Settings
Configure appearance and authoring defaults, preview the roadmap, and review how the studio handles responsible AI, human oversight, and your data. Preferences persist locally in this browser.
Appearance
An accessibility toolbar is available on every page (text size, contrast, and spacing controls) — look for the toolbar toggle in the corner of the screen.
Author defaults
Pre-fill new artifacts with your common choices. Presentational in this demo.
Future AI features
On the roadmap — not yet available in this demonstration build.
- Voice authoring Soon
- Curriculum translation Soon
- Automatic accessibility review Soon
- Image generation Soon
- Learning analytics integration Soon
- AI curriculum alignment engine Soon
- Student simulation testing Soon
- Multi-language publishing Soon
- API integrations Soon
- Enterprise management Soon
Implementation guide
A concise rollout playbook for Ministries of Education, curriculum departments, districts, publishers, and edtech partners adopting the studio at scale.
- Implementation strategy. Begin with a scoped pilot in one subject and grade band, define success criteria up front, then expand in waves once quality and adoption are proven.
- Author training. Onboard curriculum teams with role-based training on prompting, the pedagogy templates, and the review workflow so AI accelerates — never replaces — professional judgment.
- Governance. Establish ownership, decision rights, and standards bodies; document who may author, review, approve, and publish, and against which frameworks.
- Workflow design. Map the author → review → approve → publish pipeline to your existing processes, with clear hand-offs and status tracking.
- AI governance. Set policies for acceptable AI use, model and data boundaries, disclosure, and audit logging of AI-assisted content.
- Quality assurance. Require subject-matter and pedagogy review, standards-alignment checks, and accessibility validation before any artifact advances.
- Publishing process. Standardize export formats and destinations (LMS, web, print) with versioning and rollback.
- Scaling strategy. Template and reuse successful patterns, build shared libraries, and stage expansion across subjects, grades, and sites.
- Success metrics. Track authoring time saved, standards coverage, review pass rates, time-to-publish, and educator and learner outcomes.
Responsible AI & human review
In this portfolio demonstration, all AI is simulated client-side from templates. Every generated artifact is a draft that requires educator and subject-matter-expert review for accuracy, standards fit, and pedagogy before it is used or published. Nothing leaves the browser — there is no server, account, or external AI call.
In a production deployment, the same outputs would be governed by:
- Data governance — defined ownership, retention, and access controls for all content and prompts.
- Intellectual-property & copyright checks — verification of source rights and licensing before publication.
- Bias monitoring — review of content for representation, fairness, and inclusivity.
- Accessibility review — conformance to WCAG and inclusive-design standards.
- Human-oversight gates — mandatory expert sign-off at each stage; no AI draft auto-publishes.
Data
Manage the information this demo stores locally in your browser.
This site uses localStorage only. Keys: acs:theme (appearance), acs:library (saved artifacts), acs:hist (assistant conversation), and acs:stats (drafts created and time saved). Clearing data removes the library, history, and stats; your theme preference is left intact.