The exact text we saved

This is the version exactly as it was saved, character for character. The SHA-256 hash below is a 64-character code worked out from that text. Run the same text through SHA-256 and you get the same code; change a single letter and the code comes out completely different. Each version also stores the previous version’s hash, which chains them together so no version can be swapped out quietly.

TRUVACE RECORD VERSION
record: TRV-2026-2847
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:34:18.104556Z
status: published
lens: trace
sector: education
headline: AI in informal digital English learning: A meta-analysis of its effectiveness on proficiency, motivation, and self-regulation
dek: This meta-analysis examines the efficacy of generative artificial intelligence (GenAI) in second language acquisition within self-directed, out-of-classroom informal contexts. A total of 15 studies meeting the inclusion criteria were identified that examined the impact of GenAI on second-language proficiency, motivation, and self-regulation. GenAI was shown to have significant effects on English proficiency and self-regulation, demonstrating its versatility in enhancing language learning outcomes. However, GenAI…
gain_title: A meta-analysis of 15 studies found generative AI had significant effects on English proficiency and self-regulation among learners studying outside the classroom.
problem_title: A meta-analysis of 15 studies found generative AI showed no significant effect on motivation among learners of English as a second language studying outside the classroom.
trace_subject: Generative AI in informal, self-directed English language learning
gain_reading: A meta-analysis of 15 studies found generative AI had significant effects on English proficiency and self-regulation among learners studying outside the classroom.
gain_evidence: GenAI was shown to have significant effects on English proficiency and self-regulation
problem_reading: A meta-analysis of 15 studies found generative AI showed no significant effect on motivation among learners of English as a second language studying outside the classroom.
problem_evidence: GenAI failed to show significant effects on learning motivation
quick_read: A meta-analysis pooled 15 studies on generative AI in self-directed, out-of-classroom second-language learning. It found significant effects on English proficiency and on self-regulation, the ability to manage one's own learning.

The same analysis found no significant effect on learning motivation. The authors conclude that motivation measures suited to generative AI in education need to be developed, which suggests existing instruments may not capture what these tools change.

The findings cover informal learning outside classrooms, where people study without a teacher. The authors also discuss possible ways to apply generative AI in such settings, drawing on the included literature.
limitation: The authors say the null motivation result points to a need for motivation measures suited to generative AI, which suggests current instruments may not capture its effects.
tag: Dual reading
key_points: The meta-analysis included 15 studies that met its inclusion criteria. | It focused on self-directed, out-of-classroom informal English learning with generative AI. | Generative AI had significant effects on English proficiency. | Generative AI had significant effects on self-regulation. | Generative AI showed no significant effect on learning motivation. | The authors call for motivation measures suited to generative AI in education.
rundown: The study pooled research on generative AI used for second-language acquisition outside formal classes. It examined three outcomes: proficiency, motivation and self-regulation.

Two of the three outcomes improved significantly. The authors describe this as showing the versatility of generative AI in enhancing language learning outcomes.

Motivation did not show a significant effect. Based on that result, the authors argue that new motivation measures designed for generative AI in education are needed, and they discuss practical ways to apply the tools in informal learning.
sources:
- peer_reviewed | Computers and Education: Artificial Intelligence | https://doi.org/10.1016/j.caeai.2024.100323 | 2024-10-30
prev: 0000000000000000000000000000000000000000000000000000000000000000

SHA-256 hash

a632d9708c96cc756995b584d7ac8dc1c5ea08b46b8e4354050bcde28f6d4138

Previous version’s hash

0000000000000000000000000000000000000000000000000000000000000000