Writing, research, and composition have an uneven, complicated history in higher education. In an institution created for wealthy white males, so-called academic discourse is still upheld as a virtue by many faculty, and its perceived lack of evidence in student writing is often condemned. Many students of color are not celebrated for their use of language but punished excessively in a system that linguistically overlooks the beauty of diversity in language and dialect, and women’s writing has been traditionally portrayed as passive no matter how direct and active their writing may be. Beyond grammar, mechanics, and other conventions of academic writing, faculty choose which student essays to audit for plagiarism. Disproportionately, students of color and women have been accused of, audited, and punished for plagiarism. Unethical academic auditing has the potential to perpetuate racial, ethnic, and gender bias in the evaluation of student writing no matter the system of writing, feedback, and technology. This chapter examines the history of academic writing in higher education and the role of bias in asynchronous feedback and grading. It provides methods for how faculty might equitably evaluate student writing in the age of artificial intelligence.

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Artificial Intelligence and Academic Auditing: Bias in Systems and Institutions

  • Jennifer L. Reichart

摘要

Writing, research, and composition have an uneven, complicated history in higher education. In an institution created for wealthy white males, so-called academic discourse is still upheld as a virtue by many faculty, and its perceived lack of evidence in student writing is often condemned. Many students of color are not celebrated for their use of language but punished excessively in a system that linguistically overlooks the beauty of diversity in language and dialect, and women’s writing has been traditionally portrayed as passive no matter how direct and active their writing may be. Beyond grammar, mechanics, and other conventions of academic writing, faculty choose which student essays to audit for plagiarism. Disproportionately, students of color and women have been accused of, audited, and punished for plagiarism. Unethical academic auditing has the potential to perpetuate racial, ethnic, and gender bias in the evaluation of student writing no matter the system of writing, feedback, and technology. This chapter examines the history of academic writing in higher education and the role of bias in asynchronous feedback and grading. It provides methods for how faculty might equitably evaluate student writing in the age of artificial intelligence.