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The shape-from-shading (SFS) technique uses the pattern of shading in images in order to obtain 3D view information. By virtue of their ease of implementation, linearization-based SFS algorithms are frequently used in the literature. In this study, Fourier coefficients of central differences obtained from gray-level images are employed, and two basic linearization-based algorithms are combined. By using the functionally generated surfaces and 3D reconstruction datasets, the hybrid algorithm is compared with linearization-based approaches. Five different evaluation metrics are applied on recovered depth maps and the corresponding gray-level images. The results on defective sample surfaces are also included to show the effect of the algorithm on surface reconstruction. The proposed method can prevent erroneous estimates on object boundaries and produce satisfactory 3D reconstruction results in a low number of iterations.

The purpose of the present study was to examine the effect of individual and school average achievement on students' self-concept in science. The data of the last four Trends in International Mathematics and Science Study (TIMSS) cycles were used, and a two-stage individual data meta-analysis was conducted to examine the relationship between achievement and self-concept in science. In the first stage, multilevel structural equation modeling was performed for each dataset. Furthermore, the effect sizes were synthesized via meta-analysis with a three-level random-effect model. In addition, moderation analysis was conducted for the year, grade, and degree of stratification in countries. The results suggested a positive and significant effect of individual science achievement on the self-concept of students in science. On the other hand, the relation of the average school achievement was negative. The results were discussed by considering the big-fish-little-pond effect.

Artificial intelligence is a popular technology that affects many fields today. Its impact is noticeable daily, especially in education, design, and other essential areas. This technology, which stands out with the convenience it creates for users and its help in organizing the workflow, will play a critical role in our lives in the future. This study is aimed to touch upon the innovations provided by artificial intelligence in the field of education and some of its basic features. Some software, especially ChatGPT, is included based on the potential of language models and their essential usage areas. In addition, in the study, it is mentioned how artificial intelligence can be evaluated as a material in text and visual form, the essential functions of artificial intelligence technologies, which are rapidly changing today, are explained in this article, and stimulating points about the current situation are mentioned for those who will work in the field.

Objective. To identify those who develop pulmonary embolism with Ddimer levels by evaluating pulmonary CT angiographies of patients who are followed up with suspicion of coronavirus disease 2019 (COVID-19). Methods. Patients who were followed up in a community hospital with suspicion of COVID-19 and underwent Pulmonary CT angiography examination were evaluated. Clinical and demographic parameters and DDimer values for patients with and without pulmonary embolism were evaluated in the pulmonary CT angiogram. Results. During the COVID-19 pandemic, Thorax CT examination was performed in our center for suspicion or follow-up of COVID-19 infection in 3396 patients. Pulmonary CT angiography was applied to 312 (9.2%) of these cases. Of these 312 patients, 141 were identified as COVID-19 patients. Acute pulmonary embolism was detected in 33 (23.4%) of 141 patients with COVID-19 and pulmonary CT angiogram. D-dimer levels (5964.97±4036.8 μg/L) of patients with COVID-19 infection and pulmonary embolism were significantly higher than D-dimer levels (972.4±1766.8 μg/L) of patients without pulmonary embolism. In patients with COVID-19 infection, a Ddimer value higher than 1013 μg/L was determined as a cut-off value with 100% sensitivity for the presence of pulmonary embolism. Conclusions. For those struggling with the COVID-19 pandemic, pulmonary embolism should be kept in mind if D-dimer values increase more than expected in the presence of respiratory distress that Thorax CT findings cannot explain.

The research aims to analyse the most current (2015-2023) literature on STEM education to gain a deeper understanding of current trends, priorities and developments in the field of STEM education. Scientific studies determined within the scope of the study were examined using bibliometric and content analysis methods, which are among the systematic compilation methods. First, access to the WoS database was gained, and a subject-based search was conducted using the keywords "STEM education" and "Meta-analysis." In this context, 38 scientific studies containing these relevant keywords were found in the search. The collected data were initially analyzed on the basis of descriptive attributes in the WoS. Subsequently, the listed publications were analyzed using the bibliometric analysis tool VOSviewer for bibliographic attributes, including citation counts, co-citation, co-authorship, cooccurrence, and bibliographic coupling analysis types, based on authors, institutions, and countries. Finally, 18 articles from these scientific publications were evaluated through content analysis in terms of various characteristics of following the PRISMA flowchart. The most prominent keywords associated with the examined concepts included technology-related terms like "computer-based learning," "digital game-based learning," "academic achievement," "active learning," and "problem-centered instruction." Furthermore, the general focus of scientific studies appears to be on determining the impact of a STEM education method on student performance.

