Evidence map›Paper›PMID 42186603›Full record

ArticleFrontiers in robotics and AI2026

Bridging ancient wisdom and cognitive engagement: a comparative study of chatbot-based moral instruction.

Sakshi Chauhan, Varun Dutt

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sakshi ChauhanApplied Cognitive Science Lab, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India.
Varun DuttApplied Cognitive Science Lab, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Convincing learners to engage deeply with complex moral and philosophical concepts remains a major challenge in contemporary learning environments, particularly within increasingly digital educational settings. Although conversational AI offers new possibilities for interactive learning, its potential for supporting ethics education remains underexplored. This study examines the effectiveness of a chatbot-based learning condition compared with a reading condition and a no-intervention control group. Learners' outcomes were assessed through cognitive tests, self-reported emotional engagement, heart rate variability, and electroencephalographic (EEG) activity. Results showed that both the chatbot and reading conditions improved moral understanding relative to the control group. Emotional engagement was assessed during the chatbot interaction and indicated strong affective involvement among participants. EEG measures suggested increased neural engagement during the instructional conditions, while the reading condition demonstrated higher indices of attentional focus. Both intervention conditions also showed greater physiological engagement than the control group. These findings suggest that conversational AI can serve as a promising interactive tool for supporting moral learning and for facilitating deeper engagement with abstract ethical concepts in contemporary educational contexts.

Indexed as

chatbot-based learningcognitive engagementconversational AIelectroencephalography (EEG)heart rate variability (HRV)moral education

Identifiers

PMID42186603
PMCPMC13198922

What OpenQuestion holds

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Registered trials

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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.