Impact of AR Delivery on People Living in Multidimensional Poverty

The Multidimensional Poverty Index (MPI) “measures the complexities of poor people’s lives, individually and collectively, each year.” It is a key measure for developing countries with regards to progress toward eliminating world poverty. Importantly, this specific measure accounts for many elements of non-monetary poverty to calculate an overall score, composed of three dimensions: health, education, and standard of living.

According to the 2020 report, “this is a key moment to study how nonmonetary poverty goes down. It is 10 years before 2030, the due date of the Sustainable Development Goals (SDGs), whose first goal is to end poverty in all its forms everywhere.”

Because AR is a unique information delivery format that is highly conducive to providing increased accessibility to skill acquisition, learning, and even remote healthcare, and given the challenges that COVID has brought into the mix in 2020, UN nations will increasingly be looking for ways to sustain growth and minimize regression with regards to 2030 UN SDG targets. Because education accounts for 1/3 of the Multi-dimensional Poverty Index and this index is measured annually and can be applied flexibly to individuals, this is an ideal opportunity in time to investigate the impacts of AR with regards to reducing world poverty. There is likely to be substantial interest within local governments as well as amongst corporate entities supporting the UN 2030 SDGs.

This research topic focuses on measuring how access to AR systems for delivery of educational and healthcare programs over the course of a year impacts individual MPI. It will involve engagement with at-risk communities and require a combination of social and technological measurement tools.

Stakeholders

Government officials and policymakers in World Bank Group and UN nations, social performance/impact executives in large, global organizations, particularly those with a large social license to operate – preference to industries in which corporations provide educational and healthcare services for many aspects of community life (e.g. metals and mining), education policy makers/professionals.

Possible Methodologies

The proposed research would need to decide upon a flexible scoring mechanism for individual multidimensional poverty calculation. The principal investigator would develop partnerships with a host corporation and community. Research would include calculation of pre-study MPIs and introduction of AR intervention via A/B trial scenarios, potentially with a few different levels of AR intervention. Then researchers would collect data about post-intervention behaviors and worker status. Post-study MPIs could be calculated and recommendations developed for future implementation.

Research Program

This study could link closely with existing research programs associated with metals and mining, education, and policy, as well as potentially healthcare, depending upon the scope of the research project.

Miscellaneous Notes

The following is from the most current Multidimensional Poverty Index (MPI) report: The MPI measures the complexities of poor people’s lives, individually and collectively, each year. The measure was co-developed between the Oxford Poverty and Human Development Initiative at the University of Oxford and the Human Development Report Office of the United Nations Development Programme in 2010. Importantly, this specific measure accounts for many elements of non-monetary poverty to calculate an overall score, comprised of three dimensions: health, education, and standard of living.

Keywords

United Nations, Sustainable Development Goals (SDG), Multidimensional Poverty Index (MPI), poverty, policy, education, skill development, socio-economic effects, social

Research Agenda Categories

Business, End User and User Experience

Expected Impact Timeframe

Near

Related Publications

Using the words in this topic description and Natural Language Processing analysis of publications in the AREA FindAR database, the references below have the highest number of matches with this topic:

• Al Akil, D., Ahmed, V., & Saboor, S. (2020). The Utilization of Augmented Reality Technologies within the Engineering Curricula – Opportunities and Challenges. 2020 IFEES World Engineering Education Forum – Global Engineering Deans Council (WEEF-GEDC)
• Mubeen, T., Hussain, S. K., & Aqeel, F. (2019). TALEM(The Advanced Learning and Education Management) System With OBE(Outcome-based Education). 2019 International Conference on Information Science and Communication Technology (ICISCT)
• Blattgerste, J., Renner, P., & Pfeiffer, T. (2019). Augmented reality action assistance and learning for cognitively impaired people. Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments
• Ahmad, N. I. N., & Junaini, S. N. (2020). Augmented Reality for Learning Mathematics: A Systematic Literature Review. International Journal of Emerging Technologies in Learning (iJET), 15(16), 106
• Khowaja, K., Banire, B., Al-Thani, D., Sqalli, M. T., Aqle, A., Shah, A., & Salim, S. S. (2020). Augmented Reality for Learning of Children and Adolescents With Autism Spectrum Disorder (ASD): A Systematic Review. IEEE Access, 8, 78779-78807

More publications can be explored using the AREA FindAR research tool.

Author

Jennifer Rogers

Last Published (yyyy-mm-dd)

2021-08-31

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