Huang, David Junsong

This research seeks contemporary understanding of how we can develop teachers' Technological-Pedagogical-Content Knowledge (TPACK) when scaling pedagogical innovation to different contextual situations. Teaching with technology has long been a wicked problem as the nature of technology is ''protean'' (used in versatile ways), ''unstable'' (rapidly changing) and ''opaque'' (elusive backend mechanisms), resulting in multifarious complexities which are exacerbated when its use is scaled and situated within the broader socio-cultural context of diverse learning ecologies. Scaling innovations to new contexts is rarely a mere supplanting of what works at the seeding school to new pedagogic sites with less hospitable conditions. It entails the perpetual marshalling of resources to mitigate the enfolding tensions that can emanate from many incompatibilities at the new site. Herein lies the tensions of diffusion: the conflation between fidelity adherence and localised accommodation. The purpose of this research then is to study how teachers' three knowledge bases - technology, pedagogy and content - can be holistically developed so that the core ingredients of success at the seeding school can be sustained and not ''amputated'' at new innovation sites. Informed by complexity theory, the qualitative case study will employ the complexity constructs of ''distribution'', ''enaction'' and ''emergence'' to examine how teachers' epistemic resources are distributed during the knowledge creation process and how teachers leverage on TPACK to enact co-designed lessons or improvise their lessons in-situ. More importantly, by studying the diffusion process of Seamless Science Learning project from the seeding FutureSchool (ICT prototype school) to another non-affiliated mainstream primary school, the study aims to articulate how teachers' reified TPACK can emerge through feedback loops between components of TPACK and interaction with other actors in an ecological complex adaptive system. The study will also articulate the implications of such interaction on the translations of teachers' professional learning and the conceptual model related to challenges of nurturing readiness. It has the potential to inform policymakers on the theoretical principles of professional learning support which may culminate into ensuing successful uptake of innovations. By inter-meshing three domains: complexity theory, TPACK and scaling, this project can provide novel methodological perspective to how the inter-locking influences underpinning teacher's TPACK can be studied. Through cross-case analysis, the proposed study aims to reify both ''local divergence'' and the ''noncontextually bounded'' theoretical principles about scaling school-based intervention.

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.

This article provides an overview of research in the Learning Sciences from a Design Research perspective, as it has been framed in Singapore by the National Institute of Education (NIE). The initial research agenda is considered in the light of challenges and the subsequent re-casting of objectives, based on the working out of a tripartite relationship between the NIE, the Ministry of Education, and local schools. A conceptual model is proposed as an attempt to provide structure for new research interventions going forward.

Cultivating teachers to be active and agentic learners is crucial for contemporary teacher education (Lipponen & Kumpulainen, 2011). Those teachers’ qualities are essential in preparing students’ future readiness in an increasingly complex world (P21 Framework Definitions, 2015). In fact, both learning principles and evidence from practice inform us that purposeful collaboration in networked learning communities (NLCs) encourage teacher agency to learn (Lieberman & Wood, 2003; Muijs, West & Ainscow, 2010). As a complement to the literature, we are interested in the development of social relationships among teachers, which enables and facilitates their learning. We propose “laterality” – the relations and networks among peers (e.g., teachers) as an important concept to characterize NLCs.
Studies on laterality, which have shown to support teacher learning, are usually found in the decentralized systems where individuals are the best entities to form these networks to support each other’s growth (Hargreaves & Goodman, 2006; Muijs et al., 2010). Thus, developing laterality from the bottom-up becomes natural in the decentralized contexts (Granovetter, 1973). Despite considerable theoretical promise of laterality and its increasing prevalence in practice, we wonder whether teacher laterality matters in the centralized education systems, and if it does, how it grows.