Who can apply
Submission details
Applicants must be ABD by the application deadline, meaning all coursework and comprehensive exams are complete and the dissertation proposal has been accepted.
Applications should be submitted online. Submissions for 2026 are closed.
2026
Application dates
Call opens
April 15, 2026
Proposal deadline
June 15, 2026
Applicants notified
September 1, 2026
Applying
What to send us
- 1
Basic contact information
So we can reach you about the outcome.
- 2
A research summary
Summary of the background literature that contextualizes the dissertation research
Clearly stated research questions
Description of the methodology employed
Expected results and potential implications for second language acquisition, educational technology, and related fields
Maximum of 2 pages, single-spaced, including references. Up to 2 additional pages of figures and tables may be included
- 3
Your CV
- 4
Your research supervisor's contact information
We may contact them to complete a brief survey regarding your advanced standing and likelihood of completion.
Recipients
Meet the award winners
We've recognized 13 graduate students for their stand-out research at the intersection of second language learning and educational technology. Check out the winners from past years below.
2026 recipients

Matt Malone
Linguistics
CUNY Graduate Center
“Beyond Indo-European: New Benchmarks and Synthetic Data Methods for Grammatical Error Correction in Turkish and Vietnamese”
Matt's dissertation research focuses on developing better tools for correcting grammatical errors in low-resource languages. While English has many sophisticated writing and grammar tools, languages like Vietnamese and Turkish have far fewer resources available. This project explores how we can build useful grammar-correction technology for these languages without relying on huge collections of writing that have been manually corrected by experts. Specifically, we use computer-generated examples of grammatical mistakes to train language models to identify and correct errors. We also investigate ways of determining which examples are most useful for training these models. By developing more effective methods for working with limited data, this research aims to make grammar technology more accessible to speakers and learners of Vietnamese and Turkish.
This dissertation work is being completed in collaboration with CUNY Graduate Center Computational Linguistics student, Zilola Samigjonova.

Soyeon Sim
Applied Linguistics & ESL
Georgia State University
“Human and AI interlocutors in L2 spoken interaction: A corpus-based study of phraseological and interactional competence”
Although voice-based AI chatbots are increasingly used for language practice, little is known about whether learners communicate with them in the same ways they communicate with people. Soyeon's research examines how the person, or technology, we speak with shapes the way we use a second language. Around 200 Korean university students learning English will complete short decision-making tasks with three partners: another English learner, a person whose first language is English, and a voice-based AI chatbot. Their recorded conversations will form a spoken-language dataset. Soyeon will compare the recurring word and sentence patterns learners use in each setting, as well as how they introduce and develop ideas and show that they are listening and understanding. By identifying similarities and differences across AI and human conversations, this dissertation aims to help teachers and researchers design speaking tasks that provide meaningful opportunities for learners to practice communicating in a second language.

Annika Wallander
Spanish Linguistics & Second Language Acquisition
University of Wisconsin-Madison
“How L2s VOCAL-ize: Understanding progress and goals through a Spanish vowel pronunciation intervention”
First-language (L1) English speakers often retain their speech patterns when learning Spanish as a second language (L2), which can pose challenges for learning accurate pronunciation. Target-like pronunciation of Spanish vowels is especially important for distinguishing words and communicating clearly, but educational technologies specifically designed to support the learning and practice of Spanish vowel sounds are limited. Annika's research focuses on VOCAL-ize, a pronunciation tool that was created to train Spanish vowels by giving learners visual feedback on their pronunciations and comparing them with those of a Spanish speaker. Through weekly pronunciation training over the course of a semester with beginner-level university Spanish learners, she is studying how different pronunciation feedback approaches affect Spanish vowel accuracy and communicative effectiveness. Learners also complete weekly reflections and surveys about their experiences, motivation, and pronunciation progress. Through these findings, Annika aims to understand the effectiveness and overall experience of visual feedback in Spanish vowel learning. She also hopes to contribute a novel, engaging tool to support vowel pronunciation and enable learners to strengthen their communication skills in Spanish.
2025 recipients

