Call for Papers – Quantitative ethnography in education research and evaluation in low- and middle-income nations

Closes:

Call for Papers: Quantitative ethnography in education research and evaluation in low- and middle-income nations

Overview:

This special issue invites education research and evaluation studies that apply tools of Quantitative Ethnography (QE) in low- and middle-income countries. It aims to make these tools, now gaining traction in numerous social science domains, more visible and useful for determining the efficacy of education development interventions or initiatives.

Quantitative ethnography (QE) refers to methodologies that computationally interpret data from what historically has been primarily qualitative approaches of ethnographic study. The publication of Quantitative Ethnography (Shaffer) in 2017 spurred consideration of the methodology across a spectrum of social sciences, along with a statistical tool called epistemic network analysis (ENA). Development of QE and ENA have been extensively funded by the US National Science Foundation, are freely available, and have been adopted by a global mix of researchers. QE, especially in conjunction with ENA, can interpret large datasets through the prism of ethnographic analysis, with levels of statistical precision and visual depictions of critical data not previously available. QE is one means to scaffold ethnographic analysis into the era of large data sets and computational power.

While the application of QE and related tools is climbing and creating a substantial literature, research and evaluation communities in education development and interventions in low- and middle-income nations have benefited only minimally from this ascendant methodology and are not significantly represented in this young corpus.

Topics of interest:

This special issue thus seeks early papers that demonstrate the analytic traction of QE methodologies across the broad spectrum of education research and evaluation in low- and middle-income nations. Such early papers promise to shape the way QE approaches are conceptualized and applied, whether by national or local education systems, NGOs, aid agencies, private philanthropies, or multilateral organizations. The special issue especially welcomes any contribution in this broad spectrum.

Specific topics of interest include:

  1. Evaluations of national education development policy directions at a national or regional level are of significant interest. 
  2. Research that supports interventions or initiatives that are limited to age ranges or curriculum subject matter.  
  3. Papers that demonstrate how cultural nuance and complexity in education development may become more visible through QE approaches. 

Timeline:

Submission open: 1st of October 2023
Submission close: 8th of April 2024

Submission information:

  • Papers should be up to 8,000 words, including the structured abstract and references. Please refer to this page for detailed submission guidelines under ‘Manuscript Requirements’.
  • Submissions are made using ScholarOne Manuscripts. Registration and access are available here.
  • Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e., in response to “Please select the issue you are submitting to.”
  • Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Guest Editor:

Eric Hamilton, PhD, Davidson Endowed Professor of Education and Technology (Pepperdine University, USA)
Dr. Hamilton is principal investigator of projects funded by the US National Science Foundation that explore the mutually reinforcing processes of identity formation and STEM competence development among adolescents as they collaborate with peers in global collaborations between learners in a rich mixture of low-income, middle income, and high income countries. A former visiting professor at Hiroshima University & CICE and former sr. programme officer at UNESCO, he was a founding board member of the International Society for Quantitative Ethnography.

Danielle P. Espino, EdD, Adjunct Professor of Education (Pepperdine University, USA)
Dr. Espino is co-principal investigator of projects funded by the US National Science Foundation that explore the mutually reinforcing processes of identity formation and STEM competence development among adolescents as they collaborate with peers in global collaborations between learners in a rich mixture of low-income, middle income, and high income countries. She has helped to lead global data challenges in Quantitative Ethnography (QE) and Epistemic Network Analysis (ENA), teaches university seminars in QE and ENA, supervises dissertations using these approaches, and is actively involved and visible in the International Society for Quantitative Ethnography. She served on the program committee for 2022 International Conference on Quantitative Ethnography.

Seung B. Lee, Ph.D., Assistant Professor of Education (Pepperdine University, USA)
Dr. Lee is co-principal investigator of projects funded by the US National Science Foundation that explores the mutually reinforcing processes of identity formation and STEM competence development among adolescents as they collaborate with peers in global collaborations between learners in a rich mixture of low-, middle , high- income countries. He has helped to lead global data challenges in QE and ENA, teaches university seminars in QE and ENA, supervises QE/ENA dissertations, and is actively involved and visible in the International Society for Quantitative Ethnography. He was program co-chair for the second International Conference on Quantitative Ethnography in 2020.

Kristina M. Lux, Ph.D., Postdoctoral Research Fellow (Pepperdine University, USA)
Dr. Lux is a postdoctoral research fellow on two projects funded by the US National Science Foundation. Her dissertation involved an ethnographic study exploring critical variables for an alternative model for technical and vocational tertiary education in Kenya. Her dissertation applied QE and ENA methodology and techniques. Prior research and efforts while in doctoral study have included multiple journeys and stays in Kenya and Namibia to assist in advancing education opportunities across the elementary to tertiary spectrum.

Examples and relevant references:

Arastoopour Irgens, G., & Eagan, B. (2022). The Foundations and Fundamentals of Quantitative Ethnography. International Conference on Quantitative Ethnography Damşa, C., & Barany, A. (2023). Advances in Quantitative Ethnography: 4th International Conference, ICQE 2022, Copenhagen, Denmark, October 15–19, 2022, Proceedings. Springer Nature.
Espino, D., Lee, S. B., Van Tress, L., Baker, T. T., & Hamilton, E. R. (2020). Analysis of US, Kenyan, and Finnish discourse patterns in a cross-cultural digital makerspace learning community through the IBE-UNESCO global competences framework. Research in Social Sciences and Technology, 5(1), 86-100.
Espino, D. P., Lee, S. B., Hokama, M., & Hamilton, E. R. (2021). Initial Analysis of Prompted Discourse Patterns in an Informal, Online, Global Collaborative Learning Environment. Proceedings of the 14th International Conference on Computer-Supported Collaborative Learning-CSCL 2021.
Hamilton, E., Espino, D., Jones, N., & Lee, S. (2022). Broadening participation, building STEM competencies, and strengthening identity formation through cross-cultural and international collaboration in project-based learning: Asset-Based Learning Environments (ABLE). DRL-2215613 [Grant].
Hamilton, E. R., Lee, S. B., Charles, R., & Molloy, J. (2022). Peering a Generation into the Future: Assessing Workforce Outcomes in the 2020s from an Intervention in the 1990s. In B. Wasson & S. Zörgő, Advances in Quantitative Ethnography Cham.
Ruis, A. R., & Lee, S. B. (2021). Advances in Quantitative Ethnography: Second International Conference, ICQE 2020, Malibu, CA, USA, February 1-3, 2021, Proceedings (Vol. 1312). Springer Nature.
Shaffer, D. W. (2017). Quantitative ethnography. Cathcart Press.
Shaffer, D. W. (2018). Epistemic network analysis: Understanding learning by using big data for thick description. In F. Fischer, C. E. Hmelo-Silver, S. R. Goldman, & P. Reimann (Eds.), International handbook of the learning sciences (pp. 520-531). Routledge. 
Shaffer, D. W., & Ruis, A. R. (2017). Epistemic network analysis: A worked example of theory-based learning analytics. In C. Lang, G. Siemens, A. F. Wise, & D. Gasevic (Eds.), Handbook of learning analytics (pp. 175-187). Society for Learning Analytics Research. 
Shum, S. B., Irgens, G. A., Moots, H., Phillips, M., Shah, M., Vega, H., & Wooldridge, A. (2021). Participatory Quantitative Ethnography. Advances in Quantitative Ethnography, 126-138.