Reusable, evidence-based instructions your AI teaching assistant can retrieve and apply in any conversation — from error analysis to retrieval practice. Expand a card to preview the full skill, or open its page for the complete guide.
Redesign teaching sequences to embed productive struggle before instruction, leveraging generation and desirable difficulties to deepen conceptual understanding and transfer.
By Gareth Manning
This skill transforms traditional "teach-then-practice" sequences into "struggle-then-consolidate" models that produce stronger, more durable learning. Rather than explaining a concept before students attempt problems, productive failure requires students to generate solution approaches before receiving instruction. Research shows this generates deeper understanding, despite producing initially lower performance.
Kapur's Productive Failure Framework (2008, 2016): Students attempt novel, challenging problems before instruction, generating multiple approaches in small groups. The teacher then provides direct instruction comparing student-generated methods to the canonical solution. Kapur found students in this condition significantly outperformed direct-instruction-first groups on "conceptual understanding and transfer — even though immediate procedural tests favoured direct instruction."
Bjork's Desirable Difficulties (1994, 2011): Learning conditions that reduce immediate performance but enhance long-term retention. Four key mechanisms: spacing (distributed practice), interleaving (mixed problem types), generation (producing rather than receiving answers), and retrieval practice (testing oneself). These make learning feel harder while strengthening memory traces.
Performance vs. Learning Distinction (Soderstrom & Bjork, 2015): Performance (what students demonstrate now) differs from learning (long-term knowledge change). Desirable difficulties reduce visible performance during lessons but enhance invisible learning—measurable only later through delayed tests and transfer tasks.
Phase 1 — Generation: Students attempt tasks without prior instruction, activating prior knowledge and revealing its limits. The goal is productive struggle, not correct answers. Teachers observe and collect student approaches without intervening.
Phase 2 — Consolidation: Direct instruction explicitly compares student-generated approaches to the correct method, highlighting what worked, what failed, and why the canonical solution addresses those limitations.
Best for conceptual understanding in STEM domains (strongest evidence in mathematics). Less suitable for purely procedural skills or domains without robust productive failure research. Requires teacher expertise in the content.
Turn an unstructured brain dump into sub plans a stranger can follow. Mirror back what the teacher said without adding anything they did not say, format for the specific substitute covering the room, then produce the admin checklist and coordinator email. Use when a teacher needs coverage, often while sick or rushed.
By TeamTeacher
Takes everything a teacher can get out of their head — the lesson, the schedule, materials, student considerations, room procedures — and returns organised, sub-ready plans containing nothing they did not say.
The constraint is the whole skill. A sub plan reaches a stranger who cannot tell your invention from the teacher's instruction, and who will act on it in a room full of children. Fluent guessing is the failure mode.
A teacher mentions sub plans, substitute plans, guest teacher plans, coverage, or being out tomorrow. Often they will open with an apology for the mess. That is the expected input, not a problem to fix.
Teachers usually reach for this at 6am while ill, or in a rush before a funeral, a sick child, or a hospital appointment. Respond like a colleague picking up the slack: warm, quick, no lecture about planning ahead, no guilt, no questions about why they are out. If they sound like they are struggling, say the reassuring thing and then get the work done.
Take the dump exactly as given and reorganise it into something legible: the day in order, materials, student considerations, procedures. Then hand it back and ask what is missing.
This stage is not a draft. It is a memory aid — seeing their own information organised is what lets a foggy, sick teacher notice the thing they forgot. Add nothing at this stage. Not a warm-up, not a transition, not a "students will then...". If a section is empty because they said nothing about it, leave it empty and list it as a question.
Ask, or use what they have already told you:
Then produce a scannable document: headings, short lines, times down the left, the things that matter most impossible to miss. Assume it will be read in a hurry, standing up, five minutes before the bell.
Produce a short checklist of the wrap-up tasks, and draft the messages that go with them:
This is executive-function support for someone running on empty. Being thorough here is the highest-value part of the whole task.
