An Application of Item Response Time: The Effort‐Moderated IRT Model

By S. Wise, Christine E. DeMars. 2006

272 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Social Psychology

View Paper: https://www.semanticscholar.org/paper/d7701cf870ad2807a145d944d107c875e4804a5e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Management Science and Operations Research

In Social Psychology

Citations in the corpus

Evaluating the Impact of Careless Responding on Aggregated-Scores: To Filter Unmotivated Examinees or Not? (2017, methodology): “…estimates (e.g., De Ayala, Plake, & Impara, 2001) and other measurement properties, such as item parameter estimates (e.g., DeMars & Wise, 2010; Wise & DeMars, 2006), reliability estimates (e.g., Sundre & Wise, 2003; Wise & DeMars, 2009; Wise & Kong, 2005), and correlations with external…”
Modeling Student Test-Taking Motivation in the Context of an Adaptive Achievement Test. (2016, methodology): “(2) S. L. Wise and DeMars (2006) found that, when rapid guessing was present, the effortmoderated model showed better model fit than a traditional IRT model.”
A Mixture Rasch Model With Item Response Time Components (2010, methodology): “Wise and DeMars (2006) created the effort-moderated item response model (EMIRM) as a way to classify examinees and adjust item response model parameter estimates according to test-taking behavior.”
Detecting and Deterring Insufficient Effort Responding to Surveys (2012, unknown): “Wise and DeMars (2006) further showed that the incorporation of response time in the item response theory (IRT) model yielded more accurate proficiency estimates.”
Measuring Motivation in Low-Stakes Assessments (2015, methodology): “Another IRT modification that has been offered is for IRT to specify item characteristic curves for solution behavior and for rapid guessing behavior (Wise & DeMars, 2006).”
Measuring Learning Outcomes in Higher Education (2012, methodology): “Besides relying on student self-report, researchers have also examined response time effort (RTE) for computer-based, unspeeded tests to determine student motivation (S. L. Wise & DeMars, 2006; S. L. Wise & Kong, 2005).”
Correlates of Rapid-Guessing Behavior in Low-Stakes Testing: Implications for Test Development and Measurement Practice (2009, background): “Third, Wise and DeMars (2006) developed an effort-moderated IRT model that specifies, for each item, two item characteristic curves: one for solution behavior and another for rapid-guessing behavior.”
Two Approaches for Identifying Low-Motivated Students in a Low-Stakes Assessment Context (2011, background): “Regardless of the context (elementary school, high school, or college), data from unmotivated examinees can tamper with the psychometric properties of an instrument and ultimately the validity of the inferences made from the scores ( DeMars, 2000 ; Eklof, 2006 ; Wise, 2006 ; Wise & DeMars, 2006 )”
Examinee Noneffort and the Validity of Program Assessment Results (2010, methodology): “guessing has the effect of spuriously increasing internal consistency (S. Wise, 2006; S. Wise & DeMars, 2006, in press ).”
Changing “Course” (2014, methodology): “Many reoperationalizations of achievement are possible, from simplistic partial-credit policies that penalize initially incorrect answers to more elegant solutions using item-response modeling techniques (e.g., Wise & DeMars, 2006).”