Advanced Specialist, Learning Scientist

Advanced Specialist, Learning Scientist

Measurement & Learning | School Assessment

Role Overview 

We are seeking an Advanced Specialist, Learning Scientist (Assessment & Learning Experience Systems) to shape the design, guidance, and continuous improvement of student-centered assessment and learning experiences within intelligent assessment systems.

This role sits within the Measurement & Learning team and operates at the intersection of Learning Science, Measurement, Product, UX, Content Development, Technology, and AI Science. The role is responsible for helping ensure assessment and learning experiences within Pearson’s formative assessment system, Navvy, are instructionally meaningful, cognitively engaging, motivationally supportive, and aligned to evidence-based learning principles.

This role helps ensure AI-assisted assessment and learning systems promote thinking, reflection, productive struggle, and meaningful learning rather than replacing student cognition.

The role supports the design of student-facing engagement experiences, intelligent practice and review systems, AI-assisted academic guidance approaches, and learning support ecosystems connected to standards-based assessment evidence.

This role also contributes to the evolution of the Navvy Learning Library as a supplemental instructional and learning support ecosystem, helping guide strategic decisions around instructional experiences, standards-aligned learning supports, high-quality instructional materials, AI-assisted content expansion, and student-centered learning design.

Student-Centered Learning Experiences

• Lead learning science and student experience design considerations for student-facing assessment and learning features within the platform

• Help shape experiences related to goal setting, metacognitive reflection, growth mindset and motivation, achievement and growth recognition systems, student reporting and communication, and student agency and engagement

• Partner with UX, Product, Technology, Measurement, and Content teams to translate learning science principles into product requirements and student experiences

• Help ensure platform experiences promote healthy learning behaviors, reflection, persistence, and meaningful engagement

Intelligent Practice & Learning Pathways

• Provide learning science guidance for intelligent practice and review systems, including SmartSets and future adaptive learning experiences

• Help guide decisions around prerequisite skill support, productive struggle, cognitive load and engagement, reinforcement and retrieval practice, building on student strengths, and personalized review and practice pathways

• Collaborate with measurement and product teams to help ensure practice experiences support meaningful knowledge development, prerequisite skill connections, and deeper learning rather than isolated performance optimization

AI-Assisted Academic Guidance & Learning Supports

• Lead learning science input related to AI-assisted academic guidance experiences within the platform

• Help shape approaches for AI-assisted review and reflection experiences, worked examples and instructional supports, Socratic questioning and guided inquiry, AI-generated explanations and concept supports, and AI-assisted feedback and learning guidance

• Help ensure AI-assisted guidance systems support thinking, reasoning, metacognition, and learning transfer without overloading or replacing student cognition

• Collaborate with AI Science, Measurement, Product, and Technology teams to establish learning-centered guidance principles and guardrails for AI-assisted learning experiences

Learning Library Strategy & Instructional Ecosystem

• Lead strategic learning science input for the evolution of the Navvy Learning Library as a standards-aligned instructional support ecosystem

• Help guide decisions related to digital learning activities and assignable learning experiences; high-quality instructional materials and supplemental learning supports aligned to standards and subskills; independent and teacher-facilitated learning activities; teacher-facing instructional supports; external instructional content partnerships; AI-assisted approaches to responsibly expanding learning materials; and cross-standard instructional and pedagogical supports

• Help guide evaluation approaches for instructional quality, alignment, and educational usefulness of learning materials and supports

• Help ensure learning supports meaningfully support both student learning and teacher instructional understanding

• Help ensure learning materials and instructional supports remain instructionally coherent, standards-aligned, cognitively appropriate, and educationally meaningful

Research, Innovation & Thought Leadership

• Stay informed on emerging research related to cognitive science, learning science, motivation, metacognition, AI-assisted learning, and instructional design

• Contribute to innovation discussions around next-generation assessment and learning experiences

• Help design and interpret experiments, pilots, and A/B-style evaluations related to student engagement, learning supports, instructional experiences, and AI-assisted guidance approaches

• Support development of learning science frameworks, design principles, guidance documentation, and dissemination materials

• Contribute to internal and external thought leadership related to assessment-as-learning, intelligent learning systems, and student-centered learning design

• Help translate complex learning science concepts into practical guidance for cross-functional teams

Cross-Functional Collaboration

• Partner closely with Product, UX, Technology, AI Science, Measurement, and Content teams

• Collaborate with SMEs and instructional experts to inform learning experience and instructional support decisions

• Support alignment between assessment evidence, learning experiences, instructional supports, feedback systems, and student guidance experiences

• Help ensure coherence across assessment, learning, engagement, feedback, and instructional systems within the broader Navvy ecosystem

Required Qualifications

• Advanced degree in Learning Sciences, Educational Psychology, Cognitive Science, Instructional Design, Educational Technology, Educational Measurement, or a related field

• Experience applying learning science principles within digital learning, assessment, or educational product environments

• Strong understanding of motivation and engagement, metacognition and self-regulated learning, productive struggle and cognitive load, retrieval practice and learning transfer, and growth mindset and student-centered learning

• Experience collaborating across cross-functional teams including Product, UX, Technology, Content, Measurement, or AI-related teams

• Ability to think systematically about assessment and learning experiences within intelligent educational systems

• Strong written and verbal communication skills, including the ability to translate learning science concepts into actionable product guidance

• Comfort exploring and prototyping AI-assisted approaches to learning and instructional support

Preferred Qualifications

• Experience designing or supporting student-centered digital learning experiences

• Experience working within standards-aligned instructional or assessment systems

• Familiarity with formative assessment systems and assessment-as-learning principles

• Experience supporting adaptive learning, intelligent tutoring, recommendation systems, or AI-assisted learning experiences

• Experience evaluating instructional quality, supplemental learning materials, or instructional support ecosystems

• Experience contributing to learning product strategy, instructional ecosystem design, or digital learning innovation

• Familiarity with AI-assisted instructional supports, academic guidance systems, or generative AI learning applications

• Experience contributing to presentations, publications, technical documentation, or thought leadership initiatives

• Curiosity about emerging approaches to intelligent learning systems and AI-assisted educational experiences

Design Philosophy

• Student thinking and learning as the core system priority

• Productive struggle over answer delivery

• Reflection, metacognition, and student agency as essential learning processes

• Assessment as a mechanism for learning, not just measurement

• Human-centered and educationally meaningful AI-assisted learning experiences

• Innovation grounded in evidence-based learning principles

Why This Role Matters

This role is foundational to helping ensure intelligent assessment and learning systems meaningfully support student learning, motivation, reflection, and growth. By grounding assessment and learning experiences in cognitive science, learning science, and thoughtful AI-assisted design, this leader will help shape systems that support deeper learning while preserving student thinking, agency, and instructional integrity.

Compensation at Pearson is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific location. As required by the California, Colorado, Hawaii, Illinois, Maryland, Minnesota, New Jersey, New York State, New York City, Vermont, Washington State, and Washington DC laws, the pay range for this position is as follows: 

The minimum full-time salary range is between $110,000 - $125,000.

This position is eligible to participate in an annual incentive program, and information on benefits offered is here.

Applications will be accepted through Monday, July 6, 2026. This window may be extended depending on business needs. 

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