Adapted from the TeamTeacher guide Sub Plans: Brain Dump to Coherent Plans in Three Prompts — https://www.teamteacher.ai/docs/guides/sub-plans-three-prompts
Write seasonal or holiday informational texts that hold more than one tradition, differentiate them for readers above and below grade level, and add standards-aligned comprehension questions plus a family-connection extension. Use when generic seasonal resources do not match the students in the room.
By TeamTeacher
Produces a set of seasonal or holiday materials built for a specific classroom: one informational text covering several traditions, two differentiated versions, and aligned assessment with an extension that connects back to students' own lives.
The gap it fills is narrow and real. Seasonal resources are everywhere; ones that match a particular room's cultural backgrounds, reading levels, and standards are not.
A teacher needs material for a holiday, season, or time of year — end of October, winter celebrations, Lunar New Year, spring festivals, end-of-year reflection — and wants it to reflect the students actually in front of them.
Ask which traditions are present rather than inferring from a location or a set of names. Getting this wrong is the whole risk of the task.
If a curriculum knowledge base is available for their standards, or a multilingual-learner framework for their language supports, use it rather than recalling from memory.
Write an informational text at the target reading level covering several traditions connected to this time of year — including ones present in this classroom, and Indigenous traditions of the land the school is on where the teacher has named them. Align to the standards given. Build in supports for multilingual learners as you write, rather than bolting them on.
Treat each tradition on its own terms. No tradition is the default that others are compared against.
Produce two more versions:
Same content and same respect in all three. A student on the simplified version should not get a thinner or more stereotyped account.
If image generation is available in the conversation, offer to create illustrations for the text — and describe what you intend to depict before generating, so the teacher can catch a misrepresentation before students see it.
Adapted from the TeamTeacher guide Culturally Responsive Seasonal Content: Three Prompts — https://www.teamteacher.ai/docs/guides/seasonal-content-three-prompts
Read standardized assessment data — MAP, NWEA, i-Ready, STAR, state tests — find the cohort patterns worth acting on, design a short targeted intervention for the biggest gap, and write the narrative brief a team or PLC can actually use. Use when score reports land and need to become instruction.
By TeamTeacher
Moves a score report through three steps a teacher rarely has time for: cohort patterns and priorities, a concrete intervention for the biggest gap, and a narrative brief for the people who will ask what the data said.
Works with any standardised assessment — MAP and NWEA RIT scores, i-Ready, STAR, state tests, benchmark assessments — and with a teacher's own common assessments.
A teacher shares assessment data, mentions MAP or benchmark or testing season, asks what their scores mean, or needs something for a PLC, data day, or admin meeting.
If a curriculum knowledge base is available for their framework, use it rather than recalling standards from memory.
Analyse across the cohort, not student by student. Report:
Rank by instructional leverage, not by lowest score. A foundational skill that unlocks three others outranks a slightly weaker isolated strand.
For the highest-priority gap, design a two-week plan that a real teacher can run inside an existing schedule:
Name which students it is for by group and instructional need, not by score rank.
Write a narrative — prose, not a slide dump — covering what the data showed, why these priorities were chosen, what is being implemented, and how success will be measured. Keep it short enough to read in a meeting. This is the artefact that turns an individual analysis into a team decision.
Adapted from the TeamTeacher guide MAP Data Analysis: Three Prompts to Action — https://www.teamteacher.ai/docs/guides/map-data-three-prompts
Analyse student work against criteria to identify specific gaps between current performance and learning objectives, classifying each gap by type and generating targeted teaching steps.
By Gareth Manning
This skill operationalises formative assessment by systematically examining student work to identify what is missing and why. Rather than generic feedback ("needs improvement"), it classifies gaps as conceptual (misunderstanding the underlying idea), procedural (understanding the concept but erring in execution), or communication (understanding but unable to express it adequately). Each classification determines a different teaching response.
The approach is grounded in Sadler's (1989) framework requiring students and teachers to understand learning goals, assess current position relative to those goals, and take targeted action to close gaps. Hattie & Timperley (2007) emphasised that "effective feedback must address three questions: Where am I going? How am I going? Where to next?" Most teacher feedback addresses only the first two; gap analysis ensures the third—specific actionable next steps—receives equal attention.