This study proposed a three-stage measurement model utilizing the Latent Growth Curve Modeling and Latent Class Growth Analysis. The measurement model was illustrated using repeated data collected through a four-week prospective study tracking the subjective well-being of volunteer college students (n=154). Firstly, several unconditional growth models were estimated to define the model, providing a better representation of individual growth trajectories. Secondly, several conditional growth models were formulated to test the usefulness of covariate variables hypothesized to explain observed variance in growth factors. Finally, latent class growth models were estimated to further explore different latent trajectory classes. Results showed that students' subjective well-being changed over time, and the rate of this change and its covariates were not constant for the entire sample. This study clearly illustrates how a longitudinal measurement approach can enhance the scope of findings and the depth of inferences when repeated measurements are available.

Background: In this study, the effects of olmesartan therapy on asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA), L-arginine and inducible nitric oxide synthase (iNOS) levels were investigated in patients undergoing cardiopulmonary bypass. Methods: Patients were randomly allocated to two groups, control and olmesartan. Olmesartan was administered 30 mg once a day beginning from preoperative day 5 to postoperative day 28 and on operation day. Blood was drawn from all patients and ADMA, SDMA, L-arginine and iNOS levels were analyzed at six time points (T1: before anesthesia induction, T2: during cardiopulmonary bypass, T3: five min after the cross-clamp was removed, T4: after protamine infusion, T5: on postoperative day 3 and T6: on postoperative day 28). Results: In the olmesartan treated group, iNOS levels exhibited significant decreases at T2, T3, T4, T5 and T6 time points compared with control group (p< 0.001, p< 0.05, p< 0.001, p< 0.01, p< 0.05 respectively). ADMA levels were significantly lower in olmesartan treated group than in control group at T3, T4, T5 and T6 time points (p< 0.05, p< 0.05, p< 0.05, p

The aim of this study was to investigate the effect of design-based STEM activities developed by prospective secondary school maths teachers on their problem-solving skills and scientific creativity. An explanatory sequential mixed methods design was used in the current study, involving 45 senior students (i.e., prospective secondary school maths teachers) studying at a state university in the West Black Sea Region, Turkey during the academic year 2018/19. The participants were selected according to a purposive sampling method to be involved in our study, which was conducted during a course named "Science, Technology, and Society," and the implementation stage, of which took a total of 14 weeks, as three course hours per week. The "Problem Solving Inventory" (PSI) and "Scientific Creativity Test" (SCT) were used for the purpose of obtaining the quantitative data of the research, whereas interviews were conducted with the prospective teachers for collecting the qualitative data. The quantitative data were analyzed using a dependent t-test, while qualitative data was analyzed by descriptive analysis. A slight increase was detected in participants' problem-solving skills in relation to developing STEM activities, though not statistically significant. However, as a result of the implementation process, the scientific creativity of prospective teachers turned out to increase in such a way that it indicated a statistically significant difference.

Knowing a foreign language has become one of the most necessary tools in politics, economy, social life and the use of technology. Around 90% of secondary school students learn English first, whether it is compulsory or not. In 2018, the Council of Higher Education (YÖK) reconsidered the curricula of the faculties of education. With this innovation, the necessity of "language teaching to keep up with the world" was emphasized. The lack of a planning process that meets the European criteria and meets the desired requirements in the planning of foreign language education makes an effective language learning process impossible. The European Language Portfolio (ELP) was developed by the Council of Europe in Strasbourg from 1998 to 2000. The European Language Portfolio (ELP) is an assessment used in foreign language teaching across Europe to support and record language learning. The document contains a guideline by which students can define their language proficiency. The method of this study, which was carried out with the data collection method with the qualitative research design, is phenomenology. The questions to be asked to the participants by the second researcher of the study were prepared by taking expert opinion and the final version was created by making a preliminary application. In this study, it was aimed to examine the compatibility between the "English Curriculum" and the "European Language Portfolio" implemented in schools. It is aimed to make an evaluation within the scope of foreign language policies regarding the use of foreign languages.

