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Tutoring & Learning
24 gains4 Traces1 problem
Every measured gain and problem on the record for this topic, newest first. Updated .
One square per record, darker for stronger evidence:Evidence: 2 high24 moderate3 emerging
AI in tutoring and learning
A Trace is one record with both a gain and a problem, so it counts on both sides: 28 records show a gain and 5 show a problem. 15 context records are in the record list but not counted, because they report no measured gain or problem.
| Evidence | Gain side | Problem side |
|---|---|---|
| HighStrong study design, backed by at least two independent sources | 2 | 0 |
| ModerateA measured study or an official source | 23 | 4 |
| EmergingEarly, small, unreviewed or reported second-hand | 3 | 1 |
By type of evidence: 6 observational studies; 6 randomized trials; 5 surveys; 5 controlled comparisons; 4 systematic reviews or meta-analyses; 1 interview study; 1 case report; 1 commentary or narrative review. How evidence is scored
In a four-month randomized trial, 75 Chinese English learners taught with robots scored significantly higher on questionnaires of classroom engagement and willingness to attend classes than 80 controls.
Among 360 senior high school students in Ghana, AI-enhanced teaching was linked to higher mathematical language proficiency, partly through better digital literacy and learning engagement.
Among 853 university students in Melilla, Ceuta and Granada, students said AI is a valuable tool for learning mathematics when they know how to use it.
A review of 103 papers found brain-signal adaptive learning systems are not yet deployable at scale, with unresolved data privacy and security risks, algorithmic bias, and unequal access.
The AI-assisted videos still needed expert oversight and saved no production time, and the AI-assisted group's score gain was not significant at one week (p = 0.16).
A review of 40 articles flags unresolved risks in multilingual education: data privacy, algorithmic bias, unequal access, and a loss of relational and cultural aspects of teaching, which it calls an empathy gap.
1 record
This February 2025 systematic review of 103 papers examined how Cognitive Load Theory, Educational Neuroscience, and AI/ML combine in adaptive learning. It found that systems using EEG, fNIRS and other physiological signals to feed CNN, RNN and SVM models can automatically manage cognitive load and dynamically adapt…
Brain Sciences