Heritage (2010) demonstrated that "different gap types require different interventions."
Gap analysis with classified gaps, identified strengths, prioritised next teaching steps, and a feedback script communicating findings to promote improvement rather than discouragement.
Design a checking-for-understanding protocol with specific techniques for each lesson stage. Use when planning systematic comprehension checks during explicit or direct instruction.
By Gareth Manning
This skill generates evidence-based checking-for-understanding protocols that move beyond superficial "Does everyone understand?" toward diagnostic assessment. Rather than merely confirming student attention, it produces actionable techniques paired with decision trees specifying how to respond based on results.
The tool addresses a fundamental gap in classroom practice: most CFU consists of optional hand-raising, which checks only volunteering students while leaving the majority's understanding unmeasured. This skill instead designs protocols ensuring ALL students respond, using mini-whiteboards, finger votes, cold calling with thinking time, and targeted hinge questions—each matched to specific lesson moments.
Required:
Optional: class size, known misconceptions, student profiles, available resources
Chains with: Explicit Instruction Sequence Builder, Hinge Question Designer, Formative Assessment Technique Selector, Retrieval Practice Generator
Draft report card comments that sound like the teacher and cite specific evidence. Establish their voice from past comments, work either from learner archetypes or a per-student notes table, then check every comment against a quality bar before handing it back. Use during any reporting period.
By TeamTeacher
Turns a teacher's class context and evidence into report card comments that are specific, readable by a family, and recognisably in that teacher's voice. Two working paths — archetypes for common learner profiles, or individualised comments built from a row-per-student table of notes.
The failure mode this skill exists to prevent is fluent, generic comments: 25 variations of "works hard and is a pleasure to have in class" that tell a family nothing.
A teacher mentions report cards, progress reports, term comments, or end-of-semester reporting — or pastes a class list with notes and asks for comments. Also use it when they ask you to review comments they have already drafted.
Do not start drafting until you have:
If the teacher has already set up a folder with course documents and past comments, read that before asking them to retype it.
Read their sample comments and mirror back the pattern you actually see: how they open, the order they put things in, how they name a next step, how long a comment runs, whether they address the student or the family. Confirm that reading is right before you scale it to 25 comments.
Path A — Archetypes. Draft comment templates for the learner profiles in this class (for example: strong grasp and ready to stretch; solid work but quiet in discussion; inconsistent completion; growing fast from a low start). The teacher picks the closest match per student and you personalise it with their specific evidence. Faster, and the tone stays consistent across the set.
Path B — Individualised. The teacher supplies a table — one row per student, with brief notes ("asks insightful questions", "detailed lab reports", "led the group revision"). Weave each student's notes into a full comment. Better output, and it needs the teacher to have kept notes.
Offer both. Path A is the right answer for a teacher starting at 9pm with no notes.
Run each draft against the quality bar below and report what fails rather than quietly patching it. "Three comments have no next step" is more useful to a teacher than three silently rewritten comments.
For the hard ones — a struggling student, a behaviour concern, a family relationship that is already tense — give two or three versions with different emphasis and let the teacher choose.
Every comment should have:
Adapted from the TeamTeacher guide Writing Report Card Comments with TeamTeacher — https://www.teamteacher.ai/docs/guides/report-card-comments
Build a student reflection tool around content, skills, and strategies; synthesize what a whole class said into patterns worth acting on; then turn each student's own words into conference talking points. Use before parent, student, or teacher conferences, and for mid-year or end-of-unit check-ins.
By TeamTeacher
Closes the loop between reflections a teacher collects and conversations they actually have. Three stages: design the reflection, synthesise the class, prepare per-student talking points grounded in each student's own words.
The problem it solves is real and specific: teachers assign reflections because metacognition matters, then twenty-five thoughtful responses sit in a spreadsheet unread through the busiest month of the year.
