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The design-principles approach

The design-principles approach stems from the design experiments research trajectory, initiated in the early nineties by Brown (1992). These experiments were the ancestor of the design-based research methodology. At the same period, Collins (1992), called researchers to refer to education as a “design science”. He based this notion on Simon’s (1969) famous book, which identifies various professions, such as architecture, engineering, computer science, medicine, and education with the sciences of the artificial.

The design-principles approach uses ‘design-principles’ as an organizational unit for synthesizing design knowledge (Brown, 1992; Brown & Campione, 1996; Collins et al., 2004; Herrington, 2006; Kali, 2006; Linn, Bell, & Davis, 2004; Merrill, 2002; Quintana et al., 2004). Bell, Hoadley, and Linn (2004) describe design-principles as: “…an intermediate step between scientific findings, which must be generalized and replicable, and local experiences or examples that come up in practice. Because of the need to interpret design-principles, they are not as readily falsifiable as scientific laws. The principles are generated inductively from prior examples of success and are subject to refinement over time as others try to adapt them to their own experiences.” (p. 83).

The Design Principles Database (DPD)

Based on this approach, the DPD (Kali, 2006; Kali & Linn, in press) was developed to capture, coalesce and synthesize design knowledge. The DPD is a mechanism to support researchers and curriculum designers to share their design knowledge in the form of design-principles, exemplified by descriptions of features from learning environments. The database is an infrastructure for participants to publish, connect, discuss and review design ideas, as well as use these ideas to design new curricula. The current entries in the Design Principles Database represent the contributions of over sixty individual researchers. The database includes about one hundred features (mainly from physical, life, and earth sciences), connected with several dozen design-principles. Each design-principle provides a general rationale, theoretical underpinning, and important considerations, such as pitfalls, tradeoffs and limits of practical use, to help designers benefit from the many example features it is connected with in the database. Although the database stems from the design-principles approach, the hierarchical structure of the database, the connections between design-principles in various levels and between principles and example features, and the constructs that make up a design-principle, follow the spirit of Alexander’s (1979) design-pattern language. In this manner, the Design Principles Database merges between the design-principles and design-patterns approach. Recent research has shown that the database can (a) promote collaborative knowledge building for communities who design and explore educational technologies (Kali, 2006, in press), and (b) assist novice designers in creating effective technology-based curriculum units (Ronen-Fuhrmann et al., in press).

Examples of features and principles from the DPD

Some examples of design principles from the DPD:

Some examples of features from the DPD:

How does the DPD work?

The DPD is a set of interconnected features and principles. Each feature is linked with a principle and principles are linked between themselves in a hierarchical manner. Principles in the database are described in three levels of generalization: Specific Principles are those that connect directly to a single feature or single research investigation and provide the specific rationale behind the design of that feature. Pragmatic Principles connect several Specific Principles, and Meta-Principles capture abstract ideas represented in a cluster of Pragmatic Principles. The illustration below represents these multiple connections, and provides examples of software features and principles in the three hierarchical levels.

The structure of the DPD

DPD publications

Link to list of publications regarding the DPD


  • Alexander, C. (1979). The timeless way of building. New York: Oxford University Press.
  • Avgeriou, P., Papasalouros, A., Retalis, S., & Skordalakis, E. (2003). Towards a pattern language for learning management systems. Educational Technology & Society, 6(2), 11-24.
  • Bell, P., Hoadley, C., & Linn, M. (2004). Design-based research in education. In M. C. Linn, E. A. Davis & P. Bell (Eds.), Internet environments for science education (pp. 73-88). Mahwah, NJ: Lawrence Erlbaum Associates.
  • Brown, A. L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. The Journal of Learning Sciences, 2(2), 141-178.
  • Brown, A. L., & Campione, J. C. (1996). Psychological learning theory and the design of innovative environments: On procedures, principles and systems. In L. Shauble & R. Glaser (Eds.), Contributions of instructional innovation to understanding learning. Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Collins, A. (1992). Toward a design science of education. In E. Scanlon & T. O'Shea (Eds.), New directions in educational technology (pp. 15-22). New York: Springer-Verlag.
  • Herrington, J. A. (2006). Authentic e-learning in higher education: design principles for authentic learning environments and tasks. In T. C. Reeves & S. Yamashita (Eds.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2006 (pp. 3164-3173). Chesapeake, VA: AACE.
  • Kali, Y. (2006). Collaborative knowledge building using the Design Principles Database. International Journal of Computer *Support for Collaborative Learning, 1(2), 187-201.
  • Kali, Y. (2008). The Design Principles Database as means for promoting design-based research. In A. E. Kelly & R. Lesh (Eds.), Handbook of design research methods in education. Mahwah, NJ: Lawrence Erlbaum Associates.
  • Kali, Y., & Linn, M. C. (in press-a). Curriculum design - as subject matter: Science. In B. McGraw, E. Baker & P. Peterson (Eds.), International Encyclopedia of Education (3rd Edition): Elsevier.
  • Kali, Y., & Linn, M. C. (2007). Technology-enhanced support strategies for inquiry learning. In J. M. Spector, M. D. Merrill, J. J. G. V. Merriënboer & M. P. Driscoll (Eds.), Handbook of Research on Educational Communications and Technology (3rd Edition) (pp. 445-490). Mahwah, NJ: Erlbaum.
  • Merrill, M. D. (2002). First principles of instruction. Educational Technology Research and Development, 50(3), 43-59.
  • Mor, Y., & Winters, N. (2007). Design approaches in technology enhanced learning. Interactive Learning Environments, 15, 61-75.
  • Quintana, C., Reiser, B. J., Davis, E. A., Krajcik, J., Fretz, E., Golan, R. D., et al. (2004). A scaffolding design framework for software to support science inquiry. Journal of the Learning Sciences, 13(3), 337-386.
  • Ronen-Fuhrmann, T., Kali, Y., & Hoadley, C. M. (in press). Helping education students understand learning through designing. Educational Technology.
  • Simon, H. A. (1969). The Sciences of the artificial. Cambridge, MA: MIT Press.
  • van den Akker, J. (1999). Principles and methods of development research. In J. v. d. Akker, N. Nieveen, R. M. Branch, K. L. Gustafson & T. Plomp (Eds.), Design methodology and developmental research in education and training (pp. 1-14). The Netherlands: Kluwer.

Signature and Date: Yaelk 15:54, 25 December 2007 (MET)