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A current model for the early identification of students with academic struggles that is recognized by the Saskatchewan Ministry of Education is that of Response to Intervention (RTI). While the Ministry espouses the use of RTI, it does not mandate its application, nor identify which principles of the model are considered most effective. I conducted a qualitative, instrumental case study involving one rural school identified by the school division as effectively applying the principles of RTI. Using a semi-structured interviewing technique, and working with three participants, I identified which of the RTI principles the school believes to be effective, how the school implemented these principles, and the factors and conditions that contributed to their implementation. Along with interviews, documents collected from the school and school division that pertain to the application of RTI principles were analyzed. Finally, a narrative description of the research was completed. In total, ten themes were identified and further differentiated into four categories. The categories and corresponding themes are: 1) Attributes of the model that are considered critical: tiered intervention, assessment practices and division based supports. 2) Implementation strategies used: professional development, access to resources, and support provided when needed. 3) District and school factors that contribute to effectiveness of model: student and staff engagement and staff teaching philosophy. 4) Extraneous factors that contribute to the effective implementation: staffing and time. The implications of these findings are that effective implementation and maintenance of RTI principles requires careful planning, communication and a team approach. The principles of the model must be a priority for all staff involved in whatever capacity they contribute.

This study compares item and examinee properties, studies the robustness of IRT models, and examines the difference in robustness when using model-data-fit as a robustness criterion. A conceptualization of robustness as a statistical relationship between model assumption violation and invariance properties has been created in this study based on current understanding on IRT models. Using real data from British Columbia Science Assessments, a series of regressional and canonical analyses were conducted. Scatterplots were used to study possible non-linear relationships. The means and standard deviations of "a" and "c" parameter estimates obtained by applying the three-parameter model to a data sample were used as indices of equal discrimination and non-guessing assumption violation for the Rasch model. The assumption of local independence was taken as being equivalent to the assumption of unidimensionality, and Humphreys' pattern index "p" was used to assess the degree of unidimensionality assumption violation. Means and standard deviations of Yen's Q [i subscript] were used to assess the model-data-fit of items at the total test level. Another statistic to assess the model-data-fit of examinees (D [i subscript]) was created and validated in this study. The mean and standard deviation of D [i subscript] were used to assess model-data-fit of examinees at the total test level. The statistics used in this study for assessing item and ability parameter estimate invariance properties were correlations between estimates obtained from a sample and the estimates obtained from an assessment data file. It was found that model-data-fit of items and model-data-fit of examinees are two statistically independent total test properties of model-data-fit. Therefore, there is a necessity in practice to differentiate model-data-fit of items and model-data-fit of examinees. It was also found that item estimate invariance and ability estimate invariance are statistically independent total test properties of invariance. Therefore, there is also a necessity in practice to differentiate item invariance and ability invariance. When invariance is used as a criterion for robustness, the three-parameter model is robust for all the combinations of sample size and test length. The Rasch model is not robust in terms of ability estimate invariance when a large sample size is combined with a moderate test length, or when a moderate sample size is combined with a long test length. Finally, no significant relationship between model-data-fit and invariance was found. Therefore, results of robustness studies obtained when model-data-fit is used as a criterion and the results when invariance is used as a criterion may be totally different, or even contradictory. Because invariance is the fundamental premise of IRT models, invariance properties rather than model-data-fit should be used as criteria for robustness.

Mowrer's (1947) and Spence's (1956) suggestion that classical conditioning may play a significant role in the acquisition and performance of instrumental responses has fostered two broad lines of research. One of these bas been concerned with the role of classcally conditioned responses in instrumental behavior (Wynne & Solomon, 1955; Solomon & Turner, 1962; Miller & DeBold, 1965; Williams, 1965) and bas produced mainly negative results. The proposition that the occurrence of certain classically conditioned responses (e.g., autonomic "anxiety" reactions, anticipatory goal responses, or rg) is an essential step in instrumental responding seems no longer tenable. The second line of research has examined the role of classically conditioned stimuli in instrumental behavior and is based on the assumption that in the course of instrumental training, certain stimuli, apart from whatever cue function they might serve in the control of the instrumental response, serve a motivational function by being classically paired with the reinforcement. [...]

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