How lexical data is transforming the future of EdTech

EdTech is one of the fastest-growing industries, known for AI tutors that adjust to a student’s pace, gamified apps that turn vocabulary practice into a five-minute daily habit, and platforms that give teachers real-time insight into who’s falling behind. What’s less well known is what actually makes all of that possible underneath the surface: lexical data.

Lexical data is the structured information about words, their meanings, forms, and how they’re used in context. AI systems rely on lexical data to understand and generate language. As digital learning tools become more sophisticated, lexical data is enabling platforms to deliver more personalized, effective, and engaging learning experiences in an accurate and trustworthy way.

Here are five ways that lexical data is driving the future of EdTech.

1. Personalized learning experiences

Picture a student running through a few minutes of vocabulary practice before school, picking it back up on the bus, and finishing a lesson at the kitchen table that evening. Across those scattered sessions, the app she’s using has built a detailed picture of which words she knows cold, which ones still trip her up, and how her vocabulary has grown over the past month. None of that happens by accident. It’s lexical data, the record of how a learner interacts with words and language, doing the work behind the scenes.

One of the biggest challenges in education is meeting the diverse needs of students. Traditional methods often struggle to address the varying levels of comprehension and learning styles in a single classroom. Lexical data is helping EdTech companies overcome this hurdle by powering adaptive learning systems that tailor content to individual students. These systems analyze a student’s interactions: what words they know, which ones they struggle with, and how they progress over time.

This data allows the platform to adjust the difficulty of materials and offer personalized feedback, ensuring that each student is challenged just enough to stay motivated without becoming frustrated.

2. Enhancing vocabulary and literacy

Lexical data plays a crucial role in vocabulary acquisition and literacy development. Digital tools that incorporate this data can introduce students to new words in context, helping them understand not just the definition, but also how the word is used in real-world situations. This contextual learning is more effective than memorization, as it builds a deeper understanding of language. Moreover, these tools can track a student’s vocabulary growth, providing insights that teachers can use to further tailor their instruction.

Accenture found that 75% of executives regard high-quality data as the single most valuable component of generative AI, ahead of the models themselves. In education specifically, that means the lexical data behind a platform, its accuracy, its breadth, its freedom from bias, matters as much as the tool doing the tracking. A platform can log vocabulary growth all day, but if the underlying data mislabels a correct usage as an error, or misses a legitimate variant, the growth it’s tracking isn’t real, and neither is the insight a teacher ends up acting on.

3. Anticipating errors before they happen

Language learners don’t make random mistakes. They make predictable ones, shaped by their native language and, often, by the dialect of English or another language they’re learning against. A platform teaching British English to one student and American English to another needs lexical data that actually distinguishes between the two, down to spelling, pronunciation, and usage, rather than treating “English” as a single undifferentiated dataset. This is where breadth matters: datasets covering 60-plus languages and their region-specific variants let a platform anticipate the specific confusion a learner is likely to hit rather than only correcting it after the fact.

4. Breaking down language barriers

Offering translations and definitions across languages sounds like a straightforward accuracy problem, but it isn’t. A word-for-word translation can be technically correct and still mislead a student, because idioms, register, and connotation rarely map cleanly between languages, and scripts add another layer entirely. This is also where cultural awareness earns its place alongside accuracy: sensitivity markers built into lexical data help flag content that isn’t age-appropriate or culturally respectful for a given learner, something a generic scraped dataset has no way to account for. Pronunciation carries its own version of this problem. International Phonetic Alphabet (IPA) transcriptions paired with genuine audio recordings, rather than machine-generated approximations, are what let a platform teach a learner to actually sound like a fluent speaker rather than a close guess.

5. Empowering educators with insights

Teachers are also benefiting from the integration of lexical data into EdTech. These tools provide educators with detailed insights into their students’ progress, identifying areas where individual students or the entire class may need additional support. By understanding which concepts or words students struggle with, teachers can adjust their lesson plans in real-time, offering targeted interventions that address specific needs. This data-driven approach not only saves time but also enhances the effectiveness of instruction, leading to better learning outcomes.

What this looks like in practice

Oxford Languages supports 60-plus languages and their regional variants, and that lexical data already underpins many products in the EdTech space, including Preply, Virrata, and Astrid. What connects all of them is the same underlying requirement: content that’s gone through genuine editorial curation rather than scraped from the open web, built on more than 150 years of lexicographic work.

Squircle is another example. The company built LookUp, an English dictionary and vocabulary-learning app for iOS, which pairs Oxford Languages data with features like spaced repetition, contextual example sentences, and conversational-style quizzes designed to check real understanding of a word.

“Ever since we partnered with Oxford in 2018, we’ve never looked back. Oxford Languages have powered our sophisticated vocabulary building and learning tools, helping us build state of the art, yet robust learning features. In a world where the veracity of data is increasingly becoming an issue, being able to get reliable, trustworthy definitions and examples that are constantly updated is a big positive.”

Vidit Bhargava | Founder, Squircle Apps

The future of EdTech

As these technologies continue to evolve, we can expect even more innovative applications of lexical data that will further enhance learning outcomes. From creating more engaging and personalized learning experiences to breaking down language barriers and supporting teachers, lexical data is set to transform education in ways we are only beginning to understand.

In the coming years, as the EdTech industry continues to grow, those who harness the power of lexical data will be at the forefront of educational innovation. They will be the ones transforming classrooms and learning environments, making education more accessible, effective, and enjoyable for students everywhere.