Abstract
E-book reader supports users to create digital learning footprints in many forms like highlighting sentences or taking memos. Nowadays, it also allows an instructor to update their e-books in the e-book reader. However, e-book users often face problems when trying to find learning footprints they made in a new version e-book. Thus, users’ reading experience continuity across e-book revisions is hard to be maintained and seems to become a shortcoming within the e-book system. In this paper, in order to maintain users’ reading experience continuity, we deal with the transfer of learning footprints such as a marker, memo, and bookmark across e-book revisions on an e-book reader in a coursework scenario. We first give introduction and related works to demonstrate how researchers dedicated on the problem mentioned in this paper and page similarity comparison. Then, we compare three page similarity comparison methods using similarity computing models to compute page pairwise similarity in image level, text level, and image & text level. In the analysis, for each level, we analyze the performance of transferring learning footprint across e-book revisions and also the optimal threshold for similar page determination. After that, we give the analysis results to show the performances of three methods in image level, text level, and image & text level, and then, the error analysis is presented to specify the error types that occur in the results. We then propose page image & text similarity comparison as the optimal method to automatically transfer learning footprints across e-book revisions based on the analysis results and error analysis among three compared methods. Finally, the discussion and conclusions are shown in the end of this paper.
Highlights
Web-based educational applications are expected to be able to adapt users with very different background, prior knowledge of the subject, and learning goals
According to the F-measure scores and execution time, Normalized Mean Square Error (NMSE) model can perform better and faster than Structural Similarity (SSIM) model on learning footprints transferring; we propose in page image similarity comparison, NMSE is the better model
According to the F-measure scores and execution time, the F-measure scores are the same between this two models, cosine similarity model can perform faster than Jaccard similarity model on learning footprint transferring; we propose in page text similarity comparison, cosine similarity is the better model
Summary
Web-based educational applications are expected to be able to adapt users with very different background, prior knowledge of the subject, and learning goals. An e-book reader is one of the most prominent varieties of web-based educational systems (Brusilovsky et al 1998). In e-book readers, the uses of annotation technique in the electronic document environment have rapidly widely treated more and more advantageous (Brush et al 2001; Cadiz et al 2000). An e-book reader often allows users to create learning footprints in many forms. Traditional textbook usually not allows teachers to update their learning materials, so the versions of learning materials are hard to be distributed. Nowadays, e-book reading system can overcome this problem, allowing teachers to update
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