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The aim in this study was to determine the effectiveness of STEM-based robotic coding education for primary school students in terms of their decision-making skills. Mixed method research was conducted. Pretest-posttest control group designs were used in the quantitative phase, and a case study was performed in the qualitative phase of the research. The study sample consisted of 65 third graders. Pretesting of the experimental and control group students was performed using the decision-making skills scale. STEM-based robotic coding training was given to the experimental group for 6 weeks. Afterwards, the decision-making skills scale was applied as a posttest to both the experimental and control groups. The quantitative data were analyzed with paired and independent samples t-tests. A statistically significant increase was observed in the experimental group students' decision-making skills in favor of the posttest. There was no significant difference between the pre- and posttest scores of the control group students. An interview with 15 experimental group students was conducted to collect qualitative data, and the interview results were analyzed using content analysis. The robotic coding education positively affected the students' decision-making and problem-solving skills and their willingness to share ideas.

The focus of this research was to investigate how school administrators in Turkey managed the crises caused by the COVID-19 outbreak, which was a deadly threat for humanity worldwide. The research questions guiding this study are: (1) Did schools have a crisis plan? (2) If yes, how was the plan implemented in a crisis situation?; (3) What kind of changes were made in the plans?; (4) What should administrators do in such crisis situations?; and (5) What was done in the COVID-19 outbreak? The research was conducted as a qualitative case study which involved 105 school administrators. Due to the pandemic conditions that hindered direct face-to-face interviews and interactions, data collection was carried out online via a Google drive form with open-ended questions. The findings demonstrated that there were two main headings as the basis for the research problems. The first was the existence of crisis planning by school administrators; the other was the status of implementation of these plans. Finally, how school administrators handled crisis management was pointed out.

This study aimed to examine the awareness of teacher candidates towards inclusive education. This mixed method study was performed with the convergent parallel mixed pattern. The sample of quantitative part of the study consisted of 708 teacher candidates in an education faculty determined by criterion sampling. The study group of the qualitative part of the research is 14 teacher candidates (preservice teachers) selected from among these participants. The research data were collected with Awareness Scale for Inclusive Education and Interview Form for Evaluation of Inclusive Education Course. The scale data were analyzed by descriptive and inferential statistics, and the semi-structured interview data were analyzed by content analysis. The results revealed that the awareness of teacher candidates' inclusive education was at a moderate level. In addition, the awareness level of the participants who had inclusive education training was higher than the participants who did not, and the female participants had higher awareness compared to the male participants. The interview results revealed that training on inclusive education increased teacher candidates' awareness of its history, aims, the students it encompasses, and its applications. According to the results of the research, it has been suggested to expand the inclusive education provided to teachers before and during the service.

Previous studies have presented discrepant findings of e-stories' contribution to children's narrative comprehension, which can be attributed to not only the variation of multimedia features among studies but also to learner and text features. The main goal of the present study was to expand understanding of the effect of e-stories on children's narrative skills and reading attitudes for poor and good story comprehenders. A quasi-experimental factorial design was employed to explore the effect of book type and group level on children's narrative skills and reading attitudes. The participating children were pre-readers. The printed version of The Red Winged Owl was read aloud to small groups of 4-5 children. Participants included 41 good and 40 poor comprehenders (age range 59-68 months) who were identified based on narrative comprehension scores. The experimental group was exposed to four e-stories on an iPad, while the control group listened to readings of the printed versions of the same storybooks. Data were collected by administering pre- and post-tests and the preschool reading attitudes scale and by asking narrative comprehension questions. Children's retellings were audio-recorded. The findings revealed that: (a) the poor and good comprehender groups had higher narrative comprehension in the short text e-story condition; (b) there was a significant interaction effect for the narrative comprehension of poor and good comprehenders in longer texts; and (c) children's post-reading attitude scores did not differ by group level.

This research aims to examine the effect of semantic encoding strategy instruction on students' near and far transfer performances in e-learning environments. The research was performed by experimental design. Dependent variables of the research were near and far transfer performances. Independent variable was strategy instruction on encoding. Also recalling performance was included in the research as a control variable. Research data were gathered with a transfer test containing 18 multiple-choice items. The experimental study was performed with 67 students with a medium level of recalling performance. The students were randomly assigned to experimental group I (strategy instruction+integrated content), experimental group II (strategy intruction+non-integrated content), and control group (non-integrated content). The results of this research indicated that encoding strategy instruction is essential for the transfer of learning in e-learning environments. However, it is more effective when e-learning design is integrated with encoding strategies. Therefore, it is suggested that semantic encoding strategies should be integrated into the content when designing elearning environments.

