Aug 2026· The social science· Vol 15, pp. 517· 0 citations· 30 references
TL;DR
The findings show that interaction with ChatGPT rarely coincided with substantial changes in students’ underlying interpretations or positions, and highlight the need for pedagogical strategies based on source comparison, verification, and justification of generated content.
Abstract
Social Sciences education requires pedagogical approaches that foster critical thinking and enable students to analyze, contrast, and interpret complex social realities. As Generative Artificial Intelligence (GenAI) becomes integrated into higher education, it offers opportunities to support these processes while raising questions about students’ autonomy and reliance on generated content. Although previous research has examined the educational uses of GenAI, less is known about how students interact with these systems when revising source-based interpretations and how they position themselves. This study examines how 83 first-year university students enrolled in Education degree programs interacted with ChatGPT during a source-interpretation activity and how this interaction was reflected in the reformulation of their initial responses. A qualitative descriptive–interpretative design compared initial responses, prompts, revised responses, and retrospective reflections. The findings show that interaction with ChatGPT rarely coincided with substantial changes in students’ underlying interpretations or positions. Instead, it mainly supported response expansion, argumentative reinforcement, and in some cases reformulation. A central contribution of the study is the identification of four recurrent learner profiles within the analytical category of interaction orientations: autonomy-preserving, objectivity-seeking, stance-attributing, and validation-seeking. Greater textual elaboration did not necessarily reflect stronger critical thinking or more independent interpretation. These findings highlight the need for pedagogical strategies based on source comparison, verification, and justification of generated content.
The findings demonstrate that ChatGPT-4 operates effectively as an artificial mediational tool within the Zone of Proximal Development when paired with structured prompts and teacher-led reflection, transforming learners from passive consumers into active, analytical evaluators.
Fina Khiyarotun Nisa, R. Haryanti· International journal of res...· 0 citations
The study investigates how this integration affects comprehension, critical thinking, student engagement, learner autonomy, and the particular difficulties that students face using thematic analysis. Student perspectives, classroom observations, and classroom records were used to collect data. Using detailed information from ten informants with a range of skill levels, this qualitative case study examines the impact of combining language and content in academic reading for English as a Foreign Language (EFL) learners in higher education. The results show that students' reading comprehension is much improved by contextualizing reading materials, structuring instruction, and connecting the subject to real-world scenarios. Giving students the chance to relate academic material to their own experiences increases their engagement and sense of autonomy. However, issues with technical jargon, a lack of prior knowledge, and the interpretation of statistical or graphical data remain obstacles. Scaffolded analysis, modeling of reading strategies, and pre-teaching of specialist terminology are among the effective tactics identified. These findings highlight the importance of adaptable, targeted teaching strategies for EFL students. Such interventions are essential for fostering critical thinking, academic literacy, and independence. Integrating language and content supports EFL learners in overcoming reading challenges and achieving academic success.
Asrul Asrul, Abdulhalim Daud, Awaludin Rizal et al.· GLENS: Global English Insigh...· 0 citations
This study examines language and communication students’ self-perceived mastery of AI chatbot prompt engineering, with particular attention to “vibe coding” for educational mobile application development. In this study, vibe coding refers to the deliberate use of prompts to shape tone, style, audience orientation, and user-facing educational content. Using a pattern-based framework centred on roles, constraints, and examples, the study investigates how students combine structure and exploratory prompting. A quantitative cross-sectional survey was administered online during March–July 2025 (Semester 2). Complete responses from 120 undergraduates were analysed from approximately 126 invited students (analytic response rate = 95.2%). The questionnaire demonstrated excellent overall internal consistency (Cronbach’s ? = .965). Results indicate that students usually begin tasks with structured prompts but later move towards mixed or unstructured prompting styles, suggesting a control-then-explore sequence. Longer exposure to AI chatbots and more extensive prompt-engineering training were associated with higher self-perceived competency and output efficiency, whereas weekly usage frequency did not show statistically significant differences. Educational background was associated with prompting style and usage, but not with overall perceived competency or output efficiency, and gender differences were negligible. The findings suggest that scaffolded instruction in prompt engineering can support more confident and consistent student use of AI chatbots. Future research should triangulate self-reports with behavioural logs, archived prompts, and performance-based outputs.
