Elle Wang

Lead Research Scientist at National AI Institute for Adult Learning and Online Education

San Francisco, California, United States of America

Research Expertise

Online learning

Intelligent technologies

Learning Analytics

MOOCs

Education

Computer Science Applications

Communication

Molecular Biology

Biochemistry

Organizational Behavior and Human Resource Management

Strategy and Management

About

Ellen (Elle) Wang is a cognitive scientist with a focus on educational applications of artificial intelligence (AI). She is currently a lead research scientist at the National AI Institute for Adult Learning and Online Education and a staff research scientist at the Action Lab at Arizona State University. Wang received her PhD in Cognitive Science in Education from Columbia University in 2017. Her research focuses on how AI can be used to support and improve learning outcomes, with a particular focus on online and adult learners. She has developed and evaluated AI-based programs and systems for a variety of applications, including tutoring, intelligent course recommendation, and assessment. Wang’s work has been published in a variety of prestigious journals, including the Journal of Educational Psychology, the British Journal of Educational Technology, and the Journal of Experimental Psychology: Applied. She has also presented her work at numerous international conferences, including the Association for the Advancement of Artificial Intelligence (AAAI) and the International Conference on Intelligent Tutoring Systems (ITS).

Publications

Grit and Intention: Why Do Learners Complete MOOCs?

The International Review of Research in Open and Distributed Learning / Jul 11, 2018

Wang, Y., & Baker, R. (2018). Grit and Intention: Why Do Learners Complete MOOCs? The International Review of Research in Open and Distributed Learning, 19(3). https://doi.org/10.19173/irrodl.v19i3.3393

EDUCATIONAL DATA MINING

Data Mining and Learning Analytics / Sep 15, 2016

Baker, R. S., Wang, Y., Paquette, L., Aleven, V., Popescu, O., Sewall, J., Rosé, C., Tomar, G. S., Ferschke, O., Zhang, J., Cennamo, M. J., Ogden, S., Condit, T., Diaz, J., Crossley, S., McNamara, D. S., Comer, D. K., Lynch, C. F., Brown, R., … Bergner, Y. (2016). EDUCATIONAL DATA MINING. Data Mining and Learning Analytics, 55–66. https://doi.org/10.1002/9781118998205.ch4

Longitudinal engagement, performance, and social connectivity

Proceedings of the Sixth International Conference on Learning Analytics & Knowledge - LAK '16 / Jan 01, 2016

Zhu, M., Bergner, Y., Zhang, Y., Baker, R., Wang, Y., & Paquette, L. (2016). Longitudinal engagement, performance, and social connectivity. Proceedings of the Sixth International Conference on Learning Analytics & Knowledge - LAK ’16. https://doi.org/10.1145/2883851.2883934

A conceptual peer review model for arXiv and other preprint databases

Learned Publishing / Feb 06, 2019

Wang, L., & Zhan, Y. (2019). A conceptual peer review model for arXiv and other preprint databases. Learned Publishing. Portico. https://doi.org/10.1002/leap.1229

The Beginning of a Beautiful Friendship? Intelligent Tutoring Systems and MOOCs

Lecture Notes in Computer Science / Jan 01, 2015

Aleven, V., Sewall, J., Popescu, O., Xhakaj, F., Chand, D., Baker, R., Wang, Y., Siemens, G., Rosé, C., & Gasevic, D. (2015). The Beginning of a Beautiful Friendship? Intelligent Tutoring Systems and MOOCs. Artificial Intelligence in Education, 525–528. https://doi.org/10.1007/978-3-319-19773-9_53

A Longitudinal Study on Learner Career Advancement in MOOCs

Journal of Learning Analytics / Nov 18, 2014

Wang, Y., Paquette, L., & Baker, R. (2014). A Longitudinal Study on Learner Career Advancement in MOOCs. Journal of Learning Analytics, 1(3), 203–206. https://doi.org/10.18608/jla.2014.13.23

Negativity in Massive Online Open Courses: Impacts on Learning and Teaching and How Instructional Teams May Be Able to Address It

InSight: A Journal of Scholarly Teaching / Aug 01, 2015

Comer, D., Baker, R., & Wang, Y. (2015). Negativity in Massive Online Open Courses: Impacts on Learning and Teaching and How Instructional Teams May Be Able to Address It. InSight: A Journal of Scholarly Teaching, 10, 92–113. https://doi.org/10.46504/10201508co

The Evolution and Impact of Anonymous Preference in Online Communities

Academy of Management Proceedings / Jan 01, 2015

Johnson, J. C. (2015). The Evolution and Impact of Anonymous Preference in Online Communities. Academy of Management Proceedings, 2015(1), 17011. https://doi.org/10.5465/ambpp.2015.17011abstract

A Statistical Learning Theory Framework for Supervised Pattern Discovery

Proceedings of the 2014 SIAM International Conference on Data Mining / Apr 28, 2014

Huggins, J. H., & Rudin, C. (2014). A Statistical Learning Theory Framework for Supervised Pattern Discovery. Proceedings of the 2014 SIAM International Conference on Data Mining. https://doi.org/10.1137/1.9781611973440.58

Towards adapting to learners at scale

Proceedings of the Fifth Annual ACM Conference on Learning at Scale / Jun 26, 2018

Aleven, V., Sewall, J., Andres, J. M., Sottilare, R., Long, R., & Baker, R. (2018). Towards adapting to learners at scale. Proceedings of the Fifth Annual ACM Conference on Learning at Scale. https://doi.org/10.1145/3231644.3231671

Workshop on integrated learning analytics of MOOC post-course development

Proceedings of the Seventh International Learning Analytics & Knowledge Conference / Mar 13, 2017

