The paper describes the author’s personal phenomenological experience of interacting with a chat-based AI system to examine its ability to analyse online discussion and concludes that AI’s performance was high but depended on the quality of the author’s input.
Abstract
The paper describes the author’s personal phenomenological experience of interacting with a chat-based AI system to examine its ability to analyse online discussion. Jurgen Habermas’ validity claim concept was applied as the underlying theoretical framework to examine the text of posted messages by revealing the relationship between their language and semantic logic through AI lens. The key theoretical finding is that AI understood well the complex task of coding the messages’ intended meaning by discerning the link between validity claims and respective illocutionary speech acts. The key practical finding is two-fold: (a) AI worded correctly both the claims and speech acts in line with the guiding example presented by the author, and (b) AI significantly improved the accuracy of such wording following another round of specifying prompts. Overall, it can be concluded that AI’s performance in this experiment was high but depended on the quality of the author’s input.
Since the expansion of generative AI’s functions, chatbots such as Open AI’s Chat-GPT appear as more than tools. They can be perceived as communicative partners, shaping exchanges with high variability and linguistic competence. Current versions, such as Chat-GPT 5.5, even provide spoken language using different verbal...
Lea Marie Petrasch, Regina Jucks· Frontiers in Psychology· 0 citations
By positioning generative AI as a more-than-human conversational participant, the study invites qualitative researchers to think with non-human actors in the production of knowledge, extending post-qualitative approaches to digitally mediated research environments.
Wedsha Appadoo-Ramsamy· Qualitative Research Journal· 0 citations
The overall results suggest that these illustrative findings provide preliminary, context-specific support for the ACTS framework, which can be interpreted as a theoretically grounded response to the “Performance Paradox” in AI-mediated EFL academic writing.
Tuyet-Nhung Thi Nguyen, N. Huynh· Journal of Education and Tra...· 0 citations
Generative AI (GenAI) has transformed L2 writing, producing human-like prose but often impersonal feedback. This study explores the potential of GenAI–human collaborative feedback, focusing on the first author’s experience as a teaching assistant in a Hong Kong public university’s Bachelor of Education (English languag...
Lu Xi, Qinghua Chen, A. Lin· Education sciences· 0 citations
The paper examines whether AI-generated texts can serve as authentic input when engaged through three stages: interaction with text, decoding and interpretation of meaning, and contextually appropriate response production, and considers the dual role of AI as both a source of linguistic input and a mediation tool suppo...
Mehran Esfandiari, Mir Wais Gawhary· International Journal of Eng...· 0 citations
This article reconceptualizes feedback in second language (L2) writing for an era of digital and multimodal composing. It argues that feedback must extend beyond error correction to address communicative effectiveness, design, and intermodal coherence (e.g., image-text alignment). To situate our discussion within the e...
Ana Oskoz, Idoia Elola· Studies in Second Language L...· 0 citations
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