@article{hallmen-etal-2026-annotating,
    title = "Annotating Conversational Phases and Communication Techniques: A Corpus of {G}erman Teacher-Parent Counseling Conversations",
    author = "Hallmen, Tobias  and
      Gietl, Kathrin  and
      Hillesheim, Karoline  and
      Friedrich, Annemarie  and
      Andr{\'e}, Elisabeth",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    journal = "International Conference on Language Resources and Evaluation",
    volume = "main",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://preview.aclanthology.org/ingest-lrec/2026.lrec-main.505/",
    pages = "6361--6372",
    abstract = "Teacher-parent conversations are critical for student success, yet teachers often lack structured training in counseling communication skills. We present the first annotated corpus of teacher-parent counseling conversations consisting of 59 German dialogues (approximately 6k sentences, 21k annotations) simulated by prospective elementary school teachers, peers, and professional actors. The corpus features theory-grounded annotations for conversational phases (Beginning, Informational, Argumentative, Decision-Making, Concluding) and communication techniques (Paraphrasing, Verbalizing, Structuring). We provide detailed annotation guidelines operationalizing established counseling pedagogy frameworks for computational analysis. Inter-annotator agreement analysis reveals substantial agreement (Fleiss' k = 0.669 to 0.724, Krippendorff{'}s a = 0.666 to 0.735). Our analysis reveals confusion patterns, providing insights into counseling discourse structure. Baseline experiments with BERT-based models and open-source LLMs achieve F1 scores of up to 71{\%} depending on task and model. The corpus, guidelines, and baseline code are publicly available under CC BY-NC-SA 4.0 license, enabling research on automated dialogue analysis and AI-based training tools for teacher education."
}