Geographical inquiry involves collecting, using and making sense of the data to investigate some geographical phenomena. With the increasing number of mobile devices equipped with Internet access capabilities, there is a wide scope for using it in field inquiry where learning can take place in the form of social interactions between team members while performing a common task. The authors examine the use of MobiTOP (Mobile Tagging of Objects and People), a geospatial digital library system which allows users to contribute and share multimedia annotations via mobile devices, within a geographical field inquiry. A key feature of MobiTOP that is well suited for collaborative learning is that annotations are hierarchical, allowing annotations to be annotated by other users to an arbitrary depth. A group of student and teachers involved in an inquiry-based learning activity in geography was instructed to identify rock types and associated landforms by collaborating with each other using the MobiTOP system. A method combining several data collection methods was used. Four main findings on the affordances of the mobile phone, the need for specialized training in using the application with the mobile phone, design considerations of the application and the authentic context of learning with fieldwork are reported. A discussion on the implication of these findings and how mobile technology may be used for geographical field learning are also included in this paper.

Abstract.One of the uses of social tagging is to associate freely selected terms (tags) to resources for sharing resources among tag consumers. This enables tag consumers to locate new resources through the collective intelligence of other tag creators, and offers a new avenue for resource discovery. This paper investigates the effectiveness of tags as resource descriptors determined through the use of text categorisation using Support Vector Machines. Two text categorisation experiments were done for this research, and tags and web pages from del.icio.us were used. The first study concentrated on the use of terms as its features. The second study used both terms and its tags as part of its feature set. The results indicate that the tags were not always reliable indicators of the resource contents. At the same time, the results from the terms only experiment were better compared to the experiment with terms and tags. A deeper analysis of a sample of tags and documents were also conducted and implications of this research are discussed.

We investigate user perceptions of engagement and information quality of a mobile human computation game (HCG) by comparing it against a non-game-based application. Results suggest that the mobile HCG enabled participants to occupy their leisure time but the information contributed was perceived to be not as relevant. Implications of this study are discussed.

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The objective of this paper is to investigate the effectiveness of tags in facilitating resource discovery through machine learning and user-centric approaches. Drawing our dataset from a popular social tagging system, Delicious, we conducted six text categorization experiments using the top 100 frequently occurring tags. We also conducted a human evaluation experiment to manually evaluate the relevance of some 2000 documents related to these tags. The results from the text categorization experiments suggest that not all tags are useful for content discovery regardless of the tag weighting schemes. Moreover, there were cases where the evaluators did not perform as well as the classifiers, especially when there was a lack of cues in the documents for them to ascertain the relationship with the tag assigned. This paper discusses three implications arising from the findings and suggests a number of directions for further research.