Between minds and machines: A neurocognitive comparison of human and chatbot interaction in language learning

Turun Ozel G., KAZAZOĞLU S., Yavuz B., Rusen E.

Computers in Biology and Medicine, vol.203, 2026 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 203
  • Publication Date: 2026
  • Doi Number: 10.1016/j.compbiomed.2026.111499
  • Journal Name: Computers in Biology and Medicine
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, CINAHL, Compendex, EMBASE, INSPEC
  • Keywords: Chatbot-mediated interaction, EEG, Human-computer interface, Human-human interaction, Real-time English language speaking
  • Yıldız Technical University Affiliated: Yes

Abstract

This study explores neurocognitive differences between human–human interaction (HHI) and human–chatbot interaction (HCI) during English-speaking tasks using EEG analysis. Results showed that HHI elicited significantly greater neural activation, particularly in the left frontal and temporal regions (F3, F7, T3), which are associated with language processing and social cognition. The F3 site exhibited the strongest difference (HHI: 27.09 vs. HCI: 15.5, p < .001, d = −4.02). EEG band analysis revealed higher delta activity during HCI, indicating lower cortical arousal and attentional engagement, while HHI showed greater alpha and beta power (alpha: 6.5 % vs. 2.1 %; beta: 12.1 % vs. 2.4 %), reflecting enhanced cognitive processing and emotional salience. These patterns extended to central, temporal, and parieto-occipital regions, with consistently stronger beta activity in HHI. Findings suggest that natural human interaction elicits deeper and more distributed neural engagement than chatbot communication, offering key insights into the cognitive and emotional dimensions of technology-mediated language use in educational and social contexts.