Showing 11 - 20 of 43 Research Library Publications
Posted: | Erfan Khalaji, Sukru Eraslan, Yeliz Yesilada, Victoria Yaneva

Behavior & Information Technology

 

This study builds upon prior work in this area that focused on developing a machine-learning classifier trained on gaze data from web-related tasks to detect ASD in adults. Using the same data, we show that a new data pre-processing approach, combined with an exploration of the performance of different classification algorithms, leads to an increased classification accuracy compared to prior work.

Posted: | Chunyan Liu, Daniel Jurich

Applied Psychological Measurement: Volume 46, issue 6, page(s) 529-547

 

The current simulation study demonstrated that the sampling variance associated with the item response theory (IRT) item parameter estimates can help detect outliers in the common items under the 2-PL and 3-PL IRT models. The results showed the proposed sampling variance statistic (SV) outperformed the traditional displacement method with cutoff values of 0.3 and 0.5 along a variety of evaluation criteria.

Posted: | Andrew A. White, Ann M. King, Angelo E. D’Addario, Karen Berg Brigham, Suzanne Dintzis, Emily E. Fay, Thomas H. Gallagher, Kathleen M. Mazor

JMIR Medical Education: Volume 8 - Issue 2 - e30988

 

This article aims to compare the reliability of two assessment groups (crowdsourced laypeople and patient advocates) in rating physician error disclosure communication skills using the Video-Based Communication Assessment app.

Posted: | Richard A. Feinberg, Carol Morrison, Mark R. Raymond

Educational Measurement: Issues and Practices: Volume 41 - Issue 1 - Pages 95-96

 

Often unanticipated situations arise that can create a range of problems from threats to score validity, to unexpected financial costs, and even longer-term reputational damage. This module discusses some of these unusual challenges that usually occur in a credentialing program.

Posted: | Ian Micir, Kimberly Swygert, Jean D'Angelo

Journal of Applied Technology: Volume 23 - Special Issue 1 - Pages 30-40

 

The interpretations of test scores in secure, high-stakes environments are dependent on several assumptions, one of which is that examinee responses to items are independent and no enemy items are included on the same forms. This paper documents the development and implementation of a C#-based application that uses Natural Language Processing (NLP) and Machine Learning (ML) techniques to produce prioritized predictions of item enemy statuses within a large item bank.

Posted: | Victoria Yaneva, Brian E. Clauser, Amy Morales, Miguel Paniagua

Journal of Educational Measurement: Volume 58, Issue 4, Pages 515-537

 

In this paper, the NBME team reports the results an eye-tracking study designed to evaluate how the presence of the options in multiple-choice questions impacts the way medical students responded to questions designed to evaluate clinical reasoning. Examples of the types of data that can be extracted are presented. We then discuss the implications of these results for evaluating the validity of inferences made based on the type of items used in this study.

Posted: | Karen E. Hauer, Daniel Jurich, Jonathan Vandergrift, Rebecca S. Lipner, Furman S. McDonald, Kenji Yamazaki, Davoren Chick, Kevin McAllister, Eric S. Holmboe

Academic Medicine: Volume 96 - Issue 6 - p 876-884(9)

 

This study examines whether there are group differences in milestone ratings submitted by program directors working with clinical competency committees based on gender for internal medicine residents and whether women and men rated similarly on subsequent in-training and certification examinations.

Posted: | Sukru Eraslan, Yeliz Yesilada, Victoria Yaneva, Simon Harper

ACM SIGACCESS Accessibility and Computing

 

In this article, we first summarise STA (Scanpath Trend Analysis) with its application in autism detection, and then discuss future directions for this research.

Posted: | Peter Baldwin

Educational Measurement: Issues and Practice

 

This article aims to answer the question: when the assumption that examinees may apply themselves fully yet still respond incorrectly is violated, what are the consequences of using the modified model proposed by Lewis and his colleagues? 

Posted: | Martin G. Tolsgaard, Christy K. Boscardin, Yoon Soo Park, Monica M. Cuddy, Stefanie S. Sebok-Syer

Advances in Health Sciences Education: Volume 25, p 1057–1086 (2020)

 

This critical review explores: (1) published applications of data science and ML in HPE literature and (2) the potential role of data science and ML in shifting theoretical and epistemological perspectives in HPE research and practice.