Educational Impacts of the Intelligent Integrated Computer-Assisted
Language Learning (iiCALL) Environment
Harald Wahl
University of Applied Sciences Technikum Wien, Austria
Department of Information Engineering and Security
wahl@technikum-wien.at
Werner Winiwarter
University of Vienna, Austria
Research Group Data Analytics and Computing
werner.winiwarter@univie.ac.at
Abstract: The Intelligent Integrated Computer-Assisted Language Learning (iiCALL)
Environment is a Web-based platform that supports language learning integrated in specific
working environment like Web browsers or Email clients. Currently, the platform exists as a
prototype that implements a view learning cases. In future versions, iiCALL can support users to
train their context-related language expertise. Necessary skills like requirements engineering,
design of software architecture, implementation of the prototype, or dealing with standards in
NLP and e-learning: the integration of the iiCALL development in academic teaching offers
research-oriented and problem-oriented teaching and learning. Several technical and nontechnical skills are needed to implement the iiCALL environment. The paper gives an overview of
the educational impacts and shows the current results influenced by the teaching experiences.
Introduction
Especially in degree programs on a master level, research-oriented teaching plays an important role in
academic education. Our research deals with Intelligent Integrated Computer-Assisted Language Learning
(iiCALL), this is a language learning platform that additionally offers the possibility to use common working
environments like Web browsers or Email clients for learning. Development of the iiCALL environment requires
several competencies particularly in the field of information technologies like software programing, software
architecture design, or Natural Language Processing, as well as project management skills or the ability to work in a
team. The paper shows the experiences made by integrating research in academic education and describes the effect
with respect to courses designed by competence-oriented learning outcomes.
Research-based Teaching
The way we apply research-based teaching is based on concepts of (Dee Fink, 2003) which tends to result
in significant learning outcomes. The learning process starts with the definition of learning goals (based on research
issues) followed by the definition of teaching and learning activities. The feedback loop of periodic evaluation and
assessment helps students to adjust their activities to reach supposed learning goals, as illustrated in Figure 1.
Research-based teaching mainly faces goals of student-centered learning outcomes, which chiefly is meant
as building up knowledge and improving competences and skills in several disciplines. In some circumstances,
especially if students with specific previous knowledge are involved, research-based teaching can also benefit
research progress.
Defining
Goals
Research-based teaching
Feedback
and
Evaluation
Defining
Activities
Figure 1: Research-based teaching for significant learning outcome.
Learning Goals for iiCALL
To illustrate which learning goals are needed in the iiCALL research-based learning scenario, we should
take a closer look at the system overview of iiCALL, see Figure 2. Language learning is performed in common
working environments which appear, for instance, as plug-ins in Web Browsers or Email clients (cf. number 3).
These plug-ins communicate with the server using Web service technologies. At the server side, the core software
framework (see number 1) manages data exchange and is responsible for persistence purposes. Natural Language
Processing (NLP) tasks are fulfilled by the General Architecture for Text Engineering (GATE), a framework fully
implemented in Java which comes with already implemented NLP features and which can easily be extended (see
number 2). The evaluation of NLP toolkits and the decision process for using GATE in iiCALL can be viewed in
(Wahl et Winiwarter, 2010).
iiCALL environment
3
4
Workflow Engine
Platforms for integration
Web
1
2
LR
NLP
Apache Tomcat
Figure 2: The system overview of the iiCALL environment (Wahl et Winiwarter, 2011a)
Based on the requirements of iiCALL, i.e. the research goals of iiCALL, the main learning goals were
identified. Table 1 shows those goals and the corresponding competences and skills that students should gain to
reach them.
