An inquiry-based learning approach to teaching information retrieval

The study of information retrieval (IR) has increased in interest and importance with the explosive growth of online information in recent years. Learning about IR within formal courses of study enables users of search engines to use them more knowledgeably and effectively, while providing the starting point for the explorations of new researchers into novel search technologies. Although IR can be taught in a traditional manner of formal classroom instruction with students being led through the details of the subject and expected to reproduce this in assessment, the nature of IR as a topic makes it an ideal subject for inquiry-based learning approaches to teaching. In an inquiry-based learning approach students are introduced to the principles of a subject and then encouraged to develop their understanding by solving structured or open problems. Working through solutions in subsequent class discussions enables students to appreciate the availability of alternative solutions as proposed by their classmates. Following this approach students not only learn the details of IR techniques, but significantly, naturally learn to apply them in solution of problems. In doing this they not only gain an appreciation of alternative solutions to a problem, but also how to assess their relative strengths and weaknesses. Developing confidence and skills in problem solving enables student assessment to be structured around solution of problems. Thus students can be assessed on the basis of their understanding and ability to apply techniques, rather simply their skill at reciting facts. This has the additional benefit of encouraging general problem solving skills which can be of benefit in other subjects. This approach to teaching IR was successfully implemented in an undergraduate module where students were assessed in a written examination exploring their knowledge and understanding of the principles of IR and their ability to apply them to solving problems, and a written assignment based on developing an individual research proposal

From Interactive Open Learner Modelling to Intelligent Mentoring: STyLE-OLM and Beyond

STyLE-OLM (Dimitrova 2003 International Journal of Artificial Intelligence in Education, 13, 35–78) presented a framework for interactive open learner modelling which entails the development of the means by which learners can inspect, discuss and alter the learner model that has been jointly constructed by themselves and the system. This paper outlines the STyLE-OLM framework and reflects on the key challenges it addressed: (a) the design of an appropriate communication medium; this was addressed by proposing a structured language using diagrammatic presentations of conceptual graphs; (b) the management of the interaction with the learner; this was addressed by designing a framework for interactive open learner modelling dialogue utilising dialogue games; (c) the accommodation of different beliefs about the learner’s domain model; this was addressed with a mechanism for maintaining different views about the learner beliefs which adapted belief modal logic operators; and (d) the assessment of any resulting improvements in learner model accuracy and learner reflection; this was addressed in a user study with an instantiation of STyLE-OLM for diagnosing a learner’s knowledge of finance concept, as part of a larger project that developed an intelligent system to assist with learning domain terminology in a foreign language. Reviewing follow on work, we refer to projects by the authors’ students and colleagues leading to further extension and adoption of STyLE-OLM, as well as relevant approaches in open learner modelling which have cited the STyLE-OLM framework. The paper points at outstanding research challenges and outlines future a research direction to extend interactive open learner modelling towards mentor-like intelligent learning systems

Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation

Rationale Asthma phenotyping requires novel biomarker discovery. Objectives To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs). Methods An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED. Results In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-β and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation. Conclusions The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA

Cataloguing and Classification: An introduction to AACR2, RDA, DDC, LCC, LCSH and MARC 21 Standards

Cataloguing and Classification introduces concepts and practices in cataloguing and classification, and common library standards. The book introduces and analyzes the principles and structures of library catalogues, including the application of AACR2, RDA, DDC, LCC, LCSH and MARC 21 standards, and conceptual models such as ISBD, FRBR and FRAD. The text also introduces DC, MODS, METS, EAD and VRA Core metadata schemes for annotating digital resources. Explains the theory and practice of bibliographic control. Offers a practical approach to the core topics of cataloguing and classification. Includes step-by-step examples to illustrate application of the central cataloguing and classification standards. Describes the new descriptive cataloguing standard RDA, and its conceptual ground, FRBR and FRAD. Guides the reader towards cataloguing and classifying materials in a digital environment. © 2015 Elsevier Ltd. All rights reserved

E-snakes and ladders: a hypermedia educational environment for portable devices

This article presents e-snakes and ladders (e-S&L), a game-based educational environment for portable devices. The e-S&L is based on the classic table game ‘snakes and ladders’ and enriches the table game with various types of activities, such as questions and answers and webquests. It provides a pleasant electronic-learning environment with an easy to use authoring tool for the instructor. The e-S&L is based on communication services and protocols (e.g. e-mail, short message service (SMS), MMS, HTTP and FTP) and on context-aware technologies. It supports learning standards, such as the IMS question and test interoperability (QTI) specification, the IMS Learner Information Package (IMS LIP) specification, e-portfolio, Dublin Core metadata creation and webquest. Furthermore, the article presents a learning scenario which is authored for demonstrating the e-S&L functionality. The findings from this study offer interesting insights into the extent to which computer gaming might be employed as a tool for supporting learning. © 2009 Inderscience Enterprises Ltd