ArticleJournal of education and health promotion2026
A neuroeducational approach to STEM education: Integrating real-time cognitive analysis and cognitive load theory to optimize teaching and learning at universities.
Article in Journal of education and health promotion, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe relevance of science, technology, engineering, and mathematics (STEM) education to effectively meet challenging academic requirements has become imperative for university entrants. With emerging advancements within the domain of learning neuroscience and analytics, it has become possible to analyze and track the real-time mental states of learners. This has opened several avenues to apply the theoretical perspectives of Cognitive Load Theory (CLT). Though applications of neuro-technological interventions for learning have become widely sought, their effective implementation within STEM education has not been comprehensive at the university level. The innovations brought about within this study include its conceptual fusion for STEM education based upon real-time mental state analysis and CLT. The goal of this research is to integrate the current research findings on real-time cognitive analysis practices used in STEM education in universities and analyze how cognitive load can be monitored dynamically and discuss teaching practices according to principles of CLT to improve effectiveness and inclusiveness for better cognitive load management throughout learning. MATERIALS AND
methodsA systematic narrative review with cross-case synthesis was conducted using peer-reviewed empirical studies published between 2018 and 2025. The relevant articles were identified through the searching of databases such as Scopus, Web of Science, ERIC, and PsycINFO. Studies focusing on higher education STEM contexts were included if they employed neuroeducational tools (e.g., electroencephalography, functional near-infrared spectroscopy, eye tracking, or artificial intelligence-driven analytics) or incorporated instructional designs informed by Cognitive Load Theory (CLT). A standardized framework for extracting data was used, and data were thematically analyzed to identify patterns across the studies regarding cognitive load measurement, adaptive instructional strategies, learning outcomes, teacher experiences, and ethical considerations.
resultsFrom the synthesis, real-time cognitive feedback is perceived to have positively influenced teaching effectiveness by allowing the instructor to dynamically adjust pacing, scaffolding, and learning activities (
conclusionThe synergistic combination of real-time cognitive analysis and CLT has the potential for making progressive inroads for inclusive and adaptive STEM education in universities. This conceptual combination is in good harmony with the benchmarks for health and educational policy that regard evidence-based instruction, the welfare of the learner, and equity in higher educational settings as cornerstones. Longitudinal study, ethical regulation, and implementation strategies for neuroeducational data in universities need more emphasis in future studies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.