As we gear our collective efforts towards achieving the Sustainable Development Goals, the notion of 'missing data' in education recurs throughout, especially in the context of the Global South. We are often unaware of the learning situation in many resource-constrained settings even as global data regimes continue to proliferate. In response, this paper introduces the concept of 'infra-data', based on our practice in Pakistan, to identify the often-overlooked wealth of educational evidence that lies beneath the surface of traditional metrics for education.

Drawing from theoretical frameworks like James C. Scott's 'hidden transcripts' and Aníbal Quijano's 'coloniality of knowledge', this study illuminates infra-data as a window into the 'unseen' yet impactful educational practices that emerge from localized knowledge, pedagogies, and ways of thinking. Infra-data would allow us to explore the epistemic frames in which these practices are encoded. Utilizing Shaffer’s quantitative ethnography, we dive into infra-data, providing a window into diverse pedagogical approaches across the Global South. In this research, we delve into the case of Siyani Sahelian Program by Idara-e-Taleem-o-Aagahi, a second chance education program on accelerated learning reaching 50 thousand out-of-school adolescent girls across Punjab, Pakistan. By analyzing secondary data from Siyani Sahelian program, we aim to shed light on the definition, measurement, and integration of learning impact from the learner communities. This approach not only offers insights specific to the Pakistani context but also contributes to a broader understanding by providing a comparative perspective on localized vs global mainstream education narratives and perspectives.

The methodological approach for this research is anchored in Shaffer's quantitative ethnography, which allows for a rich, data-driven understanding of educational contexts. We will apply this methodology to identify and analyze infra-data from a sample of 20,000 learners within the Siyani Sahelian program. This infra-data is not a mere collection of numbers; it is a rich tapestry that weaves together various educational elements into a holistic narrative directly from the learner communities. Within the scope of the Siyani Sahelian program, our analysis will delve into a diverse range of infra-data components. This includes: • Demographic Information Recognizing the heterogeneity of learner populations, our methodology incorporates a detailed examination of Demographic Information. This aspect of infra-data collection encompasses an array of variables, including age, gender, socio-economic status, language, cultural background, and geographical location. The customization of education based on demographic insights ensures that interventions are not only contextually relevant but also equitable and inclusive, thereby contributing to the overarching goal of educational equality. • Student Learning Outcomes Our infra-data framework emphasizes the critical importance of Student Learning Outcomes, expanding beyond the limitations of standardized testing to encompass a spectrum of qualitative and quantitative data. This includes, but is not limited to, classroom-based assessments, project-based learning evaluations, and progressive, informal feedback mechanisms that capture the evolving academic and practical skill mastery of students. • Perceptions and Attitudes Perceptions and Attitudes form a qualitative component of infra-data that captures the subjective experiences and levels of satisfaction among students, educators, and parents. Through tools such as surveys, structured interviews, and focus group discussions, this data illuminates stakeholders' views on the educational interventions they experience • Enrollment Data Enrollment Data provides quantitative measures of student engagement with educational interventions, functioning as a proxy for the relevance and effectiveness of these initiatives. This encompasses attendance records, participation in educational activities, interactions with digital content, and completion rates of courses or assignments. • Practice Data The infra-data component of Practice Data entails a comprehensive documentation of the implementation of educational interventions, detailing the pedagogical strategies, curriculum adaptations, instructional materials, teacher training, and the integration of technology in the teaching and learning processes. This exhaustive record provides an overarching view of the educational landscape, offering insights into the efficacy of different teaching approaches and the contextual factors that contribute to or hinder the success of educational initiatives.

In conclusion, we intend to explore the critical role of infra-data in enabling sustainable and meaningful education systems in the Global South. Infra-data stands as a vital resource in addressing specific challenges such as high out-of-school rates, gender disparities, and resource constraints prevalent in these regions. By embedding this data, deeply rooted in local contexts and practices, into educational policymaking, we can develop strategies that are not only informed by empirical evidence but also attuned to cultural and contextual nuances. This approach aligns closely with the aspirations of Sustainable Development Goal 4, emphasizing inclusive and equitable quality education. The integration of infra-data into educational planning and implementation promises to enrich the conceptual understanding of education in the Global South, leading to policies and practices that are truly inclusive and equitable.

UNESCO Institute for Statistics (UIS). (2020). The World Needs Almost 69 Million New Teachers to Reach the 2030 Education Goals. Scott, J. C. (1990). Domination and the Arts of Resistance: Hidden Transcripts. Yale University Press. Shaffer, D. W. (2017). Quantitative Ethnography. Cathcart Press. Quijano, A. (2000). Coloniality of Power and Eurocentrism in Latin America. International Sociology, 15(2), 215-232. https://doi.org/10.1177/0268580900015002005