E. Cho Smith

dblp:339/3092 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0008-7817-690XORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Games and playful interaction · 77% Human-robot interaction · 23%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computing education · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computing education
robotics education
1.012026
Game-Based and Gamified Robotics Education: A Comparative Systematic Review and Design Guidelines · CHI 2026
Games and playful interaction
gamification
1.012026
Game-Based and Gamified Robotics Education: A Comparative Systematic Review and Design Guidelines · CHI 2026
Human-robot interaction
educational robotics
0.312026
Game-Based and Gamified Robotics Education: A Comparative Systematic Review and Design Guidelines · CHI 2026

Methods — techniques the papers use, named apart from their topics

systematic review · 2.0comparative synthesis · 2.0PRISMA · 2.0
YearPublicationVenuePosition
2026 Game-Based and Gamified Robotics Education: A Comparative Systematic Review and Design Guidelines
abstract
Robotics education fosters computational thinking, creativity, and problem-solving, but remains challenging due to technical complexity. Game-based learning (GBL) and gamification offer engagement benefits, yet their comparative impact remains unclear. We present the first PRISMA-aligned systematic review and comparative synthesis of GBL and gamification in robotics education, analyzing 95 studies from 12,485 records across four databases (2014–2025). We coded each study’s approach, learning context, skill level, modality, pedagogy, and outcomes (κ =.918). Three patterns emerged: (1) approach–context–pedagogy coupling (GBL more prevalent in informal settings, while gamification dominated formal classrooms [p <.001] and favored project-based learning [p =.009]); (2) emphasis on introductory programming and modular kits, with limited adoption of advanced software (~17%), advanced hardware (~5%), or immersive technologies (~22%); and (3) short study horizons, relying on self-report. We propose eight research directions and a design space outlining best practices and pitfalls, offering actionable guidance for robotics education.
Syed T. Mubarrat, Byung-Cheol Min, Tianyu Shao, E. Cho Smith, Bedrich Benes, Alejandra J. Magana, Christos Mousas, Dominic Kao
CHI4