🏷️ rct

> **Research methods in AIED** — the set of empirical designs, data-collection strategies, and analytic techniques researchers use to study AI in education: whether and how AI tools support (or harm) …

2026-08-13 · ai-education, educational-measurement, efficacy-study, benchmark, methodology

> **Synthesis:** In a [[rct|randomized controlled trial]] with 1,174 participants, Cruces et al. find that [[generative-ai|generative AI]] substantially narrows education-based productivity gaps, clos…

2026-08-09 · productivity, equity, generative-ai, ai-education, higher-ed

> **Assessment validity** — whether assessments measure what they claim to measure. AI in education raises fundamental validity questions: do AI-graded assessments assess student learning or AI prompt…

2026-08-09 · authentic-assessment, automated-grading, confidence-aware-ai-assessment, formative-assessment, academic-integrity

> Robinson, Gormley, Ribeiro & Loeb (2026) ran two RCTs showing that AI tutoring's binding constraint is **take-up, not capability**: despite dedicated session time, nearly half of students never used…

2026-08-03 · intelligent-tutoring, equity, engagement-metrics, k-12, ai-literacy

> The null average performance effect masks strong offsetting heterogeneity — and the exam had severe ceiling compression (control mean 89.2/100, 47% ≥ 95), which also limits power. The belief reversa…

2026-08-03 · faculty-development, teacher-role, generative-ai, k-12, student-experience

> Meyer, Page, Mata et al. (2026) ran two pre-registered RCTs at Georgia State University testing a **non-generative** academic chatbot that texted students 2–3 customized nudges per week in large-enr…

2026-08-03 · higher-ed, student-experience, generative-ai, engagement-metrics, rag

This landmark field experiment is among the first randomized controlled trials to causally demonstrate that **unguarded generative-AI tutoring can harm skill acquisition**, not merely fail to help. Co…

2026-07-19 · generative-ai, over-reliance, stem-education, k-12, learning-gains

Akgun and Toker (2026) examine whether learning gains from GenAI-enabled adaptive pretesting persist over a seven-week retention period. Undergraduate participants completed adaptive AI-assisted prete…

2026-06-23 · adaptive-learning, formative-assessment, learning-gains, higher-ed, personalized-learning

Gheisari and Salarian (2026) apply supervised machine learning classification to identify at-risk students before they withdraw from higher education programs. The study evaluates Logistic Regression,…

2026-06-23 · learning-analytics, higher-ed, dropout-reduction, student-modeling, llm

This field experiment shows that AI-generated feedback drafts can measurably increase the rate and length of feedback that teaching assistants actually deliver to students, without sacrificing perceiv…

2026-06-04 · automated-grading, feedback-loop, higher-ed, llm, teacher-role

📄 [Full article](https://edtechinsiders.substack.com/p/how-ai-is-changing-teaching-workflows) AI saves teachers roughly 30% of lesson preparation time with no measurable quality loss — but whether th…

2026-05-21 · generative-ai, teacher-role, faculty-development, efficacy-study, k-12

> Maier, Gunzenhäuser & Schweisthal (2026) conduct a **meta-analysis synthesizing evidence** on how generative AI tools affect both programming productivity and learning outcomes. This is a **confiden…

2026-05-06 · efficacy-study, generative-ai, higher-ed, learning-gains, meta-analysis