Author
Joyce Kasman Valenza
Bio: Joyce Kasman Valenza is an academic researcher from Rutgers University. The author has contributed to research in topics: Information literacy & Higher education. The author has an hindex of 2, co-authored 6 publications receiving 6 citations.
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01 Jan 2008
TL;DR: The Future of Drylands (FOD) conference as mentioned in this paper is an international scientific conference dedicated to science, education, culture and communication in arid and semi-arid zones.
Abstract: On behalf of Mr. Koichiro Matsuura, Director-General of UNESCO, it is my great pleasure to welcome you all to this international scientific conference. Drylands are often considered fragile ecosystems, yet they have a remarkable resilience to stress. They are home to unique and well-adapted plant and animal species that we need to conserve. Some of the world’s greatest cultures and belief systems have originated in drylands. On the other hand, desertification and land degradation in drylands often result in poverty and cause environmental refugees to abandon their homes. These problems can only be addressed in a holistic manner, based on sound scientific research and findings. Solutions to the problems of dryland degradation need to be communicated as widely as possible through education at all levels. These are many reasons why UNESCO – within its mandate of science, education, culture and communication – took the intiative to organize this conference. And we are glad that so many partners have responded to our call. UNESCO considers this conference as its main contribution to the observance of the International Year of Deserts and Desertification in 2006. We have deliberately chosen the title ‘The Future of Drylands’ as we feel it is time to redefine our priorities for science, education and governance in the drylands based on 50 years of scientific research in arid and semi-arid zones. In fact UNESCO has one of the longest traditions, within the UN system, of addressing dryland problems from an interdisciplinary, scientific point of view. In 1955, the ‘International Arid Land Meetings’ were held in Socorro, New Mexico (USA). They were organized by the American Association for the Advancement of Science (AAAS), sponsored by UNESCO and supported by the Rockefeller Foundation. One important output of the International Arid Land Meetings was a book entitled The Future of Drylands, edited by Gilbert F. White and published in
1,199 citations
TL;DR: A learning path recommendation model is designed for satisfying different learning needs based on the multidimensional knowledge graph framework, which can generate and recommend customized learning paths according to the e-learner’s target learning object.
Abstract: E-learners face a large amount of fragmented learning content during e-learning. How to extract and organize this learning content is the key to achieving the established learning target, especially for non-experts. Reasonably arranging the order of the learning objects to generate a well-defined learning path can help the e-learner complete the learning target efficiently and systematically. Currently, knowledge-graph-based learning path recommendation algorithms are attracting the attention of researchers in this field. However, these methods only connect learning objects using single relationships, which cannot generate diverse learning paths to satisfy different learning needs in practice. To overcome this challenge, this paper proposes a learning path recommendation model based on a multidimensional knowledge graph framework. The main contributions of this paper are as follows. Firstly, we have designed a multidimensional knowledge graph framework that separately stores learning objects organized in several classes. Then, we have proposed six main semantic relationships between learning objects in the knowledge graph. Secondly, a learning path recommendation model is designed for satisfying different learning needs based on the multidimensional knowledge graph framework, which can generate and recommend customized learning paths according to the e-learner’s target learning object. The experiment results indicate that the proposed model can generate and recommend qualified personalized learning paths to improve the learning experiences of e-learners.
107 citations
5 citations
18 Sep 2017
TL;DR: This research attempts to bridge the gap that exists between children’s uses of digital technology at home and in other informal settings and contributes and highlights the need for studying learning more holistically.
Abstract: This paper reviews research on digital literacy practices of young children (0–8 years) in out-of-school settings or in informal learning spaces/settings. The purpose of this review is to identify the literature and topics that have arisen from non-school-based or informal space research and to highlight main directions and dimensions. The major research question is: What is the role of informal learning spaces in shaping children’s digital literacy practices? This research attempts to bridge the gap that exists between children’s uses of digital technology at home and in other informal settings and contributes and highlights the need for studying learning more holistically.
3 citations
04 Nov 2021
TL;DR: This paper showed that students cannot accurately identify containers when they rely on heuristics like the URL and Google snippet, and that this requires thoughtful engagement with the information resources and critical evaluation of the sources that produced them.
Abstract: To combat misinformation, librarians can teach students to evaluate containers and the indicators of credibility that they provide. Information containers can be evaluated prior to consuming information within a resource, while fact-checking only can happen after. Because of this, container evaluation can help prevent misinformation from being encoded. Our research demonstrates that this requires thoughtful engagement with the information resources and critical evaluation of the sources that produced them, and that students cannot accurately identify containers when they rely on heuristics like the URL and Google snippet.
1 citations