Journal Article10.1177/0013164404272500
The Information Function for the One-Parameter Logistic Model: Is it Reliability?:
14
TL;DR: The information function is an important statistic in item response theory (IRT) applications as discussed by the authors, but it differs from the classical notion of reliability from a critical perspective: replication, which is often described as the IRT version of reliability.
read more
Abstract: The information function is an important statistic in item response theory (IRT) applications. Although the information function is often described as the IRT version of reliability, it differs from the classical notion of reliability from a critical perspective: replication. This article first explores the information function for the one-parameter model in detail and suggests an alternative method for its computation. Second, the difference between the IRT and classical test theory standard errors of measurement is discussed.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Direct measures of digital information processing and communication skills in primary education: Using item response theory for the development and validation of an ICT competence scale
TL;DR: The development of a performance-based digital test and the validation of a direct measure of ICT competence through the use of item response theory (IRT) are outlined, indicating that the instrument is particularly reliable for low and median ability levels.
130
Efficiency and sensitivity of multidimensional computerized adaptive testing of pediatric physical functioning.
TL;DR: Measuring physical functioning with multidimensional CATs could enhance sensitivity following intervention while minimizing response burden as well as efficiently retain the sensitivity of longer fixed-length measures even with 5 items per dimension.
20
•Dissertation
Identification and assessment of digital competences in primary education
Koen Aesaert
- 01 Jan 2015
TL;DR: In this paper, the authors identify relationships that exist between differences in primary school pupils' ICT competences and differences in pupil, classroom and school level characteristics, and construct a standardized and performance-based assessment instrument that can be used to measure pupils' IT competences in a direct and valid way.
18
Computerized Oral Proficiency Test for Japanese: Measuring L2 Speaking Ability with ASR Technology
Hitokazu Matsushita
- 01 Jan 2011
TL;DR: In this paper, the authors developed a computerized oral testing system for L2 Japanese using automatic speech recognition (ASR) technology and two testing methods called elicited imitation (EI) and simulated speech (SS) are proposed to quantify L2 accuracy and fluency via ASR processing.
References
•Book
Introduction to Classical and Modern Test Theory
Linda Crocker,James Algina +1 more
- 01 Nov 1986
5.6K
•Book
Applications of Item Response Theory To Practical Testing Problems
Frederic M. Lord
- 01 Jul 1980
TL;DR: The application of item response theory to practical testing problems is discussed in this article, where the authors present an example of the application of the theory to real-world testing problems in a practical setting.
5.6K
•Book
Item response theory for psychologists
Susan E. Embretson,Steven P. Reise +1 more
- 01 Jan 2000
TL;DR: Item Response Theory as Model-Based Measurement as mentioned in this paper is a model-based approach to measuring persons in personality and attitude assessment, and it has been applied in Cognitive and Developmental Assessment.
4.1K
•Book
Fundamentals of Item Response Theory
Ronald K. Hambleton,Hariharan Swaminathan,H. Jane Rogers +2 more
- 23 Jul 1991
TL;DR: This research attacked the mode-based approach to item response theory with a model- data fit approach, and found that the model-Data Fit approach proved to be more accurate than the other approaches.
3.4K
Fundamentals of Item Response Theory.
Abstract: Background Concepts, Models, and Features Ability and Item Parameter Estimation Assessment of Model-Data Fit The Ability Scale Item and Test Information and Efficiency Functions Test Construction Identification of Potentially Biased Test Items Test Score Equating Computerized Adaptive Testing Future Directions of Item Response Theory
2.6K