A teacher mentions parent conferences, student-led conferences, reflections, self-assessment, a mid-year check-in, or has a pile of student responses they have not been able to use.
Use three lenses, which give students different things to notice:
Write two or three open-ended questions per lens. Every question must pull for specific evidence, not a feeling. "Which part of the project was hardest, and what did you try?" gets you something. "How did you feel about the unit?" does not.
Match the reading level and the time available. A reflection students cannot finish gives you nothing to synthesise.
Given the collected responses, write a memo-style synthesis of at most 500 words covering:
Write it for the teacher to think with. Name the patterns plainly, including the uncomfortable ones.
For each student, two or three bullets drawn from that student's reflection, with any class context that makes them useful in a conference. Aim for something the teacher can say out loud: what the student sees in their own learning, where that matches or diverges from what the teacher sees, and one thing worth exploring with the family.
Adapted from the TeamTeacher guide Student Reflections for Conference Prep: Three Prompts — https://www.teamteacher.ai/docs/guides/conference-reflections-three-prompts
Audit a lesson plan against UDL's three principles—engagement, representation, and action/expression—identifying access barriers and suggesting concrete, prioritised modifications.
By Gareth Manning
This skill evaluates existing lesson plans through a Universal Design for Learning lens, functioning as a barrier analysis tool rather than a compliance checklist. It examines how design choices may unintentionally exclude learners based on information presentation, response formats, and motivational elements.
The UDL Lesson Auditor takes a completed lesson plan and learner context description, then produces:
The framework originates from CAST research (Rose & Meyer, 2002; CAST, 2018; Meyer, Rose & Gordon, 2014). While implementation research remains primarily quasi-experimental and case-study based, individual components—multiple representations, student choice, flexible assessment—draw support from multimedia learning theory, self-determination research, and formative assessment studies. UDL reduces barriers through intentional design; it does not guarantee access for all learners or replace specialist assessment.
The audit works from described learner variability, which is necessarily incomplete. Teacher knowledge of actual students surpasses any general assessment. For learners with identified needs requiring specialist evaluation, UDL modifications represent foundational design, not complete support.
Pull the academic and content-specific vocabulary students need out of any text, produce a Quizlet-ready import list with student-friendly contextual definitions, then build a practice activity. Use when a teacher has a text — article, transcript, assignment, unit plan — and needs vocabulary support from it.
By TeamTeacher
Starts from a text the teacher already has and ends with vocabulary support they can use tomorrow: the terms that matter, an import-ready study set, and a student activity.
Distinct from the Unit Glossary Designer skill: that one builds a unit-wide reference resource during planning. This one starts from a specific text and ends at student practice.
A teacher pastes or attaches a text and mentions vocabulary, academic language, word lists, Quizlet, or supporting multilingual learners with a reading.
If they have not described the students, ask before extracting. "Student-friendly" is meaningless without knowing which students.
Read the text closely and pull every term students need in order to access the material. Separate:
The second category is the one teachers under-notice and multilingual learners most often trip on. Include words that look everyday but carry a specialised meaning here (a table in a science text, volume, significant, matter).
Narrow to the terms most essential for success, and format one entry per line exactly like this:
word: definition (example sentence with ____ for the target word)
Definitions must be student-friendly and contextual — how the word is used in this text, not the dictionary's most general sense. The example sentence should let a student infer the meaning from the blank.
To import: copy the list, go to quizlet.com/create-set, choose Import, paste, and set the delimiter to a colon.
Offer these three and build whichever they pick — or all three, as a menu:
Adapted from the TeamTeacher guide Academic Vocabulary Support from Any Text: Three Prompts — https://www.teamteacher.ai/docs/guides/vocabulary-support-three-prompts
Generate argument structure scaffolds using Toulmin, PEEL, or CER frameworks for teaching argumentative writing across subjects.
By Gareth Manning
This skill produces discipline-specific argument scaffolds tailored to student level, subject context, and requested framework. Each scaffold includes labelled structural sections with guiding prompts, rhetorical function explanations, sentence starters that model argumentative thinking, and annotated examples showing realistic student-level application.
