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ILEIID 2025 | International Journal of Research and Innovation in Social Science (IJRISS)

ISSN: 2454-6186 | DOI: 10.47772/IJRISS

Special Issue | Volume IX Issue XXV October 2025

Unlocking Vocabulary in One Click: The Reedling Way a Smart AI

Approach to Enriching Language Learning

Annisa Amalia

, Endang Susilawati

, Yohanes Gatot Sutapa

1,2,3

Tanjungpura University

DOI: https://dx.doi.org/10.47772/IJRISS.2025.925ILEIID000080

Received: 23 September 2025; Accepted: 30 September 2025; Published: 07 November 2025

INTRODUCTION

In second language learning, vocabulary acquisition is still a constant problem because a lack of vocabulary

limits a learner's capacity to communicate, understand texts, and become fluent. Vocabulary is widely

recognized as a crucial component in language learning and communication, serving as the foundation for

understanding and conveying meaning (Tabassum & Naveed, 2024). Recent research underlines that

vocabulary is vital as it’s the foundation of all languages. This study investigates the use of an interactive

game-based method to teach vocabulary to EFL students (Tabassum & Naveed, 2024). Insufficient vocabulary

might make it difficult for students to understand real materials and communicate clearly.

Traditional approaches such as rote memorization, dictionary consultation, or static flashcards have long been

used to expand the student. While these strategies may help in recognizing isolated words, they often fail to

provide meaningful context. Furthermore, stopping frequently to look up definitions can interfere with the

reading process's natural flow and lower student motivation. Because of this, a lot of students think that

acquiring vocabulary is boring, disjointed, and unrelated to real-world communication.

Artificial intelligence (AI) and educational technology advancements in recent years have created new

prospects for language learning. Learners can interact with real literature using contextualized digital tools, and

they can also get adaptive support to increase their vocabulary. Prior research highlights the perceptions and

implications of Artificial Intelligence (AI) in the context of English as a Second Language (ESL) vocabulary

learning (Alharbi & Khalil, 2023). However, only a small number of studies have looked at how AI-driven

platforms might combine long-term retention with instant comprehension.

This study aims to make vocabulary building effective, relevant, and enjoyable. This study also addresses the

gap in Readlang, an AI-assisted reading tool for vocabulary enrichment. By offering one-click translation of

unfamiliar terms, automatic word storage, and spaced repetition flashcards. The objective of this article is to

analyze the pedagogical potential of Readlang and highlight its contribution to enhancing vocabulary learning.

METHOD

The present article employed a descriptive qualitative approach, as the purpose of the article is exploratory

rather than experimental. The purpose of this paper is to present and examine the pedagogical potential of

Readlang as an AI-assisted vocabulary learning tool.

The primary sources of data were drawn from two perspectives. First, a literature review was conducted to

situate Readlang within established theories of vocabulary acquisition. According to Richards (2015 cited in

Topal, 2025) Language proficiency relies heavily on vocabulary and syntax, and comprehending a document

requires extensive vocabulary knowledge. Readlang is an online e-reader where registered users can translate

words and phrases into over 60 languages.

The tool is user-friendly, with a simple layout and straightforward features: home, library, wordlist, and

flashcards. The home shows users the native language and target language that we learn, start a streak,

statistics of words and practice, and daily goal achievement. The library has three submenus (my text, public

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texts, and websites) displaying the texts users have read, target texts available in the public domain, and

websites where they can read by several websites that connect to Readlang, and users can also generate the

story, upload a text or audio in txt, epub, or a format available in Readlang. Word lists provide all translated

words, including context, pronunciation, translation, and source. Flashcards encourage users to practice certain

words and track their daily streaks. They also provide a table of reviewed things, including translation and

review time.

Second, user-based observations were conducted by observing learner interactions using Readlang while

engaging with English texts. During these sessions, students clicked on unfamiliar terms to get instant

translations, which were then automatically saved in a personal word bank and reviewed using AI-powered

spaced-repetition flashcards. Readlang's key advantage is its ability to work with any internet text, providing

access to real and unlimited content. This feature generates a personalized learning environment (PLE),

allowing language learners to adjust information to their interests and needs. This allows learners to read in

any language on any website, even if it's unfamiliar.

The investigation aimed to connect these observable experiences to theoretical frameworks. The study

specifically looked at how Readlang promotes contextual learning through authentic texts, enhances

intelligible input as indicated by Krashen, and improves long-term memory through frequent exposure and

review. The study presents a comprehensive assessment of Readlang's contribution to vocabulary enrichment,

learner motivation, and reading fluency by integrating theoretical ideas and user-based observations.

RESULTS

The findings of this descriptive qualitative study show that Readlang's integrated AI capabilities considerably

help with vocabulary acquisition and reading engagement. Observations and user feedback show that learners

have smoother and more effective reading processes since the platform reduces disruptions associated with

traditional dictionary use. The one-click translation technology enables students to rapidly understand foreign

terms without leaving the reading interface, ensuring fluency and focus throughout the work.

