A Quick and Accurate Scoring Algorithm for Rank- Order Tasks

Article Abstract:

A new approach for making individual-group consensus comparison is presented. An algorithm for scoring rank order tasks is introduced. Dispersion scoring methods have traditionally resulted in a bias favoring the group decision approach. The algorithm adjusts for this bias. The algorithm is accurate and less complex than dispersion methods. Existing research methods are reviewed. Future research ideas are suggested.

Testing

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An Accurate Look at a 'Quick' Scoring Algorithm

Article Abstract:

A critique of a scoring algorithm introduced on pages 439-454 of this journal is presented. The algorithm is said to adjust for traditional bias favoring the group decision approach. Buco, Lane and Mathews criticize the algorithm on a number of technical grounds. They claim that the algorithm is biased, inaccurate, and difficult to use. A traditional algorithm is recommended. A step-by-step outline is included.

Criticism and interpretation

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Short-term memory for serial order: the start-end model

Article Abstract:

The Start-End Model (SEM) is a new model of short-term memory that provides a solution to the problem of serial order. Simulation results indicate the ability of SEM to capture the main phenomena in serial recall, such as the effects of recency, grouping, redundant suffices, retention interval, primacy, list length, modality and proactive interference. SEM can also capture complete patterns of errors.

Models, Short-term memory, Recollection (Psychology), Recall (Memory)

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