Abstract
Digital contents contains a large number of learning concepts most of which contribute to the main learning ideas. How to focus on the learning faults and improve the learning process is important. In this paper, we propose a novel approach to retrieving the main ideas from, as well as to constructing a domain tree to represent, the contents of materials. The nodes of the domain tree consist of meaningful texts. We collect the meaningful texts by segmenting words of the digital contents and then recombining these texts to form a binary number. We define a scoring method for the digital contents by assigning a sequence of 0’s and 1’s to the texts. These binary numbers can then be easily calculated by a function of sequence with power n and base 2, where n ∈ N. Each sequence can get a unit score which indicates the location in the context. An expression of digital contents represents a unit, a chapter, a section, or a paragraph. This expression can be provided as a feedback to teachers or students. Based on the feedback, teachers can make questions in the exam sheet more evenly distributed while students can improve the way they learn.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Billings, D.M.: A conceptual model of correspondence course completion. In: Moore, M.G., Clark, G.C. (eds.) Readings in Distance Learning and Instruction, 2. University Park, PA:ACSDE (1989)
Brusilovsky, P.: Adaptive hypermedia. User Modeling and User Adapted Interaction. In: Kobsa, A. (ed.) Ten Year Anniversary Issue, vol. 11 (1/2), pp. 87–110 (2001)
Bark, C.C., Geoffrey, I.W.: Dual-Model: An Architecture for Utilizing Temporal Information in Student Modeling. In: 7th International Conference on Computers in Education, pp. 111–118 (1999)
Brusilovsky, P.: Methods and Techniques of Adaptive Hypermedia. User Modeling and User Adapted Interaction 6(2-3), 87–129 (1996)
Ball, R.: Where are we and where are we going. ADL Library (2001), http://www.adlnet.org/library/library_details.cfm?Repo_Id=555
Borgatti, S.P.: @ What Is Social Network Analysis? http://www.analytictech.com/networks/whatis.htm
Carro, R.M., Pulido, E., Rodriguez, P.: Dynamic generation of adaptive Internet-based courses. Journal of Network and Computer Applications 22, 249–257 (1999)
Dik Lun, L., Kent, E.S., Huei, C.: Document Ranking and the Vector Space Model. IEEE Software 14(2), 67–75 (1997)
Feng, T., Fionn, M.: Towards Knowledge Discovery from WWW Log Data. In: Proceedings of the The International Conference on Information Technology:Coding and Computing (2000)
Hewitt, G.: A portfolio primer: Teaching, collecting and assessing student writing. Portsmouth, NH:Heinemann (1995)
ADL Technical Team. Sharable Content Object Reference Model ( SCORMTM) Version 1.2. (2001)
AICC CMI subcommittee AICC/CMI Guideline For Interoperability Version 3.5 (2001)
Agarwal, R., Prasad, J.: Are Individual Differences Germane to the Acceptance of New Information Technologies? Decision Sciences 30(2), 361–391 (1999)
KANG HSUAN Educational Publishing Group http://www.knsh.com.tw
HAN LIN Educational Publishing Group http://www.hle.com.tw
Chinese Knowledge and Information Processing group http://ckipsvr.iis.sinica.edu.tw/
Chuang, P.J., Yang, C.-S., Lee, H.-T.: Visualizing the Multi-Direction of Portfolio. In: Conference on Information Technology and Applications in Qutlying Islands June 2-3, Kinman (2006)
Chuang, P.J., Yang, C.-S., Chiang, M.-C.: Visualizing The Learning Portfolio. In: IADIS International Conference Cognition and Exploratory Learning in Digital. Barcelona Spain (2006)
Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw Hill Book Co., New York (1983)
Liao, S.-J.: Constructing Decision Tree Using Leaners’ Portfolio for supporting e-Learning. master thesis, National Sun Yat-sen University. Kaohsiung City, Taiwan (2003)
Chen, Y.-P.: Dynamic Constructing Decision Rules from Learning Portfolio to support Adaptive Instruction. master thesis, National Sun Yat-sen University. Kaohsiung City, Taiwan (2004)
Academia Sinica http://www.sinica.edu.tw
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chuang, P.J., Yang, CS., Chiang, MC. (2007). Distribution of Lecture Concepts and Relations in Digital Contents. In: Enokido, T., Barolli, L., Takizawa, M. (eds) Network-Based Information Systems. NBiS 2007. Lecture Notes in Computer Science, vol 4658. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74573-0_18
Download citation
DOI: https://doi.org/10.1007/978-3-540-74573-0_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74572-3
Online ISBN: 978-3-540-74573-0
eBook Packages: Computer ScienceComputer Science (R0)