Wang, Y., Davis, D., Chen, G., & Paquette, L. (2017). Workshop on integrated learning analytics of MOOC post-course development. Proceedings of the Seventh International Learning Analytics & Knowledge Conference. https://doi.org/10.1145/3027385.3029430

Automated Identification of Verbally Abusive Behaviors in Online Discussions

Proceedings of the Third Workshop on Abusive Language Online / Jan 01, 2019

Joksimovic, S., Baker, R. S., Ocumpaugh, J., Andres, J. M. L., Tot, I., Wang, E. Y., & Dawson, S. (2019). Automated Identification of Verbally Abusive Behaviors in Online Discussions. Proceedings of the Third Workshop on Abusive Language Online. https://doi.org/10.18653/v1/w19-3505

Commentary: Massive open online courses

Biochemistry and Molecular Biology Education / Jul 01, 2013

Parslow, G. R. (2013). Commentary: Massive open online courses. Biochemistry and Molecular Biology Education, 41(4), 278–279. https://doi.org/10.1002/bmb.20710

Editorial: Beyond Cognitive Ability

Journal of Learning Analytics / Apr 03, 2020

Joksimovic, S., Siemens, G., Wang, Y. E., San Pedro, M. O. Z., & Way, J. (2020). Editorial: Beyond Cognitive Ability. Journal of Learning Analytics, 7(1). https://doi.org/10.18608/jla.2020.71.1

K-MOOC(Korea Massive Open Online Course) learner motivation: Initial motivation for enrollment and continuing motivation for completion

Korean Association For Learner-Centered Curriculum And Instruction / Feb 10, 2017

Byun, M., & Cho, M.-H. (2017). K-MOOC(Korea Massive Open Online Course) learner motivation: Initial motivation for enrollment and continuing motivation for completion. Korean Association For Learner-Centered Curriculum And Instruction, 17(3), 125–154. https://doi.org/10.22251/jlcci.2017.17.3.125

Bringing Non-programmer Authoring of Intelligent Tutors to MOOCs

Proceedings of the Third (2016) ACM Conference on Learning @ Scale / Apr 25, 2016

Aleven, V., Baker, R., Wang, Y., Sewall, J., & Popescu, O. (2016). Bringing Non-programmer Authoring of Intelligent Tutors to MOOCs. Proceedings of the Third (2016) ACM Conference on Learning @ Scale. https://doi.org/10.1145/2876034.2893442

Motivating Students to Ask More Questions

Lecture Notes in Computer Science / Jan 01, 2019

Wang, Y., Bohlen, T., Elkins-Tanton, L., & Tanton, J. (2019). Motivating Students to Ask More Questions. Artificial Intelligence in Education, 409–412. https://doi.org/10.1007/978-3-030-23207-8_75

Open Scale Courses: Exploring Access and Opportunity for Less-Educated Learners

2018 Learning With MOOCS (LWMOOCS) / Sep 01, 2018

Wang, Y., Fikes, T. G., & Pettyjohn, P. (2018). Open Scale Courses: Exploring Access and Opportunity for Less-Educated Learners. 2018 Learning With MOOCS (LWMOOCS). https://doi.org/10.1109/lwmoocs.2018.8534667

Mapping the Landscape of Social and Emotional Learning Analytics

Social and Emotional Learning and Complex Skills Assessment / Jan 01, 2022

Joksimović, S., Dawson, S., Barthakur, A., Poquet, O., Wang, Y. E., Marmolejo-Ramos, F., & Siemens, G. (2022). Mapping the Landscape of Social and Emotional Learning Analytics. Advances in Analytics for Learning and Teaching, 27–47. https://doi.org/10.1007/978-3-031-06333-6_3

Re-contextualizing Inclusiveness & SEL in Learning Analytics

Social and Emotional Learning and Complex Skills Assessment / Jan 01, 2022

Wang, Y. E., & Joksimović, S. (2022). Re-contextualizing Inclusiveness & SEL in Learning Analytics. Advances in Analytics for Learning and Teaching, 1–8. https://doi.org/10.1007/978-3-031-06333-6_1

What more do we need to know about the learning organization?

The Learning Organization / Jun 05, 2007

Ortenblad, A. (2007). What more do we need to know about the learning organization? The Learning Organization, 14(4). https://doi.org/10.1108/tlo.2007.11914daa.001

The reasons behind Motorola’s success in China

Strategic Direction / Mar 01, 2003

The reasons behind Motorola’s success in China. (2003). Strategic Direction, 19(2), 28–30. https://doi.org/10.1108/02580540310794327

Do Massive Open Online Course Platforms Support Employability?

Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing / Feb 27, 2016

Dillahunt, T. R., Ng, S., Fiesta, M., & Wang, Z. (2016). Do Massive Open Online Course Platforms Support Employability? Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing. https://doi.org/10.1145/2818048.2819924

Measuring learned skill behaviors post-MOOC

CHI '14 Extended Abstracts on Human Factors in Computing Systems / Apr 26, 2014

Russell, D. M. (2014). Measuring learned skill behaviors post-MOOC. CHI ’14 Extended Abstracts on Human Factors in Computing Systems. https://doi.org/10.1145/2559206.2581180

Education

Columbia University

PhD, Cognitive Science in Education / 2017

New York, New York, United States of America

Experience

National AI Institute for Adult Learning and Online Education

Lead Research Scientist / 2021 — Present

Develop AI Agents to enable ‘weak-tie’ human-human relationship building in large-scale socio-technical ecosystems. Use social and emotional learning analytics to holistically measure and support effective learning & upskilling at scale

Action Lab at ASU

Staff Research Scientist / 2017 — Present

Lead and conduct core research projects on 1) Assessing Social and Emotional Learning (SEL) at Scale 2) Building prediction models to connect online learning and career advancement 3) Assessing trans-national online learning efficacy

Links & Social Media

Research Web Site

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