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Operant conditioning, also called instrumental conditioning, is a learning process where voluntary behaviors are modified by association with the addition (or removal) of reward or aversive stimuli. The frequency or duration of the behavior may increase through reinforcement or decrease through punishment or extinction .
The evaluation phase consists of two aspects: formative and summative. Formative evaluation is present in each stage of the ADDIE process, while summative evaluation is conducted on finished instructional programs or products. Donald Kirkpatrick's Four Levels of Learning Evaluation are often utilized during this phase of the ADDIE process.
The operator precedence is a number (from high to low or vice versa) that defines which operator takes an operand that is surrounded by two operators of different precedence (or priority). Multiplication normally has higher precedence than addition, [1] for example, so 3+4×5 = 3+(4×5) ≠ (3+4)×5.
The number of operands is one of the factors that may give an indication about the performance of the instruction set. A three-operand architecture (2-in, 1-out) will allow A := B + C to be computed in one instruction ADD B, C, A A two-operand architecture (1-in, 1-in-and-out) will allow A := A + B to be computed in one instruction ADD B, A
Lazy evaluation is difficult to combine with imperative features such as exception handling and input/output, because the order of operations becomes indeterminate. The opposite of lazy evaluation is eager evaluation, sometimes known as strict evaluation. Eager evaluation is the evaluation strategy employed in most [quantify] programming languages.
Design of experiments with full factorial design (left), response surface with second-degree polynomial (right) The design of experiments , also known as experiment design or experimental design , is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation.
Bloom's taxonomy has become a widely adopted tool in education, influencing instructional design, assessment strategies, and learning outcomes across various disciplines. Despite its broad application, the taxonomy has also faced criticism, particularly regarding the hierarchical structure of cognitive skills and its implications for teaching ...
The worked-example effect is a learning effect predicted by cognitive load theory. [1] [full citation needed] Specifically, it refers to improved learning observed when worked examples are used as part of instruction, compared to other instructional techniques such as problem-solving [2] [page needed] and discovery learning.