16.3.3 Adaptability and Statistical Evaluation of Learners
The increased competition in online training platforms, requires that the platforms should be more adaptive and “intelligent”. This is achieved by providing to learners, fair and innovative evaluation methods, motivation for studying and suitable lessons for each learner individually. All these facilities, aim to boost the learning process.
In COMALAT platform we have selected to use fuzzy grading [22] for learners’ evaluation. The reason for this is that (a) The evaluation method can be more flexible about who will “pass” or “fail” a quiz and partially compensate for the absence of a human evaluator who could decide, for example, if a learner with a score close to the baseline – but below it – should pass taking into account the overall performance of the learner, (b) The system can determine automatically the difficulty of the quizzes based on all the other learners’ performances in a quiz. Fuzziness could be used to make a quiz quite easier (or quite harder) for a learner to pass it, depending on the difficulty characterization of a quiz based on all learners’ performance, without changing dramatically the overall learners’ performance scores.
Another important point that has to be addressed is the assignment of the “right” lessons to the learners depending on various characteristics of the learner. The main concern is the assignment of inappropriate lessons, which do not reflect learners’ overall interest or their needs; this may create serious problems such as poor commitment and underachievement. The output of association rules are logical expressions of the “if‐then” form and are very useful in uncovering the systematic effects of learners’ demographics (e. g. mother tongue, age, education, occupation etc.) on their performance on specific lessons. The correct interpretation of the extracted association rules leads to efficient decisions that improve not only the learners but also the entire educational environment, which is another aspect of intelligence. The ultimate goal of such a system should be the recommendation of the most suitable lessons for learners and the prediction of the effort that is needed in order to reach a specific level. The application of Association Rules, however, requires a large amount of data, which means a long‐term collection of information from participating learners. At the time of authoring the book chapter, while the platform is under development, such data are not available.
16.4 Digital E‐Learning Materials in COMALAT
From the introduction of CALL (Computer Assisted Language Learning) concept in the 60’s, the pendulum moving from enthusiasm to skepticism in the language teaching community has not stopped swinging, despite the normalization process of the ever‐increasing‐reborn technologies and the arrival of a new generation of teachers, researchers and, of course, language learners. The author of the concept of normalization, Stephen Bax, talks, in a later revision, about poles of “awe” and “fear” towards technology, and admits some excesses of optimism as to the positive‐only effects of technology in education [23]. It seems unnecessary to review again the many benefits CALL or TELL (Technology Enhanced Language Learning, in Walker and White terms [20]) bring to both language learners and public institutions in the search for intercultural and multilingual citizenship, but to enter into the discussion of how methodological issues in creating materials for COMALAT have been addressed, we must briefly mention a few of the limitations of CALL, particularly when dealing with self‐access, self‐study materials.
First of all, it is necessary to recall the need for an adequate methodological stand, since technology, as Bax warned us, cannot be the “single agent” [24] of change, nor, as Blake pointed out, it does constitute a methodology [25] for Language Learning in itself, as it has been sometimes misunderstood. Massive drop‐outs in self access courses, apps, and platforms make it obvious that their availability, cost‐effectiveness and practicality are not compelling or motivating enough for continued study, as the reports and analysis of different platforms by the Centre of Advanced Study of Language at the University of Maryland have proved [18, 19]. Proper curriculum design and adequate planning of the activities/materials will always be the key element, if we are really to live in the “constructivist phase” of “Integrative CALL”, according to the well‐known chronology proposed by Warschauer [26], or in the normalized, integrated CALL approach according to Bax’s terms. Otherwise, we will be using “new” technology only to insist on “traditional” learning materials. To accept some of the autonomous, self‐access learning limitations and to avoid promising what cannot be achieved we decided to strive for attainable goals within the scope of the COMALAT project: (a) a focus on adaptability and a search for consistency in development of language materials and their proper sequence of contents, (b) moderate ambition to include, together with the usual grammar and vocabulary settings, as much multimodal work/presentations, culture, discourse and strategic information/practice as possible, and (c) an attempt to face partially the major problem of how to include some interaction, meaningful communication and cooperative learning in a self‐study open‐source platform.
Second language Acquisition (SLA) research and most methodological standpoints would agree on the importance of strategic competence, meaningful communication and feedback in Language Learning [27, 28]. In fact, learning languages in the digital era has not (yet) become as easy and widespread as one would expect partly due to MOOCs, platforms, apps, online courses, etc. falling short on these aspects of Language Learning, even in the case of “blended” learning, and much more so in the case of independent learning, self‐study, autonomous learning, etc. (different terms have been employed – for a review, see Morrison [29]). How did the COMALAT project address those limitations? Here we will briefly explain the solutions proposed and attempted within the limited scope of a project such as COMALAT.
