Constructive alignment, at scale.
You design for alignment: objectives, activities, and assessment that line up by intent. SayaLab extends that discipline into generation, reading your material first, validating every question against its objective and Bloom's level, and showing you the evidence, across a whole curriculum rather than one quiz.
Alignment that breaks at the question level.
Constructive alignment is straightforward to state and hard to hold. You can write clean objectives and map them to a Bloom's level, but the moment generation produces questions, the alignment you designed has to survive contact with the actual items. Most AI tools skip that check: they generate from text and leave you to audit whether each question really measures what its objective claims.
Doing that audit by hand across a module, let alone a programme, does not scale. Item-writing flaws creep in, distractors stop being plausible, and questions drift toward recall while the objective says Analyze. The alignment looks intact on the blueprint and frays in the bank.
Alignment, enforced per question.
SayaLab treats your objectives as first-class input and checks alignment on every question it writes, so the constructive alignment you designed is the alignment that ships.
- Analysis before generation — it extracts learning objectives from your material in measurable terms, yours to edit, and maps the highest Bloom's level each part can fairly support. Where content is too thin to assess an objective at the level you want, it flags it rather than papering over the gap.
- Validation after generation — each question is independently checked for objective alignment, blind Bloom's re-classification, distractor plausibility, and source fidelity. Items that fall short are regenerated automatically, so weak questions do not reach your bank.
- You stay the author — every question carries its evidence, the objective it maps to, the verified level, the distractor strength, with a quality score you can review item by item. You hold the editorial decision; SayaLab holds the question to your standard.
Why it holds at curriculum scale.
The discipline of instructional design is consistency across many objectives and many items. These are the reasons designers use SayaLab to keep that consistency without auditing every question by hand.
Alignment, verified
constructive alignment is checked on each item, not assumed from the blueprint, so what an objective claims to measure is what its questions actually test.
Consistency at scale
every question across a module or programme is held to the same validation standard, so quality does not depend on which items you had time to review closely.
Evidence for review
each question's verified level, objective, and distractor plausibility are visible, which makes design review and stakeholder sign-off a matter of confirming evidence, not re-deriving it.
Common questions.
- What is the best assessment generator for instructional designers?
- Choose one that takes your objectives as first-class input and validates alignment on every question. SayaLab extracts and lets you edit the learning objectives, then checks each generated question for objective alignment, blind Bloom's level, and distractor plausibility, and shows the evidence per item. That lets you hold constructive alignment across a curriculum without auditing every question by hand.
- Does it support constructive alignment across a curriculum?
- Yes. SayaLab is built on Bloom's taxonomy and Biggs' Constructive Alignment. You can run it objective by objective across a module or programme, and each question is validated against the objective it is assigned to and re-classified for its Bloom's level, so the alignment you designed is enforced item by item rather than assumed.
- How does it handle distractor quality and item-writing flaws?
- Every multiple-choice distractor is scored for plausibility against item-writing research: a real misconception, not a giveaway or filler. Questions with weak distractors or other flaws are regenerated automatically, up to two tries, and anything that still cannot clear the bar reaches you flagged with the reason.