New Pearson data shows students build proficiency with AI-powered practice

Pearson (PSO) published new data on May 5, 2026 showing college students using AI-powered adaptive practice were more likely to build proficiency than peers using static practice.

Rhea-AI Summary

Pearson (PSO) published new data on May 5, 2026 showing college students using AI-powered adaptive practice were more likely to build proficiency than peers using static practice.

Key findings: 90% greater likelihood to reach initial mastery with adaptive practice; 60% higher likelihood when learners also set study goals; gains occurred without additional study time.

Positive

• 90% higher likelihood to reach initial mastery with AI-powered adaptive practice
• 60% additional likelihood to reach proficiency when adaptive practice is combined with goal-setting
• Learning gains achieved without more study time

Negative

• None.

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On May 5, the day this news came out, PSO closed 1.75% above the previous close.

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Key Figures

Proficiency gain vs static: 90% more likely Goal-setting benefit: 60% more likely

Proficiency gain vs static

90% more likely

Students using AI-powered adaptive practice vs static questions

Goal-setting benefit

60% more likely

Adaptive users who also set study goals vs those who did not

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Key Terms

ai-powered adaptive practice, adaptive practice, learner model, learning objectives, +1 more

5 terms

ai-powered adaptive practice technical

"college students who used AI‑powered adaptive practice questions were more likely"

A learning system that uses artificial intelligence to tailor practice exercises and feedback to each user’s strengths, weaknesses and pace, adjusting content in real time like a personal coach that makes tasks easier or harder as needed. For investors, it signals a product that can improve user results and engagement, reduce churn, and scale efficiently—factors that can boost revenue potential and provide ongoing data to refine and differentiate the offering.

adaptive practice technical

"Students who used adaptive practice and set study goals were 60% more likely"

Adaptive practice is a technology-driven approach that adjusts learning activities, treatment plans, or operational processes in real time based on individual performance and feedback. For investors, it signals products or services that can improve outcomes and customer engagement—similar to a smart thermostat that learns your habits to save energy—potentially boosting retention, efficiency and long-term revenue growth.

learner model technical

"Pearson adaptive practice is powered by a proprietary learner model developed"

A learner model is a computer program that learns patterns from historical data to make predictions or decisions, much like a student who studies past examples to answer new questions. Investors care because these models can power trading systems, credit and risk assessments, drug discovery screens, or customer forecasts, affecting revenue, costs and regulatory exposure; their accuracy, bias and transparency can materially change a company’s performance and regulatory risk.

learning objectives technical

"As students answer practice questions tied to specific learning objectives,"

Specific, measurable statements that describe what a person should know, understand, or be able to do after a training, presentation, or educational activity. For investors, learning objectives act like a roadmap or checklist that clarifies what information will be covered and what competence or awareness participants should gain, helping firms show they provided clear education, assess understanding, and reduce the risk of misinterpretation.

adaptive system technical

"Rather than delivering the same practice questions to every student, the adaptive system"

An adaptive system is a technology or process that monitors its environment and changes how it operates based on new information, learning from outcomes to improve future decisions. Investors care because adaptive systems can boost efficiency, reduce errors and costs, and respond faster to market, patient or regulatory changes—much like a thermostat that adjusts heating as the temperature shifts or a GPS that reroutes around traffic to save time.

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Students were 90% more likely to build proficiency with the same amount of study time

HOBOKEN, N.J., May 5, 2026 /PRNewswire/ -- New data from Pearson (FTSE: PSON.L) shows that college students who used AI‑powered adaptive practice questions were more likely to build proficiency than students who used traditional, static practice questions.

Key findings

• Greater proficiency: Students using AI‑powered adaptive practice to study were 90% more likely to reach initial mastery in a topic than those using non‑adaptive practice.
• Added benefit of goal‑setting: Students who used adaptive practice and set study goals were 60% more likely to reach proficiency than peers who did not set goals.
• Same effort, better results: Students achieved these learning gains without spending more time than peers using static practice questions.

"The real question in education today isn't if AI can generate answers, it's whether it can improve human learning.  This data shows that when AI is designed to support teaching and learning, it can help students learn and achieve better outcomes," stated Tom ap Simon, President of Pearson Higher Education.

Why it works

Pearson adaptive practice is powered by a proprietary learner model developed by learning scientists. As students answer practice questions tied to specific learning objectives, the system continuously adjusts—selecting new questions that focus study time on the concepts where each student can make the most progress.

Rather than delivering the same practice questions to every student, the adaptive system targets areas that need more attention, helping students improve more efficiently towards the objectives set by their instructors.

About the study

These proficiency gains were observed in an analysis of more than 62,000 higher education students who used practice questions in Pearson Study Prep during the Fall 2025 term. Pearson Study Prep offers thousands of videos and practice problems for supplemental study aligned to courses and learning objectives designed by instructors.

Tools built on trust

This analysis adds to a growing body of evidence showing that Pearson's AI learning experiences are helping students learn more effectively. Recent Pearson research finds that students using AI study tools were significantly more likely to become active readers and use the AI tools to deepen their learning.

Pearson's application of generative AI is backed by learning science, vetted by subject matter experts, and designed to promote better student outcomes. With over 80% of products now digital or digitally enabled, Pearson is committed to the responsible application of AI to enhance the teaching and learning experience for educators, students, and employers.

Related Pearson news

• New Data Shows AI Study Tools Turn Passive Reading into Active Learning for College Students
• More Than Just Answers: New Pearson Research Shows Students Using AI for Deeper Learning
• AI-Powered Mobile Learning Linked to Higher First-Time GED® Pass Rates as Adult Learners Increase Engagement

About Pearson

At Pearson, our purpose is simple: to help people realize the life they imagine through learning. We believe that every learning opportunity is a chance for a personal breakthrough. That's why our c. 18,000 Pearson employees are committed to creating vibrant and enriching learning experiences designed for real-life impact. We are the world's lifelong learning company, serving customers in nearly 200 countries with digital content, assessments, qualifications, and data. For us, learning isn't just what we do. It's who we are. Visit us at plc.pearson.com.

Media Contacts

Sami.miller@pearson.com (US)

Laura.ewart@pearson.com (UK)

View original content to download multimedia:https://www.prnewswire.com/news-releases/new-pearson-data-shows-students-build-proficiency-with-ai-powered-practice-302762025.html

SOURCE Pearson

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What did Pearson (PSO) report on May 5, 2026 about AI-powered adaptive practice?

According to the company, students using AI-powered adaptive practice were 90% more likely to reach initial mastery. The data also showed goal-setting raised proficiency likelihood by 60% while study time remained unchanged.

How does Pearson say its AI-powered adaptive practice improves student proficiency (PSO)?

According to the company, the adaptive system uses a proprietary learner model to select targeted questions. As students answer, the system adjusts to focus on weak concepts to make study time more efficient toward instructor objectives.

Does Pearson (PSO) claim students spent more time studying to get these gains?

According to the company, students achieved the reported proficiency gains without spending more time than peers using static questions. The finding indicates improved efficiency rather than increased study hours.

What additional benefit did Pearson (PSO) report when students set study goals?

According to the company, students who combined adaptive practice with goal-setting were 60% more likely to reach proficiency than peers who did not set goals. Goal-setting appears correlated with higher mastery rates.

What underlying technology does Pearson (PSO) say powers its adaptive practice?

According to the company, adaptive practice is powered by a proprietary learner model developed by learning scientists. The model continuously adjusts question selection tied to specific learning objectives as students respond.