Learning Goals
Requirements engineering
Competences and Skills
Capability of problem analysis
Use case identification
Use case specifications
Applying the Unified Modeling Language (UML)
Software architecture
Knowledge of client-server architecture
Knowledge of n-tier architecture
Interface specifications
Data modeling
Prototyping
Implementation of Browser plug-ins
Integration of software framework
Implementation of Web services
Integration of persistence frameworks
NLP algorithms
Standards
Knowledge about NLP standards
Knowledge about E-Learning standards
Project management
Project leading
Team work
Table 1: The learning goals and competences of research-based teaching using iiCALL
Learning Activities for iiCALL
Learning goals are directly connected to learning activities. The activities are based on different methods,
starting from literature research, problem analysis, documentation, or prototypical implementation. The whole
learning process is chiefly oriented to the idea of Problem-based Learning (PBL). The problem, i.e. fulfilling the
goals of iiCALL, is divided into sub-problems which students are instructed to solve in teams. We started to include
iiCALL into education by discussing the idea of iiCALL. First activities belong to requirements engineering. Here,
teachers (normally in the role of coaches) act as “customers” to simulate a customer and contractor situation. Results
come up to functional and non-functional requirements. The corresponding use cases are identified and documented
following the UML standard for future implementation: Use case diagrams, sequence diagrams, and activity
diagrams support software development process. Relevant use cases in iiCALL are categorized as shown in Table 2:
Use case category
User profiles
Exemplary use cases
Create account; Login; Change profile data; Change
learning needs; Change language preferences;
Language Testing
Do language screening test; Do vocabulary trainer; Do
cloze test; Do social translation; Do grading test;
User progress
Check personal language skills level; Synchronize with
server; Re-do test; View personal statistics
Communication
Ask for help; Communicate using social media platform;
Contact native speaker; Open chat;
Table 2: Use case categories and exemplary use cases
Based on the specified use cases, technical specifications of the system had to be defined. Infrastructure was
provided to the students. Students themselves followed the task to design and implement the software architecture
for iiCALL. Therefore, different options were selected and evaluated. Client-server architecture and 3-tier
architecture as well as interface specifications were part of teaching. At the client side, software prototyping resulted
in a Mozilla browser plug-in. This plug-in tried to implement the use case “Do vocabulary trainer” which supports
very simple context-related language learning, see (Wahl et Winiwarter, 2012b). Standards play an important role in
the area of CALL, be it on the one hand e-Learning standards and on the other hand standards of NLP. Because all
sub-problems have to be solved in teams, students are forced to comly project management rules. Students can
choose between different project management models, like PMI or Scrum, comprehensive project documentation is
requested.
Feedback and Evaluation for iiCALL
The role of teachers in research-based learning can be compared to the teachers’ role in PBL. Teachers are
coaches that support students to find a way to solve a specific problem. In traditional PBL, the coach knows pretty
well how a problem can be solved. If PBL is used in research, it is important that students interact with persons
working on that research topic. Alternatively, the coaches themselves should actively work on it; see (Wahl et al.
2009). In the iiCALL research-oriented teaching, all coaches are familiar with the current state of research. Feedback
is given with respect to applicability in iiCALL. Discussions with coaches take place frequently; they should help
students to understand the integration in iiCALL and to adjust their current work.
Effect on Academic Education and on Progress of iiCALL
From the students’ point of view, research-oriented teaching offers the advantage that learning contents
always have practical relevance. In particular, the iiCALL research offers different IT-related sub-problems that
students can try to solve in teams. These teams follow project management methods and teachers appear in the role
of coaches. They assist and direct students. Due to the own character of research – innovation does not necessarily
mean that a solution exists or the way to the solution is previously known – research-based learning is suitable for
students who have already gained an advanced level of knowledge and former experiences. Hence, research-based
learning is suitable for students studying on a master level.
The initial effort to explain the research idea grows with the complexity of research. In iiCALL, language
learning, NLP, and semantics of languages had to be explained to IT students, whilst technical IT basics have already
been known. The challenge of iiCALL was given by understanding context-related language learning and the
abstraction of learning processes being transferred into IT. Students themselves were highly motivated while working
on iiCALL. Research is a possibility to show students real applications and bring them closer to the idea of
innovation. Due to the lack of long-time experiences, inputs and ideas that come from students can rarely support
directly the progress in research. It is up to the coaches to filter the work of students and identify useful sub-result.
References
Amaral L. and Meurers D. (2011). On Using Intelligent Computer-Assisted Language Learning in Real-Life Foreign
Language Teaching and Learning. ReCALL. 2011, Vol. 23, No 1, pp.4-24.
Antoniadis G., Echinard S., Kraif O., Lebarb´ e T., Loiseau M. & Ponton C. (2004). NLP-based scripting for CALL
activities. In L. Lemnitzer, D. Meurers & E. Hinrichs (eds.), Proceedings of eLearning for Computational Linguistics
and Computational Linguistics for eLearning, International Workshop in Association with COLING 2004. Geneva,
Switzerland: COLING, pp.18-25.
Antoniadis G., Granger S., Kraif O., Ponton C. & Zampa V. (2009). NLP and CALL: integration is working. In N.
Kubler ed. Proceedings of TaLC7, 7th Conference of Teaching and Language Corpora. coll. Etudes contrastives.
Bruxelles, Belgium.
Boulton, A. (2009). Data-driven Learning: Reasonable Fears and Rational Reassurance. Indian Journal of Applied
Linguistics 35(1), pp.81-106.
Buzzetto-More N. A. (ed.) (2007). Advanced Principles of Effective e-Learning. Informing Science Press, CA, USA
2007.
Callmeier U., Eisele A., Schäfer U. and Siegel M. (2004) The DeepThought Core Architecture Framework.
Proceedings of LREC 04, 2004, pp.1205-1208, Lisbon, Portugal.
