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Scan to Learn: A Lightweight Approach for Informal Mobile Micro-Learning at the Workplace

Authors:
Katharina Frosch

Keywords: work-based learning; informal learning; mobile learning; micro-learning; QR code; instructional design; open source

Abstract:
Informal learning at the workplace is a crucial ingredient in updating and upskilling today’s workforce, but in many jobs, informal learning opportunities are scarce. Bite-sized learning via mobile devices (Mobile Micro-Learning, MML) can be a powerful means to enhance informal work-related learning also in such learning-deprived fields. Based on good practices of recent MML implementations, a lightweight approach is developed. It involves an instructional blueprint and an open-source, low-threshold technology for MML, and meets the specific needs of workers in learning-deprived fields. The main idea is a scan-to-learn system where Quick Response (QR) codes are attached to physical objects in the work environment. Workers can scan the QR codes to learn and are directed to short, interactive learning nuggets. For evaluation, a proof-of-concept is provided.

Pages: 53 to 61

Copyright: Copyright (c) IARIA, 2023

Publication date: April 24, 2023

Published in: conference

ISSN: 2308-4367

ISBN: 978-1-68558-081-0

Location: Venice, Italy

Dates: from April 24, 2023 to April 28, 2023