What's not in this toolkit — and why

The claim: Match instruction to a student's preferred modality and they'll learn more.

What the research shows: No credible study has demonstrated the matching benefit. Pashler et al.'s 2008 review for the journal of the Association for Psychological Science searched for the predicted "interaction effect" and found none. Willingham et al. (2015) called the theory's evidence base "essentially nonexistent." It survives because students do have preferences — those preferences just don't predict what helps them learn.

Do this instead: Vary modalities across a unit (visual + verbal + tactile) so all students get all channels — Paivio's dual coding framework. Use Memory Box or Graphic Organizer for the visual channel without claiming any student "is" a visual learner.

• Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105–119.
• Willingham, D. T., Hughes, E. M., & Dobolyi, D. G. (2015). The scientific status of learning styles theories. Teaching of Psychology, 42(3), 266–271.

The claim: Specific hand-eye crossover exercises ("hook-ups," "lazy 8s") improve focus and academic performance by integrating brain hemispheres.

What the research shows: The theoretical mechanism is neuroscientific fiction — the corpus callosum doesn't work that way. Hyatt's 2007 review in Remedial and Special Education found "no support" in peer-reviewed research. UK's Sense About Science published a 2008 booklet asking what evidence exists; the answer was none. It persists because the moves feel like they're doing something.

Do this instead: If you want movement for cognition, do actual physical activity. Tomporowski et al. (2008) found moderate-intensity aerobic movement improves attention and executive function. Use the Brain Break / Coping Card tool — it's based on the real exercise research, not the pseudoscience.

• Hyatt, K. J. (2007). Brain Gym: Building stronger brains or wishful thinking? Remedial and Special Education, 28(2), 117–124.
• Tomporowski, P. D., Davis, C. L., Miller, P. H., & Naglieri, J. A. (2008). Exercise and children's intelligence, cognition, and academic achievement. Educational Psychology Review, 20(2), 111–131.

The claim: Students have 8+ distinct "intelligences" (linguistic, logical, musical, spatial, etc.) and instruction should target a student's strongest one.

What the research shows: Gardner's original 1983 theory is interesting as a description of human ability — but the prescriptive leap ("teach to a student's intelligence") was never validated. Waterhouse (2006) reviewed the empirical literature and found the theory makes no testable predictions about classroom outcomes. Gardner himself has written that he never intended teachers to "tag" students with a primary intelligence.

Do this instead: Design tasks that require multiple modes of expression — write + diagram + explain aloud — so the cognitive load shifts across modes within one task. Use One-Pager or the "Adapt for..." rail for genuine differentiation.

• Waterhouse, L. (2006). Multiple intelligences, the Mozart effect, and emotional intelligence: A critical review. Educational Psychologist, 41(4), 207–225.

The claim: Teaching students that intelligence is malleable produces meaningful achievement gains.

What the research shows: Sisk et al. (2018) — a meta-analysis of 273 effect sizes — found the average growth-mindset intervention effect on academic achievement was d = 0.08 (about a 3-percentile-point gain). For students from low-SES households the effect was slightly larger but still modest. The Mueller & Dweck process-praise research is solid; what doesn't replicate is the "give students a 30-minute mindset module and watch grades rise" pitch.

Do this instead: Build mindset into how you give feedback every day — process praise, naming the strategy not the ability — rather than as a standalone unit. Boaler's Mathematical Mindsets shows the embedded version working. Use Making Mistakes to embed the "productive failure" stance into instruction.

• Sisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. L., & Macnamara, B. N. (2018). To what extent and under which circumstances are growth mind-sets important to academic achievement? Two meta-analyses. Psychological Science, 29(4), 549–571.
• Boaler, J. (2016). Mathematical Mindsets. Jossey-Bass.

The claim: Today's students learn differently because they grew up with screens; instruction must be screen-mediated to engage them.

What the research shows: Bennett, Maton, & Kervin (2008) reviewed the empirical evidence and concluded the "digital natives" claim is "neither empirically nor theoretically well-founded." Subsequent OECD PISA data has consistently shown that more classroom technology is associated with worse or no-different academic outcomes. Lorain's own push to reduce screen time aligns with this evidence.

Do this instead: Use technology when it does something paper can't (translation, AI scaffolding, search). Use paper when paper is better (note-taking, deep reading, writing practice). This whole toolkit is built on that principle — every tool has a notebook adaptation.

• Bennett, S., Maton, K., & Kervin, L. (2008). The "digital natives" debate: A critical review of the evidence. British Journal of Educational Technology, 39(5), 775–786.
• OECD (2015). Students, Computers and Learning: Making the Connection. OECD Publishing.

The claim: Children learn to read by encountering whole texts and using meaning + syntax + grapho-phonic cues to guess words.

What the research shows: The National Reading Panel (2000) reviewed 100,000+ studies and concluded systematic phonics instruction produces significantly better outcomes for K–6 students than the meaning-first approach. The "Science of Reading" movement, including journalism by Emily Hanford and books by Mark Seidenberg, has made this consensus reach classrooms over the past decade. Three-cueing in particular teaches struggling readers to avoid looking at the letters — the opposite of what they need.

Do this instead: At the high-school level you're past the decoding wars, but the principle still applies: don't ask struggling readers to "guess from context" without confirming the actual word. Use Marking the Text and Main Idea (Silver) — they require students to ground claims in actual textual evidence, not vibes.

