Reducing Cognitive Load through the Worked Example Effect within a Serious Game Environment

Bernadette Spieler, Naomi Pfaff, Wolfgang Slany

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem Konferenzband

Abstract

Novices often struggle to represent problems mentally; the unfamiliar process can exhaust their cognitive resources, creating frustration that deters them from learning. By improving novices' mental representation of problems, worked examples improve both problem-solving skills and transfer performance. Programming requires both skills. In programming, it is not sufficient to simply understand how Stackoverflow examples work; programmers have to be able to adapt the principles and apply them to their own programs. This paper shows evidence in support of the theory that worked examples are the most efficient mode of instruction for novices. In the present study, 42 students were asked to solve the tutorial The Magic Word, a game especially for girls created with the Catrobat programming environment. While the experimental group was presented with a series of worked examples of code, the control groups were instructed through theoretical text examples. The final task was a transfer question. While the average score was not significantly better in the worked example condition, the fact that participants in this experimental group finished significantly faster than the control group suggests that their overall performance was better than that of their counterparts.

Originalspracheenglisch
TitelProceedings of 6th International Conference of the Immersive Learning Research Network, iLRN 2020
Redakteure/-innenDaphne Economou, Alexander Klippel, Heather Dodds, Anasol Pena-Rios, Mark J. W. Lee, Dennis Beck, Johanna Pirker, Andreas Dengel, Tiago M. Peres, Jonathon Richter
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers
Seiten1-8
Seitenumfang8
ISBN (elektronisch)9781734899504
DOIs
PublikationsstatusVeröffentlicht - Jun 2020
Veranstaltung6th International Conference of the Immersive Learning Research Network, iLRN 2020 - Virtual, Online, USA / Vereinigte Staaten
Dauer: 21 Jun 202025 Jun 2020

Publikationsreihe

NameProceedings of 6th International Conference of the Immersive Learning Research Network, iLRN 2020

Konferenz

Konferenz6th International Conference of the Immersive Learning Research Network, iLRN 2020
LandUSA / Vereinigte Staaten
OrtVirtual, Online
Zeitraum21/06/2025/06/20

ASJC Scopus subject areas

  • !!Computer Science Applications
  • !!Media Technology
  • Ausbildung bzw. Denomination

Fingerprint Untersuchen Sie die Forschungsthemen von „Reducing Cognitive Load through the Worked Example Effect within a Serious Game Environment“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren