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A cued recall test is a procedure for testing memory in which a participant is presented with cues, such as words or phrases, to aid recall of previously experienced stimuli. [ 1 ] : 182 Endel Tulving and Zena Pearlstone (1966) conducted an experiment in which they presented participants with a list of words to be remembered.
The standard test involves the recall period starting immediately after the final list item; this can be referred to as immediate free recall (IFR) to distinguish it from delayed free recall (DFR). In delayed free recall, there is a short distraction period between the final list item and the start of the recall period.
There are three main types of recall: free recall, cued recall and serial recall. Psychologists test these forms of recall as a way to study the memory processes of humans [1] and animals. [2] Two main theories of the process of recall are the two-stage theory and the theory of encoding specificity.
However, when short-answer tests or essays are used [81] [82] greater gains in results are seen when compared to multiple-choice test [83] Cued recall can make retrieval easier [84] as it reduces the required retrieval strength from an individual which can help short term results, [85] but can hinder long term retrieval overtime due to reduced ...
Evaluation measures may be categorised in various ways including offline or online, user-based or system-based and include methods such as observed user behaviour, test collections, precision and recall, and scores from prepared benchmark test sets.
In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).
The positive prediction value answers the question "If the test result is positive, how well does that predict an actual presence of disease?". It is calculated as TP/(TP + FP); that is, it is the proportion of true positives out of all positive results. The negative prediction value is the same, but for negatives, naturally.
Precision and recall. In statistical analysis of binary classification and information retrieval systems, the F-score or F-measure is a measure of predictive performance. It is calculated from the precision and recall of the test, where the precision is the number of true positive results divided by the number of all samples predicted to be positive, including those not identified correctly ...