Nur Izzati Khairuddin, M. Rashid, Hairul Azhar Mohamad et al.· International Journal of Lea...· 0 citations
Problem-solving competence (PSC) is a central objective of contemporary science education; however, many students continue to experience difficulties when engaging in inquiry-based learning activities that require reasoning, reflection and solution refinement. This study investigated the effects of selective ChatGPT scaffolding embedded within the 5E instructional model—engage, explore, explain, elaborate, and evaluate—on middle school students’ PSC. A quasi-experimental design was conducted with 80 grade 9 students, including an experimental group receiving ChatGPT-supported 5E instruction and a control group receiving conventional 5E instruction. Unlike continuous AI integration, ChatGPT support was selectively provided during the explore and elaborate phases to facilitate inquiry reasoning, solution generation and reflective evaluation. PSC was assessed across three dimensions: problem understanding (PU), solution planning and implementation (SPI), and evaluation and improvement (EI). Baseline equivalence between groups was confirmed using independent-samples t-tests. Analysis of covariance results revealed a significant positive effect of the intervention on overall PSC, F (1, 77) = 6.080, p = .0159, partial η² = .073. Significant improvement was also observed for EI, F (1, 77) = 4.901, p = .0298, partial η² = .060, while SPI showed a positive trend, F (1, 77) = 2.953, p = .0898. No significant effect was observed on PU. The findings suggest that selective ChatGPT scaffolding is particularly effective in supporting reflective reasoning, evidence evaluation, and solution refinement in inquiry-based science learning environments.
Nguyen Chi Le, Ha Thi Nguyen, Quynh Thi Thuy Nguyen et al.· Eurasia Journal of Mathemati...· 0 citations
The rapid development of generative artificial intelligence in language education offers new opportunities to provide immediate and personalized oral feedback; however, its use as digital scaffolding in interactive communication practice remains underexplored. This study aimed to explore how undergraduate English as a Foreign Language (EFL) students engage with generative AI-mediated feedback as a digital scaffolding mechanism during interactive oral communication practice. This qualitative case study involved three intermediate EFL university students at Institut Pendidikan Indonesia Garut, West Java. Data were collected through multi-session oral interactions and semi-structured retrospective interviews and analyzed using Braun and Clarke's six-phase thematic analysis. Vygotsky's Sociocultural Theory and Schmidt's Noticing Hypothesis served as theoretical foundations for understanding scaffolding processes, linguistic awareness, and students' oral interaction development. The findings revealed that Gemini AI functioned as both an affective and cognitive scaffold during speaking practice. Affectively, interaction with AI created a low-anxiety practice environment with minimal social pressure, thereby enhancing students' willingness to communicate. Cognitively, immediate, clear, and objective feedback helped students recognize both linguistic strengths and errors. Linguistically, real-time feedback promoted explicit awareness of tense inconsistencies and lexical misuse while encouraging students to monitor articulation and regulate speaking rate. Despite a technological constraint involving premature turn-taking caused by the AI misinterpreting cognitive pauses as the end of an utterance, students demonstrated digital agency by employing strategic conversational fillers to maintain interactional continuity. Thus, Gemini AI can serve as a low-pressure practice environment that bridges students' readiness toward real-world oral interaction.
