The Impact of Andrusenko Neuro-Linguistic Method on Online Language Learning: A Case Study of Swiss NeuroLanguage Academy (Andrusenko.pro)

Abstract

This dissertation examines the pedagogical effectiveness of the Andrusenko Neuro-Linguistic Method (ANM™) as implemented within Swiss NeuroLanguage Academy (Andrusenko.pro) (hereafter, the Academy) and its integration with AI-supported educational tools in online language instruction. The study is positioned at the intersection of neuroeducation, cognitive psychology, applied linguistics, and technology-enhanced learning, and explores how ANM™ routines, including internal associative visualisation, anchoring, reframing, internal scripting, and audio-visual integration, relate to learner motivation, engagement, and perceived communicative development.
The research follows an explanatory sequential mixed-methods design. Quantitative data were collected through a structured survey (n = 34) capturing 21 operational variables related to learning behaviours, perceptions, and AI interaction. Associations among variables were analysed using Spearman’s rank-order correlation (rho) and exploratory regression modelling to identify predictors of perceived progress and satisfaction Qualitative insights were derived from ten semi-structured interviews and open-ended responses, providing depth on learners’ metacognitive shifts, affective changes, and evolving self-perceptions.
Findings indicate strong associations among motivational orientation, the perceived value of internal visualisation routines, and AI-supported continuity between lessons. Exploratory regression results suggest that motivation, speaking confidence, perceived usefulness of AI support, and structured rehearsal routines are associated with higher learner-reported progress. Qualitative themes further highlight shifts in learner agency, reduced anxiety around error, and the emergence of stable learning habits oriented toward speaking readiness and confidence.
This dissertation contributes to the discourse on psychologically informed digital education by presenting a case-based, evidence-oriented account of how structured affective-cognitive routines can be integrated with AI-supported continuity. It offers implications for hybrid learning environments that balance human-led instruction with technological augmentation and provides practical recommendations for educators and institutions seeking scalable online language instruction while preserving psychological safety and depth of learning. Findings are based on self-reported data within a single-case design and should be interpreted as indicative rather than causal or generalisable.
Keywords: Neuro-linguistic language learning; adult language education; speaking confidence; psychological engagement in learning; online language learning; artificial intelligence in language education; AI-mediated learning; case study research; mixed-methods research; language learning motivation; communicative competence development; Swiss NeuroLanguage Academy; self-regulated learning; speech production in L2 learning; technology-mediated language learning.