Redesigning Vocabulary Assessments in the Age of AI (Science of Reading and Gemini Gems)

How should vocabulary instruction and assessment change now that AI can generate (and complete) traditional vocab work in seconds? In this webinar, Ashley Haken (SWWC) and Sarah Schuman (Worthington) connect the science of reading to vocabulary development, then explore an instructional shift toward deeper, contextualized assessment. You’ll also see a practical demo of building a vocabulary chatbot using Google Gemini Gems, designed as a tutor/coach for learning (not an answer generator). ✅ You’ll learn: Why vocabulary and background knowledge matter for comprehension Key research-backed practices for vocabulary development (explicit instruction, multiple meanings, repeated exposures, active processing) How to redesign vocab assessments so students must apply, explain, and transfer A two-phase model: Learning (AI-supported) vs. Demonstrating knowledge (AI-limited) How to create a Gemini Gem vocabulary coach with guardrails + a feedback loop Timestamps (key points) 00:00 Welcome + introductions 00:32 Agenda: vocab development, instructional shift, AI + assessment redesign 00:55 Science of Reading: Simple View of Reading (word recognition + language comprehension) 01:36 Scarborough’s Reading Rope + where vocabulary fits 02:34 How vocabulary develops: explicit instruction, semantic mapping, multiple exposures, active processing 06:09 Instructional shift: why traditional vocab quizzes are easy to replace with AI 10:24 Two-phase model: Phase 1 (learn with AI support) vs Phase 2 (demonstrate learning with AI limits) 12:02 K–5 examples: teacher-led AI support + age-appropriate assessment shifts 18:08 6–12 examples: student use in learning phase + deeper assessment tasks 20:53 Bloom’s Taxonomy connection: moving from recall to analyze/apply/evaluate 22:43 Classroom examples (K–2, 3–5, 6–12) for AI-supported vocabulary learning 29:11 Building a vocabulary chatbot with guardrails (Gemini Gems) 30:21 Gemini Gems demo: create a “Vocabulary Coach” + preview feedback loop 37:24 Tips for stronger chatbot instructions (persona, task, context, format, constraints) + EduGems resource 43:00 Wrap-up + thanks ✅ You’ll learn: Why vocabulary and background knowledge matter for comprehension Key research-backed practices for vocabulary development (explicit instruction, multiple meanings, repeated exposures, active processing) How to redesign vocab assessments so students must apply, explain, and transfer A two-phase model: Learning (AI-supported) vs. Demonstrating knowledge (AI-limited) How to create a Gemini Gem vocabulary coach with guardrails + a feedback loop Timestamps (key points) 00:00 Welcome + introductions 00:32 Agenda: vocab development, instructional shift, AI + assessment redesign 00:55 Science of Reading: Simple View of Reading (word recognition + language comprehension) 01:36 Scarborough’s Reading Rope + where vocabulary fits 02:34 How vocabulary develops: explicit instruction, semantic mapping, multiple exposures, active processing 06:09 Instructional shift: why traditional vocab quizzes are easy to replace with AI 10:24 Two-phase model: Phase 1 (learn with AI support) vs Phase 2 (demonstrate learning with AI limits) 12:02 K–5 examples: teacher-led AI support + age-appropriate assessment shifts 18:08 6–12 examples: student use in learning phase + deeper assessment tasks 20:53 Bloom’s Taxonomy connection: moving from recall to analyze/apply/evaluate 22:43 Classroom examples (K–2, 3–5, 6–12) for AI-supported vocabulary learning 29:11 Building a vocabulary chatbot with guardrails (Gemini Gems) 30:21 Gemini Gems demo: create a “Vocabulary Coach” + preview feedback loop 37:24 Tips for stronger chatbot instructions (persona, task, context, format, constraints) + EduGems resource 43:00 Wrap-up + thanks