Learning innovation diffusion as complex adaptive systems through model building, simulation, game play and reflections
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.
Designing learning contexts using student-generated ideas
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.
Investigating the generation-first-instruction-later method for its effects on learning and transfer: A proposal to study analogical reasoning as the generation task
Productive Failure1,2 studies have shown that working on generative and complex activities prepares students for learning from subsequent instruction (i.e., delayed instruction). Under a delayed instruction setting, this study investigated the degree of freedom of generation and the level of task complexity as two key attributes of a preparatory task. The purpose was to make preliminary exploration on whether there is a boundary at which the benefit of a more generative task over a less generative task, such as compare and contrast, may disappear when the task complexity reduces.
Can “less” create “more” in analogical reasoning?
Successful analogical reasoning requires an analogue in a source domain to have high degrees of structural and surface similarity with a learning task in a target domain. It also requires learners to have sufficient source- and target-domain knowledge. We review the literature and speculate that “less” might create “more”; in some situations, analogies that have fewer degrees of similarity may be more effective for learning. In this exploratory study, we engaged eight school leaders in dyads to develop a bottom-up perspective on innovation diffusion through analogical reasoning. The qualitative data in the study appears to echo our speculation. The dyads that have less prior target-domain knowledge face challenges with regard to innovation diffusion when they learn with analogues that have more degrees of similarity – both structural and surface. They, however, are able to learn with analogues that have fewer degrees of similarity. Learning was shown to take place when the dyads reflected on an analogue first, before they compared the analogue and innovation diffusion to make any analogical inferences. Although constrained by the exploratory nature of the study, the findings provide preliminary evidence that “less” is possible to create “more” in analogical reasoning under certain conditions, implying an interesting direction for experimental examination in future.
Investigating analogical problem posing as the generative task in the productive failure design
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.