Sungeun Choi
Applied Linguistics
Northern Arizona University
“Comparing L2 Interactional Competence and Learner Experience in Oral Interactions with Embodied AI Chatbots versus Human Interlocutors”
Sungeun's research investigates the effectiveness of embodied AI chatbots (also known as “avatars”) as tools for second language learners to develop interactional competence, which is the ability to communicate effectively in real-time conversations. While AI offers a promising solution for language practice, we still know little about how this technology compares to traditional human interaction. This study directly examines how English as a Second Language learners' interactional competence differs when they interact with an AI chatbot versus a human partner. In addition to performance, the study will explore learners' perceptions of the experience, including their comfort, anxiety, and sense of connection. Seventy English as a Second Language learners at a university will participate in role-play tasks with both an AI avatar and a human. Their performance will be assessed and their feedback will be collected through questionnaires and interviews. The findings will provide valuable insights for educators and technology developers, aiming to enhance language education by effectively leveraging digital tools to help learners become more confident communicators.
2024 recipients

Hyun-Bin Hwang
Second Language Studies
Michigan State University
“Teacher support and persistence in app-based language learning out of class: A self-determination theory perspective”
Language learning apps offer great flexibility for learning new languages anytime, anywhere. Research consistently shows that the more people use these apps, the more language they learn. However, one major challenge with app-based learning is the high dropout rate among users. In his dissertation, Hyun-Bin explores what drives users to stick with language learning apps and how we can use these insights to encourage persistence in app usage. Korean adolescents learning English at school use the Mango Languages English for Korean Speakers course out of class to supplement their English classes for four months. While students are allowed to use the app as they wish, their teachers consistently provide various types of support to encourage sustained use. Hyun-Bin predicts that when teacher support meets students' needs in using the app, their app engagement will be enhanced, leading to more persistent usage and, ultimately, better learning outcomes. Pedagogically, the dissertation aims to understand how teachers can support young learners to autonomously use language learning apps beyond the classroom, insights that could help teachers build a learning plan integrating out-of-class app-based learning with in-class instruction.
The first Dissertation Award recipient to build the Mango app into the research project itself.
2023 recipients

Joanne Koh
Second Language Studies
Michigan State University
“Vocabulary learning through out-of-class extensive viewing in an EFL context: A longitudinal study”
Joanne's dissertation focuses on extensive viewing: prolonged and regular engagement with authentic second-language audiovisual materials outside of formal language classrooms. According to Joanne, extensive viewing has recently gained attention as a potential extramural activity for developing second-language vocabulary, particularly because of the growing availability of meaningful input through streaming platforms like Netflix. Joanne's project delves into how Korean learners of English naturally engage in extensive viewing in informal settings, in other words how they watch TV shows on Netflix. By tracking learners' viewing patterns, along with other extramural language learning activities, this project aims to explore how these practices influence vocabulary learning. Joanne predicts that extensive viewing will help learners improve their second-language vocabulary, which would mean that it's a great way for learners to take ownership of their learning in their own time. The implications? Learners are encouraged to watch more TV in their second language, especially if they are learning in a context that might not have enough meaningful input to promote vocabulary development.

Jonathan Malone
Honorable mentionSecond Language Acquisition
University of Maryland
“Toward A Theory-based Account of the Vocabulary Processing and Learning Benefits of Reading While Listening”
Jon's dissertation project focuses on how listening while you read in a second language changes the way you read and influences the learning of new words. Learning a new word involves learning information about both how it sounds and how it is written, which suggests that reading while listening may help vocabulary learning. Indeed, previous research has suggested that learners benefit from engaging in multiple modalities (reading, listening, watching videos, viewing images) when learning new words from context. Many language learning apps provide learners with the opportunity to both read and listen to new language, often simultaneously, but little research has examined the way this simultaneous presentation of multiple modalities impacts real-time reading behavior. This study aims to better understand the impacts of reading while listening by examining the eye movements of English language learners while they read a 7,500-word short story in English, determining how closely learners follow the audio while reading, and investigating the relationship between looking at and learning new words.

Xinying Zhang
Honorable mentionCollege of International Studies, Shenzhen University, China
“MALL Acceptance and Engagement”
The emergence of mobile technology has paved the way for personalized and self-directed language learning beyond the confines of the conventional classroom setting. This study aims to investigate Mobile-Assisted Language Learning (MALL) engagement among Chinese English as a Foreign Language learners in informal learning contexts, and to understand how MALL fits into the landscape of language learning. Through surveys, reflection journals, and interviews, Xinying found that a variety of factors influence MALL engagement among this group of learners, particularly related to device, social, and learner-related variables. In particular, results showed that learners primarily used mobile devices and appreciated the flexibility and convenience of MALL. And while learners preferred personalized, self-regulated learning, they also expected teachers to be more involved in supporting their self-directed learning and creating social communities of learners to facilitate sharing and communication across classes and proficiency levels. Overall, this study demonstrates that MALL influences the informal learning practices of EFL learners, and provides insights into how and why learners use MALL, what works for them, and what would make the MALL experience better.
2022 recipients

