Türk ve Azeri Öğretmen Adaylarında Çevre Bilinci

One of the main aims of this study is to increase the environmental consciousness of university students while looking into whether there is a difference in their perspectives about environmentalconsciousness between the Turk and Azeri university students. There were 593 students in Ankaraand 231 in Baku. The survey used in the investigation consisted of behaviours, knowledge andattitudes. The Cronbach’s alpha value of the scale applied in Ankara is .97, while the Baku’s is .84.Differences are found in favour of Turkish students. While there is no gender difference in Azeristudents, differences found in favour of males among the group Turkish students. The consciousnessabout environment of Azeri students is about home plants while it is about to the problems seen inenvironment and conversations about these problems, the news in media about the environmentalproblems and the home pets in Turk students. Another interesting result is that knowledge and thebehaviours of Azeri students about environmental issue do not have any positive effect on theirenvironmental attitudes. To analyze the data, t test, co-relation and multiple regression are used.Bu araştırmanın temel amaçlarından birisi, üniversite gençliğinin çevre bilincini tespit etmek,ikincisi ise Türk ve Azerbaycan üniversite gençliğinin çevre bilinçleri arasında farkların bulunupbulunmadığına bakmaktır. Araştırma, Ankara ve Bakû’de okuyan üniversite öğrencileriyleyapılmıştır. Ankara’da 593, Bakû’de ise 231 öğrenci araştırma kapsamında yer almıştır. Araştırmadakullanılan anket; tutumları, bilgiyi ve davranışları içermektedir. Ankara’da uygulanan anketinCronbach α değeri α =.97, Bakû’de uygulanan anketin Cronbach α değeri ise α =.84’tür. İki ülkeöğrencilerinin verdiği cevapların karşılaştırılması sonucunda Türkiye’de yaşayan öğrencilerinlehine anlamlı fark bulunmuştur. Azerilerdeki grupta cinsiyet farkına rastlanmaz iken Türkiye’dekigrubun tutumlarında, bilgilerinde ve davranışlarında erkekler lehine anlamlı farklar bulunmuştur.Ayrıca Azeri öğrencilerin çevre bilinçlerini evdeki bitkilerle ilgilenmeleri, Türk öğrencilerin çevrebilinçlerini ise evde ve arkadaşlarıyla çevre sorunlarından konuşmaları, çevre sorunlarıyla ilgiligazetelerde çıkan haberler ve evdeki hayvanlarla ilgilenmeleri etkilemektedir. Bir başka ilginç sonuçise Azerbaycan’daki öğrencilerin çevre bilgilerinin ve tutumlarının çevre dostu davranışlar üzerinebir etkisinin olmadığıdır. Verilerin analizinde t-testi, korelasyon ve çoklu regresyon hesaplamalarıyapılmıştır. Ayrıca anketin güvenirliğine bakılmış ve faktör analizi yapılmıştır

Teacher Candidates’ Views on the Zero Waste Project

This case study was carried out to determine the opinions of prospective science teachers about zero waste project. The study group of the research consists of 67 prospective teachers studying in the science education department at one university in Konya, Turkey. When the research results are examined, it is seen that the awareness of the science teacher candidates about the purpose and scope of the zero waste project is not sufficient. Most of the teacher candidates experience a lack of information about the zero waste project. The teacher candidates, who stated that they did not participate in any scientific activity related to the zero waste project, do not believe that this project has achieved its purpose. The results of the research show that informing about the zero waste project is not enough, many teacher candidates will graduate without having sufficient awareness. As researchers, we think that information about the scope, purpose and implementation steps of the zero waste project should be included more in education curricula, TV programs and scientific activities.</p

Phylogenetic analysis of modularity in protein interaction networks

<p>Abstract</p> <p>Background</p> <p>In systems biology, comparative analyses of molecular interactions across diverse species indicate that conservation and divergence of networks can be used to understand functional evolution from a systems perspective. A key characteristic of these networks is their modularity, which contributes significantly to their robustness, as well as adaptability. Consequently, analysis of modular network structures from a phylogenetic perspective may be useful in understanding the emergence, conservation, and diversification of functional modularity.</p> <p>Results</p> <p>In this paper, we propose a phylogenetic framework for analyzing network modules, with applications that extend well beyond network-based phylogeny reconstruction. Our approach is based on identification of modular network components from each network separately, followed by projection of these modules onto the networks of other species to compare different networks. Subsequently, we use the conservation of various modules in each network to assess the similarity between different networks. Compared to traditional methods that rely on topological comparisons, our approach has key advantages in (<it>i</it>) avoiding intractable graph comparison problems in comparative network analysis, (<it>ii</it>) accounting for noise and missing data through flexible treatment of network conservation, and (<it>iii</it>) providing insights on the evolution of biological systems through investigation of the evolutionary trajectories of network modules. We test our method, M<smcaps>OPHY</smcaps>, on synthetic data generated by simulation of network evolution, as well as existing protein-protein interaction data for seven diverse species. Comprehensive experimental results show that M<smcaps>OPHY</smcaps> is promising in reconstructing evolutionary histories of extant networks based on conservation of modularity, it is highly robust to noise, and outperforms existing methods that quantify network similarity in terms of conservation of network topology.</p> <p>Conclusion</p> <p>These results establish modularity and network proximity as useful features in comparative network analysis and motivate detailed studies of the evolutionary histories of network modules.</p

