Smart Primer

Narrative-based Learning in Context


What is
Smart Primer?

The Smart Primer is a tablet-based intelligent tutoring system for kids that leverages compelling narratives, intelligent tutoring chatbots, real-world activities, and a child’s physical and educational context.


Projects



Smart Primer
Intelligent Tutoring System for Children

BookBuddy
Virtual Reading Companion

Dragon Companion
Augmented Reality Based Geocaching

Knowledge Tracing
Mining Student Data with Deep Learning

QuizBot
Chatbot for Factual Knowledge

Key Phrase Extraction
Automatic Educational Content Generation

People


James Landay
Computer Science
Faculty

Emma Brunskill
Computer Science
Faculty

Roy Pea
Education
Faculty

Elizabeth Murnane
Computer Science
Postdoc

Sherry Ruan
Computer Science
PhD Student

Aditya Vishwanath
Education
PhD Student

Glenn Davis
Education
PhD Student

Bryce Tham
Computer Science
Masters Student

Angelica Willis
Computer Science
Masters Student

Joyce He
Education
Masters Student

Abdallah AbuHashem
Computer Science
Coterm Student

Carah Alexander
Computer Science
Coterm Student

Tracy Cai
Computer Science
Undergraduate

Lily Zhou
CS and English
Undergraduate

Jonathan Burkle
Computer Science
Undergraduate

Vincent Nicandro
CS and Classics
Undergraduate

Gabe Saldivar
Symbolic Systems
Undergraduate

Grace Baek
MCS
Undergraduate

Monique Ouk
CS and English
Undergraduate

Liwei Jiang
Computer Science
Visiting Undergraduate

Rui Ying
Electrical Engineering
Visiting Undergraduate

Anna Wang
HCI & Design
Intern

Publications


BookBuddy: Turning Digital Materials to Interactive Second Language Learning Lessons Through a Voice Chatbot [Paper] [BibTeX]
Sherry Ruan, Angelica Willis, Qianyao Xu, Glenn Davis, Liwei Jiang, Emma Brunskill, James Landay
To appear at L@S WIP: Proceedings of the Sixth Annual ACM Conference on Learning at Scale, 2019

Key Phrase Extraction for Generating Educational Question-Answer Pairs [Paper] [Dataset] [BibTeX]
Angelica Willis, Glenn Davis, Sherry Ruan, Lakshmi Manoharan, James Landay, Emma Brunskill
To appear at L@S: Proceedings of the Sixth Annual ACM Conference on Learning at Scale, 2019

QuizBot: A Dialogue-based Adaptive Learning System for Factual Knowledge [Paper] [Video] [Slides] [BibTeX]
Sherry Ruan, Liwei Jiang, Justin Xu, Bryce Joe-Kun Tham, Zhengneng Qiu, Yeshuang Zhu, Elizabeth L. Murnane, Emma Brunskill, James A. Landay
CHI: ACM Conference on Human Factors in Computing Systems, 2019

Adaptive Natural-Language Targeting for Student Feedback [Paper] [BibTeX]
Y. Alex Kolchinski*, Sherry Ruan*, Dan Schwartz, Emma Brunskill (* equal contribution)
L@S WIP: Proceedings of the Fifth Annual ACM Conference on Learning at Scale, 2018




Work With Us


Who are we looking for?
We are looking for exceptional students who are passionate about improving education with technology to join us. In particular, we are looking for students or researchers who have prior experience in any of the following areas: HCI, AI, Education, Design, and Creative Writing.

How do we usually work with Stanford students?
Stanford undergraduate and masters students usually enroll in research classes such as CS 199 and CS 399 during the school year and apply for summer research programs such as CURIS in the summer.

Can I still apply if I am not Stanford-affiliated?
Yes. We also welcome experienced classroom teachers and researchers outside of Stanford and can provide compensation.

I am interested! How can I apply?
Please send an email to smartprimer.apply@gmail.com with your resume and/or transcript attached.

Sponsors & Collaborators