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Editorial

Published online by Cambridge University Press:  29 July 2021

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Abstract

Type
Editorial
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of European Association for Computer Assisted Language Learning

As many of us complete a full academic year of online teaching, the readers of this journal may feel grateful for having been slightly better prepared for this than some of their colleagues. Whether or not computer-assisted language learning (CALL) is “better” than teaching face to face (see the editorial of the May 2020 issue of ReCALL) is a question that became temporarily redundant last year; we had no choice but to teach online, and foreign language teachers may have looked to CALL tools for help. As we cautiously and judiciously return to classrooms around the world, we may well ask ourselves which elements of this dramatic development might be worth keeping for “the new normal” yet to emerge. Perhaps it is the improved esteem of our immediate natural surroundings or our new cooking skills and healthier eating habits that are most worth keeping, but maybe there are also some elements of online teaching that are worth integrating into our toolbox for the future. The first paper in this issue by Ciara Wigham and Müge Satar is one that should interest those who found giving instructions to students on Zoom difficult to get used to. Their single case study of an experienced online teacher’s way of using the chat function to give instructions where in the traditional classroom a handout might have been distributed is an instructive illustration of bimodal communication and includes a list of clear and easily implementable advice for teachers.

Next, we have a series of papers that all concern various stages of the writing process. The first in this group is a study that took place in a process writing framework. Mohammad Hassanzadeh, Elahe Saffari and Saeed Rezaei investigate the impact of concept mapping on lexical diversity in learners’ essays, combining features from the macro and micro level in their study, and find no effect on their lexical diversity measure. Perhaps, after planning their essays, their learners should consider using another CALL tool, one to look up collocations, in one of the revision stages of writing. In the next paper, Shaoqun Wu, Alannah Fitzgerald, Alex Yu and Zexuan Chen take a “big data” approach to research on user data gleaned from the Flax system, a website for data-driven learning, over a period of two years. Their findings point to the need for more depth of vocabulary knowledge for learners rather than simply adding more words to their lexicon. After learners have drafted their texts, they are ready for some feedback. This is the stage that the study by Cédric Brudermann, Muriel Grosbois and Cédric Sarré explored. They looked at the effect of corrective feedback with follow-on micro-tasks for the learners. Their system uses the Louvain error typology (see Dagneaux, Denness & Granger, Reference Dagneaux, Denness and Granger1998) as the basis for a teacher-friendly list of canned feedback messages, in effect a kind of computer-assisted corrective feedback driven by the learners’ human tutors. Such a system is clearly more efficient for lexical errors than fully automated error feedback. Fully automated writing evaluation systems provide targeted help for second language writers, mostly on grammar and punctuation issues. These systems, although still far from perfect, have come a long way from the late 1990s (see the special issue of ReCALL edited by Schulze, Hamel & Thompson, Reference Schulze, Hamel and Thompson1999), when grammar checkers had barely been adapted to users who were not proficient speakers already. In the fourth paper on various stages of the writing process, Aysel Saricaoglu and Zeynep Bilki investigated the voluntary use of Criterion, ETS’s automated writing evaluation system, by students in English-medium courses, who are expected to write in English. This is a good example of action research that shows how NLP (natural language processing) tools are becoming normalized because learners can see the benefit almost immediately.

The penultimate paper in this issue is a narrative review of a section of MALL (mobile-assisted language learning) by Hongying Peng, Sake Jager and Wander Lowie. The authors found evidence for a newness effect, familiar from CALL generally, and interestingly a larger effect size for individual than for collaborative learning. With the first major monograph on MALL about to appear (Stockwell, Reference Stockwell2021), this meta-analysis gives an insight into the most urgent questions in this area of CALL, including the development of a theoretical framework specific to MALL. Concluding this issue is a paper on guerrilla fan translation, an area author Boris Vazquez-Calvo calls a “very special form of CALL in the digital wilds”. This is an exploratory case study on the practices game fans engage in when translating the captions of a video game from English into Catalan while respecting the space restrictions and cultural norms given by the gaming context. The lay translators use various (CALL) tools and negotiate their path to the best translation – activities that give rise to metalinguistic discussions, communication about terminology and incidental language learning. As translation is making a comeback in language teaching, and even tools such as Google Translate are no longer banned in many classrooms, this kind of study will surely find some interested readers in the CALL community.

Several studies in this volume present empirical data that was collected on learners’ voluntary use of CALL tools, where there is no control group that had the same amount of time on task as the experimental group. The MALL meta-analysis found a lack of studies on the effectiveness of voluntary learning where time on task is not a variable that can or even should be properly controlled. Surely this is an area worth investigating in today’s world where more and more (language) learning takes place outside of a traditional classroom.

References

Dagneaux, E., Denness, S. & Granger, S. (1998) Computer-aided error analysis. System, 26(2): 163174. https://doi.org/10.1016/S0346-251X(98)00001-3 CrossRefGoogle Scholar
Schulze, M., Hamel, M.-J. & Thompson, J. (eds.) (1999) Language processing in CALL. ReCALL special publication (Proceedings of a One-Day Conference “Natural Language Processing in Computer-Assisted Language Learning” Held at UMIST, 9 May 1998, Organised by the Centre of Computational Linguistics, UMIST, in Association with EUROCALL). Hull: CTICML.Google Scholar
Stockwell, G. (2021) Mobile assisted language learning: Concepts, contexts and challenges. Cambridge: Cambridge University Press.Google Scholar