NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Kilic, Abdullah Faruk; Uysal, Ibrahim – International Journal of Assessment Tools in Education, 2022
Most researchers investigate the corrected item-total correlation of items when analyzing item discrimination in multi-dimensional structures under the Classical Test Theory, which might lead to underestimating item discrimination, thereby removing items from the test. Researchers might investigate the corrected item-total correlation with the…
Descriptors: Item Analysis, Correlation, Item Response Theory, Test Items
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Ryan Schwarz; H. Cigdem Bulut; Charles Anifowose – International Journal of Assessment Tools in Education, 2023
The increasing volume of large-scale assessment data poses a challenge for testing organizations to manage data and conduct psychometric analysis efficiently. Traditional psychometric software presents barriers, such as a lack of functionality for managing data and conducting various standard psychometric analyses efficiently. These challenges…
Descriptors: Educational Assessment, International Assessment, Psychometrics, Statistical Analysis
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Tahereh Firoozi; Okan Bulut; Mark J. Gierl – International Journal of Assessment Tools in Education, 2023
The proliferation of large language models represents a paradigm shift in the landscape of automated essay scoring (AES) systems, fundamentally elevating their accuracy and efficacy. This study presents an extensive examination of large language models, with a particular emphasis on the transformative influence of transformer-based models, such as…
Descriptors: Turkish, Writing Evaluation, Essays, Accuracy
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Saatcioglu, Fatima Munevver; Atar, Hakan Yavuz – International Journal of Assessment Tools in Education, 2022
This study aims to examine the effects of mixture item response theory (IRT) models on item parameter estimation and classification accuracy under different conditions. The manipulated variables of the simulation study are set as mixture IRT models (Rasch, 2PL, 3PL); sample size (600, 1000); the number of items (10, 30); the number of latent…
Descriptors: Accuracy, Classification, Item Response Theory, Programming Languages