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K-12 öğretmenlerinin yapay zekâya yönelik genel tutumlarının ve yapay zekâ okuryazarlığı dersi için müfredat ihtiyaçlarının araştırılması
No full textArtificial Intelligence (AI) is increasingly transforming education by providing innovative tools that enhance teaching and learning. However, many educators remain uncertain about how to utilize AI effectively while ensuring ethical practices, highlighting the need for AI literacy in K-12 education. Before implementing AI literacy curricula, understanding teachers’ attitudes toward AI and their needs for successful adoption is essential.
This study explored K-12 teachers’ attitudes toward AI and their curriculum needs for implementing AI literacy. A mixed-method approach was adopted, employing the General Attitudes towards Artificial Intelligence Scale (GAAIS) to measure attitudes and open-ended survey questions to capture teachers’ perspectives. The study involved 40 teachers from public and private K-12 schools who voluntarily shared their views. Findings revealed that teachers hold moderately positive attitudes toward the beneficial aspects of AI (M = 3.33/5) and a somewhat forgiving attitude toward its negative aspects (M = 3.07/5), suggesting a general openness to AI integration in education.
Thematic analysis of teachers’ responses identified key needs for successful AI literacy implementation, including professional development training, technical support, comprehensive curriculum resources, and clear ethical and policy guidelines. Teachers also emphasized the importance of promoting responsible AI use and aligning curriculum content with real-world applications.
Overall, the study contributes to the growing field of AI in education by offering insights that can guide policymakers, curriculum developers, and educational leaders in designing effective AI literacy curricula for K-12 schools.Yapay Zekâ (YZ), öğretim ve öğrenmeyi geliştiren yenilikçi araçlar sunarak eğitimi giderek daha fazla dönüştürmektedir. Ancak birçok eğitimci, etkili bir şekilde YZ kullanma ve etik uygulamaları sağlama konusunda hâlâ belirsizlik yaşamaktadır. Bu durum, K-12 eğitiminde YZ okuryazarlığına duyulan ihtiyacı ortaya koymaktadır. YZ okuryazarlığı müfredatını uygulamadan önce, öğretmenlerin yapay zekâya yönelik tutumlarını ve başarılı bir benimseme için ihtiyaçlarını anlamak önemlidir.
Bu çalışma, K-12 öğretmenlerinin yapay zekâya yönelik tutumlarını ve YZ okuryazarlığı uygulamasına ilişkin müfredat ihtiyaçlarını incelemiştir. Karma yöntem yaklaşımı benimsenmiş, öğretmen tutumlarını ölçmek için Yapay Zekâya Yönelik Genel Tutumlar Ölçeği (GAAIS) ve öğretmenlerin görüşlerini almak için açık uçlu anket soruları kullanılmıştır. Araştırmaya gönüllü olarak kamu ve özel K-12 okullarında görev yapan 40 öğretmen katılmıştır. Bulgular, öğretmenlerin yapay zekânın faydalı yönlerine karşı orta düzeyde olumlu tutum (Ort. = 3.33/5) ve olumsuz yönlerine karşı kısmen hoşgörülü tutum (Ort. = 3.07/5) sergilediğini göstermektedir. Bu durum, öğretmenlerin genel olarak eğitimde YZ entegrasyonuna açık olduklarını ortaya koymaktadır.
Öğretmen yanıtlarının tematik analizi, YZ okuryazarlığının başarılı şekilde uygulanabilmesi için öne çıkan ihtiyaçların mesleki gelişim eğitimleri, teknik destek, kapsamlı müfredat materyalleri ve net bir şekilde etik/politika yönergeleri olduğunu ortaya koymuştur. Ayrıca öğretmenler; sorumlu bir şekilde YZ kullanımının teşvik edilmesi ve müfredatın gerçek dünya uygulamaları ile uyumlu hâle getirilmesinin önemini vurgulamıştır.
