Informatics in Education logo


Login Register

  1. Home
  2. To appear
  3. A Proposal for Performance-based Assessm ...

Informatics in Education

Information Submit your article Help
  • Article info
  • Related articles
  • More
    Article info Related articles

A Proposal for Performance-based Assessment of the Learning of Machine Learning Concepts and Practices in K-12
Christiane GRESSE VON WANGENHEIM   Nathalia da Cruz ALVES   Marcelo F. RAUBER   Jean C. R. HAUCK   Ibrahim H. YETER  

Authors

 
Placeholder
https://doi.org/10.15388/infedu.2022.18
Pub. online: 5 August 2022      Type: Article      Open accessOpen Access

Published
5 August 2022

Abstract

Although Machine Learning (ML) is used already in our daily lives, few are familiar with the technology. This poses new challenges for students to understand ML, its potential, and limitations as well as to empower them to become creators of intelligent solutions. To effectively guide the learning of ML, this article proposes a scoring rubric for the performance-based assessment of the learning of concepts and practices regarding image classification with artificial neural networks in K-12. The assessment is based on the examination of student-created artifacts as a part of open-ended applications on the use stage of the Use-Modify-Create cycle. An initial evaluation of the scoring rubric through an expert panel demonstrates its internal consistency as well as its correctness and relevance. Providing a first step for the assessment of concepts on image recognition, the results may support the progress of learning ML by providing feedback to students and teachers.

Related articles PDF XML
Related articles PDF XML

Copyright
No copyright data available.
Open access article under the CC BY license.

Keywords
Assessment Education Rubric Machine Learning K-12

Metrics (since February 2020)
255

Article info
views

0

Full article
views

1038

PDF
downloads

77

XML
downloads

Export citation

Copy and paste formatted citation
Placeholder

Download citation in file


Share


RSS

INFORMATICS IN EDUCATION

  • Online ISSN: 2335-8971
  • Print ISSN: 1648-5831

About

  • About journal
  • Copyright © 2020 Vilnius University, ETH Zürich 

For contributors

  • Submit
  • OA Policy

Contact us

  • Institute of Data Science and Digital Technologies
  • Vilnius University
  • Akademijos St. 4, 08412, Vilnius, Lithuania
Powered by PubliMill  •  Privacy policy