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This paper proposes a framework of an evolving community of practitioners along a simulation, participation, and codetermined interactions continuum. Simulation , participation , and codetermined interactions are three models of learning, which describe how learners can be brought through a scaffolded process within a community experience. The framework also focuses on the processes rather than on the outcomes or products of a community. In this paper, we describe a case study of a group of heads of Information and Communications Technology (ICT) in schools being scaffolded through an experiential workshop to achieve learning outcomes such as ICT-based project work (as product) and other constructivist dispositions of learning (as processes). The proposed framework is intended to be sufficiently broad so that learners are supported from simulation to codetermined interactions where autonomy of learners' co-construction efforts are encouraged and experienced. IntroductionThe concept of communities, both communities of learners and communities of practice (CoP), has been increasingly gaining attention in the last few years. A CoP is a sustained social network of individuals who share a common set of core values and knowledge, including a past history, grounded on common practices. As communities are central to the changing and evolving nature of persons acting (situated cognition), we cannot escape the issue of changing phenomena and practice. Hence, there is a need to conceive of frameworks that can capture the evolving history of a practice. Many efforts have been made to build communities (in particular, online communities) but many of these efforts fail to recognise the historical and evolving nature of communities.

Identifying educational competencies for the 21 st workplace is driven by the need to mitigate disparities between classroom learning and the requirements of workplace environments. Multiple descriptors of desired 21 st century skill sets have been identified through various wide-scale studies (e.g., International Commission on Education for the 21st Century) and consistently within the context of science, technology, engineering, and mathematics (STEM) learning, the ability to problem solve, particularly complex problem-solving, remains a crucial competency. In this paper, we look at how current contemporary spaces such as the immensely popular, massively multiplayer online role-playing game(MMORPG), World of Warcraft, (WoW) afford problem-solving skill acquisition in the context of Singaporean youth learners. Given that WoW exists as a contextual space with an overarching narrativized problem to be solved, our investigation focused on two important related constructs that underpin learners' problem-solving trajectory-learning and identity becoming within contemporary domains of technology learning. We present findings of an ethnographic investigation of one youth gamer within the affinity spaces of WoW. Moving away from traditional mentalistic construals of problem-solving, our findings indicate that problem-solving within WoW may be characterized by a triadic-D model of domain, disquisitional, and discursive practices within self, social, and structural dialectics. Theoretical considerations for broadening the understanding of a situated and embodied notion of problem-solving and identity becoming within STEM learning are proposed. Complex problems of the 21 st centuryThe twenty-first century learning evolves from new cultural forms of digital literacy and marks a significant shift from the conventional accessing of information to solving routine problems. Rather, contemporary work environments revolve around the management of complex information streams aligned with complex problem-solving tasks that require expertise across multiple cultures of science, technology, engineering, and mathematics (STEM) learning. Complex problems may be characterized as typically ill-structured, with unknown elements or elements not known with any degree of confidence (Reitman 1964; Wood 1983). Many interrelated factors dynamically affect the

Driven by the impetus for the school system as a whole to actualize deep twenty-first century learning, innovation diffusion has become increasingly an important vehicle for isolated pockets of successes to proliferate beyond the locale of the individual schools to form connected clusters of improvement at a greater scale. This paper articulates an ecological leadership model for enabling such system-wide innovation diffusion in the context of Singapore. Through the explication of leadership practices demonstrated by two exemplar schools that have successfully levelled up their school-based innovation, we argue that ecological leaders have to go beyond system leadership to think and act in a more encompassing way. Specifically, ecological leaders have to embody systems thinking and East-Asian collectivist beliefs to benefit other schools, converge and contextualize the kernel of innovation, align efforts by mitigating tensions and paradoxes within and across the subsystems in the ecology, leverage on resources in the ecology and manage the emergent dynamics engendered through interactions with multi-level actors. These five thrusts cut across the five dimensions of ecology: microsystem, mesosystem, exosystem, macrosystem and chronosystem. With the favourable sociopolitical climate that encourages collaboration rather than competition, we posit that leaders can endeavour to forge ecological coherence. This can be achieved by establishing synergistic structural and socio-cultural connections within and across the five subsystems of influences underpinning the hub school and networks of innovation-adopting schools, thus bringing forth transformative changes in the system.

In science, technology, engineering, arts, and mathematics (STEAM) education, artificial intelligence (AI) analytics are useful as educational scaffolds to educe (draw out) the students’ AI-Thinking skills in the form of AI-assisted human-centric reasoning for the development of knowledge and competencies. This paper demonstrates how STEAM learners, rather than computer scientists, can use AI to predictively simulate how concrete mixture inputs might affect the output of compressive strength under different conditions (e.g., lack of water and/or cement, or different concrete compressive strengths required for art creations). To help STEAM learners envision how AI can assist them in human-centric reasoning, two AI-based approaches will be illustrated: first, a Naïve Bayes approach for supervised machine-learning of the dataset, which assumes no direct relations between the mixture components; and second, a semi-supervised Bayesian approach to machine-learn the same dataset for possible relations between the mixture components. These AI-based approaches enable controlled experiments to be conducted in-silico, where selected parameters could be held constant, while others could be changed to simulate hypothetical “what-if” scenarios. In applying AI to think discursively, AI-Thinking can be educed from the STEAM learners, thereby improving their AI literacy, which in turn enables them to ask better questions to solve problems.

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