Huang, David Junsong

Conceiving innovation diffusion as a Complex Adaptive System (CAS) broadens the approaches to foster scalable and sustainable diffusion of innovation in schools. This study adopted an Interpretivist Paradigm through multiple case studies to understand education leaders’ learning with regard to innovation diffusion as a CAS. There were four cases involving eight education leaders learning in four dyads. The purpose was to seek a descriptive and interpretative understanding of their learning processes, which included the knowledge development trajectories and the learning patterns through which the learning activities induced the knowledge development trajectories. Cognitive conflict was engaged as the learning strategy and learning activities included building an agent-based model, simulating the researcher’s model and playing a first-person role-play game. Analogical reasoning was engaged in reflections.

The grounded theory coding and analysis and episodic uptake analysis revealed nonlinearity of the knowledge development trajectories. The findings suggest that, prior to the learning, the dyads maintained ten simple Newtonian knowledge elements. After learning, the dyads made progression in developing ten comprehensive CAS knowledge elements. Analyzing the knowledge development trajectories indicated that the dyads experienced difficulties in constructing the CAS knowledge elements when they maintained prior Newtonian knowledge elements. The development trajectory of each knowledge element was gradual, progressing from conceptualization to comprehension and towards knowledge application in the real world. The development trajectories of the different knowledge elements were intertwined.

Further data analysis on how cognitive conflict enabled the learning processes implied nonlinear learning patterns. Cognitive conflict induced by analogical reasoning helped the dyads conceptualized the first CAS knowledge element, whereas cognitive conflict induced by model building and simulation did not. For the dyads who had conceptualized the first CAS knowledge element through analogical reasoning, the discrepancies generated from model building and simulation, from knowledge incompatibility and from game play induced cognitive conflicts and sustained the intertwined knowledge development trajectories.

There are sources of evidence in this study that could potentially extend the conventional conditions for analogical reasoning and cognitive conflict. The literature of analogical reasoning suggests that effective analogical reasoning requires learners’ adequate knowledge on the analogy and the target domain, and analogy’s sufficient degrees of similarities with the target. The learning patterns in this study seemed to suggest that, when the dyads, who lacked CAS knowledge, were conceptualizing the first CAS knowledge element, they did not learn through analogies that had more degrees of similarities; however, they learnt through analogies that had fewer degrees of similarities. Similarly, the findings may also suggest alternative views about the premises for cognitive conflict. The literature suggests that meaningful cognitive conflict requires discrepancies to be credible and relevant, and learners to have more prior knowledge. In this study, the agent-based models provided by the researcher were direct modeling of innovation diffusion, whereas the analogies used in reflections were from domains different from innovation diffusion and were only plausible to be mapped for the dyads to learn innovation diffusion. While the analogies induced valid discrepancy and meaningful cognitive conflict in this study, the model building and simulation did not. The findings in this study also alluded that salient knowledge that mediates learning Complex Systems is perhaps learner dependent and domain specific. The study thus advocates that research on analogical reasoning and cognitive conflict should focus on understanding learners’ meaning-making processes, rather than conditions for analogical reasoning and cognitive conflict.

Based on the findings, this study also espouses that learning Complex Systems perhaps involves meta-complexity: the learning of individual knowledge elements is complex, and the intertwined knowledge development trajectories also exhibit characteristics similar to scale-free network topologies. The implications of meta-complexity for learning design are also discussed to complement the design principles for learning Complex Systems.

This symposium proposes a genre of learning designs called Student-Generated Ideas (SGIs), based on designing learning contexts that promote students as critical producers, distributors, and consumers of knowledge. SGIs place students’ ideas at the center of learning designs, considering the learning process as well as the learning goals/outcomes. By soliciting and foregrounding students’ diversified ideas in the classroom and beyond, the learning environment communicates to students that their ideas matter to others and that they have a position of responsibility to their own and their peers’ learning processes. The notion of SGIs is embodied in a repertoire of studies at the Learning Sciences Lab, National Institute of Education, Singapore, that offer varied yet overlapping interpretations of how student ideas can inform the design of learning contexts. In sharing the core design principles for SGIs approaches, this work contributes important components to the learning sciences discipline and changing educational practice.

To effectively foster innovation diffusion, school leaders need to learn innovation diffusion as Complex Adaptive Systems (CAS). In this study, two school leaders formed a dyad to learn both the knowledge about innovation diffusion and the knowledge in fostering innovation diffusion. Agent-based model building, model simulation, game play of a simulation game and reflections were designed as learning activities in this study. In the learning process, the learners developed the following understanding in innovation diffusion: teachers’ adoption decisions are based on limited rationality and local information; teachers have nonlinear influence on each other through social networks; teachers are heterogonous agents; and diffusion is a process of emergence. The learners also learnt to leverage on social networks to foster effective innovation diffusion. While agent-based model building faces challenges for learning CAS in the social science domain, this study shows that engaging learners in reflection activities helps to overcome the challenges.

Research management is an emerging field of study and its development is significant to the advancement of research enterprise. Developing the science of research management requires investigating social mechanisms involved in research management. Yet, studies on social mechanisms of research management is lacking in the literature. To address this gap, this paper proposes importing methodologies and theories from other social science disciplines to study the social mechanisms of research management and to build the science of research management. The paper first articulates what constitutes the science of research management, then proposes to appropriate Design-Based Research (DBR), a methodology in education research, for building the science of research management while at the same time strengthening the theory-practice nexus. A study of education research is then presented to illustrate how DBR is used to enact the theory of homophily which is imported from sociology. It reveals an opportunity to use social designs to develop social relationships among teachers from different schools for networked learning. Such a research endeavour also has potential to advance theories of relationship-building in sociology. Inferring from the example as an analogue to what is suggested for research management, the paper advocates a way to reciprocally connect research management as an emerging research field with more established social science disciplines at large and to advance both the theory and practice of research management.

Research on Productive Failure and preparatory mechanisms has consistently demonstrated a positive learning effect when students generate problem solutions before receiving formal instruction. However, it has been less examined whether the effect still holds when the generative task does not involve problem solving. Using a 2x2 experimental design, this study investigated the effects of generative tasks that involve analogical problem posing (without solving) on learning and transfer. Pedagogical sequence (i.e., generation-first or instruction-first) and type of analogical reasoning task (i.e., generating one’s own analogical problems or generating analogical mappings between given analogical problems) were the two factors manipulated. Preliminary analysis revealed no multivariate effects of the factors. Thus, we discuss the learning mechanisms enacted by analogical reasoning, reliability of the instruments, and the participants’ prior condition as possible reasons and to inform future studies.

This paper seeks to draw from contemporary understandings of translation science to highlight and elaborate upon possible norms and procedures which the authors have found to be critical in the successful extension and scaling of design-based research interventions in education into wider practitioner-based adoption and adaptation. The impetus for this interrogation is the desire to mediate the tensions which sometimes arise between researcher, practitioner, and other stakeholders in educational research – such as policy-makers and funding agencies. It is hoped that these explications will contribute to the as yet nascent body of literature on translation science as applied to innovation in education.