Conceptual Discovery of Educational Resources through Learning Objectives

Περιέχει το πλήρες κείμενοThis poster reports on current work with the NSF-funded Achievement Standards Network (ASN) to support discovery of educational resources in digital libraries using conceptual graphs of officially promulgated achievement standards statements. Conceptual graphs or knowledge maps of achievement standards reveal the macrostructure of the learning domain modeled by those standards and support higher-level understanding by teachers and students. The work builds on the conceptual framework of the AAAS knowledge maps by providing the means to flexibly define and deploy new relationship schemas to fit the disparate modeling needs of the nearly 740 learning standards documents in the ASN repository. Using an RDF-based, node-link representation of learning goals and the relationships among them, the ASN Knowledge Map Service will provide the framework to correlate educational resources to nodes in conceptual models in order to augment more conventional mechanisms of discovery and retrieval in digital libraries

A Proposed Astronomy Learning Progression For Remote Telescope Observation

Providing meaningful telescope observing experiences for students who are deeply urban or distantly rural place-bound—or even daylight time-bound—has consistently presented a formidable challenge for astronomy educators.  For nearly 2 decades, the Internet has promised unfettered access for large numbers of students to conduct remote telescope observing, but it has only been in recent years that the technology has become readily available.  Now that this once fanciful possibility is becoming a reality, astronomy education researchers need a guiding theory on which to develop learning experiences.  As one departure point, we propose a potential learning progression anchored on one end with recognizing that stars visible at night have describable locations and predictable motions, and anchored at the other with distant robotic telescopes can be programmed to record specific astronomical data for later analysis

Can Intermediary-based Science Standards Crosswalking Work? Some Evidence from Mining the Standard Alignment Tool (SAT)

We explore the feasibility of intermediary-based crosswalking and alignment of K-12 science education standards. With the increasing availability of K-12 science, technology, engineering, and mathematics (STEM) digital library content, alignment of that content with educational standards is a significant and continuous challenge. Whereas direct, one-to-one alignment of standards is preferable but currently unsustainable in its resource demands, less resource-intensive intermediary-based alignment offers an interesting alternative. But will it work? We present the results from an experiment in which the machine-based Standard Alignment Tool (SAT)—incorporated in the National Science Digital Library (NSDL)—was used to collect over half a million direct alignments between standards from different standard-authoring bodies. These were then used to compute intermediary-based alignments derived from the well-known AAAS Project 2061 Benchmarks and NSES standards. The results show strong variation among authoring bodies in their success at crosswalking, with the best results for those who modeled their standards on the intermediaries. The results furthermore show a strong inverse relationship between recall and precision when both intermediates were involved in the crosswalking.Keywords: automatic classification, computerized cataloging, data miningKeywords: automatic classification, computerized cataloging, data minin

Supporting the Discoverability of Open Educational Resources: on the Scent of a Hidden Treasury

Open Educational Resources (OERs), now available in large numbers, have a considerable potential to improve many aspects of society, yet one of the factors limiting this positive impact is the difficulty to discover them. This thesis investigates and proposes strategies to better support educators in discovering OERs. The literature suggests that the effectiveness of existing search systems, including for OER discovery, could be improved by supporting users, such as teachers, in carrying out more exploratory search activities closer to their existing methods of working. Hence, a preliminary taxonomy of OER-related search tasks was produced, based on an analysis of the literature, interpreted through Information Foraging Theory. This taxonomy was empirically evaluated to preliminarily identify a set of search tasks that involve finding other OERs similar to one that has already been identified, a process that is generally referred to as Query By Example (QBE). Following the Design Science Research methodology, three prototypes to support as well as to refine those tasks were iteratively designed, implemented, and evaluated involving an increasing number of educators in usability oriented studies. The resulting high-level and domain-oriented blended search/recommendation strategy transparently replicates Google searches in specialized networks, and identifies similar resources with a QBE strategy. It makes use of a domain-oriented similarity metric based on shared alignments to educational standards, and clusters results in expandable classes of comparable degrees of similarity. The summative evaluation shows that educators do appreciate this strategy because it is exploratory and – balancing similarity and diversity – it supports their high-level tasks, such as lesson planning and personalization of education. Finally, potential barriers and opportunities for the uptake of OER discovery tools were investigated in a structured interview study with experts from the OER field. Identified issues included how to work across multiple OER portals, variability in the use of metadata and how to align with the working practices of teachers. The findings of the thesis can be used to inform the research and development of methods and tools for OER discovery as well as their deployment to serve the needs of educators

Designing Digital Work

Combining theory, methodology and tools, this open access book illustrates how to guide innovation in today’s digitized business environment. Highlighting the importance of human knowledge and experience in implementing business processes, the authors take a conceptual perspective to explore the challenges and issues currently facing organizations. Subsequent chapters put these concepts into practice, discussing instruments that can be used to support the articulation and alignment of knowledge within work processes. A timely and comprehensive set of tools and case studies, this book is essential reading for those researching innovation and digitization, organization and business strategy