Determining the Level of Understanding and Misconceptions of Science Teacher Candidates about the Concepts Related to Material and Its Properties

This study was carried out to determine the level of understanding and misconceptions of science teacher candidates about some concepts related to material and its properties. This research was carried out with 260 science teacher candidates in Science Teaching Education Program of Education Faculty of Necmettin Erbakan University in 2015-2016 academic year. There are 17 scientifically and logically true and false sentences in the questionnaire in order to determine the level of understanding of science teacher candidates about some concepts related to material and its properties. In addition, in order to measure the participation degree of candidate teachers, three options were offered; “I agree”, “I do not agree” and “I have no idea”. The data obtained from this 3-point Likert scale questionnaire were analyzed statistically. When the obtained data were evaluated, it was determined that teacher candidates had misconceptions about some concepts related to material and its properties, and some suggestions were made to eliminate these misconceptions. Keywords: Chemistry education, Misconception, Material and its properties, Level of understandin

THE EFFECTIVENESS OF POINT-OF-VIEW-VIDEO MODELING ON IMPROVING SOCIAL AND COMMUNICATION SKILLS

Autism spectrum disorder (ASD) is a complex neurobiological disorder with symptoms that affect individuals’ social interaction capabilities, their verbal and nonverbal communications, and the repertoires of activities and interest. These deficits in social and communication skills directly or indirectly influence the individual with ASDs’ lives. Therefore, many interventions have been developed to increase social and communication skills for individuals with ASD. Video modeling (VM) is one of the effective interventions in teaching social communication skills for children with ASD. There are multiple variations of VM interventions. One of the forms of VM intervention is point-of-view video modeling (POVVM) that has been potential to address the deficits of social communication skills and improve these skills for children with ASD. In this intervention, videos are filmed from the perspectives of the person who is the target of the intervention. The camera angle is presented with activity, skill, or context. The POVVM directly presents relevant stimuli and eliminates irrelevant stimuli of the target behavior. Thus, the POVVM intervention has provided a clear frame of imitating the behavior. The current study investigated the effectiveness of point-of-view video modeling on improving social initiation skills for young children with ASD. Three preschool-age children with ASD were implemented multiple-baseline across participants design to improve social initiation skills using point-of-view video modeling intervention. Specifically, the participants were taught greetings and engaging play activity behaviors using POVVM intervention. All participants improved their greetings and engaging play activity behaviors. The result of the study showed that POVVM is an effective intervention for improving social initiation skills. Consideration for interpretation and recommendations for future research are discussed

Nano nikel metali ile aromatik nitro bileşiklerin indirgenmesi

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Nitro gruplarının NaBH4 ve geçiş metalleri ile indirgenmesiyle aromatik aminlerin eldesi çok yaygın olarak kullanılan bir yöntemdir. 1960 yılından bu yana hızlı ve yüksek verim sağlayarak sonuç veren birçok katalizör geliştirilmiştir. Günümüzde ise yüksek etkinlik sağlayan geçiş metallerinin kullanıldığı indirgeme reaksiyonları için hazırlanan katalizörler geliştirilmeye devam etmektedir. Bu amaçla hazırlanan katalizörlerin düşük katalitik yükleme, katalizörü yeniden kullanabilme ve uygun maliyetli olma özelliklerinin sağlanması başlıca hedeftir. Ayrıca, sunulacak yöntemin çevre dostu olması da oldukça önemlidir. Bu çalışmada, nano-Nikel partikülleri hazırlanarak, nitro indirgeme reaksiyonlarında EtOH/H2O ortamında NaBH4'ü etkinleştirecek katalizör olarak kullanıldı. Geliştirilen yöntemin uygulanabilirliği 16 farklı substituent taşıyan aromatik nitro bileşiğinde başarıyla denendi.Receiving aromatic amines by reducing nitro groups with NaBH4 and transition metals is a very commonly used method. Since the 1960s, many of catalysts have been developed which present fastly and high yield in mild conditions. Nowadays, the catalysts prepared for the reduction reactions using transition metals proving high activity are still under devolopment. The main objective is to ensure that the catalysts prepared for this purpose are capable of low catalytic loading, re-use of the catalyst and cost-effective properties. In addition, it is quite important that the method to be presented should be environmentally friendly. In this study, nano-nickel particles were prepared and used as catalyst to activate NaBH4 in nitro reduction reactions in EtOH / H2O medium. The scope of the developed method was successfully tested in 16 different aromatic nitro compounds bearing different substituents