ABSTRAK
Perkembangan kecerdasan buatan generatif dalam pembelajaran bahasa membuka peluang baru untuk menyediakan umpan balik lisan yang cepat dan personal, tetapi pemanfaatannya sebagai perancah digital dalam praktik komunikasi interaktif masih memerlukan kajian lebih lanjut. Penelitian ini bertujuan mengeksplorasi keterlibatan mahasiswa Program Studi Pendidikan Bahasa Inggris dengan umpan balik berbasis Kecerdasan Buatan (AI) generatif sebagai mekanisme perancah digital (digital scaffolding) selama praktik komunikasi lisan interaktif. Penelitian ini menggunakan studi kasus kualitatif yang melibatkan tiga mahasiswa EFL tingkat menengah di Institut Pendidikan Indonesia Garut, Jawa Barat. Data dikumpulkan melalui interaksi lisan dalam beberapa sesi dan wawancara retrospektif semi-terstruktur, kemudian dianalisis menggunakan analisis tematik enam tahap Braun dan Clarke. Penelitian ini menggunakan Teori Sosiokultural Vygotsky dan Hipotesis Noticing Schmidt sebagai landasan teoretis untuk memahami proses perancahan, kesadaran linguistik, dan perkembangan interaksi lisan mahasiswa. Hasil penelitian menunjukkan bahwa Gemini AI berfungsi sebagai perancah afektif dan kognitif dalam praktik berbicara. Secara afektif, interaksi dengan AI menciptakan ruang praktik dengan tingkat kecemasan yang lebih rendah dan minim tekanan sosial sehingga meningkatkan kesiapan mahasiswa untuk berkomunikasi. Secara kognitif, umpan balik yang cepat, jelas, dan objektif membantu mahasiswa mengenali kekuatan serta kesalahan penggunaan bahasa. Secara linguistik, umpan balik waktu nyata mendorong kesadaran terhadap ketidaktepatan tense dan penggunaan leksikal, sekaligus membantu mahasiswa memantau artikulasi dan mengatur kecepatan berbicara. Meskipun terdapat kendala berupa pemotongan giliran bicara akibat AI salah menginterpretasikan jeda berpikir sebagai akhir tuturan, mahasiswa menunjukkan agensi digital melalui penggunaan penanda percakapan strategis. Dengan demikian, Gemini AI dapat berfungsi sebagai ruang latihan bertekanan rendah yang menjembatani kesiapan mahasiswa menuju interaksi lisan di dunia nyata.
Arda Arda, A. Suminar, Y. Fajriah· LANGUAGE Jurnal Inovasi Pend...· 0 citations
Teacher explanations are often viewed as monologic instructional methods associated with authoritative classroom discourse. This study challenges this assumption by examining how Life Sciences teachers’ mobilisation of Topic-Specific Pedagogical Content Knowledge (TSPCK) components within explanations shapes subsequent classroom interaction. Drawing on a qualitative single embedded case study of three experienced Grade 11 Life Sciences teachers in South Africa teaching population ecology, I analysed nine video-recorded lessons to explore how explanations function as pedagogical and interactional resources. Teacher explanations were analysed through four TSPCK components, which include learner prior knowledge, representations, what is difficult to teach, and curricular saliency. The fifth component, conceptual teaching strategies, was treated as emergent from their integration and was not coded as a separate category. Classroom interaction following the prompt embedded in explanations was examined for dialogic interaction patterns and categorised as knowledge-sharing or argumentative. The findings reveal that dialogic interaction emerged irrespective of the nature of the prompt (open-ended questions, closed-ended questions, or instructions) when explanations foregrounded and integrated multiple TSPCK components. In such cases, learners appropriated, re-voiced, and transformed the pedagogical and conceptual resources embedded in explanations, particularly representations and key conceptual distinctions, to justify claims, challenge peers, and extend lines of reasoning. I argue that teacher explanations function as framing devices that establish shared semiotic resources and discursive affordances, enabling heightened dialogic interaction beyond the effects of prompt type alone. These findings extend TSPCK research by empirically demonstrating how explanations mediate classroom discourse. I highlight implications for science teacher professional development that integrate explanatory practices with dialogic teaching.
H. Khoza· International Journal of Sci...· 0 citations
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