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-2026-2838
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:33:13.209014Z
status: published
lens: g_space
sector: education
headline: Meta-Analysis of Artificial Intelligence in Education
dek: This meta-analysis examined the effectiveness of artificial intelligence (AI) technologies in educational settings through a systematic review of 13 empirical studies conducted across eight countries. We analysed the impact of various AI technologies on educational outcomes using PRISMA guidelines and multiple analytical approaches, including novel applications of Naive Bayes, TF-IDF, and BERT-based algorithms. The overall analysis revealed a significant positive effect size (Hedges' g = 0.86, 95% CI [0.45, 1.27…
gain_title: A meta-analysis of 13 studies across eight countries found AI technologies in education were linked to better student learning outcomes (Hedges' g = 0.86), with chatbots and generative AI strongest at 1.02.
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of 13 studies across eight countries found AI technologies in education were linked to better student learning outcomes (Hedges' g = 0.86), with chatbots and generative AI strongest at 1.02.
gain_evidence: chatbots and generative AI (effect size = 1.02, 95% CI [0.45, 1.59], p < 0.0001), which demonstrated the most substantial positive impact on student learning outcomes
problem_reading: (none)
problem_evidence: (none)
quick_read: A meta-analysis of 13 empirical studies conducted in eight countries found that AI technologies were associated with better educational outcomes. The pooled effect size was Hedges' g = 0.86 (95% CI 0.45 to 1.27).

Chatbots and generative AI showed the largest effect, at 1.02 (95% CI 0.45 to 1.59). Learning management systems and AI platforms showed a smaller effect of 0.62, and online learning and virtual reality applications 0.79, with a confidence interval that crossed zero.

Results varied widely between the included studies, with heterogeneity (I²) ranging from 54.03% to 93.23%. The authors say implementation strategies and context matter for outcomes.
limitation: Heterogeneity across the 13 studies was high (I² from 54.03% to 93.23%), and the online learning and virtual reality estimate had a confidence interval that crossed zero.
tag: Evidence-backed gain
key_points: The review covered 13 empirical studies from eight countries and followed PRISMA guidelines. | The pooled effect of AI on educational outcomes was Hedges' g = 0.86 (95% CI 0.45 to 1.27, p < 0.0001). | Chatbots and generative AI had the largest effect on student learning, at 1.02 (95% CI 0.45 to 1.59). | Online learning and virtual reality applications had an effect of 0.79, but the interval (-0.04 to 1.62) included zero and p was below 0.07. | Learning management systems and AI platforms showed a more modest effect of 0.62 (95% CI 0.03 to 1.21, p < 0.05). | Heterogeneity across studies was high, with I² between 54.03% and 93.23%.
rundown: The authors pooled results from 13 empirical studies across eight countries, following PRISMA guidelines. They used Naive Bayes, TF-IDF and BERT-based algorithms alongside conventional analysis, and a weighted hybrid model that combines random and fixed effects approaches.

The overall effect was large and statistically significant (Hedges' g = 0.86, 95% CI 0.45 to 1.27). By technology type, chatbots and generative AI scored highest at 1.02, followed by online learning and virtual reality at 0.79 and learning management systems and AI platforms at 0.62.

The online learning and virtual reality estimate was not statistically significant at the conventional level (95% CI -0.04 to 1.62). The authors report significant heterogeneity across studies and say contextual factors and implementation strategies should be considered.
sources:
- peer_reviewed | Higher Education Studies | https://doi.org/10.5539/hes.v15n2p189 | 2025-03-21
prev: 0000000000000000000000000000000000000000000000000000000000000000

SHA-256 hash

ae8fd3938e50f78ecd02277904a7078d8d844798bacf1f0d7794fa418ddc2eb1

Previous version’s hash

0000000000000000000000000000000000000000000000000000000000000000