Research establishes that argument structure requires explicit instruction:
Required:
Optional: subject area, student profiles, text type, example evidence
Chains well with: Disciplinary Writing Scaffold, Critical Thinking Task Designer, Feedback Quality Analyser, Worked Example Fading Designer
Build a unit glossary that removes language barriers instead of just listing words: separate content vocabulary from assessment and command terms, define each with a concrete example and a real-world connection, and map how terms relate. Use during unit planning, when the scope is a whole unit rather than one text.
By TeamTeacher
Builds a glossary for a whole unit, designed against UDL principles — the goal is that academic language stops being the thing standing between a student and the concept.
Distinct from the Academic Vocabulary Extractor skill, which starts from one specific text and ends at Quizlet and student practice. This one is a planning artefact: a reference students and staff return to across a unit.
A teacher mentions a unit glossary, a word wall, a vocabulary list for a unit, or asks how to support academic language across a unit rather than a single reading.
If a curriculum knowledge base is available for their framework, check command terms and assessment language against it rather than recalling them.
Work through the unit material and pull the terms students genuinely need. Then split them into two lists, because they are learned differently:
Use this structure:
[Term]
Order alphabetically within each of the two lists. Then check the whole set for the things that make a glossary usable: consistent definition length, no circular definitions, an obvious path from the basic terms to the harder ones that depend on them.
Read the glossary back against the unit's objectives and, if there is one, its statement of inquiry, and flag:
Report the gaps to the teacher rather than silently filling them.
Adapted from the TeamTeacher guide Creating Unit Glossaries with TeamTeacher.ai — https://www.teamteacher.ai/docs/guides/glossaries
Generate retrieval practice questions at varied difficulty levels for a topic or concept. Use when creating quiz starters, revision activities, or low-stakes testing materials.
By Gareth Manning
This skill generates evidence-based retrieval practice questions designed to strengthen long-term retention through genuine knowledge reconstruction rather than recognition. It distinguishes between free recall (no cues), cued recall (partial scaffolding), and recognition formats, calibrating the mix based on student level and time elapsed since initial instruction.
The testing effect represents one of cognitive psychology's most robust findings. Research demonstrates that "retrieval practice produces substantially better long-term retention than re-studying" (Karpicke & Roediger, 2008). Rowland's meta-analysis of 159 studies found a mean effect size of 0.50 for testing versus restudy across diverse populations. Critically, classroom-based studies with middle school students confirm these laboratory effects transfer to real educational settings, and Dunlosky et al. (2013) rated practice testing as one of only two "high-utility" learning strategies.
Questions must require genuine reconstruction from memory—not surface-level pattern recognition. Teachers provide the topic, student level, and desired question count. Optional contextual inputs include student profiles, curriculum frameworks, time since learning, and documented misconceptions.
The skill cannot verify factual accuracy against specific syllabi; free recall questions may overwhelm lower-performing or EAL learners; and real-world scheduling constraints may necessitate adjusting theoretical spacing intervals. Teacher judgment remains essential.
Generate structured reflection prompts calibrated to specific teaching experiences, guiding teachers from description through analysis to critical reflection and action planning.
By Gareth Manning
This skill produces layered reflection prompts designed for a particular teaching challenge, moving practitioners systematically from surface observation ("What occurred?") through analytical reasoning ("Why did it occur?") to critical examination ("What beliefs am I holding?") and finally to concrete action planning ("What will I change?").
Research shows that professionals don't automatically learn from experience—they learn by reflecting deeply on it. As Schön emphasised, "professionals do not learn primarily from experience—they learn from REFLECTING on experience." Without structured reflection, decades of practice can amount to one year repeated many times.
Required:
Optional: teacher context, emotional response, reflection depth, time available
Generate progressive questioning sequences that develop conceptual understanding through guided inquiry rather than direct instruction, moving learners from current understanding to deeper positions through their own reasoning.
By Gareth Manning
This skill distinguishes Socratic questions (probing reasoning and assumptions) from leading questions (funneling toward predetermined answers). It creates branching dialogue trees anticipating multiple student responses with contingent follow-ups—work most educators cannot accomplish spontaneously.
