İbn Haldun Üniversitesi Kurumsal Akademik Arşivi
DSpace@İHÜ, İbn Haldun Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Ensuring trustworthiness in autoethnographic research in applied linguistics: Criticisms and coping strategies
(Imam Khomeini International University, 2025) Kamali, Jaber; Rektörlük, Yabancı Diller Okulu
This paper critically examines the concept of trustworthiness in autoethnographic research, a qualitative approach often challenged on various methodological and epistemological grounds. It begins with a personal narrative, illustrating how autoethnography resonates deeply with the author’s academic and professional identity. The paper then engages with four recurring critiques frequently directed at autoethnographic work, namely invisible data, over-subjectivity, misrepresentation of others, and navel-gazing. Each critique is explored in depth, followed by practical and theoretical strategies to mitigate its impact. These include data triangulation, reflexive questioning, collaborative validation, ethical representation, and alignment with established qualitative research criteria. Drawing on constructivist epistemologies, the study argues that when handled rigorously, personal experience can serve as a legitimate and valuable source of knowledge. The paper concludes with implications for both autoethnographers and critics, advocating for more reflexive, transparent, and dialogic practices that elevate the scholarly value of autoethnography while preserving its distinctive voice and transformative potential.
Exploring Iranian novice EFL trainees' perceptions of ChatGPT use for lesson planning through a critical digital literacy lens
(Springer Science and Business Media B.V., 2025) Javahery, Pourya; Alpat, Muhammet Furkan; Kamali, Jaber; Rektörlük, Yabancı Diller Okulu
As AI tools like ChatGPT continue to find their way into classrooms, it is becoming increasingly important to understand how new teachers are using them. This study adopts a phenomenological approach to explore the real-life experiences of ten participants who were selected using purposive sampling, and data were collected through interviews and narrative inquiry. The research is grounded in data collected through interviews and narrative inquiry. These insights are analyzed through the lens of Critical Digital Literacy (CDL), which emphasizes the need for critical reflection, ethical awareness, and the growth of teacher agency. Data from ten Iranian novice language teachers were analyzed using reflexive thematic analysis to explore these experiences. Thematic analysis uncovered four interconnected themes: Human-centered teaching vs. machine-centered learning, professional growth and autonomy through reflective AI engagement, ethical considerations and cultural sensitivity, and technology as a tool vs. a crutch. The findings show that the participants did not see ChatGPT as just a passive tool; rather, they regarded it as a resource that needed thoughtful evaluation. They actively modified and tailored the content ChatGPT produced to meet their teaching needs. Their interaction with AI was marked by both excitement and caution, highlighting the significance of reflective practice in fostering ethically sound and context-aware teaching methods. This study adds to the existing literature by demonstrating how CDL can empower novice teachers to responsibly integrate AI tools while preserving their pedagogical voice in the ever-evolving digital landscape.
Editorial: Technology-enhanced language teacher education: Opportunities, challenges, and futures
(Castledown Publishers, 2025) Xerri, Daniel; Kamali, Jaber; Mohebbi, Hassan; Rektörlük, Yabancı Diller Okulu
This editorial introduces the Special Issue on technology-enhanced language teacher education (LTE), situating current debates and mapping opportunities, challenges, and futures. We clarify what counts as “technology” in LTE (from CALL, MALL, RALL, to virtual platforms and generative AI) and foreground digital literacies, ethics, and equity as preconditions for meaningful integration. The collected articles span conceptual, empirical, and review work: a five-principle framework positioning technology as a partner in reflective practice; teachers’ perspectives on GenAI in Hong Kong classrooms; a reconceptualisation of TPACK that embeds affective knowledge; a bibliometric mapping of GenAI-related LTE scholarship; a critical typology of teachers’ perspectives about AI; and a narrative inquiry into technological triggers of teacher immunity and coping startegies. Together, these contributions recenter teacher agency, identity, and well-being in technology-mediated contexts and argue for context-sensitive, ethically informed design for integrating technology in LTE. We close by outlining research trajectories that prioritise teacher voice, sustained professional learning, and principled, locally responsive uses of AI, globally.
Unsupervised machine learning based anomaly detection in high frequency data: Evidence from cryptocurrency market
(Johar Education Society Pakistan, 2025) Latif, Muhammad Nouman; Kaplan, Muhittin; Khan, Asad ul Islam; Yönetim Bilimleri Fakültesi, İktisat Bölümü
The rapid integration of cryptocurrencies into the global financial ecosystem has introduced unprecedented challenges in market surveillance, risk management, and anomaly detection. While conventional statistical models such as ARIMA (Autoregressive Integrated Moving Average) and GARCH (Generalized Autoregressive Conditional Heteroscedasticity) have been widely used for anomaly detection, their reliance on assumptions of normality and stationarity often fails to capture the complexities of high-frequency, non-linear cryptocurrency trading. Furthermore, traditional risk metrics including down-to-up volatility, negative conditional skewness, and relative frequency may overlook short-term anomalies due to data aggregation limitations.In order to address these issues, this paper proposes machine-learning model for detecting anomalies in cryptocurrency markets using Jupyter Notebook. We compare four advanced unsupervised machine learning models, i.e, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Isolation Forest (iForest), One-Class Support Vector Machine (OC-SVM), and Local Outlier Factor (LOF) for anomaly detection by using Monte Carlo simulations. The findings indicate that DBSCAN has the highest precision (79.7%) with the fewest false positives, making it ideal for supervisory monitoring. However, the high false positive rates of OC-SVM and Isolation Forest limit their use. By using data of six well-known cryptocurrencies at three different temporal resolutions (daily, hourly, and 15-minute) the performance of these four unsupervised learning techniques also examined and confirmed that the anomalies identified by DBSCAN are also consistent with the other three methods. Additionally, for robustness of results, we use UpSet Plots to incorporate the shared anomalies and found across the three unsupervised learning methods. Number of anomalies also depends on the volatility and time interval of cryptocurrencies, more volatile / high frequency more anomalies. The study presents sound methodological approach for facilitating financial monitoring and mitigating risks in the cryptocurrencies market, and provides useful information for market players, analysts and policymakers. These results emphasize the importance of choosing algorithms based on specific surveillance targets to promote greater stability in digital asset environments.
Habermas as an ethnic thinker Par Excellence: On critique, Palestine and the role of intellectuals
(Routledge, 2025) Ahmad, Irfan; İnsan ve Toplum Bilimleri Fakültesi, Sosyoloji Bölümü
Taking Habermas’ 2023 statement on Palestinians-Israel as the point of entry, this article examines his concept of critique. Against the dominant view of him as a philosopher of ‘universalism’ and ‘critical rationality,’ my thesis is that Habermas is an ethnic thinker, for, his ideas of critique and universalism unidirectionally rest on ‘to all’ rather than ‘from all.’ Consequently, it is missionary and borders on Islamophobia, particularly after 9/11. I show how Habermas’ denial of Palestinians’ genocide and his unqualified support to ‘Israel's right to exist’ as integral to Germany's ‘democratic ethos’ is neither an ample departure from his participation in the Hitler Youth nor from his understanding of the Enlightenment-modernity but largely their offshoots. I also juxtapose Habermas’ role as a public intellectual with that of Imam Malik (d. 795) who chose to be flogged rather than parrot unjust language of power elites. I conclude with three broad implications this article has in the field of teaching in higher education.
