Team, LearnLM; Google,; :,; Martín, Alicia; Globerson, Amir; Wang, Amy; Shekhawat, Anirudh; Iurchenko, Anna; Choudhury, Anisha; Hassidim, Avinatan; Çakmakli, Ayça; Evron, Ayelet Shasha; Yang, Charlie; Heldreth, Courtney; Akrong, Diana; Elidan, Gal; Mu, Hairong; Li, Ian; Cohen, Ido; Chou, Katherine; Singh, Komal; Borovoi, Lev; Hackmon, Lidan; Belinsky, Lior; Fink, Michael; Efron, Niv; Singh, Preeti; Levitt, Rena; Agarwal, Shashank; Sharon, Shay; Lee-Joe, Tracey; Hao, Xiaohong; Gold-Zamir, Yael; Haramaty, Yael; Mor, Yishay; Sinai, Yoav Bar; Matias, Yossi
Towards an AI-Augmented Textbook Unveröffentlicht
Preprint on arXiv.org, 2025.
Abstract | Links | BibTeX
@unpublished{learnlmteam2025aiaugmentedtextbook,
title = {Towards an AI-Augmented Textbook},
author = {LearnLM Team and Google and : and Alicia Martín and Amir Globerson and Amy Wang and Anirudh Shekhawat and Anna Iurchenko and Anisha Choudhury and Avinatan Hassidim and Ayça Çakmakli and Ayelet Shasha Evron and Charlie Yang and Courtney Heldreth and Diana Akrong and Gal Elidan and Hairong Mu and Ian Li and Ido Cohen and Katherine Chou and Komal Singh and Lev Borovoi and Lidan Hackmon and Lior Belinsky and Michael Fink and Niv Efron and Preeti Singh and Rena Levitt and Shashank Agarwal and Shay Sharon and Tracey Lee-Joe and Xiaohong Hao and Yael Gold-Zamir and Yael Haramaty and Yishay Mor and Yoav Bar Sinai and Yossi Matias},
url = {https://arxiv.org/abs/2509.13348},
year = {2025},
date = {2025-10-01},
urldate = {2025-10-01},
abstract = {Textbooks are a cornerstone of education, but they have a fundamental limitation: they are a one-size-fits-all medium. Any new material or alternative representation requires arduous human effort, so that textbooks cannot be adapted in a scalable manner. We present an approach for transforming and augmenting textbooks using generative AI, adding layers of multiple representations and personalization while maintaining content integrity and quality. We refer to the system built with this approach as Learn Your Way. We report pedagogical evaluations of the different transformations and augmentations, and present the results of a a randomized control trial, highlighting the advantages of learning with Learn Your Way over regular textbook usage.},
howpublished = {Preprint on arXiv.org},
keywords = {},
pubstate = {published},
tppubtype = {unpublished}
}
Schließen
Textbooks are a cornerstone of education, but they have a fundamental limitation: they are a one-size-fits-all medium. Any new material or alternative representation requires arduous human effort, so that textbooks cannot be adapted in a scalable manner. We present an approach for transforming and augmenting textbooks using generative AI, adding layers of multiple representations and personalization while maintaining content integrity and quality. We refer to the system built with this approach as Learn Your Way. We report pedagogical evaluations of the different transformations and augmentations, and present the results of a a randomized control trial, highlighting the advantages of learning with Learn Your Way over regular textbook usage.
Schließen
