Learning Sciences Specialist $200,000 USD/year Pay is set based on global value, not the local market.
Most roles = hourly rate x 40 hrs x 50 weeks
Description
Much of today's educational software conflates engagement with actual learning. The outcome is material that captures interest temporarily but fails to consistently foster comprehension. Evidence from explicit instruction research and multimedia learning studies offers a more reliable path: learners perform better when instruction is organized, transparent, logically sequenced, and engineered to minimize extraneous cognitive load.
LearnWith.AI is adopting a more rigorous stance. Rather than framing instructional video as a content challenge, the team approaches it as a learning-outcomes challenge. This position ensures that every mathematics video upholds strict standards for direct instruction, evidence-based pedagogy, and learning science, so that growth does not undermine student comprehension.
This position is designed for someone who can review a lesson and immediately identify whether the instructional sequence is functionally effective. You must be capable of diagnosing shortcomings in clarity, pacing, modeling, formative assessment, and conceptual progression, and then converting that analysis into specific written guidance. This is not a general content oversight position, a creative media position, or a broad curriculum position disconnected from research-validated instruction.
You will operate at the center of the product by defining the benchmark for instructional quality throughout the library. If you are committed to ensuring students genuinely master mathematics, and you seek a position where your judgment shapes work at scale, this role offers exceptionally direct influence.
What you will be doing
- Assess mathematics videos using direct instruction and learning science frameworks, delivering explicit approval or rejection decisions, precise feedback, and embedded observations that iteratively strengthen instructional quality standards
What you will NOT be doing
- General content oversight - assessing non-instructional or non-video materials without grounding in learning science or direct instruction frameworks
- Impressionistic feedback - offering unstructured opinions about content quality that lack defined evaluation criteria
Key responsibilities
- Serve as the quality gatekeeper for learning-science-aligned, high-fidelity direct instruction mathematics videos that reliably produce measurable student learning gains
Candidate requirements
- Experience teaching K–8 mathematics or developing K–8 mathematics instructional materials (e.g., lesson plans, curriculum units, practice activities, digital learning tools)
- Experience reviewing video-based instructional materials and delivering structured written feedback
- Working knowledge of Cognitive Load Theory and Mayer's Multimedia Principles
- Currently residing in the United States
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