Domjan M. (ed.) (2009). The Principles of Learning and Behavior. 6th ed., Wadsworth, CA, USA, 2009.
Dee Fink L. (2003): Creating Significant Learning Experiences, Jossey-Bass 2003.
Gamper J., Knapp J. (2002). A Review of Intelligent CALL Systems. Computer Assisted Language Learning, Volume
15, Number 4, October 2002, pp.329-342.
Greene C. E., Keogh K., Koller T., Wagner J., Ward M., van Genabith J. (2004). Using NLP technology in CALL.
In: InSTIL/ICALL 2004 Symposium on Computer Assisted Learning, 17-19 June, ISBN 88-8098-202-8, Venice,
Italy.
Huang C., Calzolari N., Gangemi A., Lenci A., Oltramari A., Prevot L. (2010). Ontology and the Lexicon: A Natural
Language Processing Perspective. Cambridge University Press, Cambridge.
Indurkhya I. (ed.), Damerau F. J. (ed.) (2010). Handbook of Natural Language Processing. Chapman & Hall/CRC
Machine Learning & Pattern Recognition.
Levy M. (1997). CALL: context and conceptualisation, Oxford: Oxford University Press.
Meurers D., Ziai R., Amaral L., Boyd A., Dimitrov A., Metcalf V., Ott N. (2010). Enhancing Authentic Web Pages
for Language Learners. Proceedings of the 5th Workshop on Innovative Use of NLP for Building Educational
Applications, NAACL-HLT 2010, Los Angeles.
Meurers D. (in press). Natural Language Processing and Language Learning. Encyclopedia of Applied Linguistics,
edited by Carol A. Chapelle. Blackwell. (available as PDF version from the authors homepage, http://www.sfs.unituebingen.de/~dm/publications.html, accessed on April, 8th, 2011)
Ott N. and Meurers D. (2010). Information Retrieval for Education: Making Search Engines Language Aware.
Themes in Science and Technology Education. Special issue on "Computer-aided language analysis, teaching and
learning: approaches, perspectives and applications", Vol. 3, No 1-2, 2010, pp.9-30.
Semple A. (2000). Learning Theories and Their Influence on the Development and Use of Educational
Technologies. Australian Science Teachers' Journal, Vol. 46, No 3, September 2000, p21-22, 24-28.
Wahl H., Mense A., Kaufmann C. (2009). Can PBL be used for Knowledge Building in the HealthyIO Research
Project? Proceedings of the 2nd International Research Symposium on Problem Based Learning (IRSPBL), 3-4
December, Melbourne, Australia.
Wahl H., Winiwarter W., Quirchmayr G. (2010). Natural Language Processing Technologies for Developing a
Language Learning Environment. Proceedings of the 12th International Conference on Information Integration and
Web-based Applications & Services (iiWAS2010), pp.379-386, Paris, France: ACM.
Wahl, H.; Winiwarter, W.; Quirchmayr, G. (2011). Towards an intelligent integrated language learning
environment. International Journal of Pervasive Computing and Communications, Vol. 7 No. 3, 2011 pp. 220-239
Wahl, H.; Winiwarter, W. (2011a). A Technological Overview of an Intelligent Integrated Computer-Assisted
Language Learning (iiCALL) Environment. Proceedings of the World Conference on Educational Multimedia,
Hypermedia and Telecommunications (ED-MEDIA) 2011, pp. 3832-3837, Chesapeake, Lisbon, Portugal, June 27th
– July 1st.
Wahl, H.; Winiwarter, W. (2011b). The Intelligent Integrated Computer-Assisted Language Learning (iiCALL)
Environment – Work in Progress. Proceedings 13th International Conference on Information Integration and Webbased Applications & Services (iiWAS2011), pp. 426-429, ACM ISBN: 978-1-4503-0784-0, Ho Chi Minh City,
Vietnam: ACM.
Wahl, H.; Winiwarter, W. (2012a). A Prototypical Implementation of the Intelligent Integrated Computer-Assisted
Language Learning (iiCALL) Environment. Proceedings of the 11th International Conference on Web-based
Learning (ICWL 2012), Sinaia, Romania, September 1 st -4th , LNCS 7558, ISBN 978-3-642-33641-6, pp. 328–333,
Springer-Verlag Berlin Heidelberg.
Wahl, H.; Winiwarter, W. (2012b). A Context-Related Vocabulary Trainer in the Integrated Intelligent ComputerAssisted Language Learning (iiCALL) Environment. Proceedings of the 14th International Conference on
Information Integration and Web-based Applications & Services (iiWAS2012), pp. 356-359, ACM ISBN: 978-14503-1306-3, Bali, Indonesia, December 3rd -5th
Watson J. B. (1913). Psychology as the Behaviorist Views it. Etext Conversion Project - Nalanda Digital Library.