• National Reading Panel (2000). Teaching Children to Read: An Evidence-Based Assessment of the Scientific Research Literature on Reading and Its Implications for Reading Instruction. NIH Publication No. 00-4769.
• Seidenberg, M. (2017). Language at the Speed of Sight: How We Read, Why So Many Can't, and What Can Be Done About It. Basic Books.

The claim: Boys and girls have neurologically different learning needs; separating them or teaching them with different methods improves outcomes.

What the research shows: Eliot's Pink Brain, Blue Brain (2009) systematically reviewed the neuroscience literature and concluded the brain differences between boys and girls are tiny at birth and amplified by socialization — not the other way around. Same-sex classroom RCTs (Pahlke et al. 2014 meta-analysis) found no academic benefit. The claim has been used to justify lower expectations for boys' literacy and girls' math, both of which hurt students.

Do this instead: Set high expectations for every student in every subject. If you're concerned about disengagement patterns, use 2x10 Rapport — relationship-building works across demographics.

• Eliot, L. (2009). Pink Brain, Blue Brain: How Small Differences Grow Into Troublesome Gaps — And What We Can Do About It. Houghton Mifflin Harcourt.
• Pahlke, E., Hyde, J. S., & Allison, C. M. (2014). The effects of single-sex compared with coeducational schooling on students' performance and attitudes: A meta-analysis. Psychological Bulletin, 140(4), 1042–1072.

The claim: Adaptive software platforms can serve as core instruction for whole classes.

What the research shows: What Works Clearinghouse evidence for these platforms is reasonable when used as Tier 2 / Tier 3 intervention for specific students who need it — and weak-to-null when used as Tier 1 core instruction for whole classes. The product marketing often blurs this. Spending 90 minutes/day on adaptive software in place of teacher-led instruction has not been shown to outperform a competent teacher.

Do this instead: Reserve adaptive software for the MTSS tier it was actually validated at. Use teacher-facing tools (everything in this toolkit) for Tier 1 instruction. If your Read 180 students need a Tier 1 lift, give them Cornell Notes + Reading for Meaning with the rest of the class.

• What Works Clearinghouse. (2016). Intervention Report: READ 180. Institute of Education Sciences.
• National Education Policy Center. (2019). Personalized Learning and the Digital Privatization of Curriculum and Teaching.

The claim: Critical thinking, collaboration, creativity, and communication should be taught as content-free, transferable skills.

What the research shows: Willingham (2007) and decades of cognitive-science work since make a clean case: critical thinking is domain-specific, not a general skill that transfers. A student who thinks critically about history doesn't automatically think critically about biology. The skill rides on knowledge of the domain — strip the content and you strip the thinking. Hirsch's The Knowledge Deficit makes the same case for reading comprehension.

Do this instead: Teach critical thinking through rich content. Don't teach "compare/contrast" as a generic skill; teach students to compare the Articles of Confederation to the Constitution. Every tool in this toolkit pairs a thinking move with subject-area content. The Compare/Contrast tool requires a unit topic for that reason.

• Willingham, D. T. (2007). Critical thinking: Why is it so hard to teach? American Educator, 31(2), 8–19.
• Hirsch, E. D. (2006). The Knowledge Deficit: Closing the Shocking Education Gap for American Children. Houghton Mifflin.

The claim: If students look engaged — hands up, on-task, enjoying it — they're learning.

What the research shows: Bjork & Bjork's desirable difficulties work demonstrates that learning often feels harder than ineffective study. Productive struggle looks less engaging in the moment than flashy activities, but produces more durable learning. Engagement is necessary; it isn't sufficient. A class that "had fun" doesn't always mean they learned.

Do this instead: Use formative assessment to check learning, not the engagement vibe in the room. The Exit Ticket, 3-Way Tie, and Claim-Evidence-Reasoning tools all let you sample understanding, not enjoyment.

• Bjork, E. L., & Bjork, R. A. (2011). Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. In M. A. Gernsbacher et al. (Eds.), Psychology and the Real World (pp. 56–64). Worth.
• Soderstrom, N. C., & Bjork, R. A. (2015). Learning versus performance: An integrative review. Perspectives on Psychological Science, 10(2), 176–199.

The claim: AI tutors / AI graders / AI lesson generators can take over substantive instruction or assessment from a teacher.

What the research shows: Current LLMs (including Claude, ChatGPT, Gemini) produce plausible-but-wrong content (hallucinations) at rates incompatible with unsupervised classroom use. Khan Academy's own published data on Khanmigo shows teacher review remains necessary for accuracy. The Ohio DEW Guidance on AI in K–12 Education (2024) explicitly requires teacher-in-the-loop. This toolkit's design — AI suggests drafts, teacher edits and verifies — is intentional, not conservative.

Do this instead: Use AI for what it's good at: first drafts, translation, brainstorming, language-load reduction for ELs. Verify every output. Never put a student in a room with an unsupervised AI tutor for tested content. See the Compliance & AI use page for our position.

• Ohio Department of Education and Workforce (2024). Guidance on Artificial Intelligence in K–12 Education.
• Bender, E. M., Gebru, T., McMillan-Major, A., & Mitchell, M. (2021). On the dangers of stochastic parrots: Can language models be too big? FAccT '21 Proceedings, 610–623.