Indonesian presidential speeches shape public expectations about teacher welfare, yet few studies examine how specific speech acts (promises, praise, apologies) rhetorically sustain or obscure policy shortfalls. This study compares speech‑act strategies across three administrations to reveal how presidential rhetoric reproduces or challenges welfare inequalities. Combining speech‑act theory with discourse analysis, the current study conducts a thematic qualitative analysis of presidential speech transcripts from Susilo Bambang Yudhoyono (SBY), Joko Widodo (JW), and Prabowo Subianto (PS), coding for speech‑act types (assertives, directives, commissives, expressives, declaratives) and discursive strategies (modalization, repetition, applause markers). Cross‑case comparison identifies recurring patterns and their political‑functional effects. Findings show SBY foregrounded commissives about certification and skills, JW emphasized emergency measures such as contract‑status conversions and school operational assistance, and PS paired anti‑corruption framing with pay‑increase rhetoric; only two presidents (SBY & JW) relied heavily on expressives (praise, gratitude, national‑hero labels) to raise morale amid stalled promotions and workload–pay imbalances. These speech acts shape public perceptions of government responsiveness, reduce immediate dissent, and reshape accountability expectations while obscuring gaps between rhetorical commitments and policy implementation. The present study recommends mixed-method follow-ups (interviews, policy audits) to assess the effects of speech on material welfare and to inform more equitable teacher‑welfare policy in Indonesia.
The increasing use of conversational artificial intelligence in casual and academic communication raises significant questions about how such systems create interpersonal meaning through language. Limited research has been conducted in terms of linguistic mechanisms through which interpersonal relationships are established across different registers. Addressing this gap, the current study explores how ChatGPT creates interpersonal meaning in informal and formal academic interactions through the lens of the systemic functional linguistics (SFL) framework. This qualitative SFL-based analysis research examines 10 ChatGPT-generated responses to prompts that were purposely designed, comprising five casual and five academic interactions that were broken down into 86 clauses and analyzed through the lens of the interpersonal metafunction, focusing on mood, modality, and appraisal, facilitated by register theory and the three dimensions of human-machine communication (HMC). The findings reveal a clear variation in the use of ChatGPT's interpersonal strategies depending on the register. Casual interactions exhibit a higher number of appraisal resources, especially affect and engagement, which reflect a relational and user-oriented stance. In contrast, academic interactions are described by the predominance of declarative mood and medium to high. This study provides insight into how AI imitates human behavior, such as interactional roles through language selection. The findings highlight the importance of register sensitivity in AI-human communication and have implications for linguistics, language education, and chatbot design. It is suggested that further studies should consider investigating larger datasets, more registers, and comparative analyses of different AI models.
This study addresses the limited understanding of how social media and peer environments simultaneously shape English language learning, particularly in terms of their dual impact on learners’ motivation, self-regulation, and learning experiences. While previous research has often emphasized the benefits of digital tools or peer interaction, it has paid less attention to their contradictory effects and the challenges they pose for learners’ emotional well-being and self-regulation. Using a mixed-methods design, this study collected survey data from 51 English language learners (ELLs) across five major cities in Indonesia, followed by in-depth interviews with five participants. Data were analyzed through descriptive statistics and thematic analysis to enable triangulation. The findings reveal that social media enhances motivation, engagement, and language exposure, but also contributes to distraction and emotional strain. Similarly, peer environments promote collaboration and confidence while simultaneously generating anxiety and social pressure. These findings highlight the complex and often contradictory roles of digital and peer-mediated learning environments. This study contributes to the literature by foregrounding the dual impact of these environments and emphasizing the importance of fostering learner self-regulation and emotional well-being. It offers pedagogical implications for the strategic integration of social media and the development of supportive peer networks in English language learning contexts.
The rapid expansion of social media transformed communication, encouraging the emergence of slang as a creative, identity-driven linguistic practice among Generation Z (Gen Z). Previous studies extensively examined types, functions, and general impacts of slang, presenting contradictory conclusions, either its positive role or negative implications. These inconsistent findings make it difficult to understand the actual role of English slang in communication effectiveness. However, limited research examined how Indonesian Gen Z use English slang and how it affects communication effectiveness among Gen Z users with similar linguistic backgrounds and comparable English proficiency. Addressing this gap, the present study investigates the types of English slang used by Indonesian Gen Z majoring in English studies in communication and analyzes its effects on clarity and effectiveness. With a qualitative-descriptive approach, data were collected through questionnaires (N=65) and semi-structured interviews with selected participants (n=6). The collected slang was categorized using a slang taxonomy and analyzed in relation to perceived message clarity and effectiveness. The findings reveal four types of slang: fresh and creative, flippant, acronym, and clipping. Acronyms were reported as the most frequently used slang in communication. The interviews indicate participants perceive slang as having positive impacts on communication effectiveness, self-expression, vocabulary development, and strengthening solidarity. However, the use of slang causes misunderstandings for those unfamiliar with slang and may encourage its inappropriate use in formal contexts. Future research should involve more diverse participant groups and examine the long-term effects of English slang on language use and communication.
Although artificial intelligence has gained growing attention in language education, previous research has largely emphasized technical effectiveness and student outcomes, while teachers’ professional experiences remain insufficiently examined. This study explores how Indonesian EFL lecturers perceive the use of artificial intelligence in academic writing instruction, how they adjust their pedagogical practices, and how these experiences shape their professional development and professional identity, particularly in writing assessment. Employing a phenomenological approach, data were collected through semi-structured interviews, classroom observations, and teaching documents involving twelve lecturers from East Java and Central Indonesian regions. The findings reveal interconnected experiences influenced by institutional readiness, access to digital infrastructure, and lecturers’ pedagogical beliefs. Participants reported a shift in professional identity from primary evaluators of student writing toward facilitators who guide learners in critically engaging with artificial intelligence-generated feedback. In the absence of systematic institutional training, lecturers relied heavily on informal peer communities as spaces for learning, reflection, and sharing instructional strategies. The study suggests that professional development for artificial intelligence-supported writing instruction should move beyond technical orientation and provide sustained, context-sensitive support that integrates ethical awareness, reflective practice, and collaborative learning. While the qualitative design and limited number of participants require cautious interpretation, the findings contribute to broader discussions on teacher professional development in technologically evolving educational contexts.
