Abstract
In the era of rapidly emerging AI tools, educators and language learners must explore how these technologies can enhance learning. This study investigates the effectiveness of Google NotebookLM’s conversational audio compared to traditional monologue in improving listening comprehension. Google NotebookLM can transform written articles into two-way conversations, similar to podcasts, offering a more engaging method for listening practice. In this experiment, participants are divided into two groups: one listens to a monologue, where a single speaker explains a phenomenon, while the other listens to a conversational dialogue generated by Google NotebookLM from the same article. The research employs a mixed-method approach, incorporating both quantitative post-listening comprehension tests and qualitative semi-structured interviews to gather deeper insights into participants’ experiences. The results indicate that participants exposed to conversational audio scored 64% higher on post-listening comprehension tests compared to the monologue group. Additionally, qualitative feedback from the interviews suggests that students find the conversational format more engaging and believe it helps them retain key points more effectively. This research underscores the potential of AI-generated conversational audio to improve language learning by providing an innovative and engaging way to train listening skills.
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KEYWORDS
LISTENING COMPREHENSION, CONVERSATIONAL AUDIO, MONOLOGUE, AI-GENERATED
