Why Choose Our SAT® or ACT® Test?

Make assessments

Adaptive, Reliable, Accessible

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.

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

Research papers published

Patents registered

Experts involved in creating R.test

Data points used for training AI

Recognized at leading conferences

aaai
acl-2022
naacl-2022
aied-2021
edm-2021
lak-21
edm-2020
csedu-2020
acm-las
neur-ips
aaai
acl-2022
naacl-2022
aied-2021
edm-2021
lak-21
edm-2020
csedu-2020
acm-las
neur-ips

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

    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.

    ⓒ 2023 Riiid, Inc. All Rights Reserved

    521, Teheran-ro, Gangnam-gu, Seoul, Korea

    contactus@rtest.ai

    College Board® is a trademark registered by the College Board, which is not affiliated with, and does not endorse, this website.

    Neither Riiid, Inc. or R.test is affiliated with College Board® and do not have access to College Board's proprietary data.

    ACT® is a registered trademark of ACT, inc. This website is not endorsed or approved by ACT, inc.

    Neither Riiid, Inc. or R.test is affiliated with ACT, Inc. and do not have access to ACT’s proprietary data.