The class connect experimental test-bed: Pedagogical and architectural design considerations for E-learning

Chris Leberknight, Jeffrey Adamski, Sebastian Kufel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Existing efforts are underway to increase undergraduate enrollment in science, engineering, technology, and mathematics (STEM). The STEM workforce is crucial to the U. S. health and economy, yet retention rates in STEM fields are poor and the U. S. is faced with a looming workforce shortage. This paper describes a novel system being developed, known as Class Connect, that aims to enhance instruction for STEM disciplines and function as a test-bed to examine various phenomena associated with peer instruction and student outcomes.

Original languageEnglish
Title of host publicationProceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016
EditorsJ. Michael Spector, Chin-Chung Tsai, Ronghuai Huang, Paul Resta, Demetrios G Sampson, Kinshuk, Nian-Shing Chen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages70-71
Number of pages2
ISBN (Electronic)9781467390415
DOIs
StatePublished - 28 Nov 2016
Event16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016 - Austin, United States
Duration: 25 Jul 201628 Jul 2016

Publication series

NameProceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016

Other

Other16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016
CountryUnited States
CityAustin
Period25/07/1628/07/16

Keywords

  • Adaptive learning
  • Evidence-based instruction
  • Intelligent system
  • Pedagogy
  • Peer instruction
  • Personlization

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    Leberknight, C., Adamski, J., & Kufel, S. (2016). The class connect experimental test-bed: Pedagogical and architectural design considerations for E-learning. In J. M. Spector, C-C. Tsai, R. Huang, P. Resta, D. G. Sampson, Kinshuk, & N-S. Chen (Eds.), Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016 (pp. 70-71). [7756924] (Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICALT.2016.125