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Digital Rhetoric and Algorithmic Ethics: A Literature Review of Digital Communication Ibrahim, Riza Andrian; Lianingsih, Nestia
International Journal of Linguistics, Communication, and Broadcasting Vol. 3 No. 2 (2025): International Journal of Linguistics, Communication, and Broadcasting
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijlcb.v3i2.224

Abstract

In the digital age, communication has become increasingly shaped by algorithmic systems that structure interaction, visibility, and persuasion across online platforms. This literature review explores the convergence of digital rhetoric and algorithmic ethics to understand how meaning-making and moral agency are co-constructed in contemporary digital environments. Digital rhetoric, concerned with how persuasion operates in multimodal and interactive contexts, now intersects with algorithmic processes that govern content distribution and user engagement. Simultaneously, the rise of algorithmic ethics addresses the sociotechnical implications of bias, opacity, and accountability embedded in machine-driven communication infrastructures. Through a qualitative synthesis of recent scholarship, this study identifies four core themes: algorithmic persuasion, content visibility and bias, platform governance, and ethical resistance. The findings show that algorithms are no longer neutral tools but rhetorical actors that influence how narratives are constructed and circulated. Moreover, the literature highlights growing concerns about fairness, transparency, and user autonomy, especially in the realms of political discourse, media consumption, and educational technologies. The study concludes that navigating digital communication today demands both rhetorical literacy and ethical sensitivity. A deeper understanding of how algorithmic systems persuade, exclude, or amplify certain voices is vital for promoting equitable and informed public discourse. This review contributes to a critical framework that connects digital rhetoric and algorithmic ethics, offering insights into the rhetorical and moral complexities of our algorithmically mediated world.
The Role of Guidance and Counseling Teachers in Addressing Juvenile Delinquency: A Literature Review Lianingsih, Nestia; Lestari, Mugi
International Journal of Ethno-Sciences and Education Research Vol 5, No 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijeer.v5i1.840

Abstract

Juvenile delinquency is an increasingly worrying phenomenon in various countries, including Indonesia. This study aims to explore the role of Guidance and Counseling (BK) Teachers in overcoming juvenile delinquency through a literature review method. This study analyzes prevention strategies, reactive approaches, and curative efforts carried out by BK teachers to deal with deviant behavior committed by adolescents. The results of the study indicate that BK teachers have a key role in preventing and overcoming juvenile delinquency through various approaches, including providing information, group guidance, mediation, home visits, and individual and group counseling. However, the implementation of these strategies often faces internal, external, and institutional obstacles, such as students' lack of confidence to open up, minimal parental attention, and limited school resources. This study emphasizes the importance of a collaborative approach involving teachers, parents, and the community in dealing with juvenile delinquency in a comprehensive and sustainable manner
Ethno-Sciences and the Transformation of Traditional Agricultural Systems in Teluk Bintuni: Between Preservation and Modernization Jaizul, Alim; Sulistya, Astrid; Lianingsih, Nestia
International Journal of Ethno-Sciences and Education Research Vol 5, No 2 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijeer.v5i2.938

Abstract

Traditional farming systems are a form of long-term interaction between humans and their environment that manifests ecological and cultural adaptation. This study aims to explore the dynamics between the preservation of local knowledge and the pressures of modernization in the transformation of traditional farming systems of indigenous peoples in Teluk Bintuni, West Papua. Using an ethno-science approach with qualitative-descriptive methods through participatory observation, in-depth interviews, FGDs, and documentation studies in the Moskona, Wamesa, and Sumuri indigenous communities. The results of the study indicate that traditional farming systems are still maintained with high dependence on sago (85%), sweet potatoes (72%), taro (66%), and bananas (54%) as sources of food and cultural identity. The transformation of the farming system does not follow a linear pattern from traditional to modern, but rather creates a hybrid system that selectively combines traditional elements with modern technology. Indigenous peoples are not passive in facing change, but actively negotiate and adapt based on their ecological and cultural interests. The ethno-science approach offers a framework for integrating local knowledge into development planning, without ignoring the ecological and spiritual dimensions of indigenous peoples. Dialogue between local knowledge systems and modern science can produce more adaptive and inclusive agricultural policies, especially in indigenous areas such as Teluk Bintuni that face pressure from natural resource exploitation.
Contextual Learning as a Means to Improve Elementary School Students' Mathematical Literacy Skills Hidayana, Rizki Apriva; Lianingsih, Nestia
International Journal of Ethno-Sciences and Education Research Vol 5, No 2 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijeer.v5i2.935

Abstract

Mathematical literacy in the Programme for International Student Assessment (PISA) emphasizes students’ ability to analyze, justify, and effectively communicate ideas, as well as to formulate, solve, and interpret mathematical problems across various forms and contexts. The PISA assessment focuses on real-life problems rather than solely on typical classroom-based questions. Based on cognitive development stages, elementary school students are generally in the concrete operational stage, which means they require tangible objects that can be perceived through the senses. Since mathematics learning tends to be abstract, students need support in the form of media and teaching aids to clarify concepts delivered by the teacher, making them easier to understand. Mathematics instruction is expected to provide an integrated, comprehensive, and holistic understanding of the material. This understanding not only fulfills the demands of mathematical content but also offers practical benefits to students. This aligns with the contextual learning approach, which emphasizes active student engagement throughout the learning process, enabling them to discover concepts independently and relate them to real-life situations. Contextual learning is carried out through four main stages: providing motivation, conceptual understanding, application, and assessment—all of which are grounded in the core components of contextual learning.
Empowering Algebra Learning with AI-Based Adaptive Systems for High School Students Lestari, Mugi; Saputra, Moch Panji Agung; Lianingsih, Nestia
International Journal of Ethno-Sciences and Education Research Vol. 5 No. 3 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijeer.v5i3.1039

Abstract

Learning algebra is often challenging for high school students due to its abstract nature, leading to loss of motivation. This study designed and implemented an Adaptive AI Platform that personalized practice problems based on real-time performance analysis and student interests. A quasi-experimental study with 120 10th grade students demonstrated a significant effect of the platform on improving academic achievement. The experimental group (n=60) using the platform demonstrated significantly higher TPA posttest scores (adjusted mean: 81.95) than the control group (n=60) (adjusted mean: 73.65), after controlling for pretest scores. In addition, the platform substantially increased students’ learning motivation and self-confidence (Cohen’s d = 2.48 for the experimental group), supported by instant feedback and difficulty adaptation. The integration of Deep Knowledge Tracing (DKT) and Item Response Theory (IRT) models enabled dynamic content adjustments aligned with students’ cognitive progress. The results were also supported by students’ positive perceptions regarding the engagement and effectiveness of the platform. This study recommends the integration of adaptive AI platforms in high school mathematics education with adequate teacher support and infrastructure, and suggests future research for longer intervention durations and ethical analysis of AI.