Purpose:
This study used social annotation in an undergraduate nursing course to measure American Association of Colleges of Nursing [AACN] competencies in evidence-based research. For this research, social annotation is defined as groups of students using annotation through an external tool in the Learning Management System to learn vocabulary and build comprehension of healthcare evidence-based research and statistics guided by focused questions.

Background:
For evidence-based practice to be well established in nursing, nurses need a basic understanding of statistics to read, comprehend, and interpret relevant literature.

Method:
Rasch Model diagnostics and analysis were used to understand the survey item (questions) functioning of the Social Annotation rating scale instrument developed by Crystal Rose-Wainstock with her permission. Additional items were added to ensure the measurement of AACN competencies aligned to this course. Rasch Model analysis was performed to refine and validate a tool that can be used specifically for assessment purposes. The original survey was analyzed using classical test theory. Rasch Model analysis allowed a more appropriate analysis of Likert-type data, providing more detailed information about the psychometric properties of the survey. Based on these analyses, modifications of the survey were completed, leading to improved estimates of student competency development for future analyses of AACN competencies.

Conclusions:
Participating in social annotation, facilitated using technology, has developed many key competencies that students must master during their education. These include participating in scholarly inquiry as a team member, critiquing research, communicating scholarly findings, and evaluating the appropriateness and strength of the evidence.

Keywords: Rasch Model, social annotation, technology, competency-based education, statistics.