Teaching practices refer to strategies, methods, and interaction applied by a teacher to facilitate learning in the classroom. In discourse analysis, teaching practices aim at grasping how language can shape classroom dynamics, instructional techniques, and student engagement. Discourse analysis helps uncover underlying structures of communication between teachers and students, showing how, in this respect, language reflects power relations, pedagogical beliefs, and cultural norms in educational settings.

Discourse competence is a fundamental component of philological education, encompassing the ability to understand, produce, and interpret texts across various social, academic, and cultural contexts. Philology students must develop skills in academic writing, critical discourse analysis, professional communication, argumentative discourse, and conversational interaction.

Classroom discourse broadly refers to the various forms of language and interaction, as well as non-linguistic elements such as gestures and silence, that occur within the classroom setting. Other studies narrow it down to teacher-student and student-student interactions, which can be further conceptualized as the dialogue between individuals in the classroom in which one party addresses another and receives a reply. Due to its benefit in teaching and learning, such as enhancing students' thinking and academic achievement, classroom discourse has attracted researchers to conduct studies on it for decades, primarily since the 1970s. For instance, researchers have developed multiple pedagogical approaches, such as dialogic teaching (Alexander, 2008) and academically productive talk (Michaels et al., 2008), aiming to support teachers in using classroom discourse to enhance teaching and learning.

As technology advances, artificial intelligence (AI) has increasingly found applications in education, particularly in the area of classroom discourse. Recently, Chat GPT and GPT-4, the newest pre-trained large language models, have attracted unprecedented global attention owing to their exceptional capabilities in comprehending language, and several studies have begun to explore their application in education and the potential consequences of their use. Since classroom dialogue relies on language for teaching and learning, it is probable that these AI advancements will have an impact. Consequently, this paper examines the research on AI in classroom dialogue, aiming to offer valuable insights for future investigations into the integration of advanced AI technologies in teaching and learning environments. As far as we know, this paper is one of the initial attempts to comprehensively examine the application of AI in classroom discourse.

Traditional discourse instruction depends a great deal on printed texts, lectures, and teacher-centered activities. While effective in some respects, such pedagogies fall a long way short of taking account of the complexity of discourse as dynamic social practice. In today's digitally mediated world, learners must negotiate not only multimodal but also multilingual and interactive varieties of discourse. Artificial intelligence provides powerful tools for making discourse instruction more flexible, interactive, and realistic.

The paper discusses innovative AI-supported methods of teaching practical discourse to students of philology, focusing on how AI enhances interaction, improves feedback, and widens the scope of authentic communicative practice.

In philology, discourse is language use in context that is formed by social norms, communicative purposes, and cultural meanings. Practical discourse instruction should aim to develop:

Coherence and cohesion skills, pragmatic and sociolinguistic awareness, genre and register knowledge,  interactional competence, critical thinking in interpreting texts.

Instructing discourse necessitates engagement with real language usage, purposeful practice, and thoughtful examination – domains where AI can offer valuable assistance.

Technologies in AI pertinent to discourse instruction encompass: natural language processing (NLP), conversational AI and chatbots, automated tools for discourse analysis, speech recognition technologies, intelligent tutoring systems, and tools for generating content and scenarios.

These tools facilitate interactive learning settings that closely resemble actual communicative scenarios.

AI tools can replicate authentic conversation settings – scholarly discussions, job interviews, debates, customer engagements, or cross-cultural conversations.

Students engage in discourse techniques like turn-taking, topic preservation, politeness, and argumentation in realistic settings.

For example: The AI simulates a "conference panel discussion" where students answer appropriately as the speakers or moderators. AI can, for example, analyze students' discourse for coherence and cohesion markers, argumentation structure, discourse connectors, politeness strategies, speech acts, narrative structure. This gives immediate data-driven feedback useful for revising and improving.

Grammar correction using NLP systems, suggestions for pragmatic appropriateness, clarity, adjustments to register and tone, and discourse-level advice on organization. All of these types of individual feedback significantly speed up learning.

AI generates tasks based on: video-based discourse analysis, audio-text alignment activities, multimodal argument construction, visual storytelling exercises.

Students in philology learn to interpret and produce discourse in several modes: textual, visual, auditory, and digital.

Students investigate genuine conversations using AI-selected corpora. AI systems assist them in looking for: discourse markers, genre conventions, speech acts, stylistic patterns. This approach combines theoretical discourse analysis with practical application. AI tools enhance collaborative projects by: structuring tasks, overseeing teamwork, integrating ideas, assessing discussion quality. Students collaboratively generate arguments, analyses, or dialogues with AI acting as a virtual helper. AI identifies strengths and weaknesses in: fluency, pronunciation, pragmatic suitability, conversational tactics. This is especially beneficial for fostering spontaneous communication.

AI detects strengths and weaknesses in: fluency, pronunciation, pragmatic appropriateness, conversational strategies. This is particularly valuable for developing spontaneous communication.

AI can create custom communicative scenarios tailored to academic, cultural, or professional contexts relevant to philology students.

Examples include: analyzing political discourse, interpreting literary dialogues, discussing research findings, engaging in intercultural negotiations.

Students experience diverse discourse types that they will encounter in real philological work.

AI tools generate reflective prompts that help students analyze their discourse choices, identify patterns, and understand how discourse functions in context. This strengthens metacognitive awareness.

During class activities, AI can: suggest discourse markers, provide synonyms, generate context-appropriate expressions, support argumentation, help students maintain coherence.

This scaffolding encourages active participation and reduces communication anxiety.

AI tools can simulate realistic discourse contexts – academic discussions, professional interviews, debates, customer interactions, or intercultural dialogues.

Students practice discourse strategies such as turn-taking, topic maintenance, politeness, and argumentation in lifelike environments.

Example:

AI simulates a “conference panel discussion,” requiring students to respond appropriately as speakers or moderators.

AI can analyze student-produced discourse for: coherence and cohesion markers, argumentation structure, discourse connectors, politeness strategies, speech acts, narrative structure.

This provides immediate, data-driven feedback that helps students revise and improve.

During class activities, AI can suggest discourse markers, provide synonyms, generate context-appropriate expressions, support argumentation, help students maintain coherence.

This scaffolding encourages active participation and reduces communication anxiety.

AI revolutionizes practical discourse instruction by making it:

1. Highly interactive – through conversational simulations and intelligent dialogue systems.
2. Personalized – with feedback tailored to each student’s discourse patterns.
3. Multimodal – integrating visual, audio, textual, and digital formats.
4. Authentic – using real-world scenarios and corpora.
5. Analytical – through automated discourse analysis and argument structure evaluation.

For philology students, these innovations align directly with their academic needs: developing strong communication skills, mastering genre conventions, and conducting critical discourse analysis. AI also fosters autonomy, creativity, and confidence, turning students into active participants rather than passive recipients of discourse knowledge.

Artificial intelligence offers transformative opportunities for teaching practical discourse in philology programs. By incorporating AI-based simulations, automated discourse analysis, personalized feedback, multimodal tasks, and corpus-driven learning, educators can significantly enhance discourse competence. These methods make discourse instruction more dynamic, accessible, and relevant to the communicative demands of the modern world. As philology students prepare for careers in education, translation, linguistics, and intercultural communication, AI-supported discourse training equips them with essential skills for academic, professional, and digital environments.