Using AI to Support Evidence-Based Research in English Composition
Context and Goal
One identified problem with English Composition students using AI tools is that they succumb to “metacognitive laziness,” allowing AI tools to summarize content without engaging in the deep reading necessary to develop stronger metacognitive skills. Especially during the early stages of a research project, students often struggle to understand the relationships among numerous, complex sources and to synthesize those sources into a coherent thesis. This approach addresses that challenge by using an AI tool designed to support evidence-based research while encouraging reflection throughout the research process. The goal is to mitigate overreliance on AI, apply established information literacy frameworks through critical inquiry, and empower students to become efficient, confident knowledge builders while reducing the time, frustration, and cognitive overload often associated with formal research projects.
Application
Students use the free AI tool Google NotebookLM as a research assistant and study partner rather than as a content generator. The platform works only with sources selected and uploaded by the student, encouraging active engagement with evidence throughout the research process.
Step 1: Curate Credible Sources
Students locate and submit a minimum of five credible sources without using Google NotebookLM. Because the tool does not have open-web access to academic databases, students must use institutional library resources to discover, evaluate, and curate their own research materials.
Step 2: Engage with the Sources
Rather than asking NotebookLM to write the paper, students use its conversational interface to analyze the uploaded sources. The platform provides citations to specific passages, allowing students to verify claims, fact-check responses, and reduce the likelihood of relying on inaccurate or unsupported information. Students can also ask the AI to identify conflicting viewpoints among sources for further analysis.
Step 3: Develop the Research Plan
Students use NotebookLM to refine their paper outline, probe deeper into emerging ideas, clarify oversimplified explanations, and brainstorm alternative approaches. As new questions arise, they may upload additional sources and revisit earlier lines of inquiry. This human-in-the-loop process preserves student ownership while strengthening critical engagement with the research.
Instructor Evaluation
NotebookLM maintains a record of student interactions across multiple sessions. Instructors can review prompt histories and AI responses throughout the project, providing formative feedback on students’ research strategies, reasoning, and conclusions before the final paper is submitted.
Outcomes
The implementation produced several positive outcomes:
- Students practiced active reading by following AI-generated citations, verifying evidence, and evaluating relationships among sources.
- Learners developed stronger critical thinking skills by assessing suggested arguments and drawing independent conclusions.
- Students gained a deeper understanding of the importance of credible sources and the role they play in producing high-quality research.
- Students recognized both the strengths and limitations of AI tools, including situations in which AI oversimplified conclusions or emphasized one perspective over others.
- Conversation logs encouraged students to reflect on their reasoning process while providing instructors with meaningful opportunities for targeted formative feedback.
- Students learned that NotebookLM can reduce the logistical burden of organizing research while preserving the critical evaluation necessary for effective scholarship.
- The process produced stronger, evidence-based early drafts, reduced stress during revision, and supported the development of each student’s authentic voice as a researcher.