradelevel benchmarks (criterion-based), rather than using statistical percentiles (Hess, 2006). For example, DIBELS provides teachers with benchmark scores that students need to meet at specific times during each year and suggests instructional interventions that are needed by students who fail to meet benchmark scores (University of Oregon, 2005). In contrast, monitoring progress of schools for policy-related purposes can be done annually or multiannually (Barksdale-Ladd, 2000), and in the case universal coverage is recommended (so each school receives feedback). In Peru, the census assessment (ECE) meets the requirements to accomplish this goal: it is universal, annual, and there are no high stakes that could complicate even further the testing process (although its end-of-the-year application can lead teachers to believe that there are high stakes attached).

Last of all, for **_evaluating outcomes_** of an instructional program, segment or intervention at the classroom level both types of tests are appropriate, as long as they are administered to all –or a representative sample of– students and are CRMs. CRMs, are most appropriate for assessing what concepts and skills students have learned from a segment of instruction. Most CRMs are individual oral assessments, but some standardized written tests can also become CRMs by, for example, transforming scores with models such as Rasch, a standardized linear logit transformation with given weights<sup>18</sup> (Bond & Fox, 2007; Wright & Stone, 1979).

NRMs, such as pencil-and-paper tests that use raw scores or percentages of right answers are not appropriate for determining the effectiveness of educational programs because: (1) there is not, a priori, any value that can be considered as satisfactory or unsatisfactory performance; (2) raw scores do not indicate what students know or not know; (3) they do not take into account the difficulty of the questions, as all questions have the same value; (4) they cannot refer in any way to the contents of the questions; (5) they do not give information on the relative importance of the questions not answered correctly, or how many subjects did not answer them; and (6) they do not allow for comparisons between different tests, that is, it is incorrect to say that a mean of 51 percent of right answers in one test is better than a mean of 45 percent in another test<sup>19</sup> (Bazán & Millones, 2002).

The Rasch model can overcome all these limitations, and provide information that has more pedagogical value and potential for comparison over time because it can cross-reference the results in each item with the curricular standards that constituted the framework for the elaboration of the test. It also allows the reporting of results in a transformed scale that can be compared to other scales. All of this enables the written test to become a criterion-referenced measure.

In sum, “teachers need information specific to the content and strategies they are teaching, and they can best get that information through assessments built around their daily educational tasks”

> 18 The Rasch model is particularly used in psychometrics –the field concerned with the theory and technique of psychological and educational measurement– for analyzing data from assessments of abilities, attitudes, and personality trait

> 19 It is possible to address some of these limitations by doing an item-by-item analysis with raw scores. The result would be to place each child in a percentile relative to the sample for each single question. Thus, for example, in question 1 (reading a word), child “i” fails while 95 percent of children answer correctly, this only tells us that he is in the bottom 5 percent in this item. This type of analysis is even more cumbersome than using Rasch scores, and does not provide an adequate integrated picture.

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