Edtech Trends In Language Education

A must-follow list: 9 Game-changing EdTech Trends in Language Education to watch


Stay ahead of the game with these 9 game-changing edtech trends in language education. Don’t miss out on the latest innovations in language learning!

Table of Contents

When it comes to paradigmatic shifts in language education – or even education in general, I believe our largest takeaway over the last 5 years is related to educational technology (or EdTech in short). Language education is being reshaped, thanks to technology integration which was further expedited and accentuated by the pandemic.

At least within 2024, I know many of us have rode on the generative AI wave and devised amazing ways to utilise solutions enabled by large language models (LLMs) to transform the way we do our work and guide our students in learning a language. EdTech does offer fresh possibilities to educators and learners, and generative AI is only but one of the many trends that have fortified a strong position.

That being said, such trends are not mere fads. EdTech companies are still rapidly developing these technologies (for obvious reasons) that have the potential to profoundly influence the future of language education. Before ChatGPT, many of us might have heard little or use any LLM-enabled solutions. Today, most of us would have used at least one of the many LLM-enabled tools; and not just stopping at LLMs, as we might also have wandered into images and videos.

This article thus aims to keep track of the developments in EdTech for the benefit of our community. I’d commit to updating this article from time to time so that all of us can remain at the forefront of thinking about EdTech within language education. Ok, introduction done. Let’s discover the latest EdTech trends in language education as of the published or modified date on the page now.

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1. Artificial Intelligence

Ai In Language Education
Image generated by Bing Image Creator / Abstract image of a human brain connected to a network symbolising AI

In the last 2 decades, we have witnessed a significant surge in the number of AI-related publications on language education within academic journals (Huang et al., 2023). This shift reflects the evolving perception of AI as an important enabler in language learning. Indeed, the use of AI-enabled tools has become more widespread in language education, as educators and learners seek innovative EdTech solutions to turbo-charge the learning process.

“According to our results, the number of articles related to AI in language education showed an increasing trend over the period reflecting researchers’ growing interest in using AI tools to assist language learning.”

Huang et al., 2023 (Trends, Research Issues and Applications of Artificial Intelligence in Language Education)

Sure thing, while machine learning has taken flight to allow AI to be more potent today, we cannot expect AI solutions that are meant for use cases like autonomous cars to be adopted for language learning directly (yet). So, what are the main areas where AI has been leveraged to enhance language education?

  • Provides personalised learning content: Educational content for language learning tailored to an individual learner’s needs (e.g. proficiency, areas of strengths and weaknesses, interests, goals) can now be selected, curated or authored by AI to enhance engagement.
  • Translates given texts: AI-powered translation tools have been present for quite a while and is now even more accessible and intuitive to support second language or foreign language learning approaches which takes into account the first language.
  • Conducts conversations using chatbots: A whole wave of such chatbots have been made available and salient since the introduction of ChatGPT, which can be enhanced with text-to-sound plugins to allow students to practise their oracy skills. 
  • Enables intelligent language tutoring: Customised models can provide learning assistants or companions that act as tutors for our learners in our absence, especially those who are still in K-12 education or those that require additional support and guidance in the learning process.
  • Strengthens vocabulary acquisition according to the science of learning:  Through the application of AI, we can now incorporate and reiterate particular words at critical points in a student’s learning journey, thereby facilitating optimal vocabulary acquisition.
  • Facilitates formative language assessment: Certain platforms offer automated language assessment systems which can identify grammatical and structural errors in writing and speaking, thus providing foundational feedback to learners before we proceed to tackle more intricate language aspects with them.
  • Powers immersive language learning experiences: AI provides the backbone of EdTech in extended realities which then serves the immersive language learning experiences where our learners can access various communicative scenarios to apply their language skills and knowledge.

2. Personalised Learning

Boy Engrossed In Personalised Learning
Image generated by Air Brush / Boy engrossed in personalised learning activity

The concept of personalised learning is not novel to language education. Before EdTech was formalised as a term, most of us have understood the importance of optimising learning experiences which address the individual differences of our learners through Differentiated Instruction. However, we were constrained by time and resources which limited our implementation of personalised learning.

Thanks to recent innovations in educational technology, particularly the modality of digital learning and the data-processing prowess of AI, personalised learning has become increasingly attainable and efficient.  In a sense, personalisation is extended beyond traditional general customisation across broad categories (e.g. specialised remediation for a small group of learners) to addressing the intricate differences of our learners at scale. Adjusted interventions can be made on a wide range of domains based on such differences: learning objectives, pace, sequence, instructional approaches, content, resources, activities, feedback (Chen et al., 2021; Kerr, 2016).

