Applying concept mapping strategies to improve students’ lifelong learning in physical chemistry

Este artículo ofrece una reflexión sobre el papel de los mapas conceptuales en el actual escenario de la educación In the present paper, we carry out the application of concept mapping strategies to learning Physical Chemistry, in particular, of all aspect of Corrosion. This strategy is an alternative method to supplement examinations: it can show the teacher how much the students knew and how much they didn´t know; and the students can evaluate their own learning. Before giving tile matter on Corrosion, the teachers evaluated the previous knowledge of the students in the field and explained to the students how create the conceptual maps with Cmap tools. When the subject is finished, teachers are assessed the conceptual maps developed by students and therefore also the level of the students learning. Teachers verified that the concept mapping is quite suitable for complicated theorics as Corrosion and it is an appropriate tool for the consolidation of educational experiences and for improvement affective lifelong learning. By using this method we demonstrated that the set of concepts accumulated in the cognitive structure of every student in unique and every student has therefore arranged the concepts from top to bottom in the mapping field in different ways with different linking" phrases, although these are involved in the same learning task.

A systematic mapping study on the open source software development process.

Abstract?Background: There is no globally accepted open source software development process to define how open source software is developed in practice. A process description is important for coordinating all the software development activities involving both people and technology. Aim: The research question that this study sets out to answer is: What activities do open source software process models contain? The activity groups on which it focuses are Concept Exploration, Software Requirements, Design, Maintenance and Evaluation. Method: We conduct a systematic mapping study (SMS). A SMS is a form of systematic literature review that aims to identify and classify available research papers concerning a particular issue. Results: We located a total of 29 primary studies, which we categorized by the open source software project that they examine and by activity types (Concept Exploration, Software Requirements, Design, Maintenance and Evaluation). The activities present in most of the open source software development processes were Execute Tests and Conduct Reviews, which belong to the Evaluation activities group. Maintenance is the only group that has primary studies addressing all the activities that it contains. Conclusions: The primary studies located by the SMS are the starting point for analyzing the open source software development process and proposing a process model for this community. The papers in our paper pool that describe a specific open source software project provide more regarding our research question than the papers that talk about open source software development without referring to a specific open source software project.

A systematic mapping study on testing technique experiments: has the situation changed since 2000?

Context: Empirical Software Engineering (ESE) replication researchers need to store and manipulate experimental data for several purposes, in particular analysis and reporting. Current research needs call for sharing and preservation of experimental data as well. In a previous work, we analyzed Replication Data Management (RDM) needs. A novel concept, called Experimental Ecosystem, was proposed to solve current deficiencies in RDM approaches. The empirical ecosystem provides replication researchers with a common framework that integrates transparently local heterogeneous data sources. A typical situation where the Empirical Ecosystem is applicable, is when several members of a research group, or several research groups collaborating together, need to share and access each other experimental results. However, to be able to apply the Empirical Ecosystem concept and deliver all promised benefits, it is necessary to analyze the software architectures and tools that can properly support it.