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Article Citation - Scopus: 1Analyzing Students' Academic Success in Pre-requisite Course Chains: A Case Study in Turkey(Tempus Publications, 2018) Karakaya, Murat; Eryilmaz, Meltem; Ceyhan, Ulas; Computer EngineeringThere are several principles which have been accepted as approaches to successful curriculum development. In spite of the differences in the proposed sequencing of topics, all approaches basically depend on the pre-requisite chains to implement their educational approach in the curriculum development for specifying the order of the subjects. In this research, two prerequisite chains representing two different curriculum development approaches are taken into consideration in a case study. The first research question considered is whether academic success in a follow-up course is positively related to success attained in the pre-requisite course. The second one is whether or not the selected curriculum development approach for deciding the chains has a significant impact on the academic success relationships between a pre-requisite and its follow-up course. To answer these questions, course data of 441 undergraduate students who graduated from the Atilim University between Fall 2001 and Spring 2015 semesters were collected and analyzed. The results indicate that the succes levels gained in a pre-requisite and its follow-up course are corelated. Moreover, different cirriculum development methods can affect this corelation. Thus, cirriculum developers should consider appropriate approaches to improve student success for deciding chaining courses and their contents.Article Citation - WoS: 1Citation - Scopus: 1Machine Vs. Deep Learning Comparision for Developing an International Sign Language Translator(Taylor & Francis Ltd, 2022) Eryilmaz, Meltem; Balkaya, Ecem; Ucan, Eylul; Turan, Gizem; Oral, Seden GulayThis study aims to enable deaf and hard-of-hearing people to communicate with other individuals who know and do not know sign language. The mobile application was developed for video classification by using MediaPipe Library in the study. While doing this, considering the problems that deaf and hearing loss individuals face in Turkey and abroad modelling and training stages were carried out with the English language option. With the real-time translation feature added to the study individuals were provided with instant communication. In this way, communication problems experienced by hearing-impaired individuals will be greatly reduced. Machine learning and Deep learning concepts were investigated in the study. Model creation and training stages were carried out using VGG16, OpenCV, Pandas, Keras, and Os libraries. Due to the low success rate in the model created using VGG16, the MediaPipe library was used in the formation and training stages of the model. The reason for this is that, thanks to the solutions available in the MediaPipe library, it can normalise the coordinates in 3D by marking the regions to be detected in the human body. Being able to extract the coordinates independently of the background and body type in the videos in the dataset increases the success rate of the model in the formation and training stages. As a result of an experiment, the accuracy rate of the deep learning model is 85% and the application can be easily integrated with different languages. It is concluded that deep learning model is more accure than machine learning one and the communication problem faced by hearing-impaired individuals in many countries can be reduced easily.Article Citation - WoS: 3Citation - Scopus: 3Online Learning Perceptions Amid Covid-19 Pandemic: the Engineering Undergraduates' Perspective(Tempus Publications, 2022) Eryilmaz, Meltem; Kalem, Guler; Kilic, Hurevren; Tirkes, Guzin; Topalli, Damla; Turhan, Cigdem; Yazici, Ali; Information Systems Engineering; Computer Engineering; Software EngineeringThe COVID-19 pandemic caused face-to-face education in just about all universities worldwide to shift to online education. For most students, this educational model was a compulsory first experience. In this study, the survey results are analyzed and discussed related to a group of students in the Engineering Faculty of a university in Turkey regarding their online education perceptions. Briefly summarized, the findings of the study indicate that: (a) most of the students still prefer face-to-face learning, which is also favored if accompanied by distance learning; (b) the concentration level of the students has dropped due to the concerns about the COVID-19 pandemic which affects their learning negatively; and (c) around half of the students participating in the study feel that the online exams conducted without a secure exam software, is considered unsafe. Additionally, the study's results were further extended to evaluate the questionnaire results and reported along with the suggestions of necessary actions in emergency online learning (EOL).Article Citation - WoS: 1The Evaluation of Students' Academic Achievements in Adaptive Environments(Turkish Education Assoc, 2014) Eryilmaz, Meltem; Simsek, Nurettin; Computer EngineeringIn this experimental research, academic performance of the students who were grouped according to their prior knowledge levels. In the research, three different environments were developed on the Mood le platform. The environments were designed without adaptations, with content adaptations that contain changes pertaining to the presentation style of the information that is to be included on pages, and with navigation adaptations which offer the suitable links by changing the link structure. The students worked for a period of five weeks in the designed environments. A multiple choice test and a practice examination were prepared in order to determine the knowledge level of the students pertaining to the subject matter prior to the experimental process, and to measure their academic performance after the experimental process. The findings derived from the scores of the tests which were given as pre test and final test indicated that the academic performance of the students who study in adaptive and non-adaptive learning environments may differ.