Influence of scientific stories on students ideas about science and scientists

Abstract This study was conducted to determine whether a lesson, in which context-based learning approach and scientific stories were used, changed students&apos; (aged 11-12) stereotypical images of science and scientists. Data was collected from two separate sources: Interviews conducted with six students and Draw a Scientist Test (DAST) document that was given to 80 students (before and after the intervention). In the study, context-based learning approach with scientific stories was used as intervention after which a change in students&apos; ideas about science and scientists was observed. At the end of the study, changes were observed in various categories of stereotypical images of scientists, such as use laboratory tools (test tubes, glass bottles, magnifying glasses, chemicals, etc.), use of technological appliances (computers, microscopes, telescopes, machines, robots, etc.), scientists who study living things (plants, animals, humans), scientists who study inside a laboratory, scientists who study outdoors (nature, space, etc.). At the same time changes in students&apos; understanding of nature of science were observed. After the intervention, clues about student ideas such as, there is more than one scientific method, there is no single criteria for doing science, scientists use their imagination in their studies, and scientists&apos; studies are not limited to one field were observed. In the course of the study, student&apos;s ideas about science changed from a positivist philosophy toward a heuristic philosophy

DADA: Degree-Aware Algorithms for Network-Based Disease Gene Prioritization

<p>Abstract</p> <p>Background</p> <p>High-throughput molecular interaction data have been used effectively to prioritize candidate genes that are linked to a disease, based on the observation that the products of genes associated with similar diseases are likely to interact with each other heavily in a network of protein-protein interactions (PPIs). An important challenge for these applications, however, is the incomplete and noisy nature of PPI data. Information flow based methods alleviate these problems to a certain extent, by considering indirect interactions and multiplicity of paths.</p> <p>Results</p> <p>We demonstrate that existing methods are likely to favor highly connected genes, making prioritization sensitive to the skewed degree distribution of PPI networks, as well as ascertainment bias in available interaction and disease association data. Motivated by this observation, we propose several statistical adjustment methods to account for the degree distribution of known disease and candidate genes, using a PPI network with associated confidence scores for interactions. We show that the proposed methods can detect loosely connected disease genes that are missed by existing approaches, however, this improvement might come at the price of more false negatives for highly connected genes. Consequently, we develop a suite called D<smcaps>A</smcaps>D<smcaps>A</smcaps>, which includes different uniform prioritization methods that effectively integrate existing approaches with the proposed statistical adjustment strategies. Comprehensive experimental results on the Online Mendelian Inheritance in Man (OMIM) database show that D<smcaps>A</smcaps>D<smcaps>A</smcaps> outperforms existing methods in prioritizing candidate disease genes.</p> <p>Conclusions</p> <p>These results demonstrate the importance of employing accurate statistical models and associated adjustment methods in network-based disease gene prioritization, as well as other network-based functional inference applications. D<smcaps>A</smcaps>D<smcaps>A</smcaps> is implemented in Matlab and is freely available at <url>http://compbio.case.edu/dada/</url>.</p

MOBAS: identification of disease-associated protein subnetworks using modularity-based scoring

Network-based analyses are commonly used as powerful tools to interpret the findings of genome-wide association studies (GWAS) in a functional context. In particular, identification of disease-associated functional modules, i.e., highly connected protein-protein interaction (PPI) subnetworks with high aggregate disease association, are shown to be promising in uncovering the functional relationships among genes and proteins associated with diseases. An important issue in this regard is the scoring of subnetworks by integrating two quantities: disease association of individual gene products and network connectivity among proteins. Current scoring schemes either disregard the level of connectivity and focus on the aggregate disease association of connected proteins or use a linear combination of these two quantities. However, such scoring schemes may produce arbitrarily large subnetworks which are often not statistically significant or require tuning of parameters that are used to weigh the contributions of network connectivity and disease association. Here, we propose a parameter-free scoring scheme that aims to score subnetworks by assessing the disease association of interactions between pairs of gene products. We also incorporate the statistical significance of network connectivity and disease association into the scoring function. We test the proposed scoring scheme on a GWAS dataset for two complex diseases type II diabetes (T2D) and psoriasis (PS). Our results suggest that subnetworks identified by commonly used methods may fail tests of statistical significance after correction for multiple hypothesis testing. In contrast, the proposed scoring scheme yields highly significant subnetworks, which contain biologically relevant proteins that cannot be identified by analysis of genome-wide association data alone. We also show that the proposed scoring scheme identifies subnetworks that are reproducible across different cohorts, and it can robustly recover relevant subnetworks at lower sampling rates

An evaluation of science teacher canditates’ energy saving behavior ıntention based on the theory of planned behaviour

The aim of the study is to evaluate science teacher candidates’ behaviour of energy saving intention among sustainable behaviours within the frame of the Theory of Planned Behaviour. The study was conducted with 1947 teacher candidates studying in six geographical regions of Turkey (Central Anatolia Region, Black Sea Region, Aegean Region, Marmara Region, Mediterranean Region and Eastern Anatolia Region) in the spring semester of 2015-2016 academic year. Corelational survey model was used in the study. Within the scope of the research, the Energy Saving Scale (ESS) was developed in order to determine the factors and beliefs affecting the sustainable Behaviours of science teacher candidates, in pursuant of the Theory of Planned Behaviour and by taking into account the scale development steps. The Cronbach Alpha reliability coefficient of the dimensions of the Energy Saving Scale (N = 1947) varies between .918 and .952. The Cronbach Alpha reliability coefficient for the entire Energy Saving Scale is .944. The results of the research, indicated that science teacher candidates’ attitudes towards energy saving Behaviour are low and the "Subjective Norm" is effective in explaining the "Intention towards Behaviour " and the " Intention towards Behaviour " is most influenced by the factor of the "Perceived Behaviour al Control"