Diana Velázquez-Lopez
Spanish & Portuguese Studies
University of Florida
“The role of technology-mediated feedback in the acquisition of phonology”
Diana's project explores how different types of feedback, speech recognition versus visual feedback, can be used to improve pronunciation in a second language. This study also compares two different groups of learners: second-language learners who primarily learned Spanish in the classroom, and heritage-language learners who were primarily exposed to Spanish at home. In the study, students enrolled in Spanish classes receive pronunciation instruction and practice with either automated speech recognition or visualization tools. Learners' pronunciation abilities are tested, as well as their attitudes toward pronunciation and the training tools that they used. This study has the potential to shed light on how different technologies benefit different learner populations, which has important implications for curriculum development and educational technology for language learning and teaching.

Lillian Jones
Hispanic Linguistics
University of California, Davis
“The Task is in the Text: Texting and L2 Oral Fluency”
Lillian's dissertation project examines whether and how text messaging can help learners become better second-language speakers. In this study, Spanish learners complete weekly interactive tasks with a partner, either via WhatsApp messaging or face-to-face Zoom sessions. Their speaking fluency is measured throughout the study to compare how effective the two types of communication are for second-language learning. Interestingly, previous research has shown that written practice may help with spoken proficiency, known as a positive cross-modality effect, so the text messaging group may be expected to do at least as well as, if not better than, the face-to-face group. This study paves the way for language teachers to incorporate colloquial communication tools, like WhatsApp, into the formal language curriculum in a way that is effective and engaging for learners.

Xi Chen
Communicative Sciences and Disorders
New York University
“Real-time Pitch Biofeedback in Second-Language Tone Production: Effectiveness and Predictors”
Tone languages such as Mandarin and Cantonese use variations in vocal pitch to distinguish word meanings, which can be a challenge for people learning these languages. Xi's study investigates the effects of a technology-enhanced training technique, real-time pitch biofeedback, for English speakers learning to produce Mandarin tones. As they practice producing tones, learners can view and compare a visual representation of their own pitch contours with those of a native speaker. This study will compare this innovative real-time pitch biofeedback training to a more traditional imitation approach. Additionally, the study examines how learners with different abilities respond to different training conditions. This research will provide evidence on the effectiveness of a computer-assisted speech training technique in second language pronunciation learning. It also represents a step toward a personalized learning approach that optimizes training conditions for individual learners based on their abilities.
2021 recipients

Yingzhao Chen
Second Language Studies
Michigan State University
“Comparing L1 and L2 glosses in vocabulary learning from digital reading”
This study explores whether and how providing definitions of words during reading facilitates second language vocabulary development. Learners will read an English novel with some words underlined. When they click on the underlined words, definitions, or “glosses”, will be provided in either the learners' first or second language. Learner engagement, meaning clicks and time spent on each gloss, will be logged. After reading, learners will indicate how and why they used the definitions (for example, to aid in reading comprehension or to learn words), and evaluate how useful they found them. In addition, learners will be tested on the accuracy and speed with which they recognize and recall the meanings of the words. This study can inform the design of materials for teaching vocabulary through reading in computer-mediated environments.

Natalie Amgott
Second Language Acquisition & Teaching
University of Arizona
“Implementing and evaluating multiliteracies in college French: A nested case study”
This project evaluates a new undergraduate French curriculum that leverages resources like news articles, films, music, and social media as the central texts. Students design projects, such as satirical articles and animated poetry in French. Preliminary results show that study abroad students in Paris learned French by using multiple modes (photos, videos, music, text, voice) that allowed them to improve their vocabulary, grammar, and pronunciation. Additionally, students in intermediate French courses at their home university felt motivated by opportunities to create critical social justice connections and develop a growth mindset while designing digital projects. This project also includes a program evaluation, which revealed that the new curriculum fostered collaboration and communication within the French program. This dissertation has the potential to inform best practices for incorporating digital projects into language courses, while also establishing guidelines for evaluating and implementing a curriculum during times of crisis, like the pandemic.
Be first to know when the next call opens
Submissions for the 2026 cycle are closed. Email research@mangolanguages.com and we'll tell you when the next one opens, or work with us in the meantime.
