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Computerized Adaptive Testing
Computerized adaptive testing (CAT) is a form of computer-based test that adapts to the examinee's ability level. For this reason, it has also been called tailored testing. In other words, it is a form of computer-administered test in which the next item or set of items selected to be administered depends on the correctness of the test taker's responses to the most recent items administered. How it works CAT successively selects questions for the purpose of maximizing the precision of the exam based on what is known about the examinee from previous questions. From the examinee's perspective, the difficulty of the exam seems to tailor itself to their level of ability. For example, if an examinee performs well on an item of intermediate difficulty, they will then be presented with a more difficult question. Or, if they performed poorly, they would be presented with a simpler question. Compared to static multiple choice tests that nearly everyone has experienced, with a fixed set of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer-based Assessment
Electronic assessment, also known as digital assessment, e-assessment, online assessment or computer-based assessment, is the use of information technology in assessment such as educational assessment, health assessment, psychiatric assessment, and psychological assessment. This covers a wide range of activities ranging from the use of a word processor for assignments to on-screen testing. Specific types of e-assessment include multiple choice, online/electronic submission, computerized adaptive testing such as the Frankfurt Adaptive Concentration Test, and computerized classification testing. Different types of online assessments contain elements of one or more of the following components, depending on the assessment's purpose: formative, summative and diagnostic. Instant and detailed feedback may (or may not) be enabled. In formative assessment, often defined as 'assessment for learning', digital tools are increasingly being adopted by schools, higher education institutions an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Information
Information is an abstract concept that refers to that which has the power to inform. At the most fundamental level information pertains to the interpretation of that which may be sensed. Any natural process that is not completely random, and any observable pattern in any medium can be said to convey some amount of information. Whereas digital signals and other data use discrete signs to convey information, other phenomena and artifacts such as analog signals, poems, pictures, music or other sounds, and currents convey information in a more continuous form. Information is not knowledge itself, but the meaning that may be derived from a representation through interpretation. Information is often processed iteratively: Data available at one step are processed into information to be interpreted and processed at the next step. For example, in written text each symbol or letter conveys information relevant to the word it is part of, each word conveys information rele ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linear Programming
Linear programming (LP), also called linear optimization, is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear function#As a polynomial function, linear relationships. Linear programming is a special case of mathematical programming (also known as mathematical optimization). More formally, linear programming is a technique for the mathematical optimization, optimization of a linear objective function, subject to linear equality and linear inequality Constraint (mathematics), constraints. Its feasible region is a convex polytope, which is a set defined as the intersection (mathematics), intersection of finitely many Half-space (geometry), half spaces, each of which is defined by a linear inequality. Its objective function is a real number, real-valued affine function, affine (linear) function defined on this polyhedron. A linear programming algorithm finds a point in the polytope where ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gender
Gender is the range of characteristics pertaining to femininity and masculinity and differentiating between them. Depending on the context, this may include sex-based social structures (i.e. gender roles) and gender identity. Most cultures use a gender binary, in which gender is divided into two categories, and people are considered part of one or the other (boys/men and girls/women);Kevin L. Nadal, ''The SAGE Encyclopedia of Psychology and Gender'' (2017, ), page 401: "Most cultures currently construct their societies based on the understanding of gender binary—the two gender categorizations (male and female). Such societies divide their population based on biological sex assigned to individuals at birth to begin the process of gender socialization." those who are outside these groups may fall under the umbrella term ''non-binary''. Some societies have specific genders besides "man" and "woman", such as the hijras of South Asia; these are often referred to as ''third gende ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Educational Testing Service
Educational Testing Service (ETS), founded in 1947, is the world's largest private nonprofit educational testing and assessment organization. It is headquartered in Lawrence Township, New Jersey, but has a Princeton address. ETS develops various standardized tests primarily in the United States for K–12 and higher education, and it also administers international tests including the TOEFL (Test of English as a Foreign Language), TOEIC (Test of English for International Communication), Graduate Record Examination (GRE) General and Subject Tests, HiSET and The Praxis test Series—in more than 180 countries, and at over 9,000 locations worldwide. Many of the assessments it develops are associated with entry to US tertiary (undergraduate) and quaternary education (graduate) institutions, but it also develops K–12 statewide assessments used for accountability testing in many states, including California, Texas, Tennessee, and Virginia. In total, ETS annually administers 20 m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Likelihood Ratios In Diagnostic Testing
