Refinement of Utterance Fluency Feature Extraction and Automated Scoring of L2 Oral Fluency with Dialogic Features

It is a common feature of the 21st century workplace to be multicultural. Working professionals need to possess strong Interactional Competence to handle professional communication in various intercultural encounters in their workplace. This has however posed challenges to professional communication education since educators need to incorporate different cultural practices and interlocutor profiles in their teaching and assessment materials. In this paper we reflect on the practical challenges of professional communication education in intercultural contexts and envisage what AI can offer in this place. We start with some practical, on-the-ground dilemmas in integrating diverse cultural representation in professional communication education. We then use an operational AI-mediated assessment tool to elaborate the possibilities, affordances and caveats in using AI to develop teaching and assessment materials for professional communication education. We conclude with directions for future research and practice in the emerging space of AI for professional communication in intercultural contexts (AI-for-PCIC).

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Refinement of Utterance Fluency Feature Extraction and Automated Scoring of L2 Oral Fluency with Dialogic Features

Cited by 2 publications

References 28 publications

Prompt-Independent Automated Scoring of L2 Oral Fluency by Capturing Prompt Effects

Prompt-Independent Automated Scoring of L2 Oral Fluency by Capturing Prompt Effects

Generative AI for professional communication training in intercultural contexts: where are we now and where are we heading?

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