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Assessment instruments that generate quantitative data on attributes (cognitive, affective, behavioral,etc.) of participants are commonly used in the chemistry education community to draw conclusions in research studies or inform practice. Recently, articles and editorials have stressed the importance of providing evidence for the validity and reliability of data collected with these instruments following guidance from the Standards for Educational and Psychological Testing. This study examines how quantitative instruments have been used in the journalChemistry Education Research and Practice(CERP) from 2010–2021. Of the 369 unique researcher-developed instruments used during this time frame, the majority only appeared in a single publication (89.7%) and were rarely reused. Cognitive topics were the most common target of the instruments (56.6%). Validity and/or reliability evidence was provided in 64.4% of instances where instruments were used inCERPpublications. The most frequently reported evidence was single administration reliability (e.g., coefficient alpha), appearing in 47.9% of instances. Only 37.2% of instances reported evidence of both validity and reliability. These results indicate that, as a field, opportunities exist to increase the amount of validity and reliability evidence available for data collected with instruments and that reusing instruments may be one method of increasing this type of data quality evidence for instruments used by the chemistry education community. 

Abstract Developing and using scientific models is an important scientific practice for science students. Undergraduate chemistry curricula are often centered on established disciplinary models, and assessments typically provide students with opportunities to use these models to predict and explain chemical phenomena. However, traditional curricula generally provide few opportunities for students to consider the epistemic nature of models and the process of modeling. To gain a sense of how introductory chemistry students understand model changeability, model multiplicity, the evaluation of models, and the process of modeling, we use a construct‐mapping approach to characterize the sophistication of students' epistemic knowledge of models and modeling. We present a set of four related construct maps that we developed based on the work of other scholars and empirically validated in an undergraduate introductory chemistry setting. We use the construct maps to identify themes in students' responses to an open‐ended survey instrument, the models in chemistry survey, and discuss the implications for teaching.