The research explores the effect of STEM and STEM-based robotic activities on the development of students' perceptions of mental risk-taking and its predictors and their perceptions of inquiry learning skills related to science. A mixed method was applied in the research. Its sample consisted of 35 students in a high school of the Ministry of National Education in a medium-scale province of the Eastern Anatolia Region between the 2017-2018 educational year. The Scale for Perceptions of Mental Risk-taking in Science Learning and Its Predictors (SPMRSLIP) and the Scale for Perception of Inquiry Learning Skills for Science (SPILSS) were applied to obtain the quantitative data in the research. In addition, the focus group interview was held. The STEM and STEM-based robotic activities have been performed with the students for 14 weeks. In the findings obtained at the end of the research, no significant difference was determined between the perception pre-test and post-test scores related to mental risk-taking and its predictors in science learning. However, difference was found in the dimension of interest. It was found that there was a significant difference between the pre-test and post-test scores in the inquiry learning skills perception scale for science and the qualitative findings also supported this result. According to the results, it can be recommended that STEM and Robotic educations should be given in other grades.

This study aims to create a rubric based on the pedagogical properties of educational robots for pre-school students and determine the compliance level with educational robot sets. In this sense, the study is considered a first and significant step toward selecting robots based on pedagogical-driven factors. For this aim, a mixed-method research design was employed. A qualitative method was used to create the rubric items, and the rubric development was also supported through a quantitative process by including expert opinions and ensuring content validity. Furthermore, a descriptive survey model, one of the quantitative designs, was used to examine the suitability of educational robots for the pre-school education level. As an outcome of this study, a rubric of four dimensions with 28 items related to the pedagogical features of educational robots in pre-school was created. Furthermore, widely used educational robots at the pre-school level, such as Kidoboto, Lego Wedo, Mbot, Lego Spike, Lego Ev3, and Matatalab, were evaluated by experts using the created rubric.

Innovative activities carried out during school laboratory sessions include 'flipped learning' (FL), which is an interactive learning environment where the teacher guides students learn individually. This study examined the impact of the adoption of the FL approach on the academic performance of 2nd year science student teachers enrolled in the course General Chemistry Laboratory -- III and on their opinions related with the course. Eighty-one student teachers acted as a control group i.e., followed the conventional course approach while 85 students participated in the experimental groups following the FL approach. Data collection tools were examination scripts and semi-structured interview questions. A significant difference was found in academic performance in favor of the experimental group. Besides, it was observed that the FL approach increased students' motivation, encouraged them to take responsibility for their own learning, and enabled more meaningful learning to take place. It is recommended for more practical lessons be designed with this approach and for more research to be conducted on the impact of this approach on learning motivation and self-efficacy of students as well as their academic performance.

The aim of this study is to examine the ability of pre-service mathematics teachers to detect errors made in solving questions about matrices. The study particularly focused on revealing the internalization of the teachings such as the meanings and relational dimensions of concepts and operations about matrix. The study was conducted with 26 teacher candidates at a university in the Eastern Anatolia Region. They were given a written exam, and their responses were analyzed by two field experts. The results showed that the pre-service teachers did not fully understand the concepts and operations of matrices. They made a variety of errors, including misconceptions and incomplete understanding. They were also not very good at solving proof-based questions. However, they were more successful at solving problems that were based on plain logic or could be solved using rules.

With this study we aimed to evaluate the effectiveness of a collaborative and reflective school-based training model on the teachers' professional transformation in a middle school in Turkey. This study emerged as a result of a need for this school to transform its instructional approach to the understanding by design (UbD) approach. Considering the needs of teachers for instructional design, a 1-year training programme was planned. Thirteen teachers from different subject fields in the school participated in this case study. The teachers prepared 4 UbD plans collaboratively under the coaching of the researchers, implemented them in the class, and participated in the reflection meetings after each implementation. While evaluation of plans showed their progress, focus-group interviews revealed that this training had changed the teachers' instructional approach and developed their design skills. Additionally, even though there were some challenging issues such as intense workloads, time constraints, coordination problems, the teachers generally emphasised the contributions of studying UbD to their peer collaboration, classroom practices, and their students' understanding and learning. We concluded that not only this collaborative and reflective training model but also the UbD itself had positive effects on teachers' professional transformation.