Required:
Optional: target understanding, student profiles, time available, subject area
Structured sequences including:
Questions progress from concrete examples toward abstraction and principle identification. The approach maintains genuine exploratory dialogue where multiple valid answers remain possible throughout.
Design an error analysis protocol to diagnose the root cause of student mistakes and misconceptions. Use when error patterns appear in student work and targeted feedback is needed.
By Gareth Manning
The protocol distinguishes between three error types: procedural (incorrect method application), conceptual (fundamental misconception), and careless (execution slip despite correct understanding). Research demonstrates that "errors followed by corrective feedback produce stronger learning than errorless learning" due to prediction violation deepening encoding. However, each error type requires fundamentally different instructional responses—re-teaching for conceptual errors, guided practice for procedural errors, and metacognitive monitoring for careless mistakes.
Research establishes that errors, properly analyzed rather than simply corrected, become powerful learning mechanisms. Borasi's work demonstrated errors as diagnostic windows into student thinking. Black & Wiliam identified error analysis as central to formative assessment's diagnostic power. Metcalfe's review confirms learning gains from error analysis. Siegler's microgenetic research showed mathematical development depends on understanding why incorrect strategies fail. Tulis et al. modeled productive error processing through three components: error detection, attribution, and correction strategy—all teachable through systematic analysis.
Evidence sources:
Required:
Optional:
Error classification requires working samples, not isolated answers. Diagnostic questioning is essential for accurate classification.
This skill addresses individual errors; whole-class patterns require instructional redesign through class-level diagnostic approaches.
Selective application is necessary given time constraints—use for persistent, surprising, or shared errors rather than comprehensive analysis of every student mistake.
Chains well with: feedback-quality-analyser, gap-analysis-from-student-work, metacognitive-prompt-library, worked-example-fading-designer
Design mastery experience sequences that systematically build student confidence in skills they avoid, using Bandura's self-efficacy theory.
By Gareth Manning
This intervention constructs a structured progression of tasks that methodically develops self-efficacy for learners who hold limiting beliefs about their capabilities in specific areas. Rather than relying on verbal encouragement alone—which research shows is the weakest efficacy intervention—the approach engineers genuine success experiences starting from the student's current competence level and advancing through carefully calibrated increments.
The method leverages Bandura's four efficacy sources in strategic sequence: mastery experiences (actual success at progressively challenging tasks), vicarious experience (observing similar peers succeed), verbal persuasion (credible, evidence-based encouragement), and physiological state management (reducing performance anxiety).
Bandura's research established that "self-efficacy" is a central determinant of motivation and task performance, particularly noting it predicts outcomes even when controlling for actual ability. Hattie's synthesis identified self-efficacy as one of the strongest individual predictors of achievement. The critical insight: self-efficacy develops through accumulated evidence of capability, not reassurance.
Schunk and Pajares demonstrated that learners' confidence beliefs shape academic outcomes independent of actual ability level. Dweck's work on growth mindset complements this framework, though mindset messaging alone proves ineffective without genuine mastery experiences.
Start from demonstrable strength. Identify what the student already does competently that connects to the target skill. First task success should be near-certain.
Increment difficulty minimally. Each subsequent task represents one small step upward—students must perceive the connection between their last success and the new challenge.
Embed attribution coaching. After each success, guide learners to attribute outcomes to their specific strategies and efforts: "You used the planning method we practised" rather than "You're naturally talented."
Manage physiological state. Anxiety undermines self-efficacy. Employ low-pressure conditions, private rather than public performance, and normalise difficulty as evidence of learning.
Apply vicarious experience strategically. Show peers with similar starting points succeeding, not only high achievers, so the message is credible: "If someone like me can do this..."
Avoid generic praise ("You're so clever!"), unsupported encouragement, public comparison to peers, ability-focused language, and extrinsic reward systems. These undermine credibility and can damage self-efficacy if the student later encounters difficulty.