This paper aims to better understand the development of students' metacognitive learning processes when participating actively in a CSCL system called KnowCat. To this end, a longitudinal case study was designed, in which 18 university students took part in a 12-month (two semesters) learning project. The students followed an instructional process, using specific features of the KnowCat design to support and improve their interaction processes, especially peer-learning processes. Our research involved both supervising the students' collaborative learning processes throughout the learning project and focusing our analysis on the qualitative evolution of their interaction processes and of their metacognitive learning processes. The results of the current research suggest that the pedagogical use of the KnowCat system may favour and improve the development of the students' metacognitive learning processes. In addition, the implications of the design of CSCL networks and related pedagogical issues are discussed.
Meta-modelling is one of the pillars of Model-Driven Engineering (MDE), where it is used for language engineering and domain modelling. Even though the current trend is the use of two-level meta-modelling frameworks, several researchers have pointed out limitations of this scheme for some scenarios and suggested a metamodelling approach with an arbitrary number of meta-levels in order to obtain more flexible and simpler system descriptions. Unfortunately, such multi-level meta-modelling systems are still in their infancy, lacking for example, integration with model manipulation languages, a characterization of different possibilities for instantiation and inheritance, and primitives for interconnecting multi-level languages in a flexible way. In this paper, we propose a number of extensions to multi-level (also called deep) meta-modelling, based on the needs raised by its use for practical MDE. In particular, we discuss on the issues related to code generation from deep languages, the benefits of allowing inheritance at every meta-level, and patterns and techniques for a fine-grain control of the meta-level of elements. Finally, we provide primitives to control the impedance mismatch when connecting models at different meta-levels.
This article presents a new approach based on “collaborative scenarios” to enhance teaching–learning programming in non‐Computer Science oriented curricula. In this context, a literature review of tools related to teaching programming since a collaborative approach is presented. The collaborative scenarios was supported by a platform called TASystem, and applied in a case study carried out with students from Topographic Engineering Department at the Universidad del Valle (Colombia). The students’ social interaction was analyzed with Social Network Analysis and Content Analysis techniques and so was the students’ performance. The results showed an improvement in the students’ performance and an increment in the social relationship among the students.
This paper studies how the integration of group awareness tools in the knowledge management system called KnowCat (Knowledge Catalyser), which promotes collaborative knowledge construction, may both foster the students' perception about the meaningfulness of visualization of group awareness information and promote better collaborative processes as well as enhance better task performance. Forty-seven university students participated in a research study, where one group of 23 students used KnowCat without the awareness console (non-awareness group); the other 24 students used KnowCat with the awareness console (awareness group). Both groups used KnowCat during one semester. Data analysis revealed that the awareness group means were higher than those of the non-awareness group in terms of participation, cognitive and metacognitive learning activities, and task performance. Moreover, students revealed that knowing what, where and how much their classmates were contributing acted as positive feedback by encouraging participation and orienting their own behaviour and their contribution to the collaborative work. In this paper, we claim that the visualization group awareness information in KnowCat, a utility allowing students to visualize and track what, where, how much and how often other participants contributed to the KnowCat knowledge area, had a positive impact on the students' collaborative behaviour.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.