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Learning Effectiveness of Adaptive Learning in Real World Context
Proceeding

, , , Adaptemy, Ireland

EdMedia + Innovate Learning, in Vancouver, BC, Canada ISBN 978-1-939797-24-7 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC

Abstract

This paper investigates the learning effectiveness of adaptive learning in real world context in over 1,700 K12 Maths classroom sessions powered by the Adaptemy system. More than 10,000 students used the system over a period of 6 months. The paper focuses on analyzing the learning effectiveness when the system was used through multiple revisions in unique learning journeys. The results have shown that students’ Maths ability improved by 8.3% on average per concept for an average of 5 minutes. Furthermore, the results have shown statistical significant improvements across various ability ranges, reducing the gap between low and high achievers.

Citation

Ghergulescu, I., Flynn, C. & O'Sullivan, C. (2016). Learning Effectiveness of Adaptive Learning in Real World Context. In Proceedings of EdMedia 2016--World Conference on Educational Media and Technology (pp. 1391-1396). Vancouver, BC, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved December 10, 2018 from .

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References

  1. Adaptemy. (2016). Https://www.adaptemy.com/ Forbes. (2014). Rethinking Higher Ed: A Case for Adaptive Learning-Forbes. Retrieved February 16, 2015, from http://www.forbes.com/sites/ccap/2014/10/22/rethinking-higher-ed-a-case-for-adaptive-learning/
  2. Ghergulescu, I., Flynn, C., & O’Sullivan, C. (2015). Adaptemy – Building the Next Generation Classroom (Vol. 2015, pp. 79–88). Presented at the EdMedia: World Conference on Educational Media and Technology. Retrieved from /p/151335/
  3. Ghergulescu, I., Flynn, C., O’Sullivan, C., Ghergulescu, I., Flynn, C., & O’Sullivan, C. (2015). Adaptemy Science: Adaptive Learning for Science for Next Generation Classroom (Vol. 2015, pp. 1477–1482). Presented at the E-Learn: World Conference on E-Learning in
  4. Greer, J., & Mark, M. (2015). Evaluation Methods for Intelligent Tutoring Systems Revisited. International Journal of Artificial Intelligence in Education, 26(1), 387–392. Http://doi.org/10.1007/s40593-015-0043-2Howlin,C.(2015).Realizeit-servingProgressive Educators in K-12, Higher Education, Professional and Corporate Learning. Retrieved December 3, 2015, from http://realizeitlearning.com/customers/
  5. Huang, X., Craig, S.D., Xie, J., Graesser, A., & Hu, X. (2016). Intelligent tutoring systems work as a math gap reducer in 6th grade after-school program. Learning and Individual Differences, 47, 258–265. , S., Estrada, V., & Freeman, A. (2015). NMC HORIZON REPORT: 2015 Higher Education Edition (P. 56). New
  6. Ma, W., Adesope, O.O., Nesbit, J.C., & Liu, Q. (2014). Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of Educational Psychology, 106(4), 901–918. Http://doi.org/10.1037/a0037123Pane,J.F.,Griffin,B.A.,McCaffrey,D.F., & Karam , R. (2014). Effectiveness of cognitive tutor algebra I at scale. Educational Evaluation and Policy Analysis, 162373713507480.
  7. Steenbergen-Hu, S., & Cooper, H. (2013). A meta-analysis of the effectiveness of intelligent tutoring systems on K–12 students’ mathematical learning. Journal of Educational Psychology, 105(4), 970–987. Http://doi.org/10.1037/a0032447Tyner,K.(2014).Literacyin a digital world: Teaching and learning in the age of information. Routledge.

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