Browsing by Author "Yurdugül, H."

Now showing 1 - 2 of 2

Online Learners’ Navigational Patterns Based on Data Mining in Terms of Learning Achievement
(Springer International Publishing, 2019) Keskin, S.; Sahin, M.; Yurdugül, H.
The aim of this study is to explore navigational patterns of university students in a learning management system (LMS). After a close review of the literature, a scarcity of research on the relation between online learners’ navigational patterns and their learning performance was found. To contribute to this research area, the study aims to examine whether there is a potential difference in navigational patterns of the learners in terms of their academic achievement (pass, fail). The data for the study comes from 65 university students enrolled in online Computer Network and Communication. Navigational log records derived from the database were converted into sequential database format. According to students’ achievement (pass, failure) at the end of the academic term, these data were divided into two tables. Page connections of the users were transformed into interaction themes, namely homepage, content, discussion, messaging, profile, assessment, feedback, and ask the instructor. Data transformed into sequential patterns by the researchers were organized in navigational pattern graphics by taking frequency and ratio into consideration. The z test was used to test the significance of the difference between the ratios calculated by the researchers. The findings of the research revealed that although learners differ in terms of their achievement, they draw upon similar processes in the online learning environments. Nevertheless, it was observed that students differ from each other when considering their system interaction durations. According to this, learning agents, interventional feedbacks, and leaderboards can be used to keep failed students in the online learning environment. Studies were also proposed on the ordering of these LMS navigational themes, which are important in the e-learning process. Findings from these studies can guide designers and researchers in the design of adaptive e-learning environments, which are also called next-generation digital learning environments. © Springer Nature Switzerland AG 2019.
Online Learners’ Readiness and Learning Interactions: a Sequential Analysis
(IADIS Press, 2018) Şahin, M.; Keskin, S.; Yurdugül, H.
An important advantage of e-learning environments is the numerical observation of the learning behaviors of students. The use of e-learning environments by students creates a learner data. From these learner data, the navigation patterns obtained by using educational data mining have a very important place in learning and teaching design. Studies have shown that learners' learning behaviors in online learning environments may vary according to the characteristics of learners. Studies on the differentiation of the navigation patterns according to the psycho-educational characteristics of the learners provide very strong inputs to the design of the learning environment appropriate to the characteristics of the students which is named as adaptive learning environments. According to these inputs, learning environment designs can be developed according to the individual characteristics of the students. Online learners' readiness (OLR) for e-learning is an important psycho-educational structure. The aim of this study is to investigate students' navigations in the e-learning environment according to the level of readiness for e-learning. Lag sequential analysis was used when students' system interactions were analyzed sequentially. According to the results of the analysis, it has been found that the sequential navigation patterns of the students differ according to the OLR structure. The findings of this research are expected to provide important information and suggestions to online learning environment designers. © 2018 IADIS Press. All Rights Reserved.