Data set for Feedback Sources and Feedback Sense-Making in Undergraduate Biology Writing

This dataset contains anonymized quantitative and coded qualitative data collected for a mixed-methods study examining how different formative feedback sources shape undergraduate biology students’ writing, scientific reasoning, and engagement with revision. Data were collected from students enrolled in General Biology II and Botany courses at a U.S. community college (N = 104) and include final essay performance scores based on an analytic writing rubric, pre- and post-assessment measures of multiple scientific reasoning subskills, and coded student perception data derived from written reflections on feedback use. Students were assigned to one of four feedback conditions: AI-generated feedback, peer feedback, expert feedback, or instructor-provided guidelines. All variables are de-identified and reported at the individual level to support transparency, replication, and secondary analysis. The data were analyzed using descriptive statistics, regression models, paired-sample comparisons, and thematic coding, with analyses conducted in Jamovi. These data support research on formative feedback, feedback literacy, scientific reasoning, and disciplinary writing in undergraduate biology, particularly in community college STEM contexts.