The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Traditionally, the assessment of the advanced knowledge about science such as problem solving or inquiry process is a challenging issue. In this paper, we aim to develop a Role Playing Learning platform called "The Banana Farm" to support the assessment of the nature science learning with collaborative fruit planting and marketing scenario. To support the assessment for inquiry process, our idea is to design the learning platform based on the multi-stage graph model in which the stages of vertices represent the student's actions and decision making during the assessment. Thus, the paths chosen to perform can be seemed as the science inquiry processes of them. Since the actions of the same stage may be executed several times, the model is extended to have self edge. Besides, the environmental status and the effectiveness of the learning objects are also extended by the working status and constraint rules in each stage. Thus, the extended Modified Multi-stage Graph (MMG) is proposed to support the assessment of inquiry process by the portfolio paths chosen in different stages. Next, the portfolio is collected for the collaborative behavior mining to discover the students' frequent collaborative action and interaction patterns during the learning. Combining with the characteristics of students, the assessment of teams with different learning strategy and behavior patterns can be obtained. Finally, the experiment on 40 junior high school students has been done and the findings were presented.
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