KATE GRUNOW
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Design Experiments in Educational Research

9/21/2022

 
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​Photo by Edho Pratama on Unsplash
In their article "Design Experiments in Educational Research", Cobb et al. (2003) draw on prior understandings about conducting design experiments to share characteristics of the methodology and to describe what conducting a design experiment entails. Design experiments  are an iterative process in which the "designed context is subject to test and revision" (pg. 9). Design experiments are conducted t develop theories that target domain-specific learning processes. Special emphasis is placed on theories to reflect the view that "explanations and understandings inherent in them are essential if educational improvement is to be a long-term, generative process" (pg. 9). Design experiments are also said to ideally end in greater understanding of a learning ecology by designing the element of the complex system and predicting how these element interact to support learning. In this way, design experiments aptly represent the complexity of educational systems. Cobb et al. notes that design experiments move beyond tinkering with effective designs by focusing on a design theory that explains why designs work and making recommendations for how they be modified to new circumstances.

Five crosscutting features apply to design experiments:
  1. The purpose of design experimentation is to develop a class of theories about the process of learning and what factors are designed to support that learning.
  2. The methodology of design experiments highly interventionist in nature because the intent is to investigate the possibilities for educational improvement by bringing about new forms of learning to study them.
  3. The third crosscutting feature builds on the previous two in that design experiments create the conditions for developing theories yet to do so must put these theories at risk. For this reason, design experiments are two-faced. On the prospective side, designs are implemented, a learning process is hypothesized with a plan for supporting it in mind, to later expose the process to examination. On the reflective side, design experiments are said to be conjecture-driven tests that undergo several levels of analysis.
  4. The two faces of design experiments--prospective and reflective--result in the fourth crosscutting feature--iterative design. Conjectures are generated and refuted; alternative conjectures can also be generated and tested.
  5. Finally, theories are deemed "humble" for two reasons: they are concerned with domain-specific learning processes and more importantly they are accountable to the activity of design.

Several issues must be addressed when preparing for a design experiment. First, before conducting a design experiment one must answer the question: What is the point of the study? Research teams should also draw on and synthesize the prior research literature to "identify central organizing ideas for a domain" (Cobb, et al., pg.11). Other preparations include clearly defining the conjectured starting points, elements of trajectory, and prospective endpoints as well as formulating a design that embodies testable conjectures. The size of the research team and their expertise will vary.

In order to conduct a design experiment, the team must simply have the collective expertise needed to carry out the preparation procedures and conduct the experiment. Cobb et al. identify four important functions that will require the teams direct engagement.
  1. A clear view of the anticipated learning pathways and the potential means of support must be maintained and communicated within the research team
  2. Ongoing relationships with practitioners must be maintained.
  3. Design researchers must seek to develop a deep understanding of the ecology of learning.
  4. Regular debriefing sessions should be held to discuss and interpret past events as well as plan for prospective events.

Successful design experiments will also attend to the problem of measure. To conclude, Cobb et al. reiterates that the five crosscutting features outlined in the article are defining characteristics of a genre of science that holds great potential if researchers manage the preparation of difficulties associated with conducting design experiments appropriately.

Given that the potential for rapid pay-off is high with design experiments, the five crosscutting features and critical components for successfully planning and conducting this type of research is invaluable. Design experiments are also said to ideally end in greater understanding of a learning ecology by designing the element of the complex system and predicting how these element interact to support learning. Both the crosscutting features and the complex nature of a learning ecology are developed with detailed example that make the article invaluable to anyone looking to better understand the various methods of research in educational technology.

Design experiments are certainly an area of educational research that has peaked my interest now that I understand they ideally end in greater understanding of a learning ecology. Barron (2004) defined a learning ecology as a “set of contexts found in physical or virtual spaces that provide opportunities for learning.” Each context consists of a unique blend of activities, resources, relationships, and developing interactions. The research discussed by Barron in "Interest and self-sustained learning as catalysts of development: A learning ecologies perspective. Human Development" had strong connections to the ISTE Student Standards (Global Collaborator and Knowledge Constructor). These standards guide a portion of my work as an instructional technology consultant for grades K-12. For this reason, all discussions that lead to a greater understanding of a learning ecology are of interest to me at this point in my doctoral journey.

