Transition network analysis shows the chatbot's prompts and explanations structured the interaction while participants generated their own interpretations¶

Claim · All claims
Evidence · 1 study · qualitative r3 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? The most prominent chatbot-coded nodes were RI.Reflection (46 times), RI.Interpretation (20), PI.Explanation (26), and A.Validation (40), while the most prominent user-coded node was PI.SharingInsight (84), including a self-loop showing users remained in an interpretive mode. → Marques 2026

Evidence¶

Marques 2026¶

Marques, F., Ortiz-Beltrán, A., Amarasinghe, I., & Hernández-Leo, D. (2026). Responsible Institutional Analytics: Interpreting Bias with AI Support. Journal of Universal Computer Science, 33(6). https://arxiv.org/abs/2610.07205 doi:10.48550/arxiv.2610.07205

q2 · i? · qualitative · r3

Transition network analysis (TNA) across all four IA cases, visualizing transitions with relative probability above 0.25. The distribution shows "assistant prompts and explanatory moves structured the interaction, while participants subsequently generated interpretations."

"The most prominent chatbot-coded nodes were RI.Reflection (appeared 46 times), RI.Interpretation (20), PI.Explanation (26), and A.Validation (40), while the most prominent user-coded node was PI.SharingInsight (84) (see appendix VI for further information about the coding scheme)."

Discussion¶

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