This study investigates the strategic use of language in social media political campaigns, with particular emphasis on its impact on audience engagement and public discourse transformation. Through a comprehensive theoretical framework incorporating the Sapir-Whorf Hypothesis, Elaboration Likelihood Model, Critical Discourse Analysis, and Framing Theory, the research examines complex linguistic patterns, sentiment variations, and framing strategies across 10,000 campaign posts from major social media platforms. The study employs a mixed-methods approach, combining computational linguistics analysis with qualitative discourse examination. Using natural language processing tools and manual coding, researchers analyzed linguistic features including lexical choice, syntactic structures, metaphorical expressions, and rhetorical devices. Results reveal sophisticated patterns of deliberate linguistic manipulation designed to evoke specific emotional responses (72% of posts), reinforce political ideologies (65%), and adapt to temporal and platform-specific contexts (83%). The findings demonstrate that campaign language strategically evolves across different platforms, with Twitter showing more aggressive rhetoric (58%) compared to Facebook (31%) and Instagram (27%). Additionally, temporal analysis reveals significant shifts in linguistic strategies during critical campaign periods, with increased emotional language use during key political events (92% correlation). This research contributes to our understanding of digital political communication and offers practical insights for analyzing social media campaign strategies.

This research aims to evaluate the effectiveness of project-based collaborative learning in improving the English speaking skills of high school students. Using a quasi-experimental design, this study involved 64 eleventh-grade students divided into an experimental group (n=32) using project-based collaborative learning methods and a control group (n=32) using conventional methods. Data were collected through pre-test and post-test speaking assessments, classroom observations, and interviews with students and teachers. The results showed that the experimental group experienced a significant improvement in English speaking skills compared to the control group (p<0.05) with a large effect size (d=0.87). Qualitative analysis revealed that project-based collaborative learning increased students' motivation, confidence, and critical thinking abilities. These findings indicate that the project-based collaborative learning approach can be an effective strategy for developing English speaking skills in the EFL (English as a Foreign Language) context.

This research analyzes teachers' perceptions and practices regarding technology integration in English language teaching within the Indonesian educational context. Using a mixed methods approach, this study involved 120 English teachers from various educational levels (primary, junior high, senior high, and higher education) through an online survey, with 15 teachers selected for in-depth interviews and classroom observations. The findings reveal a gap between teachers' positive perceptions of technology (M=4.21 on a 5-point scale) and actual implementation in teaching practices (M=3.15). Statistical analysis identified four main factors influencing technology integration: teachers' digital competence (?=0.43, p<0.01), institutional support (?=0.38, p<0.01), teachers' pedagogical beliefs (?=0.35, p<0.01), and infrastructure accessibility (?=0.32, p<0.01). Qualitative data revealed that while teachers acknowledge the potential of technology to increase student motivation and create authentic language learning environments, they face challenges in aligning technology use with learning objectives, classroom management, and learning assessment. This research provides recommendations for teacher professional development and educational policies that support effective technology integration in English language teaching.