The Experts below are selected from a list of 294 Experts worldwide ranked by ideXlab platform

Autar Kaw - One of the best experts on this subject based on the ideXlab platform.

Kathleen Walsh Free - One of the best experts on this subject based on the ideXlab platform.

  • Writing Multiple-Choice Test items that promote and measure critical thinking
    The Journal of nursing education, 2001
    Co-Authors: Susan Morrison, Kathleen Walsh Free
    Abstract:

    Faculties are concerned about measurement of critical thinking especially since the National League for Nursing Accrediting Commission cited such measurement as a requirement for accreditation (NLNAC, 1997). Some writers and researchers (Alfaro-LeFevre, 1995; Blat, 1989; McPeck, 1981, 1990) describe the need to measure critical thinking within the context of a specific discipline. Based on McPeck's position that critical thinking is discipline-specific, guidelines for developing Multiple-Choice Test items as a means of measuring critical thinking within the discipline of nursing are discussed. Specifically, criteria described by Morrison, Smith, and Britt (1996) for writing critical-thinking Multiple-Choice Test items are reviewed and explained for promoting and measuring critical thinking.

Andre De Champlain - One of the best experts on this subject based on the ideXlab platform.

  • evaluating the psychometric characteristics of generated Multiple Choice Test items
    Applied Measurement in Education, 2016
    Co-Authors: Mark J Gierl, Hollis Lai, Debra Pugh, Claire Touchie, Andrephilippe Boulais, Andre De Champlain
    Abstract:

    ABSTRACTItem development is a time- and resource-intensive process. Automatic item generation integrates cognitive modeling with computer technology to systematically generate Test items. To date, however, items generated using cognitive modeling procedures have received limited use in operational Testing situations. As a result, the psychometric characteristics of generated Multiple-Choice Test items are largely unknown and undocumented. We present item analysis results from one of the first empirical studies designed to evaluate the psychometric properties of generated Multiple-Choice items using the results from a high stakes national medical licensure examination. The item analysis results for the correct option revealed that the generated items measured examinees’ performance across a broad range of ability levels while, at the same time, providing a consistently strong level of discrimination for each item. Results for the incorrect options revealed that the generated items consistently differentiat...

Mark J Gierl - One of the best experts on this subject based on the ideXlab platform.

  • evaluating the psychometric characteristics of generated Multiple Choice Test items
    Applied Measurement in Education, 2016
    Co-Authors: Mark J Gierl, Hollis Lai, Debra Pugh, Claire Touchie, Andrephilippe Boulais, Andre De Champlain
    Abstract:

    ABSTRACTItem development is a time- and resource-intensive process. Automatic item generation integrates cognitive modeling with computer technology to systematically generate Test items. To date, however, items generated using cognitive modeling procedures have received limited use in operational Testing situations. As a result, the psychometric characteristics of generated Multiple-Choice Test items are largely unknown and undocumented. We present item analysis results from one of the first empirical studies designed to evaluate the psychometric properties of generated Multiple-Choice items using the results from a high stakes national medical licensure examination. The item analysis results for the correct option revealed that the generated items measured examinees’ performance across a broad range of ability levels while, at the same time, providing a consistently strong level of discrimination for each item. Results for the incorrect options revealed that the generated items consistently differentiat...

  • using automatic item generation to create Multiple Choice Test items
    Medical Education, 2012
    Co-Authors: Mark J Gierl, Hollis Lai, Simon R Turner
    Abstract:

    CONTEXT Many Tests of medical knowledge, from the undergraduate level to the level of certification and licensure, contain MultipleChoice items. Although these are efficient in measuring examinees’ knowledge and skills across diverse content areas, Multiple-Choice items are time-consuming and expensive to create. Changes in student assessment brought about by new forms of computer-based Testing have created the demand for large numbers of Multiple-Choice items. Our current approaches to item development cannot meet this demand. METHODS We present a methodology for developing Multiple-Choice items based on automatic item generation (AIG) concepts and procedures. We describe a three-stage approach to AIG and we illustrate this approach by generating Multiple-Choice items for a medical licensure Test in the content area of surgery. RESULTS To generate Multiple-Choice items, our method requires a three-stage process. Firstly, a cognitive model is created by content specialists. Secondly, item models are developed using the content from the cognitive model. Thirdly, items are generated from the item models using computer software. Using this methodology, we generated 1248 MultipleChoice items from one item model. CONCLUSIONS Automatic item generation is a process that involves using models to generate items using computer technology. With our method, content specialists identify and structure the content for the Test items, and computer technology systematically combines the content to generate new Test items. By combining these outcomes, items can be generated automatically.

Naomi Schultheis - One of the best experts on this subject based on the ideXlab platform.

  • writing cognitive educational objectives and Multiple Choice Test questions
    American Journal of Health-system Pharmacy, 1998
    Co-Authors: Naomi Schultheis
    Abstract:

    Guidelines for writing cognitive objectives and Multiple-Choice Test questions for pharmacy educational programs are suggested. Cognitive educational objectives relate to intellectual skills and can usually be Tested with Multiple-Choice questions. Pharmacy educators writing cognitive objectives should focus on the major, not minor, knowledge or skills that participants in an educational program are expected to acquire; ensure that the objectives are supported by instruction; define the desired performance of the learners; ensure that the objectives are observable and measurable; and define the learning level for each objective (i.e., knowledge, comprehension, application, analysis, synthesis, or evaluation). Each Multiple-Choice Test question should be written with a view to assessing the learner's achievement of one of the stated objectives. Educators should write Test questions that are clear and concise, are in the form of complete sentences, include one clearly correct or best response, are phrased positively rather than negatively, and give no clues as to the correct answer. The learning level of each question should match that of the objective the question is designed to Test. Educators should weight Tests fairly by including the same number of questions for each objective. It may be necessary to include some higher-level questions to ensure assessment of the competence level at which the program is aimed. Cognitive educational objectives should be observable and measurable; Multiple-Choice Test questions should correspond to specific objectives and be based on the appropriate learning level.