Furthermore, contextual learning emerged as one of Readlang's primary strengths. Engaging with actual

English texts allows students to absorb vocabulary in meaningful contexts rather than in isolation. Words

taught in this manner are more likely to be remembered and used in real-world interactions. Furthermore, the

tool's automatic vocabulary collection guarantees that each translated word is recorded in a personalized word

bank, which serves as the base for subsequent evaluation. The AI-based spaced repetition approach improves

long-term retention by reintroducing previously learned words at optimal intervals, which reinforces memory

consolidation.

Overall four key outcomes were identified:

1. Improved reading fluency – students no longer lose attention when they meet unfamiliar words.

2. Contextualized vocabulary acquisition entails learning from actual literature, which promotes a better

understanding.

3. Enhanced retention—the spaced-repetition flashcards improve recall and long-term storage.

4. Increased motivation and autonomy - when working with complex reading materials, students report

feeling more engaged and confident.

These findings indicate that Readlang efficiently blends comprehension and vocabulary development, resulting

in a balanced, learner-centered approach that is consistent with current theories of second language acquisition.

DISCUSSION

The results of this study are consistent with existing theories of second language acquisition, particularly

Krashen's information Hypothesis (1989, cited in Mehak Jawed et al., 2025), which emphasizes the importance

of intelligible information in supporting language growth. Readlang creates an environment in which input is

both relevant and comprehensible by allowing students to obtain rapid translations without disrupting their

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reading flow. This confirms Krashen's theory that effective learning happens when learners comprehend

messages slightly above their current competency level, with appropriate scaffolding to facilitate

comprehension. Readlang's one-click translation serves as scaffolding, allowing students to connect with

authentic resources that might otherwise be too difficult.

The findings are consistent with Nation's (2001 cited in Nation & Macalister, 2020) vocabulary learning

theory, which emphasizes the significance of both receptive and productive information, as well as recurrent

exposure for retention. Readlang's spaced-repetition system encourages systematic review, which improves

memory consolidation. By saving each translated word in a personal vocabulary bank, learners participate in a

continual cycle of exposure, recognition, and recall—all of which are necessary activities for long-term

vocabulary acquisition. This combination of input and repetition turns vocabulary acquisition from an isolated

job to a continuous, individualized learning experience.

However, the study notes one potential limitation: over dependence on translation may impede the

development of inferencing skills. As a result, Readlang should be used in conjunction with tactics that enable

students to derive meaning from context. Overall, Readlang demonstrates how artificial intelligence may

improve the balance of comprehension, motivation, and retention—all of which are critical components of

good vocabulary learning.

CONCLUSION

This study concludes that Readlang is a successful AI-assisted strategy to vocabulary enrichment in second

language learning. The technology overcomes the comprehension-retention gap by combining one-click

translation, automatic vocabulary storage, and spaced-repetition flashcards. Learners can keep their reading

skills while learning new words in authentic situations, resulting in deeper comprehension and better long-term

memory. The findings highlight the importance of contextualized and flexible learning environments in

encouraging long-term vocabulary expansion.

Readlang's pedagogical value comes from its capacity to mix contextual input, technology aid, and learner

autonomy. The platform supports Krashen's notion of intelligible input, enhances retention as defined by

Nation, and encourages self-directed learning, which is consistent with Schmitt's vocabulary building tactics.

As a result, it not only improves language skills but also creates a more interesting and inspiring learning

environment.

However, this work acknowledges drawbacks such as possible over-reliance on translation and the necessity

for guided training in inferencing methodologies. Future study could use experimental or mixed-method

methods to assess Readlang's long-term influence on vocabulary retention and reading comprehension across a

variety of learner groups. Overall, Readlang is an example of how artificial intelligence may serve as a catalyst

for innovation in language pedagogy, changing vocabulary learning into a more efficient, contextual, and

individualized process.

Keywords: Vocabulary Acquisition, Artificial Intelligence, Readlang, Language Learning, Digital Pedagogy

REFERENCES

1. Alharbi, K., & Khalil, L. (2023). Artificial Intelligence (AI) In ESL Vocabulary Learning: An Exploratory

Study on Students And Teachers’ Perspectives. Migration Letters, 20(12), 1030–1045.

www.migrationletters.com

2. Mehak Jawed, Dr. Kamran Ali, & Tanveer Ahmed. (2025). Exploring the Connection between Presence

and Absence of Krashen’s Theory on Learner’s Input and Affective Filters: A Triangulation Approach.

Journal of Arts and Linguistics Studies, 3(2), 1811–1839. https://doi.org/10.71281/jals.v3i2.305

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4. Tabassum, A., & Naveed, A. (2024). Interactive strategies for Enriching English as a Foreign Language

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