Learning approaches refer to the differentiation in the purpose that students consider and the activities they choose to perform a particular learning task. Many studies have been carried out at university level, in various grade levels and fields, in order to determine the learning approaches of students and to enable them to learn to learn by enabling them to gain effective learning approaches in the light of these determinations. In this study, it was aimed to determine the learning approaches of biology teacher candidates. The study group of the research consists of 12 teacher candidates studying in the 2nd, 3rd, and 4th grades of Gazi Education Faculty, Department of Mathematics and Science Education, Biology Education Department in the fall semester of the 2022-2023 academic year. The teacher candidates were selected to be 12 teacher candidates from each grade level and 9 of the candidates were girls and 3 were boys. This study is a qualitative research and the data of the research were obtained by using a semi-structured interview form consisting of 5 questions developed by the researchers. In the analysis of the data, content analysis was used in qualitative data analysis methods. When the statements of the teacher candidates were examined, the results of the research showed that one of the learning objectives of the teacher candidates was the sense of curiosity and they aimed to improve themselves in the process based on learning. The results obtained as a result of the research indicate that some of the teacher candidates aim to get high grades, organize their studies, plan their time consciously and avoid memorization. [The publication year (2022) shown on the PDF is incorrect. The correct publication year is 2023.]

Latent Class and Latent Profile Models are widely used in psychological assessment settings, especially when individual differences are suspected to be related to unobserved class memberships, such as different personality types. This paper provides an easy-to-follow introduction and application of the methodology to the data collected as part of more extensive educational research investigating social-emotional competency profiles of preservice teachers (n=184) who responded to an Emotional Awareness Questionnaire. Suspected that there would be two or more latent emotional awareness sub-groups in the sample, a series of latent profile models was estimated. The results suggested three distinct emotional awareness profiles; namely, introverted, extroverted, and less sensitive to others' emotions, with proportions of 9%, 56%, and 35%, respectively. Subsequent analyses showed that preservice teachers with higher levels of emotionality, sociability, and well-being were more likely to be in the extroverted profile. The findings suggest that nearly half of the teachers in the sample could be expected to possess the most professionally desirable teacher profile. Nonetheless, it was noted that if timely diagnostic and tailored training or intervention programs were available, at least some of the preservice teachers in the less sensitive to others' profiles, and most of the preservice teachers in the introverted profile could be helped to self-observe the way which they tend to identify and regulate their emotions.

Purpose: This study aims to develop and validate a scale to determine university students' attitudes toward assessment and evaluation in online exams. Background: Measuring students' attitudes toward online exams is crucial, especially in the context of emergency transitions to online learning and the impact of external factors such as the COVID-19 pandemic. Students' perspectives on online examination practices in higher education institutions are significant in understanding students' attitudes and perceptions of online exams for effective implementation. Method: During the developmental phase of the scale, 13 items were created and presented for expert opinion. The scale propositions are designed to question the compliance of the courses with the curricula in the online education process, the transparency of online exams, and the University's technological infrastructure for online exams. The participants in the study consist of 1095 students studying in different programs at the Vocational Schools of three foundation universities in Istanbul, and they were reached via e-mail. Explanatory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were conducted. Findings: The results obtained prove that the 13-question scale is valid and reliable and is a good measurement to determine university students' attitudes to online exams. Implications for Research and Practice: Attitudes are likely determinants of academic achievement. Furthermore, utilizing e-tests positively impacts higher education students' performance and participation in online testing. Therefore, it is essential to consider students' attitudes towards online exams to increase academic success in online courses and provide better learning outcomes. Thus, scale development plays a pivotal role in advancing knowledge within specific domains of social science research, and it is integral to ensuring the quality and reliability of online exam instruments used in higher education.