skip to main content
10.1145/3027385.3029431acmotherconferencesArticle/Chapter ViewAbstractPublication PageslakConference Proceedingsconference-collections
abstract

DesignLAK17: quality metrics and indicators for analytics of assessment design at scale

Published:13 March 2017Publication History

ABSTRACT

Notions of what constitutes quality in design in traditional on-campus or online teaching and learning may not always translate into scaled digital environments. The DesignLAK17 workshop builds on the DesignLAK16 workshop to explore one aspect of this theme, namely the opportunities arising from the use of analytics in scaled assessment design. New paradigms for learning design are exploiting the distinctive characteristics and potentials of analytics, trace data and newer kinds of sensory data usable on digital platforms to transform assessment. But, characteristics of quality assessment design need to be reconsidered, and new metrics for capturing quality are required. This symposium and workshop focuses on what might be appropriate quality metrics and indicators for assessment design in scaled learning. It aims to build a community of interest round the topic, to share perspectives, and to generate design and research ideas.

References

  1. David Boud and Elizabeth Molloy. 2013. Rethinking models of feedback for learning: the challenge of design. Assessment & Evaluation in Higher Education 38, 6 (2013), 698--712.Google ScholarGoogle ScholarCross RefCross Ref
  2. Nancy Law, Dale S Niederhauser, Rhonda Christensen, and Linda Shear. 2016. A multilevel system of quality technology-enhanced learning and teaching indicators. Journal of Educational Technology & Society 19, 3 (2016), 72--83.Google ScholarGoogle Scholar
  3. Allison Littlejohn and Chris Pegler. 2007. Preparing for blended e-learning. Routledge. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Wenting Ma, Olusola O Adesope, John C Nesbit, and Qing Liu. 2014. Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of Educational Psychology 106, 4 (2014), 901.Google ScholarGoogle ScholarCross RefCross Ref
  5. Geoff N Masters. 2013. Reforming educational assessment: Imperatives, principles and challenges. (2013).Google ScholarGoogle Scholar
  6. Sandra Kaye Milligan and Patrick Griffin. 2016. Understanding Learning and Learning Design in MOOCs: A Measurement-Based Interpretation. Journal of Learning Analytics 3, 2 (2016), 88--115.Google ScholarGoogle ScholarCross RefCross Ref
  7. Ulla Ringtved, Sandra Milligan, and Linda Corrin. 2016. Learning design and feedback processes at scale: stocktaking emergent theory and practice. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge. ACM, 479--480. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Marlene Scardamalia, John Bransford, Bob Kozma, and Edys Quellmalz. 2012. New assessments and environments for knowledge building. In Assessment and teaching of 21st century skills. Springer, 231--300.Google ScholarGoogle Scholar
  9. Valerie Shute and Matthew Ventura. 2013. Stealth assessment: Measuring and supporting learning in video games. MIT Press. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. DesignLAK17: quality metrics and indicators for analytics of assessment design at scale

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      LAK '17: Proceedings of the Seventh International Learning Analytics & Knowledge Conference
      March 2017
      631 pages
      ISBN:9781450348706
      DOI:10.1145/3027385

      Copyright © 2017 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 13 March 2017

      Check for updates

      Qualifiers

      • abstract

      Acceptance Rates

      LAK '17 Paper Acceptance Rate36of114submissions,32%Overall Acceptance Rate236of782submissions,30%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader