Gamification involves the incorporation of game elements and design principles for the purposes of enhancing user engagement and motivation. Game elements such as points, badges, medals and leader-boards provide incentives for active participation and healthy competition. In higher learning applications, gamification can be effective provided these elements are tailored to fit the specific context and balance both intrinsic and extrinsic motivators. APICURON is a biocuration database that tracks and rewards curator contributions using gamification principles. Biocuration involves collecting, organising and annotating biological data; and gamification can enhance the efficiency and accuracy of this process. The goal of this study was to use a two-pronged approach,i.e. quantitative and qualitative, to analyse the impact and effects (if any) of gamification strategies on user engagement and ultimately propose alternative user strategies to help improve the APICURON platform and in turn increase biocuration events. The quantitative approach had two main modes : forecasting and clustering. The prior used historical curation events to forecast the number of future curation events and the latter aimed to identify common curator behaviours and curation styles and perform a classification. Four models were used to perform the forecasting - Linear Regression, ARIMA, Window ETS and Prophet and the cluster analysis involved HMM and wavelets. The qualitative approach utilised two surveys measuring attitudes towards APICURON and gamification as well as intrinsic and extrinsic motivators. The main results showed an increase in the number of curation events but that could not be attributed to gamification. Results suggested that the gamification implementation had minimal effect on the curation trend and highlighted curator reluctance, disinterest and lethargy in engaging with current gamification implementations. Recommendations were made to implement a user-centered design based on the two main classification categories that the curators fell under : “Philanthropist” and “Achiever”, according to the Marczewski Gamification Type Framework ; as well as performing further research, continuous feedback and evaluation of new components. The main constraints of the study included errors in data collection by the knowledge resources resulting in incorrect data logging therefore limited usable data points as well as a general lack of curator participation in surveys.

Gamification involves the incorporation of game elements and design principles for the purposes of enhancing user engagement and motivation. Game elements such as points, badges, medals and leader-boards provide incentives for active participation and healthy competition. In higher learning applications, gamification can be effective provided these elements are tailored to fit the specific context and balance both intrinsic and extrinsic motivators. APICURON is a biocuration database that tracks and rewards curator contributions using gamification principles. Biocuration involves collecting, organising and annotating biological data; and gamification can enhance the efficiency and accuracy of this process. The goal of this study was to use a two-pronged approach,i.e. quantitative and qualitative, to analyse the impact and effects (if any) of gamification strategies on user engagement and ultimately propose alternative user strategies to help improve the APICURON platform and in turn increase biocuration events. The quantitative approach had two main modes : forecasting and clustering. The prior used historical curation events to forecast the number of future curation events and the latter aimed to identify common curator behaviours and curation styles and perform a classification. Four models were used to perform the forecasting - Linear Regression, ARIMA, Window ETS and Prophet and the cluster analysis involved HMM and wavelets. The qualitative approach utilised two surveys measuring attitudes towards APICURON and gamification as well as intrinsic and extrinsic motivators. The main results showed an increase in the number of curation events but that could not be attributed to gamification. Results suggested that the gamification implementation had minimal effect on the curation trend and highlighted curator reluctance, disinterest and lethargy in engaging with current gamification implementations. Recommendations were made to implement a user-centered design based on the two main classification categories that the curators fell under : “Philanthropist” and “Achiever”, according to the Marczewski Gamification Type Framework; as well as performing further research, continuous feedback and evaluation of new components. The main constraints of the study included errors in data collection by the knowledge resources resulting in incorrect data logging therefore limited usable data points as well as a general lack of curator participation in surveys.

Analysis of the Effectiveness of Gamification implementations in Academic Research : APICURON case study

MAMINIMINI, MUNESU
2023/2024

Abstract

Gamification involves the incorporation of game elements and design principles for the purposes of enhancing user engagement and motivation. Game elements such as points, badges, medals and leader-boards provide incentives for active participation and healthy competition. In higher learning applications, gamification can be effective provided these elements are tailored to fit the specific context and balance both intrinsic and extrinsic motivators. APICURON is a biocuration database that tracks and rewards curator contributions using gamification principles. Biocuration involves collecting, organising and annotating biological data; and gamification can enhance the efficiency and accuracy of this process. The goal of this study was to use a two-pronged approach,i.e. quantitative and qualitative, to analyse the impact and effects (if any) of gamification strategies on user engagement and ultimately propose alternative user strategies to help improve the APICURON platform and in turn increase biocuration events. The quantitative approach had two main modes : forecasting and clustering. The prior used historical curation events to forecast the number of future curation events and the latter aimed to identify common curator behaviours and curation styles and perform a classification. Four models were used to perform the forecasting - Linear Regression, ARIMA, Window ETS and Prophet and the cluster analysis involved HMM and wavelets. The qualitative approach utilised two surveys measuring attitudes towards APICURON and gamification as well as intrinsic and extrinsic motivators. The main results showed an increase in the number of curation events but that could not be attributed to gamification. Results suggested that the gamification implementation had minimal effect on the curation trend and highlighted curator reluctance, disinterest and lethargy in engaging with current gamification implementations. Recommendations were made to implement a user-centered design based on the two main classification categories that the curators fell under : “Philanthropist” and “Achiever”, according to the Marczewski Gamification Type Framework ; as well as performing further research, continuous feedback and evaluation of new components. The main constraints of the study included errors in data collection by the knowledge resources resulting in incorrect data logging therefore limited usable data points as well as a general lack of curator participation in surveys.
2023
Analysis of the Effectiveness of Gamification implementations in Academic Research : APICURON case study
Gamification involves the incorporation of game elements and design principles for the purposes of enhancing user engagement and motivation. Game elements such as points, badges, medals and leader-boards provide incentives for active participation and healthy competition. In higher learning applications, gamification can be effective provided these elements are tailored to fit the specific context and balance both intrinsic and extrinsic motivators. APICURON is a biocuration database that tracks and rewards curator contributions using gamification principles. Biocuration involves collecting, organising and annotating biological data; and gamification can enhance the efficiency and accuracy of this process. The goal of this study was to use a two-pronged approach,i.e. quantitative and qualitative, to analyse the impact and effects (if any) of gamification strategies on user engagement and ultimately propose alternative user strategies to help improve the APICURON platform and in turn increase biocuration events. The quantitative approach had two main modes : forecasting and clustering. The prior used historical curation events to forecast the number of future curation events and the latter aimed to identify common curator behaviours and curation styles and perform a classification. Four models were used to perform the forecasting - Linear Regression, ARIMA, Window ETS and Prophet and the cluster analysis involved HMM and wavelets. The qualitative approach utilised two surveys measuring attitudes towards APICURON and gamification as well as intrinsic and extrinsic motivators. The main results showed an increase in the number of curation events but that could not be attributed to gamification. Results suggested that the gamification implementation had minimal effect on the curation trend and highlighted curator reluctance, disinterest and lethargy in engaging with current gamification implementations. Recommendations were made to implement a user-centered design based on the two main classification categories that the curators fell under : “Philanthropist” and “Achiever”, according to the Marczewski Gamification Type Framework; as well as performing further research, continuous feedback and evaluation of new components. The main constraints of the study included errors in data collection by the knowledge resources resulting in incorrect data logging therefore limited usable data points as well as a general lack of curator participation in surveys.
Gamification
Classification
Wavelet
Forecasting
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/64792