AI & ML
Neurophysiological Insights into Multimedia-based Education: A PRISMA-ScR Review of fNIRS in Game-Integrated Learning Systems
arXiv cs.HC0 views
arXiv:2411.02650v5 Announce Type: replace Abstract: Game-integrated learning systems (GILS) are a growing form of multimedia education. Neurophysiological evidence can complement behavioral and learning measures when examining how users interact with these environments. This scoping review follows PRISMA-ScR and synthesizes 20 empirical studies published between 2014 and 2025, identified through searches updated in April 2026, in which functional near-infrared spectroscopy (fNIRS) measured task-related cortical hemodynamic responses during GILS use. The review maps learning contexts, multimedia platforms, outcome measures, and methodological approaches across the included studies. Individual studies reported differences in cortical responses across interaction conditions and associations with behavioral or learning outcomes. However, only 10 of the 20 studies assessed learning outcomes, and methodological heterogeneity limits cross-study comparisons. These findings do not establish that specific multimedia platforms cause particular neural or learning outcomes. Future research should prioritize standardized methods, ecologically valid learning settings, and evaluation of the feasibility and educational value of real-time neural adaptation.
Source:https://arxiv.org/abs/2411.02650PreviousWho Is Sycophantic to Whom? Confident LLMs, Human Deference, and the Collapse of Trust CalibrationNextSocial Life Simulation for Non-Cognitive Skills Learning
Related posts
Cilium 1.20.0 Requires BTF Flag in Linux Kernel, Raspberry Pi OS Kernel Incompatible Without It
0dev.to
YC Labs and Olam Labs ran 50 AI agents in a Minecraft civilization experiment
0dev.to
Lavoro su piattaforma e algoritmi: cosa cambia con la direttiva europea per chi progetta il software
0dev.to
LifeVal Benchmark Targets Everyday Personal Assistant Tasks Shaped by ChatGPT User Feedback
0dev.to
Oracle files to sell $20B in new stock, bonds to finance AI buildout
0Hacker News
7.9% to 48.1%: LLM rewrote Qwen weights, no training
0dev.to