Language education currently benefits greatly from the Internet and other new technologies in that it allows instant sharing of materials and ideas. Both the learners and the teachers gain instant access to a variety of options suitable to their level of L2 practice. The focus here is to describe the initial stage of a larger research plan that aims at examining the state of freely accessible websites for language learning in thirty-three languages used in Europe and that from a user (learner) point of view. In this first stage, Content Analysis was used in order to find out in which categories the language learning websites have commonality. It is important to come up with a valid set of categories in order to carry out a further in-depth analysis planned for the second stage of the research. The initial results advocate thirteen different categories and indicate that crowdsourcing is not involved in any of them. This suggests that this method of sharing and creating language learning content and other information seems to be popular throughout commercial online courses, such as Babel, Busuu, and Duolingo. The free online language learning courses usually do not include such a feature.
One of the currently applied trends in L2 education is the
implementation of technology from various perspectives of
use. The application of computers and smart mobile
devices has played a key role for the last couple of decades.
In this context, the computer assisted language-learning
(CALL) approach has brought about many positives, such
as creating a stress-free learning environment; supporting
the development of various learning strategies, e.g.
individual learning; enabling the learning outside of the
traditional classroom; providing instant feedback;
monitoring learners’ progress; and promoting exploratory
and global learning
The present paper focuses on an existing content analysis
of existing language learning resources found online. The
analysis is conducted from a user (learner) point of view
and includes various websites or platforms in the teaching
of thirty-three languages from thirty-eight countries in
Europe that are currently being represented in the COST
Action enetCollect
They analyse the use of various recent applications and practices in blended learning amongst educators but do not focus on crowdsourcing. As a result, and without further conclusion based on their analysis, they only recommend using such tools in order to motivate others to incorporate such techniques and technology in their L2 practices. More recently, Kukushka-Hulme and Viberg (2017) similarly focused on MALL in the context of collaborative language learning. In their qualitative review of online publications of a five-year span between 2012 -2016, they conclude that such technologies may help learners to become exposed to shared materials about authentic local discourse and that done in a global collaborative manner online. The authors use the term collaborative work rather than crowdsourcing, even though some features described refer rather to the latter term. Social context is very important in L2 learning, especially with the reference to the exposure and use of the target language. The use of technology and related tools in language learning does not only depend on their availability and accessibility but also on the digital skills of both teachers and learners. Collaborative work within specific classroom tasks, or crowdsourcing activities incorporated within available online tools or learner activities in MALL can be beneficial, however, according to Kukushka-Hulme and Viberg (2017), there are still gaps in how mobile learning should be designed. The aboverelated research represents only a short review of relevant studies; other studies related to websites or platforms could not be found at present.
2.
The first step of this research refers to defining the language learning resources online. The term L2 websites has been preferred to platforms for reasons presented in the results section. When browsing the Internet, the initial search was based on L2 websites that offer teaching of those languages belonging to the member states of the Action. All research including typing keywords into the online browser Google Chrome was conducted in the English language, as it was a practical way of putting ourselves in the shoes of a general L2 learner searching for websites to learn various European languages. instruction as well as for practicing the exercises. In sixteen cases the online language websites offered more than one language of instruction. The tenth category created within the content analysis was marked as level in order to find out whether it was for beginners or advanced learners. Some of these sites provided classification according to the Common European Framework of Reference for Languages: Learning, Teaching, Assessment, specifically levels detected usually referred to A1, A2, B1. There were also cases that offered difficulty of tasks by levels, such as beginner, elementary, intermediate, and advanced. The eleventh category was labelled as ‘access’, which helped to categorise free access to websites. Over 83% of all included learning resources were of free access. The rest of them had some minor requirements for use. The twelfth category was added based on the aim of this research, i.e. to find out whether some of the websites use a crowdsourcing element. In regard to this the survey has demonstrated that the crowdsourcing features were not enabled within the content of inspected language websites from the user’s point of view. The last, thirteenth, category refers to the analysis of the content and is labelled as ‘additional information’. Here, the researcher could add remarks regarding additional material or bonuses offered by websites. These categories were recorded in an Excel spreadsheet for further analysis. The preliminary results are presented in the next chapter.
4.
The present paper has discussed an ongoing effort to find the state of language learning websites in thirty-eight countries in Europe. This research forms the initial part of a larger work in progress, which aims at two objectives, 1) to analyse the free L2 European websites to detect common categories and whether they include some form of crowdsourcing, and 2) an in-depth analysis of each category. This article concludes the first objective. Crowdsourcing has not been found in any of the analysed free online resources. This suggests that there is a difference between free and freemium (commercial) online resources, i.e. paid or partially paid L2 platforms are likely to include crowdsourcing. Further work suggests a second coder, i.e. another researcher conducting the same research and comparing results in order to double-check the classification of categories, and possibly expand the list and to carry on a deeper analysis of each category. After completing the second stage, we will be able to further describe the attributes of free L2 learning websites in Europe by providing examples and an overview of content analysis based on the thirteen categories described in this article.
This article is based upon work from COST Action enetCollect (CA 16105European Network for Combining Language Learning with Crowdsourcing Techniques) supported by COST (European Cooperation in Science and Technology).