INTRODUCTION: Central precocious puberty (CPP) is treated with long-acting gonadotropin releasing hormone (GnRH) analogues (GnRHa). Some adult patients undergoing GnRHa treatment experienced prolonged QT syndrome, which is associated with an increased risk of serious cardiac events, such as myocardial infarction, stroke, arrhythmias, and sudden cardiac death. METHODS: Seventy-four patients, aged between 5 and 11 years and diagnosed with CPP but with no other concomitant disease or medication use, underwent electrocardiogram (ECG) assessment. They had been receiving 3.75 mg leuprolide acetate (Lucrin® Depot) injections every 28 days for at least three months. RESULTS: The ECGs of all patients showed a corrected QT (QTc) interval within normal limits, consistent with the data for healthy Turkish children of the same age and gender. No other pathological physical examination or ECG findings were observed. Furthermore, there was no significant difference in QTc interval when adjusted for age, anthropometric data, or the duration or cumulative dose of the treatment. DISCUSSION AND CONCLUSION: The study found no correlation between QTc interval values and age, treatment duration, total cumulative dose, and anthropometric data. These findings suggest that cardiovascular adverse events associated with GnRHa treatment may be related to age and other underlying physiopathological conditions in adults rather than being directly due to the drug.

Abstract Cellular target engagement technologies enable quantification of intracellular drug binding; however, simultaneous assessment of drug-associated phenotypes has proven challenging. Here, we present cellular target engagement by accumulation of mutant as a platform that can concomitantly evaluate drug-target interactions and phenotypic responses using conditionally stabilized drug biosensors. We observe that drug-responsive proteotypes are prevalent among reported mutants of known drug targets. Compatible mutants appear to follow structural and biophysical logic that permits intra-protein and paralogous expansion of the biosensor pool. We then apply our method to uncouple target engagement from divergent cellular activities of MutT homolog 1 (MTH1) inhibitors, dissect Nudix hydrolase 15 (NUDT15)-associated thiopurine metabolism with the R139C pharmacogenetic variant, and profile the dynamics of poly(ADP-ribose) polymerase 1/2 (PARP1/2) binding and DNA trapping by PARP inhibitors (PARPi). Further, PARP1-derived biosensors facilitated high-throughput screening for PARP1 binders, as well as multimodal ex vivo analysis and non-invasive tracking of PARPi binding in live animals. This approach can facilitate holistic assessment of drug-target engagement by bridging drug binding events and their biological consequences.

Abstract Background Academic procrastination (AP), a common behavior among students, is influenced by factors such as fear of failure, task aversiveness, anxiety, and stress. Self-generated stress (SGS) refers to the subjective experience of tension that occurs in response to an existing situation. Individuals often overestimate the difficulty and attainability of a task, resulting in increased stress and extended stress duration. SGS can worsen mental and physical health problems, including bruxism. Therefore, this study investigates the possible underlying connections by examining the relationship between AP, SGS, and self-reported (SR) bruxism in medical and dental students. Methods The present cross-sectional study was undertaken among a sample of 379 students pursuing medical and dentistry degrees in Turkey. The questionnaire, including the Academic Procrastination Scale-Short Form, SR bruxism Scale, and SGS Scale, was administered to the students. According to the responses given to the SR bruxism Scale, 3 types of SR bruxism groups were created as sleep, awake, and compound. A comparative analysis was conducted on AP, SGS, and SR bruxism among medical and dental students. Furthermore, the associations among AP, SGS, and SR bruxism were assessed using the utilization of correlation tables and regression analysis. Results The prevalence of awake bruxism was higher among dental students (46.6%) compared to medical students (34.7%), suggesting a faculty-dependent trend. A significant positive correlation was observed between SGS and AP (r = 0.212, p

Abstract Background Maxillofacial complex automated segmentation could alternative traditional segmentation methods to increase the effectiveness of virtual workloads. The use of DL systems in the detection of maxillary sinus and pathologies will both facilitate the work of physicians and be a support mechanism before the planned surgeries. Objective The aim was to use a modified You Only Look Oncev5x (YOLOv5x) architecture with transfer learning capabilities to segment both maxillary sinuses and maxillary sinus diseases on Cone-Beam Computed Tomographic (CBCT) images. Methods Data set consists of 307 anonymised CBCT images of patients (173 women and 134 males) obtained from the radiology archive of the Department of Oral and Maxillofacial Radiology. Bilateral maxillary sinuses CBCT scans were used to identify mucous retention cysts (MRC), mucosal thickenings (MT), total and partial opacifications, and healthy maxillary sinuses without any radiological features. Results Recall, precision and F1 score values for total maxillary sinus segmentation were 1, 0.985 and 0.992, respectively; 1, 0.931 and 0.964 for healthy maxillary sinus segmentation; 0.858, 0.923 and 0.889 for MT segmentation; 0.977, 0.877 and 0.924 for MRC segmentation; 1, 0.942 and 0.970 for sinusitis segmentation. Conclusion This study demonstrates that maxillary sinuses can be segmented, and maxillary sinus diseases can be accurately detected using the AI model.

