Development Evaluation Comparison

Pandem-Data fills a vital role in informing secondary life science students and their teachers about content, applications, and careers related to biomedicine and big data. Higher education (Grant, 2012), secondary schools (Grillenberger, 2014), and even middle schools (Buffum et al., 2014) seek new ways to embed big data applications into their curriculum. However, programs that illuminate what to focus on, how to develop the program, and what metrics to use are nonexistent. A preliminary literature review highlights the need to develop quickly and pilot test new programs for secondary education. No apparent “best practice” approach to resolving the void of big data programs exists. It will be important to evaluate Pandem-Data using a novel approach that uses a case study methodology to (a) describe the preformative development of the innovative Pandem-Data program and b) detail and analyze the processes of developmental evaluation that enabled the innovative response. This developmental evaluation process combines complexity concepts and systems thinking  to describe the program development. Development evaluations serve a small niche for programs that need to develop a rapid response and show promise for preformative development of a potentially broad-impact, scalable innovation (Patton, 2011).

Grillenberger and Romeike (2015) identified the need for an educational reconstruction of secondary computer science curriculum. They pointed to several questions that need to be examined in the educational reconstruction. First, the gap between science content and modern secondary computer science education needs further delineation. Secondly, how do potential areas (such as epidemiology) fit into existing high school computer science education? In this context, Grillenberger and Romeike (2015) highlighted the importance of considering students’ and teachers’ perspectives for the reconstruction.

Pandem-Data will use purposeful sampling to select 2 or 3 high school teachers who will engage in participatory feedback for the preformative evaluation. We’re currently recruiting high school math, science, or computer science teachers to review the Pandem-Data materials.


Grant, E. (2012). The promise of big data. Harvard Public Health, Spring/Summer, 14-19, 43-44. Retrieved from https://issuu.com/harvardpublichealth/docs/2012_spring_summer

Grillenberger, A. (2014). Big data and data management: a topic for secondary computing education. Proceedings of the tenth annual conference on international computing education research, Glasgow, Scotland, United Kingdom.

Grillenberger, A., & Romeike, R. (2015). Bringing the innovations in data management to CS education: An educational reconstruction approach. Proceedings of the workshop in primary and secondary computing education (pp. 88-91). London, United Kingdom: ACM. doi: 10.1145/2818314.2818330.

Leonard, S. N., Fitzgerald, R. N., & Riordan, G. (2016). Using developmental evaluation as a design thinking tool for curriculum innovation in professional higher education. Higher Education Research & Development, 35(2), 309-321.doi: 10.1080/07294360.2015.1087386

Patton, M. Q. (2011). Developmental evaluation: Applying complexity concepts to enhance innovation and use. New York, NY: Guilford Press.