Authentic Learning with Ubiquitous-Ness
Authentic learning describes real-life learning by applying knowledge in various real-life situations and contexts. Learning experiences in authentic contexts are considered to be a precious resource for learning, particularly in foreign language learning. For instance, Gilmore stated that authentic materials and authenticity in foreign language learning opposes contrived materials of traditional textbooks, which typically display a meager and frequently distorted sample of the target language while authentic materials offer a much richer source of input for learners (Gilmore, 2007). Duda and Tyne addressed authentic materials as the valuable resources for target language input (Duda & Tyne, 2010).
Some studies gently suggested using authentic learning materials as an alternative to traditional textbooks. For example, according to Tomlinson’s review study, various English language teaching materials, particularly global course-books currently make a significant contribution to the failure of many learners of English to acquire even basic competence in English and to the failure of most of them to develop the ability to use it successfully (Tomlinson, 2008). An authentic learning style inspires learners of new languages to create their authentic artifacts while traveling, studying overseas, working overseas, etc. that to be shared with their world, which is not possible in the traditional textbook-based learning approach.
Over the past years, we have observed the massive development of sensing technologies (e.g., smart glass, lifelong camera, multi-touch interface, wearable smart tracker, and bluetooth) (Hasnine et al., 2018). These technologies made it possible to capture contextual information such as people, date, precise time, location, and theme regarding the learners’ usage of various ubiquitous technologies. By using such technologies, learners' authentic learning experiences can be tracked and recorded quickly. For instance, an international student, upon experiencing a culturally authentic content, records it in the system with its context information (memo), picture/video/voice-data, together with its textual information. Ubiquitous functionalities automatically track the learning location, time, and place (Hasnine et al., 2019).
In this way, a vast amount of rich educational big data on authentic learning experiences can be captured. Now the questions arise, a) how this vast amount of educational data can be used to improve next-generation education? Also, b) can learning analytics provide solutions to sharing and reusing those captured authentic learning experiences (i.e., logs) among a community of language learners having similar learning interests in the right way at the right time and place?
A learning theory-oriented approach may solve the problem by playing an impact on the learning process; however, it depends on many factors, including timing, quality of feedback, interaction level with the feedback tool and many more.