Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1722
Title: Ingame Worked Examples Support as an Alternative to Textual Instructions in Serious Games About Programming
Authors: Toukiloglou, Pavlos
Xinogalos, Stelios
Type: Article
Subjects: FRASCATI::Natural sciences::Computer and information sciences
FRASCATI::Social sciences::Educational sciences::Education, general (including: training, pedagogy,didactics)
Keywords: serious games
support design
computer programming
worked examples
Issue Date: 2022
Source: Journal of Educational Computing Research
Volume: 60
Issue: 7
First Page: 1615
Last Page: 1636
Abstract: Serious games are considered an effective method to engage students in programming education and have been increasingly used in classrooms. An important part of the learning process with serious games involves the presentation of the new concepts and the provided support to encounter student difficulties. Although the most common approach is the use of instructional text, it comes with some drawbacks. This paper proposes an alternative method for user support in serious games about programming which mitigates current problems and provides improved learning efficiency. An experiment was conducted (N = 291) to test textual instructions learning efficiency compared to in-game worked examples. Two randomly assigned groups used different types of support in a block-based game, developed for the study. Our implementation provided support through a non-player character who executed worked examples inside the game world. The analysis showed a significant statistical difference in score performance between the two supports on both novice and experienced students. The results point to increased learning efficiency by students, when in-game worked examples and problem-solving are combined. We further argue that the Cognitive load theory can provide adequate justification for the outcomes.
URI: https://doi.org/10.1177/07356331211073655
https://ruomo.lib.uom.gr/handle/7000/1722
ISSN: 0735-6331
1541-4140
Other Identifiers: 10.1177/07356331211073655
Appears in Collections:Department of Applied Informatics

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