Quality of Narratives in Assessment: Piloting a List of Evidence-Based Quality Indicators.

Background & Need for Innovation: Appraising the quality of narratives used in assessment is challenging for educators and administrators. Although some quality indicators for writing narratives exist in the literature, they remain context specific and not always sufficiently operational to be easily used. Creating a tool that gathers applicable quality indicators and ensuring its standardized use would equip assessors to appraise the quality of narratives. Steps taken for Development and Implementation of innovation: We used DeVellis' framework to develop a checklist of evidence-informed indicators for quality narratives. Two team members independently piloted the checklist using four series of narratives coming from three different sources. After each series, team members documented their agreement and achieved a consensus. We calculated frequencies of occurrence for each quality indicator as well as the interrater agreement to assess the standardized application of the checklist. Outcomes of Innovation: We identified seven quality indicators and applied them on narratives. Frequencies of quality indicators ranged from 0% to 100%. Interrater agreement ranged from 88.7% to 100% for the four series. Critical Reflection: Although we were able to achieve a standardized application of a list of quality indicators for narratives used in health sciences education, it does not exclude the fact that users would need training to be able to write good quality narratives. We also noted that some quality indicators were less frequent than others and we suggested a few reflections on this.

Narrative Assessments in Higher Education: A Scoping Review to Identify Evidence-Based Quality Indicators.

PURPOSE: Narrative comments are increasingly used in assessment to document trainees' performance and to make important decisions about academic progress. However, little is known about how to document the quality of narrative comments, since traditional psychometric analysis cannot be applied. The authors aimed to generate a list of quality indicators for narrative comments, to identify recommendations for writing high-quality narrative comments, and to document factors that influence the quality of narrative comments used in assessments in higher education. METHOD: The authors conducted a scoping review according to Arksey & O'Malley's framework. The search strategy yielded 690 articles from 6 databases. Team members screened abstracts for inclusion and exclusion, then extracted numerical and qualitative data based on predetermined categories. Numerical data were used for descriptive analysis. The authors completed the thematic analysis of qualitative data with iterative discussions until they achieved consensus for the interpretation of the results. RESULTS: After the full-text review of 213 selected articles, 47 were included. Through the thematic analysis, the authors identified 7 quality indicators, 12 recommendations for writing quality narratives, and 3 factors that influence the quality of narrative comments used in assessment. The 7 quality indicators are (1) describes performance with a focus on particular elements (attitudes, knowledge, skills); (2) provides a balanced message between positive elements and elements needing improvement; (3) provides recommendations to learners on how to improve their performance; (4) compares the observed performance with an expected standard of performance; (5) provides justification for the mark/score given; (6) uses language that is clear and easily understood; and (7) uses a nonjudgmental style. CONCLUSIONS: Assessors can use these quality indicators and recommendations to write high-quality narrative comments, thus reinforcing the appropriate documentation of trainees' performance, facilitating solid decision making about trainees' progression, and enhancing the impact of narrative feedback for both learners and programs.