So, what are the kinds of personalisation that we have observed that can potentially be scaled by EdTech? Below is the list adapted from the taxonomy proposed by Chen et al. (2021):

  • Personalised recommendations: Recommender systems which pushes appropriate learning material recommendations based on selected factors such as learning history, performance, current proficiency and learning goals, so that the cognitive load of processing new materials for our learners is optimised (i.e. “right” information at the “right” time and in the “right” way);
  • Personalised content: Ubiquitous generation of learning content that is personalised for an individual that may capitalise on the interest (thus to tackle motivation), learning opportunities (e.g. location-related lexical items to be generated, communicative context-related formulaic sequences to be practised), learning/leisure time, and abilities, thus affording the optimisation of authentic language learning for our learners;  
  • Personalised practice: More pervasive use of chatbots, online communities and virtual reality (VR) dialogues served on mobile devices for flexible language learning, especially on interactional skills (both spoken and written modalities), to cut down dependence on a physical human (such as us) for specific practices;
  • Personalised feedback and assessment: Emerging environments which support continuous adaptive diagnosis and monitoring of learning progress for our learners, with feedback modalities which are better received (e.g. visual dashboard of personal learning analytics, video-based feedback) and targeted interventions based on the feedback and assessment (e.g. vocabulary development when it is required, conversational practice on a selected topic).

“Language learners experiencing personalized learning generally showed improvement in learning gains and engagement, satisfaction with the personalized learning experience, and an increase in self-efficacy and confidence.”

Chen et al., 2021 (Twenty Years of Personalized Language Learning: Topic Modeling and Knowledge Mapping)

3. Mobile Learning

Group Of Diverse Students And Mobile Learning
Image generated by Bing Image Creator / Group of students engaged in learning on-the-go

I briefly touched on the trend of ubiquitous language learning afforded by EdTech in the earlier section. Central to this trend is the advancements in mobile technology, as it offers unparalleled flexibility and convenience, enabling learners to study with flexible schedules and not be constrained by location or space. It also allows us to capitalise on authentic opportunities of language learning that our learners can access without our direct involvement.

This trend is evidenced by the increasing number of presentations on mobile learning at language teaching conferences. Personally, I’ve also observed a surge in discussions and dissemination of information regarding mobile language learning on social media platforms, blogs, webinars, and digital resources.

So, what are some interesting applications of mobile learning in language education from which we can gather inspiration? Here is the list:

  • Using Augmented Reality (AR) for vocabulary acquisition: Applications have been developed to display vocabulary words in a target language with real-world objects and environments, allowing our learners to create meaningful connections and provides context for learning.
  • Using Google Translate as an omnipresent scaffold: Primarily a translation application, Google Translate has been upgraded over the years to become more efficacious in its key functionalities to support translation for different use cases, with particularly the image translation (e.g. using image recognition technologies to provide translation of printed words from images) and speech-to-text enabled translations (e.g. facilitating cross-lingual conversations) becoming an integral scaffold for learners trying to use a target language in authentic contexts.
  • Using instant messaging text platforms for on-the-go learning exchanges: Almost everyone with a mobile phone would have at least one instant messaging app on their phone (e.g. WhatsApp, WeChat, Telegram, Line), and these apps have been used extensively for conversation practice, individualised guidance, on-the-go image sharing with vocabulary, role-playing interactions, etc.
  • Using Open Education Resources extensively as and when needed: Instead of waiting for institutionally created/curated learning materials, we have learners guided by teachers to take advantage of the array of web-based open resources (including podcasts, news, videos, and e-books) as sources of naturalistic input to learn on-the-go (e.g. during commute) or at any spare moment;
  • Using Apps to support language learning: There is a wide range of apps that have been developed to specifically support mobile language learning, including Duolingo, Memrise, Mondly, and Babbel to name a few, by designing short bite-sized learning experiences to help busy individuals build up their proficiency in between pockets of time.

“Mobile learning lends itself to activities involving sustained language practice over time and learning beyond classroom walls, including exploration of authentic language problems and challenges in everyday life.”

Kukulska-Hulme, 2016 (Personalization of language learning through mobile technologies)

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4. Micro-Learning

School Kids Doing Science Tests At A Science Centre
Photo from Envato Elements / Learners doing micro-learning at different learning stations

I ended the last section by subtly introducing the concept of micro-learning, which is also a prominent trend within EdTech-enabled language learning as well as the wider educational landscape. In fact, micro-learning is indeed a trend very much propelled by mobile learning.

