Pearson data links AI study tools to surge in active reading among college students

Nearly 80 million student interactions suggest responsible AI use may shift digital learning from passive scrolling to deeper engagement.

Pearson says new analysis of nearly 80 million student interactions shows AI study tools embedded within its digital higher education materials significantly increase the likelihood that students engage in active reading behaviors, a skill closely tied to academic performance.

The Hoboken, New Jersey-based learning company analyzed global interaction data from close to 400,000 higher education students using its digital materials during the semester beginning January 2025. The findings suggest that when AI tools are integrated directly into course content, students are more likely to adopt behaviors associated with deeper comprehension.

AI use tied to active reading behaviors

According to Pearson, a single interaction with its AI study tool within a standalone eTextbook increased the likelihood that a learner would be classified as an active reader by three times. Repeat use raised that likelihood to 3.5 times.

In instructor-led digital courseware, the impact was more pronounced. A single use of the AI study tool increased the likelihood a student would be classified as an active reader by 23 times. Repeat users were 24 times more likely to receive that designation.

Tom ap Simon, President of Higher Education at Pearson, says: “After two years of studying how students actually learn with AI, the signal is clear that AI designed responsibly and grounded in learning science strengthens how students engage with digital materials. This research shows AI can be a true learning multiplier—providing instructors with tools that help move students from passive consumption to active reading and deeper cognitive engagement, essential for college and career success.”

Pearson defines active reading as the use of strategies such as highlighting, note-taking, asking clarification questions, and retrieving information from memory. These behaviors are strongly associated with deeper comprehension, stronger retention, and improved academic performance.

The company notes that reading comprehension remains one of the strongest predictors of early college GPA. However, national data indicates declining readiness. Only 39 percent of students taking the ACT in 2025 met college-level reading benchmarks, and nearly half of professors report that first-year students are “much less prepared” for close reading and analysis compared to pre-pandemic cohorts.

Addressing AI misuse concerns

Pearson says the design of its AI tools is intended to reduce risks of cognitive offloading and overreliance.

Dr. Emily Lai, Head of Research at Pearson and co-author of the study, says: “Active reading remains one of the most powerful mechanisms we have for building durable knowledge and skills. Cognitive offloading and students’ overreliance on AI tools are serious concerns for educators that we are studying and working to circumvent. That’s why the way we design AI tools to work really matters. Our research shows that when AI is responsibly integrated into the flow of learning, it can promote learning, rather than replace it.”

A separate Fall 2025 analysis of a widely used introductory biology eTextbook found that 97 percent of students used Pearson’s AI study tool responsibly. According to Pearson, three percent attempted to paste homework or assessment questions into the tool.

The same analysis found that one in three students using the tool’s question-asking feature posed questions beyond basic remembering and understanding under the revised Bloom’s Taxonomy, instead attempting to apply, analyze, or evaluate course content. Pearson says this finding aligns with previous learning outcomes research conducted in June 2025.

Implications for digital higher education

Pearson states that more than 80 percent of its products are now digital or digitally enabled. Unlike general-purpose AI chat tools, the company says its generative AI applications are backed by learning science, reviewed by subject matter experts, and designed to support measurable learning outcomes.

The scale of the dataset, nearly 80 million interactions, will likely draw attention from institutions evaluating the role of embedded AI within course materials. The findings also enter a broader debate about whether AI in education accelerates shortcuts or supports deeper cognitive engagement.

For edtech providers and universities alike, the question is shifting from whether students are using AI to how tool design influences learning behaviors.

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