User Modeling for Language Learning in Facebook Maria Virvou,1 Christos Troussas,1 Jaime Caro2 , and Kurt Junshean Espinosa2 1 Department of Informatics, University of Piraeus, Piraeus, Greece Department of Computer Science, University of the Philippines Diliman, Quezon City, Philippines {mvirvou,ctrouss}@unipi.gr,
[email protected],
[email protected] 2
Abstract. The rise of Facebook presents new challenges for matching users with content of their preferences. In this way, the educational aspect of Facebook is accentuated. In order to emphasize the educational usage of Facebook, we implemented an educational application, which is addressed to Greek users who want to learn the Conditionals grammatical structure in Filipino and vice versa. Given that educational applications are targeted to a heterogeneous group of people, user adaptation and individualization are promoted. Hence, we incorporated a student modeling component, which retrieves data from the users Facebook profile and from a preliminary test to create a personalized learning profile. Furthermore, the system provides advice to each user, adapted to his/her knowledge level. To illustrate the modeling component, we presented a prototype Facebook application. Finally, this study indicates that the wider adoption of Facebook as an educational tool can further benefit from the user modeling component. Key words: User Modeling, Facebook, Social Networking Sites, Intelligent Tutoring Systems, Computer Assisted Language Learning, Initialisation
1
Introduction
In the last decade, we have witnessed major improvements in the area of information and communications technology, which induced changes in pedagogy. Currently, social networks are being adopted rapidly by millions of users worldwide, most of whom are students [19]. Social network tools support educational activities by making feasible the interaction, collaboration, active participation, information and resource sharing, and critical thinking between users [20]. Social networks may offer students the possibility of increasing avenues for learning. Hence, the use of educational applications along with the opportunity of communicating with peers in order to achieve a common purpose has become significant. Using social networks, such as Facebook, in educational and instructional contexts can be considered as a potentially powerful idea simply because students spend anyway a lot of their spare time on these online networking activities [21].
2
User Modeling for Language Learning in Facebook
On the other hand, this rapid development accentuates the learning of multiple foreign languages, a phenomenon which is responsible for joining different cultures from all over the world. Considering the scientific area of Intelligent Tutoring Systems (ITSs), there is an increasing interest in the use of computerassisted foreign language instruction. The need for tutoring systems that may provide user interface friendliness and also individualized support to errors via a student model are even greater when students are taught a foreign language through a social network. Student modeling may include modeling of students skills and of declarative knowledge and can perform individualized error diagnosis of the student.The use of social networks in educational contexts is a burning issue in recent scientific literature. However, the integration of social networks in the learning environment along with the modeling of users who are trying to attain more robust learning opportunities is not yet well studied. In view of the above, we propose an educational application in Facebook for learning the grammatical phenomenon of conditionals. This application is addressed to Greek students who want to learn conditionals in Filipino and vice versa. The users are modeled so that they can receive advice from the system. The prototype system combines an attractive multimedia interface and adaptivity to individual student needs in the social network. The communication between the system and its potential users as students is accomplished through the use of web services.
2
Related Work
In this section we present the scientific work for student modeling, related firstly with Social Networking Sites(SNSs) and secondly with Computer Assisted Language Learning (CALL). The advent of SNSs has made an impact in various areas including educational context. Many researchers investigated the use of SNSs such as Facebook in the context of learning, specifically language learning. Piriyasilpa[10] discussed the effects of the inclusion of a Facebook activity as part of the language classroom. Ho-Abdullah et al[7] also found out that the informal setting of a web-based social networking site has provided students opportunity for improving in their English language skills. Ota[12] investigated the benefits of SNS communities (i.e. Facebook) for learning Japanese as a second language (L2). They found out that SNSs has provided a portal for L2 learners to access other information and sources. Hiew[6]studied the perceptions of English as a Second Language (ESL) learners in the use of Facebook journal as a channel for language learning outside the classroom. Furthermore, PromnitzHayashi[11] has found out that simple activities in Facebook has helped the less language-proficient students to become more actively involved in the language learning process. On the other hand, Antal and Koncz[2] reviewed the student modeling problem for computer-based test systems and proposed a novel method for the graphical representation of student knowledge. Moreover, Ferreira and Atkinson[5] presented a model of corrective feedback for an ITS for Spanish as a foreign language and proposed the design of a component of effective teaching strategies into this ITS. Dickinson et al[3]designed a paper-based system that
User Modeling for Language Learning in Facebook
3
provides feedback on particle usage for first-year Korean learners, who learn a second language. Amaral et al[1]analyzed student input for different activities and motivated a broader perspective of student models. Tsiriga and Virvou[16] presented a framework for the initialization of student models in web-based educational applications. Finally, Virvou and Troussas[18] described a ubiquitous e-learning tutoring system for multiple language learning in which students naturally interact with the system in order to get used to electronically supported computer-based learning via user modeling and error proneness. However, after a thorough investigation in the related scientific literature, we came up with the result that there was no implementation of language learning application in social networks and specifically in Facebook that incorporates user modeling. Hence, we implement a prototype application, which provides intelligence in its diagnostic component and offers advice based on students performance.
