İHÜ Araştırma ve Akademik Performans Sistemi
DSpace@İHÜ, İbn Haldun Üniversitesi’nin bilimsel araştırma ve akademik performansını izleme, analiz etme ve raporlama süreçlerini tek çatı altında buluşturan bütünleşik bilgi sistemidir.
Güncel Gönderiler
An innovative non-formal learning model based on nature and science: Content, pedagogy and continuous professional development
(Springer Nature, 2026) Kaya, Volkan Hasan; Bulut, Mehmet Akın; Göçen, Ahmet; Eğitim Bilimleri Fakültesi, Rehberlik ve Psikolojik Danışmanlık Bölümü
The current education model is gradually shifting away from its traditional framework, evolving towards a more informal, out-of-brick, outdoor learning culture. In this context, the topic of non-formal out-of-school learning environments, which bridge education with real-life experiences and enhance individuals' learning through daily activities, requires further examination and clarification within relevant frameworks. To this end, this study aims to clarify a framework for "nature and science-based out-of-school learning environments" encompassing content, pedagogy, continuous professional development by achieving a consensus based on expert opinions. This Delphi study employs an exploratory sequential design, a type of mixed-method research. By incorporating the insights of trainers, the study provides significant perspectives on non-formal outdoor learning, particularly in the areas of definition, content, pedagogy, professional development and education technology. The findings highlight the importance of effectively integrating content, pedagogy, professional development, and the pedagogical application of education technology in non-formal learning settings.
"Aidemics" examined analytically through the connectivist theory: Institutional AI-mediation in higher education via an artificial intelligence center (CILT-AI)
(Taylor & Francis, 2026) Bulut, Mehmet Akın; Eğitim Bilimleri Fakültesi, Rehberlik ve Psikolojik Danışmanlık Bölümü
The rapid expansion of artificial intelligence (AI) in higher education has intensified calls for pedagogically grounded approaches to AI education that extend beyond tool adoption and participation metrics. This qualitative case study examines how an institutional AI center (CILT-AI: Center for Innovative Learning and Teaching Artificial Intelligence) mediates educators' learning, experimentation, and professional identity. Rooted in connectivist theory, it views AI-mediated learning as a networked process involving educators (faculty-academics), students, structures, and tools. Analysis includes institutional records (n = 567) and interviews with faculty (n = 40) and students (n = 20$). Rather than treating participation as a proxy for learning, the analysis interrogates how, under what conditions, and for whom engagement in AI-focused initiatives translated into pedagogical change, ethical reflection, and shifts in professional self-understanding. The findings show that networked participation only supports learning through collaborative structures that enable disciplinary translation and sustained experimentation; without this mediation, engagement remains aspirational and symbolic. The study introduces Aidemics as an emergent, ethical professional identity formed through sociomaterial engagement within institutional networks, rather than fixed expertise. By complicating assumptions about connectivist networked learning, this research clarifies the role of institutional AI centers and offers design considerations for AI-mediated learning that prioritize both capacity building and ethical reflexivity.
Jenis kopi boru dari Turki: Menengiç Kahvesi
(IKA FAPSI UNPAD, 2026) Bulut, Sefa; Herawati, Netty; Eğitim Bilimleri Fakültesi, Rehberlik ve Psikolojik Danışmanlık Bölümü
[No Abstract Available]
Peran kopi dalam budaya Turki
(IKA FAPSI UNPAD, 2026) Herawati, Netty; Bulut, Sefa; Eğitim Bilimleri Fakültesi, Rehberlik ve Psikolojik Danışmanlık Bölümü
[No Abstract Available]
ChatGPT for mental health support: A systematic scoping review of human-computer interaction implications
(Sage Publications, 2026) Nazir, Thseen; Eğitim Bilimleri Fakültesi, Rehberlik ve Psikolojik Danışmanlık Bölümü
Large language models (LLMs) such as ChatGPT are increasingly used around mental health, yet design-oriented syntheses remain limited. We conducted a PRISMA-aligned systematic scoping review focused specifically on ChatGPT (GPT-3.5/4+) in mental health-related use including "in the wild" adoption by laypeople, training applications, and clinical-adjacent pilots. Searches of five databases (November 2022 to August 2025), with citation tracking and gray-literature screening, yielded 34 studies spanning randomized and non-randomized experiments, pilot trials, surveys/interviews, simulations, digital ethnography, and structured editorials. Evidence supports adjunct, not replacement, roles. In education/supervision, one randomized trial and a comparative supervision study show skill gains when practice is scaffolded with rubrics and human oversight; expert ratings judged trainee case conceptualizations acceptable. In clinical/adjacent contexts, signals include quality-of-life improvement (small inpatient pilot), short-term anxiety reduction when the model provides empathetic feedback, and a clinical RCT (outside psychiatry) showing reduced anxiety/depression with a ChatGPT adjunct. Studies of public/self-help use document appropriation of ChatGPT as a "digital therapist" with identified risks including privacy concerns, boundary violations, and over-reliance. Safety-critical tasks remain unreliable (e.g., under-identification of suicide risk, degradation with complexity, and cultural-fit gaps). We derive human-computer interaction requirements: clear scope-of-use messaging, prompt scaffolding, human-in-the-loop, privacy-preserving defaults, and explicit escalation/hand-off pathways.