Abstract Background Sarcopenia is an age‐related muscle disease that increases the risk of falls, disabilities, and death. It is associated with increased muscle protein degradation driven by molecular signalling pathways including Akt and FOXO1. This study aims to identify genes, gene interactions, and molecular pathways and processes associated with muscle aging and exercise in older adults that remained undiscovered until now leveraging on an artificial intelligence approach called artificial neural network inference (ANNi). Methods Four datasets reporting the profile of muscle transcriptome obtained by RNA‐seq of young (21–43 years) and older adults (63–79 years) were selected and retrieved from the Gene Expression Omnibus (GEO) data repository. Two datasets contained the transcriptome profiles associated to muscle aging and two the transcriptome linked to resistant exercise in older adults, the latter before and after 6 months of exercise training. Each dataset was individually analysed by ANNi based on a swarm neural network approach integrated into a deep learning model (Intelligent Omics). This allowed us to identify top 200 genes influencing (drivers) or being influenced (targets) by aging or exercise and the strongest interactions between such genes. Downstream gene ontology (GO) analysis of these 200 genes was performed using Metacore (Clarivate™) and the open‐source software, Metascape. To confirm the differential expression of the genes showing the strongest interactions, real‐time quantitative PCR (RT‐qPCR) was employed on human muscle biopsies obtained from eight young (25 ± 4 years) and eight older men (78 ± 7.6 years), partaking in a 6‐month resistance exercise training programme. Results CHAD, ZDBF2, USP54, and JAK2 were identified as the genes with the strongest interactions predicting aging, while SCFD1, KDM5D, EIF4A2, and NIPAL3 were the main interacting genes associated with long‐term exercise in older adults. RT‐qPCR confirmed significant upregulation of USP54 (P = 0.005), CHAD (P = 0.03), and ZDBF2 (P = 0.008) in the aging muscle, while exercise‐related genes were not differentially expressed (EIF4A2 P = 0.99, NIPAL3 P = 0.94, SCFD1 P = 0.94, and KDM5D P = 0.64). GO analysis related to skeletal muscle aging suggests enrichment of pathways linked to bone development (adj P‐value 0.006), immune response (adj P‐value

In the study, we compared the effectiveness and efficiency of two error correction (EC) procedures --a model of the correct response (MoCR) and remove and re-present (RRp)--when using discrete trial training (DTT) in teaching to identify the community signs to children with autism spectrum disorder. We also examined the maintenance and generalization effects on children's behaviours and the preferences of neurotypical peers about the EC procedures. Four children participated in the study. We used an adapted alternating treatments design. The findings demonstrated that MoCR and RRp did not differ significantly in terms of their effectiveness, although DTT with MoCR was more efficient than DTT with RRp for all participants. Moreover, the findings revealed that all participants had maintained the behaviours, while three of the four participants were able to generalize. The neurotypical peers had a more definite preference for MoCR over RRp. Implications for future research were discussed.

Debugging is an intellectually rich and a challenging process when learning a programming language. This process is important for increasing the quality of the program and making it functional. Debugging, by its nature, is thought to be a practice with a state of focus and concentration. This study explored whether the debugging performance could be predicted by attention networks of students studying at the IT department of vocational high schools. 108 vocational high school IT department students participated in the research. First, students' attention levels were determined by utilizing the Attention Network Test. Second, a Debugging Performance Test was administered to determine their debugging performance. The analysis result indicated that the general attention network statistically predicted the debugging performance but the effect size was found to be small. Furthermore, the singular and dual interactions of the alerting attention network, the orienting attention network, and the executive attention network did not predict debugging performances. Yet, the interactions of the three attention networks on predicting the debugging performances were found to be statistically significant. These findings were discussed together with the existing studies in the literature and suggestions to obtain more in-depth information regarding these results were provoked.

The teacher must, first of all, have a good knowledge of mathematics to detect the errors in the student's mathematical knowledge and to identify the general situation in the classroom. This depends on the mathematical knowledge gained in the teacher training schools. General mathematics topics occupying an important place in the departments of mathematics and science education form the basis for a better understanding and comprehension of subsequent mathematics and science topics (Gökçek & Açikyildiz, 2015). In this study, approaches of teacher candidates to errors in the questions on limits, derivatives, integrals, and asymptotes were determined as the case of the research. Perspectives regarding this case were examined in detail in line with the candidates' answers to the questions "what, how, why" and presented to the reader (Yin, 1984). Participants of the study consisted of sixty first-year students studying in the Department of Science Education of a university in Central Anatolia. In the research, a knowledge test consisting of six open-ended questions was used as the data collection tool.