3
General Architecture of the System
This section describes the general architecture of the user modeling for language learning in Facebook. 3.1
Description
Our system’s architecture (Fig. 1) is an Intelligent Language Tutoring System (ILTS) that runs on the Facebook platform[4]. It takes advantage of the provided social networking APIs of the Facebook platform to handle basic web application tasks such as user account authentication, data persistence through the Graph API, and social analytics.
Fig. 1. Architecture of ILTS
3.2
Architecture
Our system is a multi-tiered client-server architecture which consists of the user interface (the Facebook application), the Facebook server, and the application
4
User Modeling for Language Learning in Facebook
server which hosts the ILTS modules: Intelligent Tutoring/Teaching Model, the Student Model, and the Domain Model. 1.User Interface The User Interface is the Facebook application. In the Facebook platform[4], the application runs on a Canvas Page, which contains the HTML, JavaScript, and CSS. When the user requests for a page, that request is sent through the Facebook server and is loaded back and rendered on an iframe on that page for user viewing. Then the user interface renders an adapted content generated by the tutoring module strategy for the said user. 2.Facebook Server The Facebook Server acts as an intermediary of the application with the user. The user interacts with the Facebook application, which sends the request to the App server through the Facebook server. And the feedback is sent through the same path as discussed in[14]. 3.Application Server This hosts the core modules of the proposed system, namely the Tutoring/Teaching Model, Domain Model, Student Model. The Tutoring/Teaching Model includes the Advice Generator Component. All the core modules interact with a database server, which contains the domain representation, the student models, and the bug libraries. a. Teaching Model This module determines the pedagogical strategies that structure the interaction with the student[13]. It decides what item to teach next, what problem to give next and how to correct the bugs. Firstly, the student may start by studying the domain theory and then proceeding with the evaluation section, which consists of exercises in the form of multiple-choice questions. In the evaluation section, the system provides advice to students on preventing errors. The system evaluates the students answer and delivers the appropriate feedback, namely a proposal of revising the theory. In each cycle, the said student model is dynamically updated. This process is supported by the main component of ILTSs, which is the intelligent error diagnosis[17] which makes use of the bug library. b. Advice Generator Component The advice generator component is activated in the evaluation section before the student answers the multiple choice questions. Initially, the system gathers information about each student from his/her Facebook profile and from the preliminary test. When the student is about to answer the multiple choice exercises, the system offers him/her advice in order to prevent him/her from committing error. In this way, the system provides advice in preventing students errors and ensures the integrity of the learning process. c. Domain Model This module describes the necessary knowledge for the problem domain[13] and of the correct solution process[8]. In language learning, this module defines all the grammatical structures through what we can call a concept, which we can write as production rules. Each concept is part of a course unit, which can be a theory, an example, or an exercise as described in [9]. In addition, each course unit includes meta-descriptions such as level of difficulty and student cognitive level. Aside from the core concepts, this module also contains the bug library component, which is described next. d. Bug Library Component This is the library of the mal-rules in the chosen domain topic [13] [8]. In the application domain, this refers to the common or
User Modeling for Language Learning in Facebook
5
possible mistakes in learning conditional grammatical structures in both language domains. This can also be expressed in production rules and is used by the tutoring module particularly in the intelligent error diagnosis. e. Student Model There are two phases of the student modeling: initial phase and the subsequent phase. The student model is initialized by gathering information about the user and by taking the preliminary test and is updated through all the interactions in the learning process. In the application domain, the Facebook user profile is the basis of the initial student model. Information concerning the user, such as the age, the country of origin and residence, the knowledge background and the number of spoken languages, are drawn from his/her Facebook profile. Each student will also take a preliminary test to assess the level of knowledge in the application domain. The aforementioned preliminary test will use the English language so that each student will be evaluated solely on his/her knowledge in the application domain. For this application, it is assumed that users are well-versed in the English language. Based on the students performance in the preliminary test and the information gathered from his/her Facebook profile, the system will assign him/her into one of the four categories, namely: novice, intermediate, advanced, expert. Hence, at the start the system is able to gather personal data, knowledge of the domain if any, and student characteristics that will be helpful in initializing each students model. The stereotype and overlay techniques in classifying users are also applied[15] because it is taken in one single observation (as the case in the initialization phase), represents a model of the user as a subset of the expertise model. Subsequent phase includes the multiple observations obtained during the interaction process. This helps in constructing a more reliable model using inductive methods like Bayesian networks. During the learning process, this module keeps a historical log of the students weakness and progress[17].