Microlearning’s essence lies in condensing lessons into focused, bite-sized segments versus lengthy, dense classes. The core idea is to chunk content into small, digestible learning units that learners can complete in less than 20 minutes (note that definition of this period can vary by institution or scholar). This contrasts with more traditional, lengthy lessons (e.g. 50 mins) that demand extended periods of concentration.

The efficacy of micro-learning comes from the part where brief and focused chunks of information mirror the way our brains naturally process knowledge. By breaking learning into smaller, bite-sized pieces, cognitive fatigue is minimised, allowing for more effective retention and understanding.

With these said, how has EdTech-enabled micro-learning shaped language education for our learners? Let’s see as follows:

  • Quick one-page content nuggets within digital flashcards: Digital flashcards usually contain either a one-page infographic, short paragraphs of words or sometimes just a single word with an image (both static and moving) to promote focused learning or practice on one word/phrase/grammatical rule at a time.
  • Intermittent short videos or quizzes: Accessibility and availability of many EdTech tools have made it possible for a traditional “lengthy” classroom language lesson to be broken up into various short segments, using intermittent short videos to tweak modality of learning and quizzes for quick check progress with immediate feedback.
  • Use of chatbots for short conversational episodes: Conversations with chatbots are generally characterised by short, focused exchanges rather than lengthy, complex dialogues (possibly due to human engagement needs and limitations of chatbot to stay coherent), and are thus apt to address immediate learning needs (e.g. targeted vocabulary, pronunciation tips) on demand.
  • Bite-sized learning episodes in language learning apps: Content in language learning apps is often packaged into small, manageable chunks focusing on specific skills or topics (e.g. testing users on word groups then revisiting areas of difficulty until mastery) and hinges on frequent short practice opportunities with immediate feedback, reinforcing material through spaced repetition.

“This advantage of just-in-time microlearning with smartphones could especially benefit the people who work outside in the field and have no time to join a long set of training courses, for example, mobile journalists, who need to gather and disseminate breaking news on the go and in a limited time frame.”

Lee, 2023 (Mobile microlearning: a systematic literature review and its implications)

5. Gamification

Group Of Students Engrossed In Educational Games
Image generated by Bing Image Creator / Learners playing an educational game in a classroom

Gamification is defined as the use of game design elements in non-game contexts to promote expected behaviours in our learners (Deterding et al., 2011). I believe most of us would have some experience with gamification, especially with wave that has gone through education over the last decade.

Notwithstanding such, I would also like to highlight that gamification is not strictly restricted to a digital environment. A traditional pen-and-paper classroom with only a blackboard/whiteboard can also be gamified by incorporating game elements within lesson designs. Personally, I have also implemented such mechanisms in my language classrooms for grade 7 and 8 learners by putting in place a group point system featuring leaderboards and a redemption system to foster a sense of camaraderie and motivation among learners.

Of course, with EdTech affordances, gamification designs can scale to a different paradigm. Digital games, for instance, allow for more interactivity, instant feedback, and adaptive learning mechanisms to be embedded, such that learners can be challenged at the optimal level (i.e. according to the Goldilocks Principle) to maintain the “flow” state of learning.

What are some notable manifestations of gamification in language learning as driven by EdTech? Below are a few for our reference:

  • Pervasive incorporation of gamification elements in language learning apps: Language learning apps such as Duolingo, Rosetta Stone, Babbel, Memrise, etc have developed interactive platforms that combine game-like activities with language exercises, on which learners can accumulate experience points, unlock progressively challenging levels, and attain virtual rewards, thereby instilling a tangible sense of achievement and advancement.
  • Extensive use of gamified quizzes in traditional classrooms: Gamified quizzes powered by platforms like Kahoot and Quizlet have almost become a staple in many language classrooms that have the privilege of enabling infrastructure in place.
  • Increasing use of gamified social media networks: Leveraging the flexibility brought about by social media networks, such as general used networks (e.g. Discord, WhatsApp, Telegram) or those that are specifically designed for educational purposes (e.g. Moodle, Google Classroom), more of us are actually using game elements to incentivise active participation and language use (e.g. increased active posting on discussions).

“The most frequently used gamification elements were feedback, points, quiz, digital badges, leaderboard, and reward, followed by progress bar, story-telling, challenge, videos, time limit, and competition.”