Bu çalışma, K-12 okulları için etkili YZ okuryazarlığı müfredatlarının tasarlanmasında politika yapıcılar, müfredat geliştiriciler ve eğitim liderlerine rehberlik edecek önemli bulgular sunmaktadır.M.S. - Master of Scienc
Low-Temperature Au-In TLP Bonding for Compact Hermetic Packaging of Piezoelectric MEMS Devices
No full textTarget-specific de novo design of drug candidate molecules with graph-transformer-based generative adversarial networks
No full textDiscovering novel drug candidate molecules is a fundamental step in drug development. Generative deep learning models can sample new molecular structures from learned probability distributions; however, their practical use in drug discovery hinges on generating compounds tailored to a specific target molecule. Here we introduce DrugGEN, an end-to-end generative system for the de novo design of drug candidate molecules that interact with a selected protein. The proposed method represents molecules as graphs and processes them using a generative adversarial network that comprises graph transformer layers. Trained on large datasets of drug-like compounds and target-specific bioactive molecules, DrugGEN designed candidate inhibitors for AKT1, a kinase crucial in many cancers. Docking and molecular dynamics simulations suggest that the generated compounds effectively bind to AKT1, and attention maps provide insights into the model’s reasoning. Furthermore, selected de novo molecules were synthesized and shown to inhibit AKT1 at low micromolar concentrations in the context of in vitro enzymatic assays. These results demonstrate the potential of DrugGEN for designing target-specific molecules. Using the open-access DrugGEN codebase, researchers can retrain the model for other druggable proteins, provided a dataset of known bioactive molecules is available
Self-Organized Actions for the "Slow and Incremental Adaptation" of Heritage Places: Learning from Pilavoglu Han in Ankara, Turkey
No full textTürkiye-Azerbaycan İlişkileri ve Karabağ Savaşı
No full textThis thesis aims to explain how the Second Karabakh War and the discourses of official decision-makers in Türkiye and Azerbaijan during the war altered the perceptions of mutual and shared security in post-war relations. The thesis problematizes both the First Karabakh War, which broke out in the 1990s, and particularly the Second Karabakh War, which lasted 44 days in 2020. While this research does not propose a fully-fledged theoretical model, it analyses the discourses of "solidarity, brotherhood, and unity" and "one nation, two states" that persisted between Türkiye and Azerbaijan during the 44-Day War, drawing on concepts that can be linked to constructivist theory and regional security themes. It concludes by finding that these discourses resulted in unification, integration, and institutionalisation in areas such as security and defence in the post-war period. This spirit of solidarity, displayed on national and international platforms during and after the war, created a qualitative leap in bilateral relations, elevating them from strategic partnership to alliance. This conclusion was reached by comparing the regional and international security perceptions of both countries in the 1991-2020 and post-2020 periods. Since current literature on Türkiye-Azerbaijan relations after the Second Karabakh War has focused primarily on areas such as military cooperation, joint exercises, and energy, this thesis emphasises the importance of the wartime rhetoric on solidarity between the two friendly states and the deepening institutional security-based relations that followed. A limitation of this thesis is the use of almost exclusively Turkish and English sources and the lack of elite interviews involving decision-makers and politicians.Bu tez, İkinci Karabağ Savaşı’nın ve bu savaş sırasında Türkiye ve Azerbaycan’ın resmi karar alıcılarının söylemlerinin, savaş sonrası ilişkilerde karşılıklı ve ortak güvenlik algılarında nasıl değişiklikler yarattığını açıklamayı amaçlamıştır. Tez hem 90’larda patlak veren Birinci Karabağ Savaşını hem de ve özellikle 2020’de 44 gün süren İkinci Karabağ Savaşı’nı problematize eder. Bu araştırma, tam teşekküllü bir teorik model önermese de inşacı teori ve bölgesel güvenlik temalarıyla ilişkilendirilebilecek kavramların ışığında, Türkiye ve Azerbaycan arasında 44 Gün Savaşı boyunca süreklilik teşkil eden “dayanışma, kardeşlik, ve birlik” ve “tek millet, iki devlet” gibi söylemleri analiz edilmiştir. Sonuç olarak bunların savaş sonrası dönemde güvenlik ve savunma gibi alanlarda birleşme, entegrasyon ve kurumsallaşma ile sonuçlandığını tespit etmiştir. Savaş sırasında ve sonrasında ulusal ve uluslararası platformlarda sergilenen bu dayanışma ruhu, ikili ilişkilerde niteliksel bir sıçrama yaratarak ilişkilerin stratejik partnerlikten müttefiklik seviyesine yükselmesine yol açmıştır. Bu sonuca, 1991-2020 ve 2020 sonrası dönemler, her iki ülkenin bölgesel ve uluslararası güvenlik algıları karşılaştırılarak varılmıştır. İkinci Karabağ Savaşı sonrası Türkiye-Azerbaycan ilişkileri, güncel literatürde daha çok askeri işbirlikleri, tatbikatlar ve enerji gibi alanlara odaklanılarak ele alındığından bu tez, iki dost ülke arasında savaş boyunca sürmüş olan diyaloğun ve dayanışmanın önemine ve daha sonra derinleşen kurumsal güvenlik bazlı ilişkilerin önemine vurgu yapmaktadır. Neredeyse yalnızca Türkçe ve İngilizce kaynakların kullanılmış olması ve karar alıcılar ve siyasetçiler gibi öznelerin yer aldığı bir elit mülakatı yapılamamış olması bu tezin bir kısıtıdır.M.S. - Master of Scienc
