This case study aims at ensuring preservice science teachers to acquire experience by creating paper-based mind maps (PB-MM) and digital mind maps (D-MM) in technology education and to reveal their opinions on these mind mapping techniques. A total of 32 preservice science teachers, enrolled in the undergraduate program of Science Teaching at a university in Turkey, participated in this study. During the first three weeks of the six-week study, participants created PB-MM for certain subjects in science education. For the rest of the weeks, they created D-MM by using Coggle. As data collection tool, a form, consisting of open-ended questions, was used in this study. The obtained results demonstrated that the participants generally reported positive opinions including that mind maps are beneficial and useful tools in reinforcing, assessing and visualizing learning in general, making lessons more entertaining as well as offering ease of use. It was also concluded that students can also use mind maps in teaching of other topics such as “Vitamins”, “The Earth and the Universe” and “Systems” in particular, as well as in events like meetings, presentations, brainstorming. Advantages of D-MM were listed as the possibility of adding multimedia material, ease of correction processes and the visual richness, while its disadvantage was listed as experiencing technical problems. PB-MM contribute to psychomotor development of students as well as learning by performing/experiencing. The difficulty in processes such as deleting, editing, etc. and in adding videos and images constitute the restrictions of PB-MM technique.
Information Visualisation strategies can be applied in a variety of domains. In the context of temporal networks, i.e., networks in which interactions between individuals occur throughout time, efforts have been conducted to develop visual approaches that allow finding interaction patterns, anomalies, and other behaviours not previously perceived in the data. This paper presents two case studies involving real-world education networks from a primary school and a high school. For this purpose, we used the Massive Sequence View (MSV) layout with the Community-based Node Ordering (CNO) method, two well established approaches for visual analysis of temporal networks. Our results show that the identified patterns involving students/students and students/teachers represent important information to benefit and support decision making about school management and teaching strategies, especially those related to strategic group formation.
This paper proposes a student-oriented approach tailored to effective collaboration between students using mobile phones for language learning within the life cycle of an intelligent tutoring system. For this reason, in this research, a prototype mobile application has been developed for multiple language learning that incorporates intelligence in its modeling and diagnostic components. One of the primary aims of this research is the construction of student models which promote the misconception diagnosis. Furthermore, they are the key for collaboration, given that students can cooperate with their peers, discuss complex problems from various perspectives and use knowledge to answer questions and/or to solve problems. Summarizing, in this paper, a mobile tutoring framework, built up in the context of student collaboration, is presented. Collaborative student groups are created with respect to the corresponding user models. Finally, the prototype was evaluated and the results confirmed the usefulness of collaborative learning.