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 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.
School leaders’ learning of diffusion of innovation through agent based modeling: Coupling modeling and simulation process with learners’ interaction with diffusion system
If school diffusion of innovation is viewed as complex adaptive process, how shall we prepare school leaders to be effective diffusion decision makers? Coming from the epistemological belief that knowledge is subjective and embodied, this paper proposes to use Agent Based Modeling (ABM) for learning by focus on learning to “do” diffusion of innovation rather than learning about diffusion of innovation. We therefore recommend to engage school leaders in iterative agent based model development process and to couple it with their interaction in real world diffusion system. With feedback from real world system used for iterative model calibration and validation, the affordances of the agent based model allow school leaders to participate, experience, appropriate, perform and therefore to learn to make effective diffusion decisions in their schools.
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.