diSessa and Cobb (2004) in their article emphasize the important role of theory in design experiments, specifically through what they call ‘ontological innovations’. At the beginning of their article, they argue that theories, such as grand theories, orienting frameworks, frameworks for action, and specific instructional theories are valuable for design research studies, but these theories don’t provide the “real design work in generating, selecting, and validating design alternatives at the level at which they are consequential for learning” (diSessa & Cobb, 2004, p.80). Ontological innovations, on the other hand, provide “new lenses for making sense of what is happening” in instructional settings, allowing researchers to better grasp and enhance learning processes. (diSessa & Cobb, 2004, p.99). Through the two case studies, Meta-Representational Competence (MRC) and sociomathematical norms, the authors demonstrate how developing and refining these new theoretical constructs can lead to more effective instructional design and deeper insights into learning. As an instructional designer, I could see the strong connection between my role with this article. Instructional design often involves navigating complex learning environments, where factors like learner diversity, context, and technology play an important role. Ontological innovations can serve as a “lens” for instructional designers, helping interpret the dynamics of these environments more clearly and useful during the design process, where instructional strategies need to be tested, refined, and adapted based on the observed behaviour of learners.
The overall argument from Sandoval (2014) shows that conjecture mapping can make design research more systematic and productive in generating both practical designs and theoretical knowledge about learning. Conjecture mapping is a way systematically linked to the design of learning environments and mapping out “how learning happens” and “how to support it” (Sandoval, 2014, p.20), while also aiming to produce desired outcomes. In the article, Sandoval (2014) not only provides a detailed explanation of how conjecture mapping works, including its key elements and relationships, but also connects to broader issues like causal attribution, contextual factors, and research trajectories. He emphasizes that “mapping the conjectures guiding a design can guide the systematic test of particular conjectures about learning and instruction in specific contexts” (p.19). This process helps create more structured and effective learning experiences. Personally, I believe Sandoval’s claim is highly relevant to me as an instructional designer, When I develop courses or learning environments, I often base my designs on certain theories or ideas, which can be considered “conjectures” or hypotheses about how learning occurs and how instruction should be structured. Mapping these conjectures makes the reasoning behind the design decisions explicit, helping to meet the needs of learners in specific learning settings. It also provides a clear framework for evaluating and refining designs based on evidence, making the instructional design process more transparent and effective. Besides that, Sandoval (2014) distinguishes “between conjectures about how design functions and conjectures about how those functions produce learning” (p.25). This separation between design conjectures (about how design elements will function) and theoretical conjectures (about how those functions produce learning) emphasizes the need to be intentional and reflective when creating and evaluating instructional materials. This insight impacts my work by reminding me to separate my assumptions about how a course design will operate, such as how students will engage with a discussion forum, from assumptions about how that engagement will foster deeper learning, like critical thinking or collaboration. Thus, conjecture mapping provides a systematic approach for connecting theory to practice, testing, and refining educational interventions.
The last article from this week, Gutiérrez and Jurow (2016), introduces the concept of “social design experimentation (SDE)” as an approach to design-based research that aims to transform educational and social circumstances. The authors mainly focus on two key principles, equity and historicity which work together to foster meaningful learning and transformations in environments that can drive social change. Equity “focuses on challenging and transforming inequitable social systems, organizing pathways for expansive learning and identity development, and working with community partners to identify the most pressing concerns and needs of non-dominant communities” (p. 569). Historicity is “attention to history in the present and makes possible new arrangements for learning that extend the resources and understandings of the past into the future” (p.571). The authors emphasize the importance of historicity to see how past inequities shape current learning contexts. They also highlight the significance of collaborative design, where stakeholders co-construct interventions that reflect their communities’ needs. Through case studies, the article illustrates how SDE fosters critical consciousness and consequential learning by empowering marginalized learners to engage in “new perspectives on the ‘why’ and ‘how’ of their community’s marginalization” (p. 567) and participate in transformative social action.
A common theme across the three readings is the role of theory in design-based research, and the development of educational interventions, which aligns strongly with my research focus on the intersection of instructional design and educational equality, particularly in the context of asynchronous online courses. diSessa and Cobb’s (2004) concept of “ontological innovation” ties into my exploration of active learning strategies by highlighting the need to create new categories or constructs that are essential to understanding how different design decisions impact learning. Their emphasis on the theory of “doing real design work” in shaping instructional strategies resonates with my interest in implementing these strategies in asynchronous environments. I can use this framework to develop innovative approaches that support equity by ensuring that all students have access to meaningful learning experiences, regardless of their background or learning context. Sandoval (2014) emphasizes the importance of conjecture mapping, which directly supports my research goal of investigating how course design, instructional strategies, and assessment methods impact online instructor-student interactions. By systematically mapping conjectures about design elements in asynchronous online courses, I hope to explore how specific strategies lead to desired learning outcomes, such as increased engagement and active learning. Lastly, Gutierrez and Jurow’s (2016) work on social design experiments further builds on these ideas by framing educational practices for more equitable participation. This approach aligns with your goal of supporting instructors in designing courses that are not only effective but also inclusive. In creating environments where online instructors can foster equitable interactions, the principles of social design experiments offer a pathway for embedding equity into every aspect of course design from the structuring of discussions to the methods of assessment. This ensures that the online learning environment is not just a space for content delivery, but also actively works to remove barriers to participation and engagement for all students. Across these readings, there is an evolving understanding of how theory, design, and equity interact in the pursuit of improving educational outcomes.
References
diSessa, A. A., & Cobb, P. (2004). Ontological Innovation and the Role of Theory in Design Experiments. The Journal of the
Learning Sciences, 13(1), 77–103. https://doi.org/10.1207/s15327809jls1301_4
Sandoval, W. (2014). Conjecture Mapping: An Approach to Systematic Educational Design Research. The Journal of the Learning Sciences, 23(1), 18–36. https://doi.org/10.1080/10508406.2013.778204
Gutiérrez, K. D., & Jurow, A. S. (2016). Social Design Experiments: Toward Equity by Design. The Journal of the Learning Sciences, 25(4), 565–598. https://doi.org/10.1080/10508406.2016.1204548
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