16.4.1 Strategies and Skills
As far as Strategic Competence is concerned, cues, presentations and activities in COMALAT try to not just deploy strategies but to stimulate reflection and explicit knowledge. Even today, experts are not sure about the effectiveness of Strategy Based Instruction or, more specifically, about how to assess scientifically that effectiveness, how to demonstrate, as stated by Macaro, that “strategic behavior is the key independent variable in bringing about higher proficiency” but there is certain consensus about the connection between strategy use and motivation and its relevance in language learners’ achievement [30]. In developing materials for Sakai, and due to the restrictions regarding individualized feedback, most strategic work has been included in presentations and activities, mainly in receptive skills (reading and listening). However, from the intermediate level on, a great deal of work has been done in including strategy‐based material in writing activities, and some peer assessment of strategies in the social module of the platform. A combination of top‐down and bottom‐up strategies has been sought in reading and listening materials, and of course, despite skill‐specific work and sections, a good deal of the course tries to integrate different skills in tasks, exercises and activities in the same way they would be integrated in real life situations and contexts. Thus, five sections were created for assessment, statistical analysis and adaptability purposes (Functions/Grammar, Listening/Speaking, Reading/Writing, Vocabulary and Language for Specific Purposes, this last one only being present in the Intermediate level) but the student moves naturally from one to the other depending on the content, not on the internal course /assessment structure. Each section includes three subsections, allowing for different contents and strategies to be focused on in a unit and for recurrence of both lexical and functional items to be considered. The learning path is, then, thoroughly designed, but adapted to a learners’ profile and performance after completion of each subsection, when the learner receives feedback and further practice on the sp
ecific contents he/she had more difficulties with, since one major characteristic in the materials to face the limitations is adaptability: COMALAT provides the student with a certain degree of fine‐grain feedback and opportunities for content‐specific extra practice and self‐monitoring that can foster his/her autonomy, tracking his/her progress, identifying weaknesses and establishing a basis and an impetus for further learning. Extra practice, when completion is not satisfactory, does not mean here repeating the same exercises/sentences again but in a different order, as is the case in some self‐study apps or courses, trying to avoid discouragement and attrition issues and looking for “stickiness” [31], commitment and motivation. In productive skills, particularly from the Intermediate level on, some activities encourage peer‐correction and allow to partially compensate for the lack of corrective feedback an actual teacher would provide.
16.4.2 Meaningful Communication and Cooperative Work
There has been a move in research trends from the role of interaction and negotiation of meaning as an addition to comprehensible input to its evolution/inclusion in task‐based approaches [32]. Although there are open issues as to their weight in SLA, their being a panacea for all levels of proficiency, learning contexts and languages, their relationship to formal explicit knowledge, etc., hardly anyone would question the importance of meaningful communication, open‐ended activities and tasks, interaction and cooperative learning [33]. For this reason, these elements represent the biggest challenge for any self‐study material, and there is actually little evidence of this type of work taking place out of teacher‐driven courses. In COMALAT, we addressed this problem and the inevitable limitations of self‐study platforms mainly in two ways: (a) having meaning in mind as much as possible in grammar presentations and activities, reading/listening work, etc. trying to create the conditions, awareness and reflection to prepare for communication (and to keep the will and motivation to do so), and (b) including, from the intermediate level on, a social tool/chat available for learners. The social module allows a Student A to contact and communicate with a student B, native or highly proficient speaker of Student A’s target language and in turn learning Student A’s mother tongue. Participation in the social module of the platform is highly encouraged by part of the activities and materials, although cannot be assessed by the system, and some open‐ended activities are designed to be carried out cooperatively or with the help and peer correction of another learner. Finally, some chat/forum materials have been devised, to include community development and thus allow for some of the possibilities for Independent Language Learning that have been pointed out for the future, in environments, developments and directions we cannot/should not really envision or control [21]. In any case, we depart from a “multicompetence” point of view, and even if we assume some learners will not develop all skills to the same level, we would still be achieving interesting results in creating multicompetent plurilingual citizens, with different degrees or competence in different languages (including their mother tongue) for different purposes in different situations.
16.5 Conclusions and Future Work
COMALAT is a project that targets the acquisition of language skills from learners mainly wishing to pursue a career in another country. We discussed the platform under development for this purpose and we explained the rationale for selecting a specific platform that could be used as a base for the COMALAT project. We also discussed the digital e‐learning materials and their design philosophy. Since COMALAT has the goal of language learning for the European workforce it is highly relevant to enterprises in Europe because workforce mobility is a prominent goal of the EU. Furthermore, the materials will be provided as Open Educational Resources to allow the usage by interested parties at no cost. The platform itself will be provided with a permissive Open Source license which may allow the creation of a digital marketplace around COMALAT with related business and services that will be offered in the future by other parties.
