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Yawen Yu; Yang Tao; Gaowei Chen; Can Sun – Journal of Computer Assisted Learning, 2024
Background: Deep discussions play an important role in students' online learning. However, researchers have largely focused on engaging students in deep discussions in online asynchronous forums. Few studies have investigated how to promote deep discussion via mobile instant messaging (MIM). Objectives: In this study, we applied learning…
Descriptors: Learning Analytics, College Students, Epistemology, Computer Mediated Communication
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Valtonen, T.; Havu-Nuutinen, S.; Dillon, P.; Vesisenaho, M. – Journal of Computer Assisted Learning, 2011
This paper reports a case study for developing lecture teaching in higher education by connecting simultaneously the benefits of face-to-face teaching and social software for capturing and sharing students' lecture notes. The study was conducted with 12 university students taking a degree course on pre-primary education. Data were collected on (1)…
Descriptors: Discourse Analysis, Content Analysis, Lecture Method, Cooperation
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Salminen, T.; Marttunen, M.; Laurinen, L. – Journal of Computer Assisted Learning, 2010
This study investigates whether combining chat discussion and construction of an argument diagram stimulates students to formulate new ideas in practising argumentation. In this study, 16 secondary school students discussed vivisection and gender equality in pairs using both free and structured chat tools. In structured chat, the students selected…
Descriptors: Persuasive Discourse, Prior Learning, Secondary School Students, Visual Aids
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Pfister, H.-R.; Oehl, M. – Journal of Computer Assisted Learning, 2009
Net-based collaborative learning discourses often suffer from deficiencies such as lack of coherence and coordination. It is suggested that the provision of two functionalities, referencing and typing, which learners may optionally use to ground their contributions during a chat-based discourse, can improve collaborative learning. In particular,…
Descriptors: Content Analysis, Discussion Groups, Cooperative Learning, Group Dynamics