Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Conference Object Citation - Scopus: 2Moodle: Practical Advices for University Teachers(Springer Verlag service@springer.de, 2017-09-28) Pedersen, Jens Myrup; Kuran, Mehmet ŞükrüMoodle is a widely used Learning Management System, with a market share of 20% in the US/Canada and 65% in Europe. However, it is our experience that the system is too often used just as a website or repository for classical teaching material such as literature references, slides and problems for students to solve after the lectures, and that the fully potential of the platform is not exploited. In this paper we demonstrate some of the functionalities that university teachers can make use of to increase the learning experience of the students. For each of the features we demonstrate, we both show how it can be used, and give some didactic considerations. We have tested all of the presented features ourself in a blended learning course carried out as part of an Erasmus+ Strategic Partnership. © 2017 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 13Learning Management Systems on Blended Learning Courses: An Experience-Based Observation(Springer Verlag service@springer.de, 2017-09-28) Kuran, Mehmet Şükrü; Pedersen, Jens Myrup; Elsner, RaphaelThis paper gives an overview of Learning Management System (LMS) features based on observations on a blended learning course under the Erasmus+ project COLIBRI. We explain the main features of LMSes under two main categories: accessibility content-related and underline the capabilities of four LMSes, Moodle, Blackboard Learn, Canvas, and Stud.IP with respect to these. We explain how these features were utilized to increase the efficiency, tractability, and quality of experience of the course. We found that an LMS with advanced features such as progress tracking, modular course support, interactive content support, and content access restriction is of paramount importance for blended learning courses. © 2017 Elsevier B.V., All rights reserved.Conference Object Evaluation of Hybrid Classification Approaches: Case Studies on Credit Datasets(Springer Verlag service@springer.de, 2018) Cetiner, Erkan; Güngör, Vehbi Çağrı; Kocak, TaskinHybrid classification approaches on credit domain are widely used to obtain valuable information about customer behaviours. Single classification algorithms such as neural networks, support vector machines and regression analysis have been used since years on related area. In this paper, we propose hybrid classification approaches, which try to combine several classifiers and ensemble learners to boost accuracy on classification results. We worked with two credit datasets, German dataset which is a public dataset and a Turkish Corporate Bank dataset. The goal of using such diverse datasets is to search for generalization ability of proposed model. Results show that feature selection plays a vital role on classification accuracy, hybrid approaches which shaped with ensemble learners outperform single classification techniques and hybrid approaches which consists SVM has better accuracy performance than other hybrid approaches. © 2018 Elsevier B.V., All rights reserved.