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Diagnosing Learner Deficiencies in Algorithmic Reasoning

Description: It is hypothesized that useful diagnostic information can reside in the wrong answers of multiple-choice tests, and that properly designed distractors can yield indications of misinformation and missing information in algorithmic reasoning on the part of the test taker. In addition to summarizing the literature regarding diagnostic research as opposed to scoring research, this study proposes a methodology for analyzing test results and compares the findings with those from the research of Birenbaum and Tatsuoka and others. The proposed method identifies the conditions of misinformation and missing information, and it contains a statistical compensation for careless errors. Strengths and weaknesses of the method are explored, and suggestions for further research are offered.
Date: May 1995
Creator: Hubbard, George U.