Objectively measuring learning outcomes of information technology-assisted training courses
Year: 2022
Type: article
Abstract: Purpose The objective of the presented pilot study was to test the applicability of a metric to specifically measure performance improvement via a hands-on workshop about collaborative robotics. Design/methodology/approach Candidates interested in acquiring basic practical skills in working with a collaborative robot completed a distance learning exercise in preparation for a hands-on training workshop. The candidates executed a test before and after the workshop for recording the parameters compiled in the tested performance index (PI). Findings The results reflected the potential of the tested PI for applications in detecting improvement in practical skill acquisition and revealed potential opportunities for integrating additional performance factors. Research limitations/implications The low number of candidates available limited in-depth analyses of the learning outcomes. Practical implications The study outcomes provide the basis for follow-up projects with larger cohorts of candidates and control groups in order to expedite the development of technology-assisted performance measurements. Social implications The study contributes to research on performance improvement and prediction of learning outcomes, which is imperative to this emerging field in learning analytics. Originality/value The development of the presented PI addresses a scientific gap in learning analytics, i.e. the objective measurement of performance improvement and prediction along skill-intensive training courses. This paper presents an improved version of the PI, which was published at the 12th Conference on Learning Factories, Singapore, April 2022.
Authors: Gerald Schneikart, Walter Mayrhofer
Institution: FHWien der WKW
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4295990965