Evidence map›Paper›PMID 33917409›Full record

ArticleSensors (Basel, Switzerland)2021

Qualitative Assessment of Effective Gamification Design Processes Using Motivators to Identify Game Mechanics.

Eva Villegas, David Fonseca, Enric Peña, Paula Bonet, Sara Fernández-Guinea

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Eva VillegasGroup of Research on Technology Enhanced Learning (GRETEL), Universitat Ramon Llull, La Salle, 08022 Barcelona, Spain.
David FonsecaGroup of Research on Technology Enhanced Learning (GRETEL), Universitat Ramon Llull, La Salle, 08022 Barcelona, Spain.ORCID 0000-0001-9471-153X
Enric PeñaGroup of Research on Technology Enhanced Learning (GRETEL), Universitat Ramon Llull, La Salle, 08022 Barcelona, Spain.
Paula BonetCommunities and Children Faculty, University of St. Mark and St. John, Plymouth PL6 8BH, UK.
Sara Fernández-GuineaFacultad de Psicología, Universidad Complutense de Madrid, 28223 Madrid, Spain.

Funding

Ministerio de Economía, Industria y Competitividad, Gobierno de España BIA2016-77464-C2-2-R
6 · The paper itself

Abstract

This research focuses on the study and qualitative assessment of the relationships between motivators and game mechanics per the ratings of expert gamification consultants. By taking this approach, it is intended that during the design phase of a gamified system, decisions can be made about the design of the system based on the motivators of each of the profiles. These motivators can be determined from the information provided by the potential players themselves. The research presented starts from a previous analysis in which, based on the three most used gamification frameworks and through a card sorting technique that allows the user to organize and classify the content, a set of mechanics are determined. In the present study, each of the mechanics is analyzed, and a more precise motive is decided. As a result, a higher level of personalization is achieved and, consequently, approximates a higher level of gamification effectiveness. The main conclusions are implemented in the development of the Game4City 3.0 project, which addresses gamified and interactive strategies to visualize urban environments in 3D at an educational and social level.

Indexed as

design strategyeffective gamificationengagementgaming experiencemechanicsmotivationuser experience

Identifiers

PMID33917409
PMCPMC8038701

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.