Combined 5x2cv FF-Test for Comparing Supervised Classification Learning Algorithms

Dietterich (1998) reviews five statistical tests proposing the 5x2cv t test for determining whether there is a significant difference between the error rates of two classifiers. In our experiments, we noticed that the 5x2cv t test result may vary depending on factors that should not affect the test and we propose a variant, the combined 5x2cv F test, that combines multiple statistics to get a more robust test. Simulation results show that this combined version of the test has lower Type I error and higher power than 5x2cv proper

Support Vector Machine for Multiclass Classification

Support vector machines (SVMs) are primarily designed for 2-class classification problems. Although in several papers it is mentioned that the combination of $K$ SVMs can be used to solve a $K$-class classification problem, such a procedure requires some care. In this paper, the scaling problem of different SVMs is highlighted. Various normalization methods are proposed to cope with this problem and their efficiencies are measured empirically. This simple way of using SVMs to learn a $K$-class classification problem consists in choosing the maximum applied to the outputs of $K$ SVMs solving a \textit{one-per-class} decomposition of the general problem. In the second part of this paper, more sophisticated techniques are suggested. On the one hand, a stacking of the $K$ SVMs with other classification techniques is proposed. On the other end, the \textit{one-per-class} decomposition scheme is replaced by more elaborated schemes based on error-correcting codes. An incremental algorithm for the elaboration of pertinent decomposition schemes is mentioned, which exploits the properties of SVMs for an efficient computation

Combining Linear Dichomotizers to Construct Nonlinear Polychotomizers

A polychotomizer which assigns the input to one of $K, K \ge 3$, is constructed using a set of dichotomizers which assign the input to one of two classes. We propose techniques to construct a set of linear dichotomizers whose combined decision forms a nonlinear polychotomizer, to extract structure from data. One way is using error-correcting output codes (ECOC). We propose to incorporate soft weight sharing in training a multilayer perceptron (MLP) to force the second layer weights to a bimodal distribution to be able to interpret them as the decomposition matrix of classes in terms of dichotomizers. This technique can also be used to finetune a set of dichotomizers already generated, for example using ECOC; in such a case, ECOC defines the target values for hidden units in an MLP, facilitating training. Simulation results on eight datasets indicate that compared with a linear one-per-class polychotomizer, pairwise linear dichotomizers and ECOC-based linear dichotomizers, this method generates more accurate classifiers. We also propose and test a method of incremental construction whereby the required number of dichotomizers is determined automatically as opposed to assumed a priori

Graphene-based hybrid for enantioselective sensing applications

Chirality is a major field of research of chemical biology and is essential in pharmacology. Accordingly, approaches for distinguishing between different chiral forms of a compound are of great interest. We report on an efficient and generic enantioselective sensor that is achieved by coupling reduced graphene oxide with γ-cyclodextrin (rGO/γ-CD). The enantioselective sensing capability of the resulting structure was operated in both electrical and optical mode for of tryptophan enantiomers (D-/L-Trp). In this sense, voltammetric and photoluminescence measurements were conducted and the experimental results were compared to molecular docking method. We gain insight into the occurring recognition mechanism with selectivity toward D- and L-Trp as shown in voltammetric, photoluminescence and molecular docking responses. As an enantioselective solid phase on an electrochemical transducer, thanks to the different dimensional interaction of enantiomers with hybrid material, a discrepancy occurs in the Gibbs free energy leading to a difference in oxidation peak potential as observed in electrochemical measurements. The optical sensing principle is based on the energy transfer phenomenon that occurs between photoexcited D-/L-Trp enantiomers and rGO/γ-CD giving rise to an enantioselective photoluminescence quenching due to the tendency of chiral enantiomers to form complexes with γ-CD in different molecular orientations as demonstrated by molecular docking studies. The approach, which is the first demonstration of applicability of molecular docking to show both enantioselective electrochemical and photoluminescence quenching capabilities of a graphene-related hybrid material, is truly new and may have broad interest in combination of experimental and computational methods for enantiosensing of chiral molecules