Exploring data mining and gamification as tools for poverty analysis and policy formulation: A methodological framework
College
College of Computer Studies
Department/Unit
Software Technology
Document Type
Article
Source Title
Journal of Economics and Economic Education Research
Volume
15
Issue
3
First Page
25
Last Page
38
Publication Date
1-1-2014
Abstract
Economies are deemed to have automated systems of collecting their respective poverty statistics because the availability of these databases are imperative, which have generated a need for new techniques that will transform the data into useful information that can assist policymakers in formulating effective poverty-reduction policies. An alternative method is the use of data mining techniques - the extraction of hidden patterns of information from large databases, beyond regression, that will allow for the generation of a prediction on the direction and extent of change on the status of a sample. After determining these hidden patterns, the application of gamification can be utilized as a behavior change mechanism particularly for people who are predisposed to engaging in games on issues that are reality-based. The change in behavior gets manifested in their opinions about an issue or problem and subsequently takes positive actions towards a solution to a problem. Various problems besetting poverty stricken households can be solved through change in behavior once they realize the opportunities that can come their way by doing so. The change is much more effective if part of the motivation comes from within the individual and the immediate environment makes it possible for them to see the positive effect this change will bring.
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Recommended Citation
Bulos, R. D., Delfino, N. M., & Rivera, J. R. (2014). Exploring data mining and gamification as tools for poverty analysis and policy formulation: A methodological framework. Journal of Economics and Economic Education Research, 15 (3), 25-38. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/3769
Disciplines
Economics
Keywords
Poverty--Statistics; Information storage and retrieval systems—Poverty; Data mining—Statistical methods
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