COGNITIVE DIALOG GAMES AS COGNITIVE ASSISTANTS: TRACKING AND ADAPTING KNOWLEDGE AND INTERACTIONS IN STUDENT’S DIALOGS

This study introduces a system design in a form of cognitive dialog game (DiaCog) to support pedagogical factors and student learning model ideas. The purpose of the study is to describe how such a design achieves tracking and adapting students’ knowledge and mastery learning levels as a cognitive assistant. Also, this study shows alternative ways for supporting intelligent personal learning, tutoring systems, and MOOCS. This paper explains method called DiaCog that uses structure for students` thinking in an online dialog by tracking student`s level of learning/knowledge status. The methodology of computing is the semantic that match between students` interactions in a dialog. By this way it informs DiaCog’s learner model to inform the pedagogical model. Semantic fingerprint matching method of DiaCog allows making comparisons with expert knowledge to detect students` mastery levels in learning. The paper concludes with the DiaCog tool and methodologies that used for intelligent cognitive assistant design to implement pedagogical and learner model to track and adapt students’ learning. Finally, this paper discusses future improvements and planned experimental set up to advance the techniques introduced in DiaCog design

A data mining approach for desire and intention to participate in virtual communities

The purpose of this study is to investigate performances of some of the data mining approaches while understanding desire and intention to participate in virtual communities and its antecedents. A research model has been developed following the literature review and the model was tested afterwards. In research part of the study, some of the data mining approaches as JRip, Part, OneR Method, Multilayer Perceptron (Neural Networks), Bayesian Networks have been used. Based on the analysis conducted it has been found out that Multilayer Neural Network had the best correct classification rate and lowest RMSE

During the covid-19 pandemic, students' opinions on distance education in department of engineering

The decision regarding the distance education method in Turkey on March 15, 2020, has completely changed the learning and teaching methodology of all university students and educators, and it has been seen that all courses have started to be given with distance education. The purpose of this research is to examine the perspectives of engineering university students towards distance education during the Covid-19 pandemic. The research consists of engineering faculty students studying at various universities in the Aegean region and Russian Federation. In the research, a scanning model was used. The data of the research were collected from 520 engineering department university students from various universities in our country, according to the convenience sampling method, and through an online questionnaire filled out by the students. Thanks to this wide participation, results have been obtained that will explain the Covid-19 process related to distance education in a good way. In general, it has been concluded that students are happy to see them in distance education model courses, so they do not fall behind in their education, and university students watch their courses mostly with the help of smart devices.WOS:000772618100001Emerging Sources Citation IndexArticleUluslararası işbirliği ile yapılan - EVETApril2022YÖK - 2021-22Mar

Analyzing Communication Dimensions in a Ubiquitous Learning Environment

This study aims to investigate certain communication dimensions to assess the impact of Computer Mediated Communication (CMC) tendencies of students on ubiquitous environments. Communication dimensions were determined as message content, message interaction, semantic of message, emotional situation, and security. Message content was used as a determiner indicator to measure the effectiveness of communication methods in ubiquitous environments. The effects on the inclination to communicate in ubiquitous learning environments are explained in detail with Partial Least Squares Structural Equation Modeling (PLS-SEM). Message interaction, semantic of message, and security all have a great impact on the adoption of message content; therefore, they promote students' engagement through ubiquitous learning. According to the correlation values, we observed that the user is prone to participate in CMC if the message is meaningful, replied to immediately, sent from someone that looks familiar and sent to the right person

Meta-Cognitive Tool Development for History Teaching: Investigating how Software Usability Affects Student Achievements

This paper presents a Meta-Cognitive Tool (MCT) development for history teaching. It was developed to support teaching history of civilization courses at the engineering faculty. It covers hierarchically arranged concept maps which are presented dynamically by using Extensible Markup Language (XML) files. MCTs are integrated in e-learning portals to support self-learning. MCTs were investigated in terms of the Human Computer Interaction (HCI) discipline to evaluate their usability in online courses. For this purpose, relationships between learners' cognitive abilities, individual differences, and usability of e-learning portal were considered in order to create a model between individual differences and software usability. The usability of MCT was evaluated by 116 (70 male, 46 female) subjects who were registered for the HUM1005 History of Civilization I, a general elective course at the faculty of engineering. They completed four different surveys: an IQ survey, a personality survey, a motivation survey, and a software usability measurement inventory (SUMI). This research compares intelligence, personal factors, and motivation factors with the personal software usability results in order to determine the correlations and associations between the usability of the software and learners’ individual differences. In the study, results show that the usability of any education tool has effect on achievement of the learner. Noteworthy, a correlation was found between Grade Point Average (GPA) and usability scores

Cognitive dialog games as cognitive assistants: Tracking and adapting knowledge and interactions in student’s dialogs

This study introduces a system design in a form of cognitive dialog game (DiaCog) to support pedagogical factors and student learning model ideas. The purpose of the study is to describe how such a design achieves tracking and adapting students’ knowledge and mastery learning levels as a cognitive assistant. Also, this study shows alternative ways for supporting intelligent personal learning, tutoring systems, and MOOCS. This paper explains method called DiaCog that uses structure for students` thinking in an online dialog by tracking student`s level of learning/knowledge status. The methodology of computing is the semantic that match between students` interactions in a dialog. By this way it informs DiaCog’s learner model to inform the pedagogical model. Semantic fingerprint matching method of DiaCog allows making comparisons with expert knowledge to detect students` mastery levels in learning. The paper concludes with the DiaCog tool and methodologies that used for intelligent cognitive assistant design to implement pedagogical and learner model to track and adapt students’ learning. Finally, this paper discusses future improvements and planned experimental set up to advance the techniques introduced in DiaCog design