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TRUVACE RECORD VERSION
record: TRV-2026-0180
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-07-13T09:14:18.168101Z
status: published
lens: g_space
sector: education
headline: AI-enhanced pedagogical practices and mathematical language proficiency in STEM education
dek: This study investigates the effectiveness of AI-enhanced pedagogical practices on improving the mathematical language proficiency of senior high school students in Ghana. The current research adopted a quantitative cross-sectional design, where the structural equation modeling approach was used on a sample size of 360 participants, to investigate digital literacy and learning engagement as partial mediators. As expected, results from this study show that AEPP, DL, and LE are statistically significant positive pr…
gain_title: AI-enhanced pedagogical practices were associated with higher mathematical language proficiency, communication and reasoning among senior high school students in Ghana, with digital literacy and learning engagement acting as mediators.
problem_title: (none)
trace_subject: (none)
gain_reading: AI-enhanced pedagogical practices were associated with higher mathematical language proficiency, communication and reasoning among senior high school students in Ghana, with digital literacy and learning engagement acting as mediators.
gain_evidence: AI-enhanced pedagogical practices on improving the mathematical language proficiency of senior high school students in Ghana
problem_reading: (none)
problem_evidence: (none)
quick_read: Published May 26, 2026, this peer-reviewed study investigated AI-enhanced pedagogical practices and mathematical language proficiency among 360 senior high school students in Ghana. Using structural equation modeling, it found AEPP, digital literacy, and learning engagement were significant positive predictors of proficiency, with the latter two mediating the relationship.

The result suggests adaptive AI tools may support math communication and reasoning by boosting digital literacy and engagement in this context. Because the design was cross-sectional and limited to one country and age group, the findings describe an observed association by that date rather than a proven long-term or broadly generalizable causal effect.
limitation: Findings are bounded by a cross-sectional design and a sample of 360 senior high school students in Ghana, limiting causal inference and generalizability beyond that population.
tag: Evidence-backed gain
key_points: Study used quantitative cross-sectional design with structural equation modeling on 360 participants. | Digital literacy and learning engagement were tested as partial mediators between AI-supported instruction and proficiency outcomes. | Authors point to integrating adaptive AI tools to enhance digital literacy and engagement to improve mathematical communication and reasoning.
rundown: The study examined senior high school students in Ghana using a quantitative cross-sectional design and structural equation modeling with 360 participants.

It tested whether digital literacy and learning engagement partially mediate the link between AI-supported instruction and mathematical language proficiency, finding all three predictors statistically significant and positive.
sources:
- peer_reviewed | American Journal of STEM Education | https://doi.org/10.32674/6h0e3376 | 2026-05-26
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