References
1.
European Commission, “The Bruges Communiqué on enhanced European Cooperation in Vocational Education and Training for the period 2011–2020,” European Commission, 2010.
2.
N. Mittas, G. Kakarontzas, M. Bohlouli, L. Angelis, I. Stamelos and M. Fathi, “ComProFITS: A web-based platform for human resources competence assessment,” in 6th International Conference on Information, Intelligence, Systems and Applications (IISA), Corfu, 2015.
3.
A. Paramythis and S. Loidl-Reisinger, “Adaptive Learning Environments and eLearning Standards,” Electronic Journal of E-Learning, vol. 2, pp. 181–194, 2004.
4.
IEEE, “Learning Object Metadata standard,” IEEE, 2002.
5.
IMS Global Learning Consortium, “IMS Learner Information Packaging Information Model Specification,” 2001.
6.
Kontopoulos, E. et al., “An ontology-based planning system for e-course generation,” Expert Systems with Applications, vol. 35, p. 398–406, July-August 2008.Crossref
7.
Jia, Haiyang et al., “Design of a performance-oriented workplace e-learning system using ontology,” Expert Systems with Applications, vol. 38, p. 3372–3382, April 2011.Crossref
8.
D. Hauger and M. Köck, “State of the Art of Adaptivity in E-Learning Platforms,” 15th Workshop on Adaptivity and User Modeling in Interactive Systems, pp. 355–360, 2007.
9.
O. Zaiane, “Building a Recommender Agent for e-Learning Systems,” in International Conference in Education, 2002.Crossref
10.
J. Lu, “Personalized e-learning material recommender system,” in International Conference on Information Technology for Application, 2004.
11.
Minaei-Bidgoli, B. et al., “Mining interesting contrast rules for a web-based educational system,” in International Conference on Machine Learning Applications, 2004.Crossref
12.
Romero, C. et al., “Knowledge discovery with genetic programming for providing feedback to courseware author,” User Modeling and User-Adapted Interaction: The Journal of Personalization Research, vol. 14, no. 5, p. 425–464, 2004.Crossref
13.
A. Merceron and K. Yacef, “Mining student data captured from a web-based tutoring tool,” Journal of Interactive Learning Research, vol. 15, no. 4, p. 319–346, 2004.
14.
Freyberger, J. et al., “Using association rules to guide a search for best fitting transfer models of student learning,” in Workshop on Analyzing Student-Tutor Interactions Logs to Improve Educational Outcomes at ITS Conference, 2004.
15.
Markellou, P. et al., “Using semantic web mining technologies for personalized e-learning experiences,” in Web-based education, 2005.
16.
A. Ramli, “Web usage mining using apriori algorithm: UUM learning care portal case,” in International. Conference on Knowledge Management, 20005.
17.
K. Doughty and C. Nielson, “Rosetta Stone™ Evaluation Executive Report.Final Technical Report E.3.1,” University of Maryland, College Park, MD, 2008.
18.
K. B. Nielson, “Self-study with language learning software in the workplace: What happens?,” Language Learning & Technology, vol. 3, no. 15, pp. 110–129, 2011.
19.
Nielson, K. et al., “Learning foreign languages at a distance: Characteristics of effective online courses (TTO 32131).,” 2009.
20.
A. Walker and G. White, Technology Enhanced Language Learning: Connecting Theory and Practice, Oxford: Oxford University Press, 2013.
21.
H. Reinders and C. White, “20 years of autonomy and technology: how far have we come and where to next?,” Language Learning & Technology, vol. 20, no. 2, pp. 143–155, June 2016.
22.
&nbs
p; C. Law, “Using fuzzy numbers in educational grading system,” Fuzzy Sets and Systems, vol. 83, pp. 311–323, 1996.Crossref
23.
S. Bax, “Normalisation Revisited: The Effective Use of Technology in Language Education,” International Journal of Computer-Assisted Language Learning and Teaching, vol. 2, no. 1, April-June 2011.
24.
S. Bax, “CALL past, present and future,” System, vol. 1, no. 31, pp. 13–28, 2003.Crossref
25.
R. J. Blake, Brave New Digital Classroom, Washington, DC: Georgetown University Press, 2013.
26.
M. Warschauer, “Computer Assisted Language Learning: an Introduction,” in Multimedia language teaching, Tokyo, Logos International, 1996, pp. 3–20.
27.
R. Ellis, The Study of Second Language Acquisition., Oxford University Press, 2008.
28.
M. Celce-Murcia, Teaching English as a Second or Foreign Language, Boston: Heinle and Heinle, 2001.
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