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Ravesloot, C. J.; Van der Schaaf, M. F.; Muijtjens, A. M. M.; Haaring, C.; Kruitwagen, C. L. J. J.; Beek, F. J. A.; Bakker, J.; Van Schaik, J.P.J.; Ten Cate, Th. J. – Advances in Health Sciences Education, 2015
Formula scoring (FS) is the use of a don't know option (DKO) with subtraction of points for wrong answers. Its effect on construct validity and reliability of progress test scores, is subject of discussion. Choosing a DKO may not only be affected by knowledge level, but also by risk taking tendency, and may thus introduce construct-irrelevant…
Descriptors: Scoring Formulas, Tests, Scores, Construct Validity
Temel, Gülhan Orekici; Erdogan, Semra; Selvi, Hüseyin; Kaya, Irem Ersöz – Educational Sciences: Theory and Practice, 2016
Studies based on longitudinal data focus on the change and development of the situation being investigated and allow for examining cases regarding education, individual development, cultural change, and socioeconomic improvement in time. However, as these studies require taking repeated measures in different time periods, they may include various…
Descriptors: Investigations, Sample Size, Longitudinal Studies, Interrater Reliability
Holster, Trevor A.; Lake, J. – Language Assessment Quarterly, 2016
Stewart questioned Beglar's use of Rasch analysis of the Vocabulary Size Test (VST) and advocated the use of 3-parameter logistic item response theory (3PLIRT) on the basis that it models a non-zero lower asymptote for items, often called a "guessing" parameter. In support of this theory, Stewart presented fit statistics derived from…
Descriptors: Guessing (Tests), Item Response Theory, Vocabulary, Language Tests
Dimoliatis, Ioannis D. K.; Jelastopulu, Eleni – Universal Journal of Educational Research, 2013
The surgical theatre educational environment measures STEEM, OREEM and mini-STEEM for students (student-STEEM) comprise an up to now disregarded systematic overestimation (OE) due to inaccurate percentage calculation. The aim of the present study was to investigate the magnitude of and suggest a correction for this systematic bias. After an…
Descriptors: Educational Environment, Scores, Grade Prediction, Academic Standards
Peer reviewedMitchelmore, M. C. – British Journal of Educational Psychology, 1981
This paper presents a scientific rationale for deciding the number of points to use on a grading scale in any given assessment situation. The rationale is applied to two common methods of assessment (multiple-choice and essay tests) and an example of a composite assessment. (Author/SJL)
Descriptors: Error of Measurement, Essay Tests, Grading, Higher Education
Peer reviewedMcGaw, Barry; Glass, Gene V. – American Educational Research Journal, 1980
There are difficulties in expressing effect sizes on a common metric when some studies use transformed scales to express group differences, or use factorial designs or covariance adjustments to obtain a reduced error term. A common metric on which effect sizes may be standardized is described. (Author/RL)
Descriptors: Control Groups, Error of Measurement, Mathematical Models, Research Problems
Peer reviewedKleven, Thor Arnfinn – Scandinavian Journal of Educational Research, 1979
Supposing different values of the standard measurement error, the relation of scale coarseness to the total amount of error is studied on the basis of probability distribution of error. The analyses are performed within two models of error and with two criteria of amount of error. (Editor/SJL)
Descriptors: Cutting Scores, Error of Measurement, Goodness of Fit, Grading
Peer reviewedHuynh, Huynh – Journal of Educational Statistics, 1986
Under the assumptions of classical measurement theory and the condition of normality, a formula is derived for the reliability of composite scores. The formula represents an extension of the Spearman-Brown formula to the case of truncated data. (Author/JAZ)
Descriptors: Computer Simulation, Error of Measurement, Expectancy Tables, Scoring Formulas
Attali, Yigal – ETS Research Report Series, 2007
Because there is no commonly accepted view of what makes for good writing, automated essay scoring (AES) ideally should be able to accommodate different theoretical positions, certainly at the level of state standards but also perhaps among teachers at the classroom level. This paper presents a practical approach and an interactive computer…
Descriptors: Computer Assisted Testing, Automation, Essay Tests, Scoring
Tsujimoto, Richard N.; Berger, Dale E. – Child Abuse and Neglect: The International Journal, 1988
Two criteria are discussed for determining cutting scores on a predictor variable for identifying cases of likely child abuse--utility maximizing and error minimizing. Utility maximizing is the preferable criterion, as it optimizes the balance between the costs of incorrect decisions and the benefits of correct decisions. (Author/JDD)
Descriptors: Child Abuse, Cost Effectiveness, Cutting Scores, Error of Measurement
Peer reviewedLord, Frederic M. – Journal of Educational Measurement, 1984
Four methods are outlined for estimating or approximating from a single test administration the standard error of measurement of number-right test score at specified ability levels or cutting scores. The methods are illustrated and compared on one set of real test data. (Author)
Descriptors: Academic Ability, Cutting Scores, Error of Measurement, Scoring Formulas
Saunders, Joseph C.; Huynh, Huynh – 1980
In most reliability studies, the precision of a reliability estimate varies inversely with the number of examinees (sample size). Thus, to achieve a given level of accuracy, some minimum sample size is required. An approximation for this minimum size may be made if some reasonable assumptions regarding the mean and standard deviation of the test…
Descriptors: Cutting Scores, Difficulty Level, Error of Measurement, Mastery Tests
Littlefield, John H.; And Others – 1983
Observational ratings of student clinical performance are influenced by factors other than the quality of the performance. Individual raters may be more stringent or lenient than their colleagues. In this medical school setting, multiple raters evaluated each student. To reduce the influence of "error" due to differences among raters, each rater…
Descriptors: Bias, Error of Measurement, Higher Education, Interrater Reliability
Livingston, Samuel A. – 1986
This paper deals with test fairness regarding a test consisting of two parts: (1) a "common" section, taken by all students; and (2) a "variable" section, in which some students may answer a different set of questions from other students. For example, a test taken by several thousand students each year contains a common multiple-choice portion and…
Descriptors: Difficulty Level, Error of Measurement, Essay Tests, Mathematical Models
Tatsuoka, Kikumi – 1980
This paper presents a new method for estimating a given latent trait variable by the least-squares approach. The beta weights are obtained recursively with the help of Fourier series and expressed as functions of item parameters of response curves. The values of the latent trait variable estimated by this method and by maximum likelihood method…
Descriptors: Computer Assisted Testing, Error of Measurement, Higher Education, Latent Trait Theory
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