4
Objective and educational usage of Facebook
Social networks, particularly Facebook, attracted great number of users in a short span of time [22]. Furthermore, it is highly considered as an educational tool because of its beneficial features such as enabling peer feedback and collaboration or either interactivity and active participation. It can enhance informal learning and support social connections within groups of learners and with those involved in the support of learning. The following model (Fig. 2) is constructed to shed light on the adoption of Facebook platform for our application along with its educational usage, by providing [21]: a. Ease of access: The ease of use of many social networking services such as Facebook, can provide benefits to users by simplifying access to other tools and applications. b. Familiarization: A significant factor, which influenced the adoption of Facebook, is the little technical knowledge that a user should possess to use it due to its widespread use and common acceptance. c. Usefulness: Facebook enhances the individuals productivity. Moreover, var-
6
User Modeling for Language Learning in Facebook
ious opportunities, among which information sharing, collaboration and entertainment, influence the adoption of Facebook. d. Social influence: Given that Facebook is a social utility used by many people worldwide, social norms must have a significant role in individuals use of this tool [21]. People join Facebook in order to connect with several social environments or to keep the communication with their existing friends, while others become members of a group upon their friends invitation. Hence, this fact accentuates the perception that social influence plays a crucial role in peoples decision to take part in social networking. e. Peer feedback: Educational usage of Facebook for peer feedback consists of the enabling of communication among users/students so that they stay aware about significant information shared by others related to the curriculum. f. Cooperation: The idea of collaborative learning can undoubtedly be expressed through the use of Facebook. In this way, students can exchange ideas, help their peers and work together in order to enhance the educational experience. g. Knowledge sharing: A crucial aspect incorporated in the educational usage of Facebook is the exchange of resources, documents and useful knowledge concerning the curriculum taught. Furthermore, Facebook provides the additional possibility of multimedia sharing so that students may share with their peers audio, video, images, and other materials related to their curriculum.
Fig. 2. Adoption and Educational usage of Facebook
5
General overview of the system
The following figure (Fig. 3) are snapshots of the preliminary test, which aims to evaluate the students understanding and mastery of the subject matter and the exercise part of the lesson. In the preliminary test (left), the English language is used as the medium of instruction so that the student will be evaluated solely on his/her knowledge state in the application domain. Particularly, in this figure the student is asked to identify the conditional type of the sentence structure presented. Correspondingly, he/she then selects the correct answer from the given choices. In this way, the system attempts to cluster the students in order to better assist them in the educational process. The exercise part of the lesson (right) basically contains three fundamental components, namely the question, the choices, and the systems advice. In this case, the student is asked to translate
User Modeling for Language Learning in Facebook
7
a Filipino conditional structure into Greek. S/he picks from the choices given the best translation of the given conditional. The systems advice that appears, highlighted at the bottom, guides the student on what to be careful about. The aforementioned system advice is generated dynamically based on the students previous interaction with the application.
Fig. 3. Overview of the system
6
Conclusions and Future work
We have presented a user modeling architecture for language learning in Facebook. The related scientific literature showed that the use of SNSs, such as Facebook, as a platform for learning may further benefit the educational process, while user modeling offers personalization in language learning. Hence, we introduced a prototype Facebook application that can model the users for adaptive and individualized learning experience. Future plans include system evaluation to examine the degree of usefulness of the user modeling and error proneness components of our Facebook application.
