University of Siegen (GERMANY)
About this paper:
Appears in: EDULEARN19 Proceedings
Publication year: 2019
Pages: 4118-4125
ISBN: 978-84-09-12031-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2019.1041
Conference name: 11th International Conference on Education and New Learning Technologies
Dates: 1-3 July, 2019
Location: Palma, Spain
The shape of modern classrooms has been witnessing considerable changes in the recent years. With the utilization of new technologies, a great potential has been offered for developing the learning environment. This development has been affecting both collaborative and individual educational activities, such as in schools and self-learning scopes respectively. Achieving this technological support of education took several forms, depending on the use of educational software or hardware. While effective learning tools utilized only one of those two components, the combination of specific computer science algorithms with suitable corresponding devices and sensors can increase not only the efficiency of the learning tool, but also its usability in real-world applications.

In the language learning context, technology enhanced educational tools have been mainly based on pure software solutions, in the form of mobile or desktop applications. Some language learning skills and activities, such as the ability to link words to a certain context, or learn new vocabulary related to that context, can be well supported by utilizing text mining and the CIMAWA approach (Concept for Imitating the Mental Ability of Word Association). The former algorithm has the ability to analyze the content of a text, while the later can link the existing words and phrases in this content to other similar or related vocabulary in a wider scope, such as online resources. This, in turn, corresponds to commonly practiced methods in learning new vocabulary of a new language by understanding the semantics of words from their context.

The utilization of those algorithms can also be enhanced by adding a hardware component to them. This hardware-based support can improve the interaction between the algorithm and real-world objects, as well as enhance the representation of the algorithm’s results to the user. Enabling word association algorithm to find words that are not only related to a certain written text but also to a real object can positively influence the learning outcome reached through the educational tool. This is due to the fact that knowledge visualization has the potential to embed and illustrate more knowledge within the same time and space. In order to achieve this effect, this paper proposes the use of Augmented Reality (AR) technology in the interaction model between the learner and the system. Augmented reality offers the ability to recognize real objects or printed texts, then project more information on those objects in the augmented world.

Thus, a new educational tool for language learning is presented in this paper. The suggested system utilizes a word association algorithm in order to link variant vocabulary samples in a learning context. Then, the results of the algorithm are presented to the learner visually through an augmented reality approach, which projects not only the related words, but also further information about them, such as the strength of their connection to the object or word in question. As a result, the language learner is supported to discover new words, visually observe their relations to another word or object; and receive additional knowledge about those relations themselves.
Augmented Reality, Text Mining, Word Association, Knowledge Visualization, Language Learning.