http://hdl.handle.net/20.500.12323/608 2026-05-21T14:31:19Z 2026-05-21T14:31:19Z Eyvazov, Pərvin http://hdl.handle.net/20.500.12323/8324 2026-05-21T09:41:19Z 2026-01-01T00:00:00Z

Title: Bəkir Çobanzadə: dil tarixi konsepsiyası Authors: Eyvazov, Pərvin Abstract: Monoqrafiyada görkəmli türkoloq alim, professor Bəkir Vahab oğlu Çobanzadənin elmi yaradıcılığında dil tarixi məsələləri ilk dəfə geniş şəkildə tədqiq olunmuşdur. Kitabda B. Çobanzadənin elmi görüşləri tarixi qrammatika və ədəbi dil məsələləri kontekstində şərh olunmuş, fonetik, leksik və morfoloji quruluşun tarixi inkişafına dair müxtəlif məsələlər sistemli şəkildə öyrənilmişdir. Eyni zamanda alimin ədəbi dil konsepsiyası ətraflı araşdırılmış, ədəbi dil tarixinin dövrləşdirilməsi, ədəbi şəxsiyyətlərin dili və ümumtürk ədəbi dili haqqındakı baxışları çağdaş elmi fikirlərlə müqayisəli tədqiqata cəlb olunmuşdur.

2026-01-01T00:00:00Z Çelik, Ferdi Duran, Volkan Curle, Samantha http://hdl.handle.net/20.500.12323/8317 2026-05-14T05:45:07Z 2026-01-01T00:00:00Z

Title: Justice and L2 motivational network: An EBICglasso based analysis of English language learners' motivation, goal orientation, mindset, and justice in the classroom Authors: Çelik, Ferdi; Duran, Volkan; Curle, Samantha Abstract: This study models second language (L2) motivational factors and classroom justice in English as a Foreign Language (EFL) learners via a network psychometric method. The study formulates a network of motivational aspects including expectancy beliefs, goal orientations, ideal and ought-to L2 selves, learning experiences, intended effort, mindsets, and anxiety and distributive, procedural, and interactional justice dimensions as an interconnected system based on the expectancy-value-cost theory, achievement goal theory, the L2 Motivational Self System, implicit theories of ability, and organizational justice frameworks. The analysis of the data on 434 Turkish undergraduate EFL students using network analysis demonstrates that the study has a moderately dense network with two major communities: cohesive justice community that offers social-relational scaffolding and motivational-affective community that focuses on English learning experience, ideal L2 self, and intended effort. The most central node, which has a significant impact, is intended effort, and the facets of justice, especially interactional and procedural justice, serve as bridges between social perceptions and cognitive-affective engagement. Perceived costs and fixed mindsets are maladaptive factors with inhibitory functions and relative isolation. The results build on the dynamic systems models of L2 acquisition by integrating the perceptions of justice into the motivational ecologies of the learners and emphasizing their control role in promoting persistence and reducing avoidance. The network approach, methodologically, provides a replicable framework of future research, and implications of the study in practice with regard to pedagogical intervention to promote justice to improve motivational outcomes.

2026-01-01T00:00:00Z Muthmainnah, Muthmainnah Aeni, Nur Nasir, Aco Elyas, Tariq Curle, Samantha Cardoso, Luis http://hdl.handle.net/20.500.12323/8316 2026-05-08T09:27:34Z 2026-03-31T00:00:00Z

Title: Robot-Assisted Language Learning (RALL) for Communication Skills Development in Maritime-Themed EFL Education: A Study of Secondary School Students in West Sulawesi, Indonesia Authors: Muthmainnah, Muthmainnah; Aeni, Nur; Nasir, Aco; Elyas, Tariq; Curle, Samantha; Cardoso, Luis Abstract: Obstacles to communication practice in English as a Foreign Language (EFL) classrooms are often experienced due to a lack of access to authentic, life-related learning materials, fear of peer assessment, culturally unfamiliar textbook content, and exam-related pressures. These situations often inhibit students’ willingness to speak and reduce ongoing engagement. In response to these issues, this study aims to explore whether Robotic Assisted Language Learning (RALL) supported by maritime-themed teaching materials can help improve students’ communicative interactions in a culturally relevant context. Respondents were students randomly selected from six junior high schools in Polewali Mandar, Indonesia. The schools were purposively selected based on the following three criteria: (a) coastal or semi-coastal areas, (b) implementation of the national EFL curriculum by the Ministry of Education, and (c) school availability to conduct technology-based classroom observations. Following this purposive sampling, classes within each school were randomly selected, and students who met the inclusion criteria (aged 13–14, in 7th grade) were invited to participate. A total of 238 students participated in the study. Mixed-methods design was used, with quantitative and qualitative data collection, with analysis occurring in parallel, and integrated during interpretation. Data sources included a 20-item Likert-scale survey to measure learner readiness, perceived usefulness, and affective responses to RALL, as well as semi-structured interviews inquiring about students’ lived experiences. Results indicated a strong learner preference for the use of AI-powered tools, thematically including ChatGPT, Duolingo, ELSA Speak, and Cici Bot. Quantitative findings consistently reflected positive perceptions and stable response patterns, while qualitative findings described how RALL reduced anxiety levels, encouraged repeated practice, and provided a safer and less stressful environment for communication. The results of this study have practical implications for the development of context-relevant, sustainable EFL instruction that enhances engagement, which does not rely solely on traditional, textbook-based acquisition.

2026-03-31T00:00:00Z Beloufa, Chahra Curle, Samantha http://hdl.handle.net/20.500.12323/8315 2026-05-08T09:19:38Z 2026-04-01T00:00:00Z

Title: AI-generated Shakespeare: A corpus stylistic analysis of ChatGPT-4's generated and adapted scenes Authors: Beloufa, Chahra; Curle, Samantha Abstract: Generative AI is reshaping literary production, raising critical questions about textual integrity and authenticity. The rise of generative AI challenges foundational concepts in literary theory, including authorship, stylistic integrity, and the very ontology of the canonical text. This study uses the case of Shakespearean adaptation by GPT-4 to interrogate not merely the capability of AI, but its function as a cultural agent that reframes literary heritage through the logics of accessibility, simplification, and algorithmic bias. A corpus stylistic and comparative textual analysis is conducted on key scenes from Romeo and Juliet, The Merchant of Venice, The Winter's Tale, King Lear, Hamlet, and Othello. The study evaluates AI-generated adaptations of the original texts, focusing on linguistic, stylistic, thematic, and contextual fidelity. Findings indicate that while GPT-4 retains core themes and narrative structures, it systematically simplifies rhetorical devices, syntactic patterns, and metaphorical richness. The analysis contributes to debates on AI's role in literature by proposing a new typology of algorithmic adaptation ranging from faithful reproduction to generative transformation that extends existing frameworks in adaptation theory. This research demonstrates that GPT-4's stylistic simplification is not a correctable bug but a fundamental feature of its operation as a cultural agent, with profound implications for how literary heritage will be mediated in the digital age.

2026-04-01T00:00:00Z