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Charles Lang
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2020 – today
- 2024
- [c17]Charles Lang, Korinn S. Ostrow:
Challenge variance: Exploiting format differences for personalized learner models. UMAP 2024: 102-109 - 2023
- [c16]Charles Lang, Laura Davis:
Learning Analytics and Stakeholder Inclusion: What do We Mean When We Say "Human-Centered"? LAK 2023: 411-417 - 2021
- [c15]Geraldine Gray, Ana Elena Schalk, Pauline Rooney, Charles Lang:
A Stakeholder Informed Professional Development Framework to Support Engagement with Learning Analytics. LAK 2021: 237-247 - 2020
- [c14]Charles Lang:
Learner-Context Modelling: A Bayesian Approach. AIED (2) 2020: 152-156 - [c13]Konstantinos Michos, Charles Lang, Davinia Hernández-Leo, Detra Price-Dennis:
Involving teachers in learning analytics design: lessons learned from two case studies. LAK 2020: 94-99 - [c12]Charles Lang, Charlotte Woo, Jeanne Sinclair:
Quantifying data sensitivity: precise demonstration of care when building student prediction models. LAK 2020: 655-664
2010 – 2019
- 2018
- [j4]Paula Ceccon Ribeiro, Melissa Biles, Charles Lang, Cláudio T. Silva, Jan L. Plass:
Visualizing log-file data from a game using timed word trees. Inf. Vis. 17(3): 183-195 (2018) - [j3]Yoav Bergner, Geraldine Gray, Charles Lang:
What Does Methodology Mean for Learning Analytics? J. Learn. Anal. 5(2) (2018) - [c11]Detra Price-Dennis, Charles Lang:
Exploring Teacher Learning through STEM Teachers' Exploration of Data Using a Domain Specific Coding Language. ICLS 2018 - [c10]Charles Lang, Leah P. Macfadyen, Sharon Slade, Paul Prinsloo, Niall Sclater:
The complexities of developing a personal code of ethics for learning analytics practitioners: implications for institutions and the field. LAK 2018: 436-440 - [c9]Andrew Gibson, Charles Lang:
The pragmatic maxim as learning analytics research method. LAK 2018: 461-465 - 2017
- [c8]Yoav Bergner, Charles Lang, Geraldine Gray:
A Focus on Methodology in Learning Analytics: Building a Structurally Sound Bridge Discipline. MLA/BLAC@LAK 2017 - [c7]Charles Lang:
Opportunities for personalization in modeling students as Bayesian learners. LAK 2017: 41-45 - [c6]Yoav Bergner, Charles Lang, Geraldine Gray:
Workshop on methodology in learning analytics (MLA). LAK 2017: 500-501 - [c5]Charles Lang, Stephanie D. Teasley, John C. Stamper:
Building the learning analytics curriculum: workshop. LAK 2017: 520-521 - [c4]Charles Lang, Stephanie D. Teasley, John C. Stamper:
Building the Learning Analytics Curriculum. MLA/BLAC@LAK 2017 - [e1]Yoav Bergner, Charles Lang, Geraldine Gray, Stephanie D. Teasley, John C. Stamper:
Joint Proceedings of the Workshop on Methodology in Learning Analytics (MLA) and the Workshop on Building the Learning Analytics Curriculum (BLAC) co-located with 7th International Learning Analytics and Knowledge Conference (LAK 2017), Vancouver, Canada, March 13th-14th, 2017. CEUR Workshop Proceedings 1915, CEUR-WS.org 2017 [contents] - 2016
- [c3]Joseph Jay Williams, Anthony Botelho, Adam Sales, Neil T. Heffernan, Charles Lang:
Discovering 'Tough Love' Interventions Despite Dropout. EDM 2016: 650-651 - 2015
- [c2]Charles Lang, Neil T. Heffernan, Korinn Ostrow, Yutao Wang:
The Impact of Incorporating Student Confidence Items into an Intelligent Tutor: A Randomized Controlled Trial. EDM 2015: 144-149 - 2014
- [j2]Charles Lang:
An Adaptive Model of Student Performance Using Inverse Bayes. J. Learn. Anal. 1(3): 154-156 (2014) - [c1]Charles Lang:
The Use of Student Confidence for Prediction & Resolving Individual Student Knowledge Structure. EDM 2014: 438-440
1990 – 1999
- 1990
- [j1]David W. Barron, Charles Lang:
SPE-The Early Years. Softw. Pract. Exp. 20(1): 3-4 (1990)
Coauthor Index
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