Refinement of an instrument measuring science teachers’ knowledge of language through mixed method

Abstract

Abstract Teachers must know how to use language to support students in knowledge generation environments that align to the Next Generation Science Standards. To measure this knowledge, this study refines a survey on teachers’ knowledge of language as an epistemic tool. Rasch modelling was used to examine 15 items’ fit statistics and the functioning of a previously-designed questionnaire’s response categories. Cronbach’s alpha reliability was also examined. Additionally, interviews were used to investigate teachers’ interpretations of each item to identify ambiguous items. The results indicated that three ambiguous items were deleted based on qualitative data and three more items were deleted because of negative correlation and mismatched fit statistics. Finally, we present a revised language questionnaire with nine items and acceptable correlation and good fit statistics, with utility for science education researchers and teacher educators. This research contributes a revised questionnaire to measure teachers’ knowledge of language that could inform professional development efforts. This research also describes instrument refinement processes that could be applied elsewhere.

Keywords

• Language
• Instrument refinement
•  Rating scale model
• Epistemic tool