Zhang & Hasim, 2023 (Gamification in EFL/ESL instruction: A systematic review of empirical research)

6. Extended Realities

Boy Learning Using AR
Image generated by Air Brush / A boy working on a geography project using XR affordances

Extended realities (XR) encompass a wide spectrum of technologies that merge real and virtual worlds, offering immersive experiences. These technologies include virtual reality (VR), augmented reality (AR), and mixed reality (MR).

For sake of clarity, VR is a computer-generated simulation of an environment in which our learners can interact with in a seemingly real or physical way (e.g. plugging our learners into the virtual world); AR is a technology that superimposes a computer-generated image on our learners’ view of the real world through their devices; and MR is the merge of both VR and AR, thus existing somewhere along the virtual-physical continuum which allows the co-existence and interaction of both physical and digital objects. The ultimate gain in education is the possibility of a more immersive type of learning experience.

Put together, XR technologies contribute to language learning by providing immersive, engaging, and context-rich experiences which have led to better engagement and learning motivation, accessibility for different learner profiles and improved learning outcomes in terms of gains in language skills (Alsayed, 2023; Guo, Guo & Liu, 2021; Luo, Zou & Kohnke, 2024; Shen, Zhou & Wang, 2023; Tegoan, Wibowo & Grandhi, 2021). Below are some interesting applications of XR in language education:

  • Avatars engaging in various communicative contexts in a metaverse: Fuelled by the restrictions imposed on physical interactions during the pandemic, many of our language learners who were privileged enough might have spawned off avatars to find themselves interacting with other speakers of the target language in a virtual environment while taking on different personalities and professional roles.
  • Simulation of targeted communicative scenarios: Though not as pervasive, there were multiple projects in recent years which sought to create simulated environments (either completely VR or in MR) for language learners to role-play in targeted communicative scenarios (e.g. a tour guide bringing groups to sites of attraction, authentic role-play of different personas in a café).
  • Story-telling powered by XR: Applicable for development of both receptive and productive skills, story-telling can now be enhanced with XR elements to leverage or provide a wider range of semiotic resources for our language learners to interpret, negotiate or create meanings.
  • Transcending time and space for cultural immersion: Our learners can now also experience virtual trips or interact with cultural elements across space and time, such as museums and ancient cities, without leaving their classrooms or homes.
  • Vocabulary acquisition on-the-go: Applications have been developed to display learning materials of vocabulary words in a target language imposed on real-world objects and environments, allowing our learners to create meaningful connections to acquire novel words and lexical items.

“It is already apparent that AR and VR are not appropriate for all aspects of language learning, but in areas where they can make an impact—from teaching pronunciation through to honing intercultural competence—their potential benefits may be substantial for a wide range of learners with a wide range of needs.”

Pegrum & Lan, 2023 (Extended reality (XR) in language learning: Developments and directions)

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7. Digital Twin Technology

what is digital twin technology
Image generated by Adobe Express / A lady with her digital twin on a futuristic screen

Thus far, we might have sensed that many of our EdTech trends seem to overlap: AI and personalised learning, mobile learning and micro-learning, mobile learning and X. What if a single conceptual framework could merge all these technologies in an organic system? This is the essence of the digital twin technology, which I have discussed in detail in another article.

At present, digital twin technology applied in education is much more pervasive in other subject areas, especially for health, engineering and high-risk applied subjects (e.g. aviation). However, considering content-based language education approaches, digital twins can potentially be tapped for language learning to enhance language learning in different content areas.

Also, we might also have heard of personas created with assistance from GPT models, such as this example. To be frank, such LLM-generated personas are not strictly the digital twins that we may be excited about but they do provide a model on how digital twins can exist for language education where our language learners can interact with virtual doppelgängers of various authentic personalities in the target language.

“Having a digital twin of an educational journey can provide further insights and access to data at individual, group, and institution levels of analysis.”

Sylvester, Mines, David & Campbell-Meier, 2023 (Conceptualization of Digital Twins in an Education Services Environment: A Straw Man Proposal)

8. Virtual Exchanges

Two Classes Engaged In Virtual Exchange
Image generated by Bing Image Creator / Two classes of students across the globe engaged in a virtual exchange session

Interestingly, as I discussed about digital twins, I came across this video that talks about digital twins but in the context of twinning partnerships. The project mentioned in the video focuses on city partnerships between regions of different majority languages, presenting ample opportunities for language education.

Virtual exchange programmes have gained traction in international education in recent years (Lee et al., 2022). Typically, such programmes leverage EdTech affordances to bridge the gap between students from different regions, enabling collaboration and mutual learning in a virtual environment. The COVID-19 pandemic has further propelled the adoption of virtual exchanges, since global travel was curbed during that period, emphasising the need for accessible and inclusive global learning opportunities.