References
​
Barron, B. (2006). Interest and self-sustained learning as catalysts of development: A learning ecologies perspective. Human Development, 49, 193-224.
​
Cobb, P., Confrey, J., Lehrer, R., & Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32(1), 9-13.

González-Sanmamed, M., Muñoz-Carril, P.-C., & Santos-Caamaño, F.-J. (2019). Key Components of Learning Ecologies: A Delphi Assessment. British Journal of Educational Technology, 50(4), 1639–1655.


Designing Spaces that Promote Better Learning

9/1/2022

 
In the "Introduction" to The Cambridge Handbook of the Learning Sciences, R. Keith Sawyer argues that schools today do not reflect what research shows about the science of learning, but rather common sense assumptions that have been made about teaching and learning. For this reason, through his handbook Sawyer seeks to show key stakeholders how to design learning environments and classrooms that are rich with technology and reflect scientific research. According to Sawyer, citizens need to be able to move beyond memorizing facts to think critically about information and develop understandings that lead to innovations that solve real-world problems, but practices that reflect Instructionism function as an anchoring mechanism to such progress. Sawyer explains that by the 1970's researchers came to consensus on several key understandings about learning--
  • Students need deeper conceptual understanding to transfer their learning to real world settings.
  • The student must take an active role in the learning process to gain deeper conceptual understanding.
  • In addition to learning facts and procedures, students need to develop deeper conceptual knowledge to grapple with complex, real-world problems.
  • Educators must activate prior knowledge for students to transfer new learning outside of the classroom.
  • Students learn best when they are given opportunities to analyze and reflect on new learning in a variety of formats (e.g. text, audio, video, etc.)
Finally, the learning sciences research has provided explicit findings about what supports must be provided by the learning environment for learners to effectively construct their own knowledge. Specifically, students benefit from scaffolding, opportunities to articulate new learning and refine their ideas, reflection, and learning experiences that allow students to build rom concrete to abstract knowledge. ​


​Sawyer provides a robust review of the related literature about Instructionism and the research findings on the science of learning with the help of two accomplished scholars that are both authorities on the learning sciences. Sawyer acknowledges that Roy Pea, a professor of Education and Learning Sciences at Stanford University and former Editor-in-Chief Emerita of The Journal of the Learning Sciences, Janet Kolodner, helped with the historical details. Sawyer uses the historical details to argue that schools today are not based on research, but rather common sense assumptions about teaching and learning. While the claim certainly holds some merit today, one would be remiss if the date of publication was not taken into consideration as since 2006 the vast majority of schools have redesigned curriculum and adopted new practices that better align with the research findings related to the science of learning. Regardless of where schools are at on the continuum of redesigning classrooms to promote better learning, Sawyer's concise list of the practical implications of the research about the science of learning will serve schools well. 


​Sawyer's recommendations for promoting better learning based on the research findings of the learning sciences could easily serve as a guide for curriculum directors and/or department teams  seeking to update learning spaces or redesign new ones to better serve the needs of today's students and foster a culture of knowledge construction and innovation. Furthermore, for schools that have adopted the ISTE Standards for Educators and Students, the historical details provide a rationale for the educator and student shifts that were made between the NETS and the current ISTE standards. As such, the introduction can one of two functions. For some, the introduction may be a practical roadmap for designing spaces to promote better learning. And for others, this resource may simply be a starting point that prompts reflection and generates conversation for future planning. 
Reference
​
Sawyer, R. K. (2006). Chapter 1 introduction: The new science of learning. In R. K. Sawyer (Ed.). The Cambridge Handbook of the Learning Sciences (p. 1-16). New York: Cambridge University Press.

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