Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Pearson via LinkedIn
The Specialist, Researcher, also know in the industry as Specialist, Applied Research Scientist, Measurement & Learning Systems supports the research agenda across our formative assessment portfolio, while contributing to coherent assessment system research and innovative applied research initiatives spanning formative, screening/progress monitoring, interim, summative, and custom assessment contexts.
Reporting to the Lead, Formative Product Measurement, this role contributes to research and validation efforts related to efficacy studies, learner and domain modeling, recommender systems, predictive validity, implementation research, case studies, AI validation studies, and innovative applied research initiatives supporting learning and measurement systems across assessment contexts.
This role supports research and validation activities that advance student learning outcomes through product innovation, AI-assisted measurement, and continuous improvement.
This position operates within a research-forward, cross-functional product environment and partners closely with psychometrics, product management, learning science, AI science, content, implementation, and technology teams. The role contributes to innovative research and validation methodologies supporting formative assessment, learner modeling, AI-assisted systems, instructional guidance, and broader assessment innovation initiatives.
Key Responsibilities
- Applied Research & Validation Studies
- Support the design, execution, and interpretation of applied research studies related to learning, assessment systems, and student outcomes.
- Conduct efficacy, implementation, predictive validity, evaluation, and innovative applied research studies aligned with product and organizational priorities.
- Contribute to studies examining instructional impact, engagement, assessment-as-learning outcomes, learner growth, and educational innovation.
- Support development of case studies and evidence narratives demonstrating product implementation, impact, and innovation outcomes.
- Support research examining coherence, alignment, and evidence continuity across formative, screening/progress monitoring, interim, summative, and custom assessment systems.
- Translate research findings into actionable recommendations that inform product and custom design, AI-assisted workflows, reporting systems, learner guidance, and instructional experiences.
- Contribute to innovative methodologies and analytical approaches supporting educational product research, learning systems, and measurement validation.
- Learner Modeling & Recommendation Research
- Support research related to learner models, domain models, recommender systems, adaptive feedback loops, and learning guidance systems.
- Contribute to investigations examining how assessment evidence can inform instructional guidance and personalized learning pathways.
- Collaborate with cross-functional teams to evaluate and refine recommendation approaches, learning insight frameworks, and next-generation formative learning systems.
- Support research and analytical activities across large-scale item banks, dynamic assessment ecosystems, and integrated learning and measurement environments.
- AI Validation & Emerging Research Applications
- Support validation studies related to AI-assisted assessment and learning workflows, including AI-assisted item generation, AI-enabled insights, and generative AI applications.
- Contribute to frameworks evaluating quality, alignment, validity, fairness, traceability, and educational usefulness of AI-assisted outputs.
- Partner with AI Science, Content, Learning Science, Technology, and Measurement teams to evaluate emerging AI-enabled capabilities across learning and assessment systems.
- Explore emerging approaches supporting personalized learning, adaptive guidance, generative AI applications, and next-generation assessment and learning systems.
- Stay informed on emerging research, methodological developments, and innovation trends related to AI in educational and learning contexts.
- Technical Documentation, Dissemination & Thought Leadership
- Contribute to technical documentation supporting product validity, efficacy, interpretive, and measurement claims.
- Develop research summaries, technical reports, conference proposals, presentations, manuscripts, and dissemination materials.
- Translate research findings into clear, actionable insights for technical and non-technical audiences.
- Support external publications, conference presentations, and enterprise thought leadership initiatives.
- Support development of research-informed evidence narratives and technical documentation supporting interpretation, innovation initiatives, and commercialization efforts.
- Cross-Functional Collaboration
- Collaborate with Psychometrics, Product Management, Learning Science, Content, AI Science, Technology, Implementation, and Commercialization teams on research prioritie
Source: Pearson careers (LinkedIn)