Goal-Oriented Random Access (GORA)
No full textWe propose Goal-Oriented Random Access (GORA), where transmitters
jointly optimize what to send and when to access the shared channel to a
common access point, considering the ultimate goal of the information
transfer at its final destination. This goal is captured by an objective
function, which is expressed as a general (not necessarily monotonic)
function of the Age of Information. Our findings reveal that, under
certain conditions, it may be desirable for transmitters to delay
channel access intentionally and, when accessing the channel, transmit
aged samples to reach a specific goal at the receiver
Generators of the mapping class group of a nonorientable punctured surface
No full textLet Mod(Ng,p) denote the mapping class group of a nonorientable surface of genus g with p punctures. For g ≥ 14, we show that Mod(Ng,p) can be generated by five elements or by six involutions
Petrographical and chemical characteristics of cleaned oltu-stone waste for their potential use (as a semi-precious stone)
No full textOltu-stone, a semi-precious stone found in the Oltu district of Erzurum, Turkey, is frequently used in the making of decorative ornaments. Approximately 90-95% of the Oltu-stone mined, consisting of substandard Oltu-stone because of mineral impurities and small fragment sizes, is considered Oltu-stone waste (OW). This waste is either discarded or burned, resulting in economic losses. The utilization of Oltu-stone waste (OW) as an alternative to standard Oltu-stone (SO) could reduce such losses. In order to see if Oltu-stone waste can be used as an alternative to standard Oltu-stone, it must first be cleaned of its inorganic impurities. After that, the cleaned Oltu-stone properties should be determined to compare their characteristics with standard Oltu-stone. In this study, the petrographic and chemical characteristics of cleaned Oltu-stone obtained by dense medium separation (float-sink method) were determined. The results indicated that the cleaned Oltu-stone was liptinite-rich coal with a small amount of huminite content. Also, it shows contorted suberinite cellular structure and has varying resinite content. Due to high liptinite content, cleaned Oltu-stone has a high volatile matter, i.e., 63-65%. The inorganic impurities in the Oltu-stone wastes were mainly quartz, calcite, pyrite, and clay mineral. After cleaning, most inorganics were separated, although pyrite and silicate minerals remained in trace amounts within the cellular structure. The FTIR results show the predominance of aliphatic hydrocarbons, low aromaticity, and low apparent maturity. It was determined that the cleaned Oltu-stone wastes have similar characteristics to the standard Oltu-stone and can be utilized for further processing as an alternative source
Threshold Structure-Preserving Signatures with Randomizable Key
No full textDigital signatures confirm message integrity and signer identity, but linking public keys to identities can cause privacy concerns in anonymized settings. Signatures with randomizable keys can break this link, preserving verifiability without revealing the signer. While effective for privacy, complex cryptographic systems need to be modular structured for efficient implementation. Threshold structure-preserving signatures enable modular, privacy-friendly protocols. This work combines randomizable keys with threshold structure-preserving signatures to create a valid, modular, and unlinkable foundation for privacy-preserving applications
Error Covariance Analyses for Celestial Triangulation and Its Optimality: Improved Linear Optimal Sine Triangulation
No full textThis study presents an improved methodology for celestial triangulation optimization in spacecraft navigation, addressing limitations in existing approaches. While current methods like Linear Optimal Sine Triangulation (LOST) provide statistically optimal solutions for position estimation using multiple celestial body observations, their performance can be compromised by suboptimal measurement pair selection. The proposed approach, called the Improved-LOST algorithm, introduces a systematic method for evaluating and selecting optimal measurement pairs based on a Cramér–Rao Lower-Bound (CRLB) analysis. Through theoretical analysis and numerical simulations on translunar trajectories, this study demonstrates that geometric configuration significantly influences position estimation accuracy, with error variances varying by orders of magnitude depending on observation geometry. The improved algorithm outperforms conventional implementations, particularly in scenarios with challenging geometric configurations. Simulation results along a translunar trajectory using various celestial body combinations show that the systematic selection of measurement pairs based on CRLB minimization leads to enhanced estimation accuracy compared to arbitrary pair selection. The findings provide valuable insights for autonomous navigation system design and mission planning, offering a quantitative framework for assessing and optimizing celestial triangulation performance in deep space missions