The open notebookEDITION MMXXVI
Research & engineering
for Europe’s exams.
The Lab is where EuraStudy is worked out in the open — the learning science we build on, the questions we have not settled, and the craft behind every surface. 6 entries across two tracks and four areas, plus a standing reading of the wider field.
Four areas
of work.
Every dispatch is filed under one area. Pick one to read only that strand — tap it again to clear.
The work.
Reading the fieldBEYOND EURASTUDY
From the field.
A standing reading of the research on artificial intelligence and learning — the work of others, across decades, that the rest of this notebook is built on. These are published findings by researchers across the field, not EuraStudy’s own results; we summarise them and point to the original work.
- 01Tutoring efficacy
One-to-one tutoring moved the average student to the 98th percentile.
Students who worked with a personal tutor outperformed conventionally taught peers by about two standard deviations — Bloom’s “two sigma” result. It set the central ambition that has driven educational technology ever since: to reproduce, at scale, what a good tutor does for one learner.
Benjamin S. Bloom1984The 2 Sigma ProblemEducational Researcher
- 02Tutoring efficacy
Intelligent tutoring systems came within a whisker of human tutors.
Reviewing decades of controlled studies, VanLehn measured human tutoring at roughly 0.79 standard deviations over no tutoring and step-based intelligent tutors at about 0.76 — far below Bloom’s famous 2.0, and close enough to each other to reframe the question from “can a machine tutor?” to “what does effective tutoring actually consist of?”
Kurt VanLehn2011The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring SystemsEducational Psychologist
- 03Evidence & meta-analysis
Across fifty controlled evaluations, intelligent tutors raised scores by about two-thirds of a standard deviation.
The median system raised scores by about two-thirds of a standard deviation — but far more on the locally designed tests that match what a system actually taught (around 0.73) than on standardised exams (around 0.13). Real, and a reminder that the size of an effect depends heavily on what you choose to measure.
James A. Kulik & J. D. Fletcher2016Effectiveness of Intelligent Tutoring Systems: A Meta-Analytic ReviewReview of Educational Research
- 04Memory & practice
Being tested on material beats re-reading it — and the gap widens with time.
Learners who practised retrieving what they had studied remembered substantially more a week later than those who simply restudied — even though the restudiers felt more confident at the time. The “testing effect” is among the most robust results in the science of learning, and the reason deliberate practice, not mere exposure, sits at the centre of exam preparation.
Henry L. Roediger III & Jeffrey D. Karpicke2006Test-Enhanced LearningPsychological Science
- 05Cognitive load
Working memory is the bottleneck — and the help a novice needs becomes noise for an expert.
Cognitive load theory holds that instruction fails when it overwhelms a narrow working memory. Later work on the “expertise-reversal effect” sharpened the point: scaffolding that helps a beginner actively hinders a more advanced learner. Together they argue that good tutoring must adapt its support to the individual, not just to the topic.
John Sweller1988Cognitive Load During Problem Solving: Effects on LearningCognitive Science
- 06Learning theory
Good help is temporary: a scaffold exists in order to be removed.
Wood, Bruner and Ross named “scaffolding” — the support an expert lends so a learner can do what they cannot yet do alone, an idea since drawn together with Vygotsky’s zone of proximal development. Its defining feature is that it fades: support that never withdraws breeds dependence, not competence. It is the principle behind any tutor that deliberately holds back the answer.
David Wood, Jerome S. Bruner & Gail Ross1976The Role of Tutoring in Problem SolvingJournal of Child Psychology and Psychiatry
- 07Feedback
Feedback is one of the most powerful influences on learning — and one of the most variable.
Synthesising hundreds of studies, Hattie and Timperley placed feedback among the strongest levers on achievement, with effects ranging from large to outright negative. What separated them was whether the feedback told a learner where they were going, how they were doing, and what to do next. Feedback that grades without directing can achieve nothing at all.
John Hattie & Helen Timperley2007The Power of FeedbackReview of Educational Research
- 08Critical perspectives
Perhaps the machine should stay simple, and the intelligence should stay human.
Baker argues the field over-invested in modelling the learner’s mind and under-invested in the simpler, robust systems that actually help — and in keeping teachers in the loop. A standing corrective for anyone building an AI tutor: sophistication is not the goal; better learning is.
Ryan S. Baker2016Stupid Tutoring Systems, Intelligent HumansInternational Journal of Artificial Intelligence in Education
Selected reading · 8 works · a starting point, not a survey