In 2026 thePersonalized feedbackfaster, but controlled. The teacher can have feedback drafts generated anchored to the criteria (“comment only on thesis, evidence, and coherence; propose a next step”) and then refine them. A good use is to ask for alternative phrasings: a short version (30 words) and a more explicit version (80 words), choosing the one suited to the student.StudierAI3) Targeted activities and differentiation. When gaps emerge, StudierAI can propose scaffolded exercises, additional examples, guiding questions, or short formative checks, always aligned with the objectives. The teacher decides what to assign, to whom, and with what constraints (time, level, format). If you want to experiment in a light way, you canstart for freeand begin with a single teaching unit.
Key element:
. AI must make clear what evidence a summary is based on and allow the teacher to modify criteria, weights, and priorities. Assessment remains a professional act: the tool speeds up, it doesn’t delegate.formative assessmentResponsible implementation: privacy, equity, transparency, and impact evaluation
To integrate AI into formative assessment in a credible way, clear rules are needed, shared with students and the institution. Four pillars help prevent problems and build trust:privacy,
transparency
The risk of data collection is accumulating information that is not very usable. To supportPrivacy: minimize data, keep only what is needed for the educational purpose, define retention times, and inform in an understandable way. Avoid uploading materials with unnecessary sensitive data; prefer internal identifiers or anonymized work when possible.you need lightweight but frequent evidence, linked to explicit criteria. In practice, what is worth monitoring along the way often falls into four areas: process, product, participation, and metacognition.
- Process: strategies used, intermediate steps, time management, use of sources and tools.
- who we are
- Participation: meaningful contributions, collaboration, questions asked, active listening, responsibility within the group.
- sign up for free
To turn this evidence into observable indicators, it helps to define 3–5 criteria per activity (not 12), described with verbs and behaviors: “formulates a testable hypothesis,” “justifies with at least two pieces of evidence,” “revises the text applying the rubric.” The goal is not to measure everything, but to make shared what “good work” means and what “next improvement” means.
Personalized and timely feedback: practical strategies for the real classroom
Effective feedback istimely, specific, and action-oriented. It doesn’t always have to be long: often two well-targeted sentences are enough. To sustain frequency without overloading the teacher, short, repeatable routines work.
Lightweight rubrics (even with 3 levels). Use them as a “common language” and as a guide for quick comments. Examples of wording:“Strength: … / To move up a level: … / Concrete next step by tomorrow: …”.
2-minute exit ticket. At the end of the lesson, ask for a single piece of evidence: “What is the key idea?”, “Where did you get stuck?”, “Which example would you use?”. Then group the answers into 3 categories (ok / partial / to revisit) and plan a mini-intervention at the start of the next lesson.
Guided revisions. Instead of correcting everything, choose just one focus per round (e.g., thesis and argumentative coherence; then citations; then style). Provide a revision model: highlight → explain why → rewrite. Feedback becomes a sequence of actions, not a judgment.
Structured peer feedback. It works if it is constrained by criteria and timing: 5 minutes reading, 5 minutes comments on two criteria, 2 minutes to decide on a change. Useful phrases to have students use:“I understood well when…”, “I’m missing a step here…”, “If you add an example, the argument becomes stronger”.
Workload management: alternate “spot-check” feedback (on one criterion for the whole class) and “priority” feedback (more detailed only where needed). Also, standardize 10–15 reusable comment templates, personalizing them with a specific detail from the student’s work.
How StudierAI supports monitoring and real-time intervention
In day-to-day work, the bottleneck isn’t “having activities,” but reading weak signals and turning them into actions.StudierAIcan support continuous formative assessment in three practical ways, without replacing teacher judgment: collecting/organizing evidence, synthesizing forlearning monitoringand generating operational proposals for targeted interventions.
1) More readable evidence. Starting from prompts, rubrics, and student work, AI can help identify recurring patterns (e.g., confusion between closely related concepts, missing logical steps, procedural errors) and group similar needs. This enables micro-interventions: a mini-lesson for one group, a targeted exercise for another, an extension for those who are already ahead.
2)Personalized feedbackfaster, but controlled. The teacher can have feedback drafts generated anchored to the criteria (“comment only on thesis, evidence, and coherence; propose a next step”) and then refine them. A good use is to ask for alternative phrasings: a short version (30 words) and a more explicit version (80 words), choosing the one suited to the student.
3) Targeted activities and differentiation. When gaps emerge, StudierAI can propose scaffolded exercises, additional examples, guiding questions, or short formative checks, always aligned with the objectives. The teacher decides what to assign, to whom, and with what constraints (time, level, format). If you want to experiment in a light way, you canstart for freeand begin with a single teaching unit.
Key element:transparency. AI must make clear what evidence a summary is based on and allow the teacher to modify criteria, weights, and priorities. Assessment remains a professional act: the tool speeds up, it doesn’t delegate.
Responsible implementation: privacy, equity, transparency, and impact evaluation
To integrate AI into formative assessment in a credible way, clear rules are needed, shared with students and the institution. Four pillars help prevent problems and build trust:privacy,equity,transparencyand impact evaluation.
Privacy: minimize data, keep only what is needed for the educational purpose, define retention times, and inform in an understandable way. Avoid uploading materials with unnecessary sensitive data; prefer internal identifiers or anonymized work when possible.
Equity: check that feedback proposals do not penalize linguistic styles, backgrounds, or different educational needs. Provide accessible alternatives (time, formats, channels) and do periodic “sampling” to verify consistency across groups. AI can amplify biases present in the data: supervision is needed.
Transparency: state when and how AI is used (feedback drafts, activity suggestions, evidence summaries). Explain that the final decision is the teacher’s and make the criteria visible. If you’re interested in exploring the project’s approach and principles, you can consultwho we are.
Impact evaluation: choose 2–3 simple metrics that can be compared over time, for example (a) reduction in recurring errors on a criterion, (b) increase in the quality of revisions between first and second submission, (c) students’ perceived usefulness of the feedback. Add a contextual note (which activity, which constraints) to interpret the results. If you want to start with a 3-week pilot, you can alsosign up for freeand test just one routine: exit ticket + brief feedback + guided revision.
In 2026 the challenge isn’t choosing between assessing and teaching: it’s designing a system in which assessing means teaching better, every week. With clear criteria, useful micro-data, and tools like StudierAI used responsibly, continuous formative assessment becomes a concrete ally of instructional quality.
