Turn-taking in Cooperative Board Games: A Study of Speech Act Clusters

Effective speaking in group interactions is crucial for foreign language learners, yet many Japanese EFL students struggle with self-selection (i.e., speaking without direct invitation). This study adopts a corpus pragmatics approach to analyze speech act clusters used among L1 English speakers during cooperative board game play, which involves convergent decision-making. By identifying common speech act patterns, the study aims to establish language targets that promote interactive utterances, to help learners self-select more effectively in group discussions. Transcriptions from YouTube of board game play were annotated for speech acts using DART v.3 (Weisser, 2019a, 2019b) and analyzed with AntConc (Anthony, 2020) to identify clusters. Results indicate that acknowledging others’ utterances is common when interlocutors self-select, while explicit opinion elicitation is rare. These insights can guide the development of materials that support group decision-making, such as consciousness-raising frameworks or guided practice, and offer a method for creating materials for other communicative contexts. 外国語学習者にとってグループ交流での効果的な発話は重要だが、日本人EFL学習者の多くは自己選択（直接誘われずに発話すること）に苦戦する。本研究は、コーパス語用論的アプローチで、収束的意思決定を伴うボードゲーム協力プレイ中の英語母語話者の発話行為クラスターを分析する。YouTubeからのトランスクリプトをDART v.3 (Weisser, 2019a, 2019b)でアノテーションし、AntConc (Anthony, 2020)で分析した結果、自己選択時には他者の発話を認める行為が多く、意見の引き出しは稀であることが示された。これらの知見は、意識喚起フレームワークやガイド付き練習など、集団意思決定を支援する教材の開発に役立ち、他の文脈の教材作成にも応用できる。