RESEARCH LIBRARY

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.

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.

Medical Science Educator: Volume 31, p 607–613 (2021)

This study extended previous research on the NBME Clinical Science Mastery Series self-assessments to investigate the utility of recently released self-assessments for students completing Family Medicine clerkships and Emergency Medicine sub-internships and preparing for summative assessments.

Teaching and Learning in Medicine: Volume 33 - Issue 4 - p 366-381

CSE scores for students from eight schools that moved Step 1 after core clerkships between 2012 and 2016 were analyzed in a pre-post format. Hierarchical linear modeling was used to quantify the effect of the curriculum on CSE performance. Additional analysis determined if clerkship order impacted clinical subject exam performance and whether the curriculum change resulted in more students scoring in the lowest percentiles before and after the curricular change.

Proceedings of the 28th International Conference on Computational Linguistics

This paper brings together approaches from the fields of NLP and psychometric measurement to address the problem of predicting examinee proficiency from responses to short-answer questions (SAQs).

Integrating Timing Considerations to Improve Testing Practices

This book synthesizes a wealth of theory and research on time issues in assessment into actionable advice for test development, administration, and scoring. 

Integrating Timing Considerations to Improve Testing Practices

This chapter presents a historical overview of the testing literature that exemplifies the theoretical and operational evolution of test speededness.

Academic Medicine: March 2019 - Volume 94 - Issue 3 - p 314-316

The United States Medical Licensing Examination Step 2 Clinical Skills (CS) exam uses physician raters to evaluate patient notes written by examinees. In this Invited Commentary, the authors describe the ways in which the Step 2 CS exam could benefit from adopting a computer-assisted scoring approach that combines physician raters’ judgments with computer-generated scores based on natural language processing (NLP).

Adv in Health Sci Educ 24, 141–150 (2019)

Research suggests that the three-option format is optimal for multiple choice questions (MCQs). This conclusion is supported by numerous studies showing that most distractors (i.e., incorrect answers) are selected by so few examinees that they are essentially nonfunctional. However, nearly all studies have defined a distractor as nonfunctional if it is selected by fewer than 5% of examinees.

Muscle Nerve, 58: 646-654

The Amyotrophic Lateral Sclerosis (ALS)‐Specific Quality of Life instrument and its revised version (ALSSQOL and ALSSQOL‐R) have strong psychometric properties, and have demonstrated research and clinical utility. This study aimed to develop a short form (ALSSQOL‐SF) suitable for limited clinic time and patient stamina.