Undoubtedly, virtual exchange need not always take the form of communication and interaction in a metaverse. It can be simply through structured video-conferencing sessions or flexible networked exchanges between individual learners after the initial contact (e.g. contemporary chat pal).

The key idea, though, is that virtual exchanges have become more pervasive among institutions with resources, and language education has benefited from such initiatives since there are more authentic opportunities for target language use (Lenkaitis, 2021; Sevilla-Pavón & Nicolaou, 2022). The degree to which such virtual exchanges are effective in facilitating positive language learning outcomes remains to be further researched though (Rienties et al., 2022). 

That being said, some examples of virtual exchanges with focus on language learning include: students from schools from different countries working on a project (e.g. climate change project, promotion of local social justice) while using resources from different target languages; individual students from two countries partnering up and meeting weekly over a prescribed period to discuss on selected cultural topics in the target language; and facilitated or moderated conversations with participants from various countries in a target language within a MOOC (Massive Open Online Course).

“Virtual exchanges provided a context for intercultural communication to occur and an opportunity to internationalize the curriculum.”

Lenkaitis, 2021 (Virtual exchanges for intercultural communication development: Using can-do statements for ICC self-assessment)

9. Online Social Networks and Communities

Group Of Avatars In A Metaverse
Image generated by Air Brush / A large group of avatars of learners in the metaverse

Before I start on this section, I just want to highlight that virtual exchanges within literature generally refer to those that are facilitated by an establishment or institution. In a sense, our language learners usually depend upon us or the organisation that we are working for to coordinate and facilitate the exchange. This section about online social networks and communities, however, relates to a language learning experience that might be similar but is more bottom-up than top-down in terms of participation.

Engaging in online social networks and communities for educational purposes can be classified as a type of networked learning. This involves a group of individuals collaborating through inquiry and negotiating meaning, all facilitated by networked technology in an online learning context, with the ultimate goal of gaining knowledge on a shared subject matter (Networked Learning Editorial Collective (NLEC)., Gourlay, L., Rodríguez-Illera, J.L. et al., 2021).

How does this manifest in the context of language learning? Generally, it involves our learners been connected with other language volunteers or learners around the world through social media groups and communities. The types of learning are either typically learning content knowledge about the target language (e.g. specific lexical items, verbalisable grammar rules, formulaic sequences, cultural content) and practice of the target language use by using as a lingua franca with fellow learners or with volunteers L1 users (or native speakers).

EdTech-enabled platforms can prove to provide a lot of affordances to facilitate these processes other than just providing a platform. For instance, Discord offers many “channels within a server” which are like sub-groups within a community that allows language learners with particular interests or learning goals to interact and work together. The wide integration of bots powered by AI also facilitates more multimodal activities within the community. For more details, you can read my other article here. Most importantly, there are many language learning servers, usually centred on a target language.

Beyond that, there are also platforms that are designed specifically to facilitate uses of the target language with other international learners. Such platforms include Livemocha, Lang-8, HelloTalk, Busuu, etc all which boast “more than 13 million international users” worldwide (Lin, Warschauer & Blake, 2016).

“The utilisation of social networking tools can enhance learners’ motivations, encourage positive attitudes, and bolster learning outcomes.”

Yu, 2024 (A systematic review of motivations, attitudes, learning outcomes, and parental involvement in social network sites in education across 15 years)

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As the age of generative AI rages on, we cannot rest on our laurels to expect language education to remain as it is. On the other hand, we do not want to be caught stranded in the glitz factor of chasing technology trends with little knowledge of their efficacy in how we teach and learn.

To do that, we must adopt a mindset of “blended learning”: the key trends may come in waves and presents us a wealth of options. We should seek to “blend” them according to the fundamentals – our understanding of learning sciences pertaining to language learning.

The TPACK (Technological, Pedagogical, and Content Knowledge) framework advocates exactly that. With new technologies emerging, we should aim to update our technological knowledge. The decision whether or not to incorporate these technologies into our classrooms, however, hinges on our content and pedagogical knowledge. Technologies should only be introduced if they offer supplementary affordances or complete transformations that the status-quo educational approach cannot provide.

EdTech can be vital in making learning, especially for languages, more effective and motivating for our learners. I believe that the future of education continues to evolve in a way that leveraging technology will remain a staple. As EdTech progresses, let us hold strong to our fundamentals but stay open to observing the trends and experimenting with innovative approaches. 

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