1) Human Grading: Rich but Highly Variable
Studies in measurement and evaluation show that human grading contains a lot of "noise": variations that have nothing to do with the student's actual competence. For example, a meta-analysis on essay grading highlights that disagreements between human graders are frequent, even with similar rubrics and training.
One of the classics in the field, the study by Wang and Brown (2008), shows that the level of agreement between two human graders is not perfect, and that automated grading systems often achieve an agreement of the same order of magnitude. According to this study, the correlation between scores from an automated grading system and those from human graders is comparable to the correlation between two well-trained humans.
Other works, such as the systematic review by Hussein, 2019 – Automated language essay scoring systems, remind us that human graders are sensitive to fatigue, mood, context, and implicit expectations about the student's level. This is precisely the type of variability that AI can reduce if given a clear framework.
2) What Scolaro's AI Does Differently
Scolaro's philosophy is simple: AI doesn't invent criteria; it applies an explicit rubric.
Specifically, for a given assessment, Scolaro's AI receives:
- a detailed rubric, inspired by MEQ evaluation frameworks and real high school teaching practices;
- criteria and weightings defined by the teacher (or the school team);
- examples of good and bad answers to guide the interpretation of criteria.
Then, grading is always done the same way:
Uniform Application of the Rubric: the same rubric for all students, from the first to the last graded. No fatigue, no loss of vigilance at 10 PM.
Criterion-by-Criterion Analysis: AI evaluates criteria separately (understanding instructions, rigor of process, quality of argumentation, etc.).
Clear Explanation: for each criterion, the AI can generate a justification in plain language, aligned with the rubric.
Full Traceability: teachers can see why each point was awarded or not, and adjust as needed.
Result: Grading becomes more disciplined than human grading alone. We don't eliminate professional judgment, but we impose a more stable framework, which is exactly what school boards and parents in Montreal and elsewhere in Quebec demand.
3) What Research Says on Automated Grading
Several scientific reviews confirm that well-designed automated grading systems can be as reliable as sets of human graders, while being faster and more consistent.
According to the review by Ramesh et al., 2021 – Automated essay scoring systems: a systematic literature review, automated grading systems generally achieve reliability at least comparable to human graders in large-scale exams. The authors emphasize a key point: these systems work well when trained and calibrated with a precise rubric.
Another important review, Bulut et al., 2024 – The Rise of Artificial Intelligence in Educational Measurement, explains that AI has achieved particularly solid results in the automated grading of constructed responses (long questions, justifications, written productions), especially when:
- evaluation criteria are explicit,
- the AI is calibrated on papers graded by experts,
- a human keeps the final word on the grade.
Finally, several recent studies directly test models like ChatGPT for grading. For example, García-Varela & Martínez, 2025 – ChatGPT as a Stable and Fair Tool for Automated Essay Scoring show that when provided with a detailed rubric and clear instructions, ChatGPT can grade essays with a level of consistency close to that of teams of human graders.
In the health field, Quah et al., 2024 – Reliability of ChatGPT in automated essay scoring for educational assessment show that ChatGPT scores are strongly correlated with human scores, and that AI is capable of following complex grading criteria if explicitly provided. The authors also highlight AI limits for high-stakes decisions, which argues for a model where the teacher remains in control — as in Scolaro.
4) Why Scolaro's AI Becomes More Objective Than Human Grading Alone
By combining a rubric, AI, and professional judgment, Scolaro reinforces grading objectivity in several ways:
4.1. Consistency Over Time
A student in Montreal graded on Monday morning and another student in Quebec City graded on Friday night benefit from the same criteria applied in the same way. The AI doesn't get tired, doesn't grade faster because the bell is about to ring, and doesn't "give up" at the end of the pile.
4.2. Neutrality Toward the Student
Scolaro's AI can grade from anonymized papers (no name, no photo), which reduces some unconscious biases: perception of level, classroom behavior, accent, etc. Criteria are applied to the production, not the reputation.
4.3. Clear and Explainable Rubric
Since the AI must use the rubric, every decision can be explained. Teachers can respond to students and parents with phrases like:
"According to the rubric, criterion 3 (justification of process) is not met because the last step of the reasoning is missing. Scolaro's AI therefore deducted 2 points on this criterion."
This alignment between rubric, grade, and explanation makes grading more transparent and defensible to school administration or a parent.
5) AI as Performant as Humans... If Well-Framed
Recent studies summarize the situation as follows: an AI left to its own devices is not reliable, but an AI guided by a precise rubric and controlled by teachers can achieve performance very close to humans, with more stability.
This is exactly the Scolaro model for schools in Montreal, Quebec, and the rest of Canada:
- Rubric First: every assessment relies on a detailed rubric inspired by MEQ frameworks or school team expectations.
- Calibration on Real Papers: the AI is tested on papers graded by teachers to stay within the same tolerance zone.
- Human-in-the-Loop: the AI proposes an explained grade, and the teacher can confirm, adjust, or reject it.
According to several synthesis works on AI in evaluation, for example Ifenthaler, 2022 – Automated Essay Scoring Systems, it is precisely this type of combination of human + AI + rubric that offers the best balance between efficiency, reliability, and ethics.
6) Limits and Safeguards: Objectivity Doesn't Mean Blindness
Researchers remind us that automated grading systems can themselves contain biases (on certain student groups, language variations, atypical styles, etc.). Works like those of Bulut et al., 2024 emphasize the need to monitor the validity, transparency, and fairness of AI systems.
Scolaro integrates these safeguards:
- the teacher always keeps the final decision on the grade;
- rubrics can be adjusted over time;
- statistics can be tracked to identify possible biases;
- AI can be limited or disabled for certain highly creative or sensitive works.
The goal is thus not to eliminate teacher judgment, but to give them a more stable measurement instrument, particularly useful when the grading load explodes (during exams, finals, or in large cohorts in Montreal and school service centers).
7) What a Montreal or Quebec School Gains with Scolaro
For a high school in Montreal, Laval, the North Shore, or the South Shore, Scolaro's AI grading brings three concrete benefits:
More Fairness for Students
Students are evaluated using the same criteria, regardless of group, time, or teacher. The grade depends on the production, not the luck of the grader.
More Transparency
Explanations generated by the AI from the rubric make the grade much more readable for parents, administration, and, if necessary, the school service center.
More Time to Teach
By delegating part of the mechanical grading to AI, teachers regain hours they can invest in oral feedback, differentiation, project preparation, etc.
8) Quick FAQ on Scolaro AI Grading
No. The AI applies a clear rubric and proposes an explained grade, but the teacher always keeps the last word. We are talking about a grading assistant, not a replacement.
Yes, in the sense that the rubric is applied identically to all students and variability related to fatigue, mood, or unconscious bias is greatly reduced. The studies cited above show that well-designed systems achieve reliability comparable to humans, with more stability.
Yes. Scolaro is designed to align with MEQ evaluation frameworks and real teaching practices in French-speaking Quebec schools. Rubrics and criteria are configurable according to the program and school service center.
Scolaro is developed in Montreal (Quebec, Canada), with the specific goal of supporting Quebec schools in the responsible integration of artificial intelligence in education.
9) Conclusion: Stable, Clear, and Defensible Grading
In summary, AI grading with Scolaro is more objective than human grading alone because:
- it relies on a clear rubric;
- it applies this rubric uniformly to all students;
- it provides a structured explanation for each criterion;
- it leaves the teacher in control of the final grade.
For a school in Montreal, Quebec, or the rest of Canada, this means fairer evaluation for students, more transparency for parents, and more sustainability for school teams.