CREATION OF ON-LINE COURSES USING EXISTING LEARNING OBJECTS Marco Alfano Anghelos Centre on Communication Studies
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Biagio Lenzitti Dept. of Mathematics University of Palermo lenzitti @math.unipa.it
Natalia Visalli SISSIS University of Palermo
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Abstract The search of a specific topic in Internet provides a lot of information and much of this information has a didactic structure. However, the found "learning objects" cannot easily be reused for the creation of a new didactic work because they are usually proposed without information on their aims and the typology of users which they are destined to. Moreover, the contents are not clearly synthesized so that the reading of the whole object is often necessary to identify them. The use of Internet for the creation of a new didactic work often means just a recompilation of already existing objects using the "cut&paste" widespread practice. As a consequence, the information about the same topic is multiplied and the net is mainly used as a deposit. The action of the collective intelligence is thus only limited to archive querying and not to a real cooperation among users. We wonder whether the multiplication of information can be avoided and the collective intelligence be directed towards an optimal use of the existing information. The aim of this work is to look for a positive answer to such a question by identifying the theories, the techniques and the adequate tools for the development of a system that, through automatic extraction of learning object features, allows creation of on-line courses using existing learning objects. Keywords: On line Education, Learning Objects, Internet, Metadata Extraction, E-learning Identification Card.
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Introduction There is an increasing number of learning materials on the net that satisfy various formation requirements, from the scholastic one (mainly courses aimed to university and post-university formation) to the professional one (basic formation or update courses) and cultural (courses given by public and private corporations). The proposals can be distinguished for the typology of the content presentation (text, multimedia, etc.), the length and level of details (from the single monothematic lesson to the whole multidisciplinary course), and the interactivity degree (depending on the interactivity level at disposal of the user). Moreover, some courses assume that the student stays alone along his/her learning path while others assume an interaction with a tutor (in a synchronous or asynchronous way). Since its birth, Internet has been used as a learning tool thanks to the amount and variety of information at hand. Nowadays, it is even more used as much of the information in the net has a didactic nature and many suitable platforms for elearning exist [1], [2]. The creation of didactic material for the net seems however to be mainly perceived as a "private" elaboration aimed to a group of specific users. Nevertheless, publishing information on the net usually means offering it to a much wider audience. The search of a specific topic in Internet provides a lot of information and much of this information has a didactic structure. However, the found "learning objects" cannot easily be reused for the creation of a new didactic work because they are usually proposed without information on their aims and the typology of users which they are destined to. Moreover, the contents are not clearly synthesized so that the analysis of the whole object is often necessary to identify them. The use of Internet for the creation of a new didactic work often means just a recompilation of already existing objects using the widely-spread "cut&paste" practice. As a consequence, the information about the same topic is multiplied and the net is mainly used as a storehouse. The action of the collective intelligence is thus only limited to archive querying and not to a real cooperation among users. We wonder whether the multiplication of information can be avoided and the collective intelligence be directed towards an optimal use of the existing information. The aim of this work is to look for a positive answer to such a question by identifying the theories, the techniques and the adequate tools for the development of a system that, through automatic extraction of learning object
features, allows optimal structuring of on-line courses by using existing learning objects. The paper is organized as follows. Chapter 2 describes a real experience on building an on-line course and Chapter 3 moves from this experience to identify some criterions for the characterization of learning objects (LO) [3]. Chapter 4 defines an architecture of a system for automatic extraction of LO features and Chapter 5 describes a first hypothesis of realization of such a system. Finally, Chapter 6, reports some conclusions and future work. 2. Building an on-line course from existing materials: Experiences and thoughts Our work started with the development of an on line course on “information and communication technologies for didactics" at SISSIS, University of Palermo [4], [5]. Since the course goal was to introduce future teachers to the techniques of on-line education, it seemed natural to make the course materials accessible through the net. Moreover, Internet resulted the best place where to gather such materials. Using search engines to scan the network, several Internet pages were found for each topic with each page presenting a rich and clear content. Then, the most suitable pages were chosen considering the aims of the course and the level of the students. The next step would have been summarizing and re-elaborating the contents of the chosen internet pages, but, in this way, we would only supply a further version of already existing information without adding anything new. Instead, we chose to create some specific learning objects that contained the links to the internet pages not as further reading but as the lesson contents. The course has then been organized as an “ad hoc” filter to Internet resources connected through a graphical diagram (Fig. 1). The students experience on the use of the course has been positive because of the accessibility to various documents with basic and advanced information and the possibility of following individual learning paths not pre-arranged by the teacher. The course is in fact in the net and not simply put on the net. Moreover, the links on a subject very often point to specific sections of a site which also deal with other parts of the course, thus creating an information redundancy on the course contents. This redundancy allows the student to navigate through sites adopting the most suitable approach to his/her cognitive style.
