Data Extraction

The study analyzed 87 papers, linking GDEs to negative effects, identifying fields of use, and categorizing empirical studies, with data shared via Zenodo.


This content originally appeared on HackerNoon and was authored by Gamifications FTW Publications

:::info Authors:

(1) Clauvin Almeida, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil;

(2) Marcos Kalinowski, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil;

(3) Anderson Uchoa, Federal University of Ceara (UFC), Itapaje, Brazil;

(4) Bruno Feijo, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil.

:::

Abstract and 1 Introduction

2. Background and Related Work and 2.1. Gamification

2.2. Game Design Elements and 2.3. Gamification Effects

2.4. Related Work on Gamification Negative Effects

3. Systematic Mapping and 3.1. The Research Questions

3.2. Search Strategy and 3.3. Inclusion and Exclusion Criteria

3.4. Applying the Search Strategy

3.5. Data Extraction

4. Systematic Mapping Results

5. Focus Group: Developer Perception on the Negative Effects of Game Design Elements

5.1. Context and Participant Characterization

5.2. Focus Group Design

5.3. The Developers’ Perception on The Negative Effects

5.4. On the Perceived Usefulness, Ease of use and Intent of Adoption of Mapped Negative Effects

5.5. Participant Feedback

6. Limitations

7. Concluding Remarks

7.1. Future Research Directions

Acknowledgements and References

3.5. Data Extraction

We extracted data from the 87 included papers focusing on answering our research questions. We used Google Sheets to organize the extracted data. To increase reliability in our extraction process, the spreadsheet with all the extracted data is available in an online Zenodo open science repository (www. doi.org/10.5281/zenodo.6279062).

\ We answered RQ1 by extracting data for RQ1.A, RQ1.B, and RQ1.C and connecting the GDEs with their respective negative effects. For RQ1.A, we extracted the GDEs that were related to negative effects. For RQ1.B and RQ1.C, we respectively extracted the negative effects caused to main users (in this case, students) and those maintaining the system working or in the position of teachers. We followed the open coding guidelines proposed in [52] to assign the text of the papers to design elements and negative effects. During this process, different terms perceived as related to the same element or effect were associated with a single code. During this process we were conservative, avoiding to group codes that could potentially refer to different concepts. In case of doubt concerning coding, discussions were held among three of the authors of the present work.

\ To answer RQ2, we extracted the fields of education/learning where the gamified software were used (e.g., computer science, medicine). Finally, to answer RQ3 we extracted the types of empirical studies conducted within each paper reporting the negative effects.

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:::info This paper is available on arxiv under CC BY 4.0 DEED license.

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This content originally appeared on HackerNoon and was authored by Gamifications FTW Publications


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