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ChatGPT as a Virtual Laboratory Teaching Assistant in Undergraduate Biology

● high · 2026-08-19 · biology-education, higher-ed, generative-ai, human-ai-collaboration, simulation, laboratory

Synthesis: Doğru and Faulconer (2026) tested ChatGPT as a virtual teaching assistant (VTA) in an introductory undergraduate biology laboratory course, comparing its responses to student-generated questions about an enzyme-activity lab exercise against those of a cohort of graduate teaching assistants (TAs). Evaluated by subject-matter experts and students, human TAs were more accurate and demonstrated more substantial teaching effectiveness (instructor voice, understanding, helpfulness). Notably, students preferred the computer-generated response 40% of the time and could identify an AI-generated response only 45% of the time. The authors conclude ChatGPT can help lift the burden of basic questions from TAs and instructors, but students must understand its error rate and a safety net is needed to prevent proceeding on incorrect information — a real safety concern in the biology laboratory.

Design

  • Setting: introductory undergraduate biology laboratory course.
  • Method: student-generated questions about a lab exercise on enzyme activity were separately given to ChatGPT and a cohort of graduate TAs.
  • Evaluation: responses were rated by subject-matter experts (SMEs) and students on content accuracy and teaching effectiveness (instructor voice, understanding, helpfulness).

Findings

  • Accuracy: human TAs provided more accurate responses than ChatGPT.
  • Teaching effectiveness: human TAs demonstrated more substantial teaching effectiveness across instructor voice, understanding, and helpfulness — significant on most items for both SME and student ratings.
  • Preference and detection: students preferred the computer-generated response 40% of the time, and could identify an AI-generated response only 45% of the time — a meaningful share of AI output was both preferred and undetected.
  • SMEs: ChatGPT's overall content accuracy was rated acceptable but with a notable error rate on specialized biology terminology and concepts.

The biology-specific challenge

The authors note LLMs may struggle with specialized terminology and concepts in biology, leading to incorrect or misleading information — a concern amplified in a laboratory context where inaccurate information can present safety risks. They draw parallels to prior findings that ChatGPT gives incomplete/misleading answers to physics questions and errors on complex tasks.

Implications

  • VTA value: ChatGPT can serve as a resource to students and lift a burden from TAs/instructors for answering basic questions.
  • Safety net required: students must understand the system's error rate, and safeguards must ensure students do not proceed with incorrect information in the lab.
  • For human TAs: even a human TA should carefully consider using AI to draft responses, with careful attention to accuracy, editing, and addressing voice, understanding, and helpfulness.
  • Future research: cognitive load associated with ChatGPT as a VTA — it may reduce intrinsic load by providing immediate answers while enhancing germane load through on-demand conversational questioning.

Connected Concepts

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Citation

Doğru, M. S., & Faulconer, E. K. (2026). ChatGPT as a virtual laboratory teaching assistant in undergraduate biology. Research in Science Education, 56, 379–399.