In evidence-based medicine, likelihood ratios are used for assessing the value of performing a diagnostic test. They use the sensitivity and specificity of the test to determine whether a test result usefully changes the probability that a condition (such as a disease state) exists. The first description of the use of likelihood ratios for decision rules was made at a symposium on information theory in 1954. In medicine, likelihood ratios were introduced between 1975 and 1980. Calculation Two versions of the likelihood ratio exist, one for positive and one for negative test results. Respectively, they are known as the (LR+, likelihood ratio positive, likelihood ratio for positive results) and (LR–, likelihood ratio negative, likelihood ratio for negative results). The positive likelihood ratio is calculated as : \text+ = \frac which is equivalent to : \text+ = \frac or "the probability of a person who has the disease testing positive divided by the probability of a pe ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Confidence Interval
In frequentist statistics, a confidence interval (CI) is a range of estimates for an unknown parameter. A confidence interval is computed at a designated ''confidence level''; the 95% confidence level is most common, but other levels, such as 90% or 99%, are sometimes used. The confidence level represents the long-run proportion of corresponding CIs that contain the true value of the parameter. For example, out of all intervals computed at the 95% level, 95% of them should contain the parameter's true value. Factors affecting the width of the CI include the sample size, the variability in the sample, and the confidence level. All else being the same, a larger sample produces a narrower confidence interval, greater variability in the sample produces a wider confidence interval, and a higher confidence level produces a wider confidence interval. Definition Let be a random sample from a probability distribution with statistical parameter , which is a quantity to be estimate ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hypothesis Test
A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. Hypothesis testing allows us to make probabilistic statements about population parameters. History Early use While hypothesis testing was popularized early in the 20th century, early forms were used in the 1700s. The first use is credited to John Arbuthnot (1710), followed by Pierre-Simon Laplace (1770s), in analyzing the human sex ratio at birth; see . Modern origins and early controversy Modern significance testing is largely the product of Karl Pearson (p-value, ''p''-value, Pearson's chi-squared test), William Sealy Gosset (Student's t-distribution), and Ronald Fisher ("null hypothesis", analysis of variance, "statistical significance, significance test"), while hypothesis testing was developed by Jerzy Neyman and Egon Pearson (son of Karl). Ronald Fisher began his life in statistics as a Bayesian (Zabell 1992), but Fisher ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sequential Probability Ratio Test
The sequential probability ratio test (SPRT) is a specific sequential hypothesis test, developed by Abraham Wald and later proven to be optimal by Wald and Jacob Wolfowitz. Neyman and Pearson's 1933 result inspired Wald to reformulate it as a sequential analysis problem. The Neyman-Pearson lemma, by contrast, offers a rule of thumb for when all the data is collected (and its likelihood ratio known). While originally developed for use in quality control studies in the realm of manufacturing, SPRT has been formulated for use in the computerized testing of human examinees as a termination criterion. Theory As in classical hypothesis testing, SPRT starts with a pair of hypotheses, say H_0 and H_1 for the null hypothesis and alternative hypothesis respectively. They must be specified as follows: :H_0: p=p_0 :H_1: p=p_1 The next step is to calculate the cumulative sum of the log-likelihood ratio, \log \Lambda_i, as new data arrive: with S_0 = 0, then, for i=1,2,..., :S_i=S_+ \log \ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computerized Classification Test
A computerized classification test (CCT) refers to, as its name would suggest, a test that is administered by computer for the purpose of classifying examinees. The most common CCT is a mastery test where the test classifies examinees as "Pass" or "Fail," but the term also includes tests that classify examinees into more than two categories. While the term may generally be considered to refer to all computer-administered tests for classification, it is usually used to refer to tests that are interactively administered or of variable-length, similar to computerized adaptive testing (CAT). Like CAT, variable-length CCTs can accomplish the goal of the test (accurate classification) with a fraction of the number of items used in a conventional fixed-form test. A CCT requires several components: # An item bank calibrated with a psychometric model selected by the test designer # A starting point # An item selection algorithm # A termination criterion and scoring procedure The startin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Collectively Exhaustive Events
In probability theory and logic, a set of events is jointly or collectively exhaustive if at least one of the events must occur. For example, when rolling a six-sided die, the events 1, 2, 3, 4, 5, and 6 balls of a single outcome are collectively exhaustive, because they encompass the entire range of possible outcomes. Another way to describe collectively exhaustive events is that their union must cover all the events within the entire sample space. For example, events A and B are said to be collectively exhaustive if :A \cup B = S where S is the sample space. Compare this to the concept of a set of mutually exclusive events. In such a set no more than one event can occur at a given time. (In some forms of mutual exclusion only one event can ever occur.) The set of all possible die rolls is both mutually exclusive and collectively exhaustive (i.e., " MECE"). The events 1 and 6 are mutually exclusive but not collectively exhaustive. The events "even" (2,4 or 6) and "not-6" ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
