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AI and education experts teamed up for a better way to prepare for tests. We believe the purpose of tests is to facilitate learning, not to stress test-takers.

OUR APPROACH

Shorter, yet deeper

Our Fast CAT algorithm adaptively selects a set of questions that can best assess a student’s test preparedness. It drastically reduces the time taken to evaluate student knowledge, while providing deep insights.

HIGHLIGHTS

Fueled by rigorous research

16+Research papers published

59+Patents registered

234Experts involved in creating R.test

332,100Data points used for training AI

Recognized at leading conferences

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aaai
acl-2022
naacl-2022
aied-2021
edm-2021
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neur-ips

RESEARCH

Shifting the paradigm through AI

Our AI lab creates new and better ways of assessing knowledge. Find out how we make assessments more adaptive, accessible, and reliable.

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The first step to getting good grades

Check out your current level with Fast CAT in 1/4 of the usual test time.

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AI knows your score better than anyone

See it, then you will believe it. The Score Prediction AI knows what score you will get.

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What you know vs. what you don’t know

Knowledge Tracing model opens up a data-driven way of preparing for tests.

Publications
  • Addressing Selection Bias in Computerized Adaptive Testing: A User-Wise Aggregate Influence Function Approach-thumbnail
    Addressing Selection Bias in Computerized Adaptive Testing: A User-Wise Aggregate Influence Function Approach

    Soonwoo Kwon, Sojung Kim, Seunghyun Lee, Jin-Young Kim, Suyeong An, Kyuseok Kim

    UPDATED: 23 AUG, 2023

  • No Task Left Behind: Holistic Student Assessment Framework based on Multi-task Learning-thumbnail
    No Task Left Behind: Holistic Student Assessment Framework based on Multi-task Learning

    Suyeong An, Junghoon Kim, Minsam Kim, Juneyoung Park

    UPDATED: 8 APR, 2022

  • GRAM: Fast Fine-tuning of Pre-trained Language Models for Content-based Collaborative Filtering-thumbnail
    GRAM: Fast Fine-tuning of Pre-trained Language Models for Content-based Collaborative Filtering

    Yoonseok Yang, Kyu Seok Kim, Minsam Kim, Juneyoung Park

    UPDATED: 6 MAY, 2022

  • Behavioral Testing of deep neural knowledge tracing models-thumbnail
    Behavioral Testing of deep neural knowledge tracing models

    Minsam Kim, Yugeun Shim, Seewoo Lee, Hyunbin Loh, Juneyoung Park

    Proceedings of The 14th International Conference on Educational Data Mining

  • Tracing knowledge for tracing dropouts: multi-task training for study session dropout prediction-thumbnail
    Tracing knowledge for tracing dropouts: multi-task training for study session dropout prediction

    Seewoo Lee, Kyu Seok Kim, Jamin Shin, Juneyoung Park

  • Condensed Discriminative Question Set Generation for Accurate and Reliable Exam Score Prediction-thumbnail
    Condensed Discriminative Question Set Generation for Accurate and Reliable Exam Score Prediction

    Jung Hoon Kim, Jineon Baek, Chanyou Hwang, Chan Bae & Juneyoung Park

    UPDATED: 1 FEB, 2021

  • SAINT+: Integrating Temporal Features for EdNet Correctness Prediction-thumbnail
    SAINT+: Integrating Temporal Features for EdNet Correctness Prediction

    Dongmin Shin, Yugeun Shim, Hangyeol Yu, Seewoo Lee, Byungsoo Kim, Youngduck Choi

  • Knowledge transfer by discriminative pre-training for academic performance prediction-thumbnail
    Knowledge transfer by discriminative pre-training for academic performance prediction

    Byungsoo Kim, Hangyeol Yu, Dongmin Shin, Youngduck Choi

    UPDATED: 12 JUL, 2021

  • Prescribing Deep Attentive Score Prediction Attracts Improved Student Engagement-thumbnail
    Prescribing Deep Attentive Score Prediction Attracts Improved Student Engagement

    Youngnam Lee, Byungsoo Kim, Dongmin Shin, JungHoon Kim, Jineon Baek, Jinhwan Lee, Youngduck Choi

    UPDATED: 1 JUL, 2020

  • Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing-thumbnail
    Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing

    Youngduck Choi, Youngnam Lee, Junghyun Cho, Jineon Baek, Byungsoo Kim, Yeongmin Cha, Dongmin Shin, Chan Bae, Jaewe Heo

    UPDATED: 1 FEB, 2021

  • BIGGER MISSION

    One step closer to equity in education

    David Loh

    AI Research Scientist

    We assess students not to judge the result, but to help them learn better throughout their learning process. We leverage AI to capture things that are unnoticed by humans.

    YJ Jang

    CEO & Founder

    To bring true innovation to education and address the exponential demand for personalization, AI is the key ingredient. And we are ready to lead this transformation.

    Jason Kang

    Content Lab Manager

    High-stakes testing has widened the education gap across socioeconomic lines. We developed R.test to help students overcome this barrier regardless of their backgrounds.

    Sam Kim

    Machine Learning Scientist

    I believe that the ultimate goal of education is realizing the highest potential of each student. Education should help students realize that they can achieve more than they think.

    Ju-ho Lee

    Education Minister and Deputy Prime Minister of South Korea

    AI-driven education is here to stay. And with the pioneering efforts of global leaders like the R.test team, it can become a reality for all students.

    AAAI

    Association for the Advancement of Artificial Intelligence

    The research quality is among the top 25% of all papers accepted to AAAI. This research will surely be popular in the next years.

    SoftBank

    SoftBank Investment Advisers

    They are driving a paradigm shift in education from a ‘one-size-fits-all’ approach to personalized instruction. We are delighted to support their vision for quality education.

    Jason Park

    AI Research Scientist

    What makes AI special in education is that it allows us to provide things that are tailored to an individual’s specific needs, the things that are potentially more costly.

    CONTACT

    Put your students on a path to success

    One of our missions is to support educational institutions and schools. Let us do all the diagnosing work, so you can solely focus on teaching and helping students improve. Find out how R.test can assist you.

    Get your score in 40 min!

    Just do 1/4 of a full test and get actionable insights.

    R.test is an AI-powered diagnostic test platform that evaluates student’s test readiness. Our mission is to get rid of inefficiency and inequality from test prep industry by making assessments more adaptive, accessible, and reliable.

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    contactus@rtest.ai

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