Digital Data Collection among Low ICT-Literate Rural Communities: A Case Study using Google Forms  via Smartphones

Wan Hussain Wan Ishak; Fadhilah Yamin; Risyawati Mohamed  Ismail; Mastora Mustafar; Siti Zakiah Abu Bakar

doi:10.63017/jdsi.v3i2.121

Authors

Wan Hussain Wan Ishak School of Computing Universiti Utara Malaysia
Fadhilah Yamin Knowledge Science Research Lab, School of Technology Management and Logistics, Universiti Utara Malaysia
Risyawati Mohamed Ismail School of Technology Management and Logistics, Universiti Utara Malaysia
Mastora Mustafar School of Technology Management and Logistics, Universiti Utara Malaysia
Siti Zakiah Abu Bakar School of Technology Management and Logistics, Universiti Utara Malaysia

DOI:

https://doi.org/10.63017/jdsi.v3i2.121

Keywords:

Google Forms, rural communities, low ICT literacy, smartphone surveys, data quality, digital data collection, rural ICT access

Abstract

This study investigates the use of Google Forms as a digital tool for daily livestock monitoring among rural, low ICT-literate chicken farmers in Malaysia. A total of 198 responses were collected via smartphones through WhatsApp-distributed forms, allowing participants to self-report poultry conditions while reducing the need for frequent site visits. While the approach proved accessible and cost-effective, analysis revealed significant data quality issues, including inconsistent data entry (e.g., mixed numeric and textual values), unstructured categorical responses, duplicate submissions, ambiguous placeholder values, and the absence of unique identifiers. These challenges limited the reliability and usability of the dataset for meaningful analysis. To address these issues, the study recommends implementing structured input fields, validation rules, unique respondent IDs, and user training materials tailored to low digital literacy. This paper highlights both the potential and pitfalls of digital self-reporting tools in underserved rural contexts and provides practical recommendations for improving data quality in similar monitoring efforts. The findings offer valuable guidance for researchers and practitioners designing data collection systems in constrained environments.

References

M. Singh and S. Burgess, "Electronic data collection methods," in Handbook of Research on Electronic Surveys and Measurements, R. Reynolds, R. Woods, and J. Baker, Eds. Hershey, PA: IGI Global, 2007, pp. 28–43. doi: 10.4018/978-1-59140-792-8.ch004.

H. Taherdoost, "Data collection methods and tools for research: A step-by-step guide to choose data collection technique for academic and business research projects," Int. J. Acad. Res. Manage. (IJARM), vol. 10, no. 1, pp. 10–38, 2021.

G. Fitzgerald and M. FitzGibbon, "A comparative analysis of traditional and digital data collection methods in social research in LDCs: Case studies exploring implications for participation, empowerment, and (mis)understanding," in Proc. 19th IFAC World Congr., Cape Town, South Africa, Aug. 24–29, 2014, pp. 11437–11443.

P. E. Choo, F. Mat Yamin, and W. H. Wan Ishak, "Customer satisfaction towards onsite restaurant interactive self-service technology (ORISST)," Data Sci. Insights, vol. 2, no. 1, pp. 35–44, 2024. [Online]. Available: https://citedness.com/index.php/jdsi/article/view/15

M. J. Hassenstein and P. Vanella, "Data quality—Concepts and problems," Encyclopedia, vol. 2, no. 1, pp. 498–510, 2022. doi: 10.3390/encyclopedia2010032.

M. F. M. Mohsin, W. H. Wan Ishak, Y. Yusof, J. Mohd Jamil, and A. Ahmad, "Web server log data pre-processing for mining zakat user profile using association rules," Int. J. Bus. Intell. Data Min., vol. 26, no. 1/2, pp. 46–65, 2025. doi: 10.1504/IJBIDM.2025.143925.

D. B. Shanmugam, J. Dhilipan, A. Vignesh, and T. Prabhu, "Challenges in data quality and complexity of managing data quality assessment in big data," Int. J. Recent Technol. Eng. (IJRTE), vol. 9, no. 3, pp. 589–593, 2020. doi: 10.35940/ijrte.C5643.099320.

L. Cai and Y. Zhu, "The challenges of data quality and data quality assessment in the big data era," Data Sci. J., vol. 14, no. 0, p. 2, 2015. doi: 10.5334/dsj-2015-002.

M. I. Jaya, F. Sidi, L. S. Affendey, I. Ishak, and M. A. Jabar, "Systematic review of data quality research," J. Theor. Appl. Inf. Technol., vol. 97, no. 21, 2019. doi: 10.5281/zenodo.5374485.

F. Dravis, "Data quality strategy: A step-by-step approach (Practice-oriented paper)," in Proc. 9th Int. Conf. Inf. Qual. (ICIQ-04), 2004, pp. 27–43.

X. Li, L. Zhang, P. Zhang, and Y. Shi, "Problems and systematic solutions in data quality," Int. J. Serv. Sci., vol. 2, no. 1, pp. 53–69, 2009.