Rajasthan SET flashcards
Rajasthan SET · Build recall with a focused review session.
31 cards. Read the term and the definition here. The deck at the top of this page is optional.
- Formative assessment
- Assessment conducted during instruction to monitor learning and adjust teaching; it is low-stakes, feedback-oriented, and contrasted with summative assessment at the end of a unit.
- Summative assessment
- Assessment administered at the end of a course or unit to judge achievement against standards; results are typically graded and used for certification or reporting rather than immediate instructional adjustment.
- Bloom's taxonomy order
- Revised taxonomy runs Remember, Understand, Apply, Analyse, Evaluate, Create; the first three are lower-order and the last three higher-order cognitive processes used to frame learning objectives.
- Criterion-referenced test
- A test interpreted by comparing a candidate's performance to a fixed standard or set of learning objectives, not to other candidates; pass/fail and mastery decisions rely on it.
- Norm-referenced test
- A test interpreted by comparing a candidate's score to a reference group; percentile ranks, stanines, and z-scores express relative standing rather than absolute mastery of content.
- z-score formula
- z = (X − mean)/standard deviation. It expresses how many standard deviations a raw score lies from the mean, allowing comparison across tests with different scales.
- T-score conversion
- T = 50 + 10z. A z-score of 0 becomes T = 50, and each standard deviation shifts the T-score by 10 points; the scale has mean 50 and standard deviation 10.
- Item difficulty index
- P = number of candidates answering correctly divided by total candidates. Values near 0.5 give maximum discrimination; very high or very low P reduces the test's ability to separate candidates.
- Item discrimination index
- D = P(upper group) − P(lower group), using roughly the top and bottom 27 percent of scorers. Positive D means the item favours high achievers; D above 0.30 is usually acceptable.
- Split-half reliability
- A reliability estimate obtained by correlating scores on two halves of a test; the Spearman-Brown formula r_tt = 2r/(1+r) corrects for the shortened length of each half.
- Validity versus reliability
- Reliability is consistency of measurement across occasions or items; validity is whether the test measures the intended construct. A test can be reliable but invalid, never valid but unreliable.
- Levels of teaching
- Memory level emphasises recall, understanding level emphasises insight and application, and reflective level emphasises problem-solving and critical thinking; reflective is the highest level.
- Experimental research design
- A design in which the researcher randomly assigns participants to conditions and manipulates the independent variable, allowing causal inference and control of confounding variables.
- Quasi-experimental design
- A design that manipulates an independent variable using intact groups without random assignment; causal claims are weaker because pre-existing group differences may confound results.
- Ex post facto research
- Research that infers relationships by examining pre-existing differences after the supposed cause has occurred; the researcher does not manipulate variables, so causation is inferred cautiously.
- Stratified random sampling
- The population is divided into homogeneous strata and random samples are drawn from each stratum; this improves representativeness when subgroups differ on key characteristics.
- Standard error of mean
- SE = standard deviation divided by the square root of n. It estimates the variability of sample means around the population mean and shrinks as sample size grows.
- Levels of measurement
- Nominal (categories), ordinal (rank order), interval (equal intervals, arbitrary zero), and ratio (equal intervals with true zero). Permissible statistics depend on the level.
- Deductive versus inductive
- Deduction moves from general premises to a necessary conclusion; induction moves from specific observations to a probable generalisation. Validity applies to deduction, strength to induction.
- Valid categorical syllogism
- A syllogism with exactly three terms where the middle term is distributed at least once and no term is distributed in the conclusion unless distributed in the premises.
- Percentage change formula
- Change = (new value − old value)/old value × 100. Percentage points describe absolute difference between two percentages, while percent change describes relative difference.
- Significant figures rule
- In multiplication and division, the result carries the least number of significant figures among the inputs; in addition and subtraction, it keeps the least number of decimal places.
- Absolute versus relative error
- Absolute error is the magnitude of the difference between measured and true value; relative error divides that difference by the true value and is often expressed as a percentage.
- Correlation versus causation
- Correlation measures the strength and direction of association between two variables; it does not establish that one variable causes the other, since a third variable may drive both.
- Primary versus secondary source
- A primary source is an original document, dataset, or work produced at the time of the event; a secondary source interprets or summarises primary material and may introduce error.
- Distractor design
- Incorrect options in a multiple-choice item should be plausible but unambiguously wrong to candidates who know the content; implausible or absolute distractors reduce item discrimination.
- Stem of an MCQ
- The stem is the question or incomplete statement that poses the problem; it should be clear, self-contained, and free of unnecessary negative wording that confuses candidates.
- Mean, median, mode
- Mean is the arithmetic average, median is the middle value when ordered, and mode is the most frequent value. The median resists outliers; the mean is sensitive to them.
- Standard deviation
- The square root of the variance, measuring average spread of scores around the mean. Roughly 68 percent of a normal distribution lies within one standard deviation of the mean.
- Null and alternative hypothesis
- The null hypothesis states no effect or no difference; the alternative states an effect exists. A significance test assesses evidence against the null, not proof of the alternative.
- Type I and Type II error
- Type I error rejects a true null hypothesis (false positive); Type II error fails to reject a false null hypothesis (false negative). Lowering one generally raises the other for fixed sample size.