Another point of strength of the Internet pages seen as learning objects, has been the possibility of reusing them in other courses with different objectives and audiences. This has allowed not only to reuse the on-line pages of other authors but also to capitalize our work of research and elaboration. This readaptation has been made possible thanks to the analysis made on the original objects that has provided us with a complete knowledge of the characteristics of each object, not only on the contents but also on the aims and used language
Fig. 1. Course map. Overall, this experience has suggested that the search for didactic materials on the net is often complex because there is not homogeneous indexing of objects and their characteristics cannot be determined without in-depth analysis. Moreover, information in Internet grows very rapidly and data are introduced
from several points in a disjunct way without taking into account already present information. An help to on-line courses development could come from (automatic) extraction of the main characteristics of existing learning object features for an easier reuse in a new on-line course. The learning objects should be characterized by their contents, communication methodology and required pre-existing knowledge. Moreover, in accordance with the hypertext peculiarity of Internet, they should be linked to each other allowing to retrieve other objects for the full comprehension of the treated subject and its deeper analysis. 3. Characterization of the learning objects for their re-use Starting from the considerations of the previous chapter, we would like to understand how to evaluate the nature of on-line courses and learning objects and derive their main characteristics. As an example, we would like to recognize which context a learning object belongs to, evaluate whether its content is theoretical or practical, synthetic or analytical, to understand what are the main and secondary topics, the level of complexity and the iper/multimedia structure. Such characteristics would also allow to connect those objects to other learning objects. Taking into account already existing objects, we wonder how it is possible to extract characteristics from a complex structure such as that of a learning object without an additional participation of the author who characterizes it through, for example, metadata [6]. This is a fundamental step because we hypothize that the information obtained by the analysis of the LO components and the study of their relations allows us to characterize the learning objects through a map, a sort of DNA, that contains the generic and specific elements. If this hypothesis is true, then a first analysis is needed in order to identify the media (text, images, video, audio, animations, etc.) of the learning object (or online course). Then, for each media, an analysis with specific algorithms has to be performed in order to extract specific features. Finally, the results of each analysis have to be "fused" together to determine the LO indicators, the sort of DNA previously discussed. It should be noted that the fusion of the elementary data must be done not simply putting together the results of the specific analyses but rather as a further analysis of the complete context. This is done similarly to some algorithms for extracting information from an image where an analysis of the relationship between
elements such as vertical and horizontal lines or a circular shaped structure is performed. The structure of the course and that of the learning objects together with the relationship between their media assumes then an important role in determining the nature of the course itself. 4. SAX: A System for Automatic eXtraction of learning object features Our idea is to build a “System for Automatic eXtraction of learning object features” (SAX). This system should be able to extract text/multimedia features of each learning object and of the course considered as a structured system of learning objects. In practice, given a course or a single learning object, SAX will produce an “E-learning Identification Card” (EIC) with the following information: − main topic; − secondary topics; − theory or practice; − level of complexity; − media types; − links to other EICs with same topics; − links to other EICs with different topics. The EICs will be organized in a database and will be shown through a graphical interface indicating the main topic and its connections. Fig. 2 shows, as an example, the EIC sets which have Mathematics and Computer Science as main topic. In particular, the first set has two EICs which deal with real and integer numbers while the second set has an EIC which deals with programming languages. The two sets are linked through an arrow (from Computer Science to Mathematics) because real and integer numbers are referred to by the programming languages EIC. Moreover, the two EICs are linked together because they refer to each other. The SAX architecture is made up of three levels (Fig. 3): − a low level to identify all the media components of the learning objects (text, images, video, audio, animations, etc); − a medium level to extract specific features of each media by using specialized algorithms;
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a high level to fuse the media features and show the structure and the indicators of the learning objects through the creation of their EICs.
Mathematics EICs
Computer Science EICs
Real numbers C language Integer numbers
Fig. 2. EIC examples. The EICs can be used by teachers to create new on-line courses and by students to organize their didactic paths. For example, a teacher develops a lesson on “C language” and in particular on “integer variables”. He/she uses SAX to find through the EICs all the learning objects that have “integer” as main topic. He/she then chooses the most appropriate ones and inserts them in the on-line course. 5. SAX initial development The first phase of SAX development will be devoted to confirm our basic hypothesis, i.e., LO indicators can be derived from information extracted from the various media components and from the study of their relationships. In particular, we will deal with the low level development to separate the different media of a learning object (given in a standard html format). For the medium level, we will initially perform a text analysis that will provide the most frequent words and their distances in absolute terms and within a paragraph. The high-level will only enumerate the media components (video, images, sounds, applets, ect.) to establish their relative weight. With this analysis we
hope to understand whether the object deals with theory (text predominance) or practice. The idea is to analyze a number of known objects and to use the extracted information as a data set for the unknown objects classification. At the end of the first phase, we will analyze the obtained results in order to estimate the method efficacy.
Fig. 3. SAX architecture. 6. Conclusions and future work This paper has dealt with the creation of on-line courses by using existing learning objects. This is achieved through automatic extraction of learning object features and creation of a specific E-Learning Identification Card (EIC) for each object. Acknowledging the complexity of this proposal, we would like to start a discussion on the opportunity and the real possibility to create such a system. We will start our work in a “closed” environment (with a limited set of learning objects) to ease the task but the general idea is to use the system on the Internet. References [1] CALVANI A. AND ROTTA M. (2000), Fare formazione in Internet. Manuale di didattica ondine, Erickson.
[2] ALFANO M., LENZITTI B., AND PACE A.. (2005), Tutor-Sky: A web environment for multimedia on-line education, Methodologies and Technologies for Learning, G. Chiazzese et al. (Eds.), pp. 297-304, WIT Press. [3] WILEY, D. A. (2000), Connecting learning objects to instructional design theory: a definition, a metaphor, and a taxonomy, in The Instructional Use of Learning Objects, p.7, Bloomington: IN Association for Educational Communications and Technology. [4] LENZITTI B. AND VISALLI N. (2003), STDIO.D Strumenti per la Didattica On line.Docenti, “Expo-Learning 2004, 9-12 ottobre 2004, Ferrara http://sissis.unipa.it/sito/levis/articolonew. [5] http://sissis.unipa.it/sito/levis. [6] IMS GLOBAL LEARNING CONSORTIUM, Learning Resource Meta-data Specification, http://www.imsglobal.org/metadata/
