Developing socially just pedagogy: what might be the role of learner agency and creativity?
Pedagogy has been identified by government and in academic research as a key element of solving the enduring problem of educational inequality in England. Within sociology of education, a response to educational inequality has been to identify the need for more socially just pedagogies (Lupton & Hempel-Jorgensen, 2012) to disrupt current ‘default’ pedagogy, which contributes to reproducing inequalities. While test results dominate policy and public discourse about outcomes, there is less focus on the role of education in developing pupils as agentic learners. Research has shown that schools located in disadvantaged areas may be more likely to adopt performative pedagogies in which pupils’ agency as learners is highly constrained in contrast to schools in less disadvantaged areas. This arguably has significant implications for pupils’ engagement with learning, their learner identities and development as socially critical and active citizens. 
 
Existing socially just pedagogies, such as productive and critical pedagogies and ‘funds of knowledge’ aim to place learner agency at their centre. However, while these pedagogies make important contributions to developing learner agency in various ways, the literature on creative pedagogy offers a unique perspective on learner agency through its central elements of relevance, ownership, control and innovation and through the concept of possibility thinking which foregrounds enquiry, risk-taking and developing creative thinking by moving from the question of ‘what is’ to ‘what might be’ (Craft et al, 2012). The presentation will explore how these aspects of creative pedagogy, in dialogue with existing socially just pedagogies, can support the development of pupils’ non-attainment characteristics in disadvantaged schools, through developing learner agency.
Reciprocity between narrative, questioning and imagination in the early and primary years: examining the role of narrative in possibility thinking
Abstract The concept of possibility thinking (PT) as a driving force of creativity has been investigated both conceptually and empirically for over a decade in early years settings and primary classrooms in England. In the first wave of qualitative empirical studies, play formed part of the enabling context. Criteria for episode selection for PT analysis were that episodes exhibited children immersed in sustained focused playful activity. During the second wave of PT studies, the research team's attention was drawn to children's imaginative storying in such playful contexts and it emerged that consideration of narrative in PT might prove fruitful. The current paper revisits key published work, and drawing on data previously analysed for features of PT, seeks to explore how narrative might relate to the current theorised framework. Fourteen published PT episodes are re-analysed in order to consider the role and construction of narrative in PT. The new analysis reveals that narrative plays a foundational role in PT, and that reciprocal relationships exist between questioning, imagination and narrative, layered between children and adults. Consequences for nurturing children's creativity and for future PT research are explored.
A Short-Term and High-Resolution Distribution System Load Forecasting Approach Using Support Vector Regression With Hybrid Parameters Optimization
This paper proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system. The performance of the proposed approach is compared to some classic methods in later sections of this paper.