Detecting Examinees With Item Preknowledge on Real Data.

IF 1 4区心理学 Q4 PSYCHOLOGY, MATHEMATICAL

Applied Psychological Measurement Pub Date : 2022-06-01 DOI:10.1177/01466216221084202

Dmitry I Belov, Sarah L Toton

引用次数: 2

Abstract

Recently, Belov & Wollack (2021) developed a method for detecting groups of colluding examinees as cliques in a graph. The objective of this article is to study how the performance of their method on real data with item preknowledge (IP) depends on the mechanism of edge formation governed by a response similarity index (RSI). This study resulted in the development of three new RSIs and demonstrated a remarkable advantage of combining responses and response times for detecting examinees with IP. Possible extensions of this study and recommendations for practitioners were formulated.

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基于真实数据的项目预知检测。

最近，Belov & Wollack(2021)开发了一种方法，用于在图中检测串谋的考生群体。本文的目的是研究他们的方法在具有项目预知(IP)的真实数据上的性能如何依赖于响应相似指数(RSI)控制的边缘形成机制。该研究开发了三种新的rsi，并证明了结合反应和反应时间来检测IP的考生的显着优势。本研究的可能扩展和对从业者的建议被制定。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Psychological Measurement Multiple-

CiteScore

2.30

自引率

8.30%

发文量

期刊介绍： Applied Psychological Measurement publishes empirical research on the application of techniques of psychological measurement to substantive problems in all areas of psychology and related disciplines.