References 1. Amaral, L., Meurers, D.:Conceptualizing Student Models for ICALL. In:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),Volume 4511 LNCS, pp. 340-344 (2007) 2. Antal, M., Koncz, S.:Student Modeling for a Web-Based Self-Assessment System.In:Expert Systems with Applications, Volume 38, Issue 6, pp. 6492-6497 (2011) 3. Dickinson, M., Eom, S., Kang, Y., Lee, C.M., Sachs, R.,:A Balancing Act: How Can Intelligent Computer-Generated Feedback be Provided in Learner-To-Learner
8
User Modeling for Language Learning in Facebook
Interactions.In:Computer Assisted Language Learning, Volume 21, Issue 4, pp. 369382 (2008) 4. Facebook Platform. Facebook Developers. February 5, 2012. http://developers. facebook.com/ 5. Ferreira, A., Atkinson, J.:Designing a Feedback Component of an Intelligent Tutoring System for Foreign Language. In:Knowledge-Based Systems, Volume 22, Issue 7, pp. 496-501 (2009) 6. Hiew, W.:English Language Teaching and Learning Issues in Malaysia: Learners’ Perceptions via Facebook Dialogue Journal.In:Journal of Arts, Science and Commerce (ResearchWorld), pp. 11-19 (2011) 7. Ho-Abdullah, I., Hashim,R.S.,Jaludin,A.,Ismail,R.:Enhancing Opportunities for Language Use through Web-based Social Networking.In:2011 International Conference on Social Science and Humanity. Singapore: IACSIT Press, pp. 136-139 (2011) 8. Mizoguchi, R.:Student Modeling in ITS. Osaka University, Japan: Institute of Scientific Research and Industrial Research. (1994) 9. Naganathan, E.R., Maheswari,N.U.,Venkatesh,R.:Intelligent Tutoring System Using Hybrid Expert System with Speech Model in Neural Networks.In:International Journal of Computer Theory and Engineering 2. pp. 1793-8201 (2010) 10. Piriyasilpa, Y.:See you in Facebook: The Effects of Incorporating Online Social Networking in the Language Classroom.In:Journal of Global Management Research, pp. 67-80 (2011) 11. Promnitz-Hayashi, L.:A Learning Success Story Using Facebook.In:Studies in SelfAccess Learning Journal 2, no. 4: pp. 309-316 (2011) 12. Ota, F.:A Study of Social Networking Sites for Learners of Japanese. Sydney: Japan Foundation Sydney. (2011) 13. Reiser, B., Anderson,J.,Farell,R.:Dynamic Student Modelling in an Intelligent Tutor for LISP Programming.In:Proceedings of the Ninth International Joint Conference on Artificial Intelligence. Pittsburgh: In Proceedings of IJCAI, pp. 8-14 (1985) 14. Stallons, J.:The Architecture of Applications Built on the Flash And Facebook Platforms.In: Adobe Developer Connection. (2011) 15. Tsiriga, V.,Virvou, M.:Web Passive Voice Tutor: An Intelligent Computer Assisted Language Learning System over the WWW. Advanced Learning Technologies. Madison, WI: Proceedings. In: IEEE International Conference on Advanced Learning Technologies, pp. 131-134 (2001) 16. Tsiriga, V., Virvou, M.:A Framework For The Initialization Of Student Models In Web-Based Intelligent Tutoring Systems.In:User Modelling and User-Adapted Interaction Volume 14, Issue 4, pp. 289-316 (2004) 17. Virvou, M.,Troussas, C.:Personalized Teaching of Multiple Languages through the Web.In:International Journal for e-Learning Security 1, no. 12: pp. 52-29 (2011) 18. Virvou, M. and Troussas, C.:CAMELL: Towards A Ubiquitous Multilingual ELearning System.In:CSEDU 2011 - Proceedings of the 3rd International Conference on Computer Supported Education, vol. 2, pp. 509-513 (2011) 19. Lenhart, A., Madden, M.:Teens, privacy, and online social networks. In: Pew Internet and American Life Project Report. (2007) 20. Ajjan, H., Hartshorne, R. :Investigating faculty decisions to adopt Web 2.0 technologies: Theory and empirical tests. In: The Internet and Higher Education, 11(2), 71-80 (2008) 21. Mazman, S., Usluel, Y.: Modeling educational usage of Facebook. In:Computers and Education, 55(2), 444-453 (2010) 22. Boyd, D. M., Ellison, N. B.: Social Network Sites: Definition, History, and Scholarship. In: Journal of Computer-Mediated Communication, 13(1), 210-230 (2007)
