Assessing context-based learning: Not only rigorous but also relevant

Economic factors are driving significant change in higher education. There is increasing responsiveness to market demand for vocational courses and a growing appreciation of the importance of procedural (tacit) knowledge to service the needs of the Knowledge Economy; the skills in demand are information analysis, collaborative working and 'just-in-time learning'. New pedagogical methods go some way to accommodate these skills, situating learning in context and employing information and communications technology to present realistic simulations and facilitate collaborative exchange. However, what have so far proved resistant to change are the practices of assessment. This paper endorses the case for a scholarship of assessment and proposes the development of technology-supported tools and techniques to assess context-based learning. It also recommends a fundamental rethink of the norm-referenced and summative assessment of propositional knowledge as the principal criterion for student success in universities

Rethinking university assessment

Developments in globalisation and new technologies are making significant impacts in higher education. Universities in a global market are increasingly concerned to reorient their degree programmes to meet the vocational needs of the Knowledge Economy. A growing adoption of technology enhanced learning, through blended and networked learning, has the potential to transform higher education practice – but assessment methods have been slow to change. This paper argues the case for universities to align assessment methods to meet the needs of 21st Century knowledge workers. It identifies skills and dispositions associated with graduate occupations in the Knowledge Economy, informing a new conceptual model for assessment. Radical recommendations are made to faculty staff and university policymakers: instead of centring assessment on the personal, academic achievements of individuals at the end of a degree course, the focus should instead be on the quality of the collective, applied achievements of students operating in project teams

Leading schools in the digital age: A clash of cultures

A cultural gap is widening in English secondary schools: between a twentieth-century ethos of institutional provision and the twenty-first century expectations and digital lifestyles of school students. Perhaps disaffected by traditional teaching methods and the competitive target culture of schools, many students have turned to social networking through the cluster of computer-based applications known as Web 2.0. Here, they can communicate, share and learn informally using knowledge systems their elders can barely understand. Some of their contemporaries have turned away altogether, rejecting school and contributing to record levels of truancy and exclusion. This paper identifies a set of challenges for school leaders in relation to the growing digital/cultural gap. The government agenda for personalised learning is discussed, alongside strategies which schools might adopt to support this through the use of ICT, and both figure in scenario projections which envision how secondary education could change in the future. The paper concludes by recommending three priorities for school leaders

On the Utility of Learning about Humans for Human-AI Coordination

While we would like agents that can coordinate with humans, current algorithms such as self-play and population-based training create agents that can coordinate with themselves. Agents that assume their partner to be optimal or similar to them can converge to coordination protocols that fail to understand and be understood by humans. To demonstrate this, we introduce a simple environment that requires challenging coordination, based on the popular game Overcooked, and learn a simple model that mimics human play. We evaluate the performance of agents trained via self-play and population-based training. These agents perform very well when paired with themselves, but when paired with our human model, they are significantly worse than agents designed to play with the human model. An experiment with a planning algorithm yields the same conclusion, though only when the human-aware planner is given the exact human model that it is playing with. A user study with real humans shows this pattern as well, though less strongly. Qualitatively, we find that the gains come from having the agent adapt to the human's gameplay. Given this result, we suggest several approaches for designing agents that learn about humans in order to better coordinate with them. Code is available at https://github.com/HumanCompatibleAI/overcooked_ai.Comment: Published at NeurIPS 2019 (http://papers.nips.cc/paper/8760-on-the-utility-of-learning-about-humans-for-human-ai-coordination

A lineage explanation of human normative guidance: the coadaptive model of instrumental rationality and shared intentionality.

This paper aims to contribute to the existing literature on normative cognition by providing a lineage explanation of human social norm psychology. This approach builds upon theories of goal-directed behavioral control in the reinforcement learning and control literature, arguing that this form of control defines an important class of intentional normative mental states that are instrumental in nature. I defend the view that great ape capacities for instrumental reasoning and our capacity (or family of capacities) for shared intentionality coadapted to each other and argue that the evolution of this capacity has allowed the representation of social norms and the emergence of our capacity for normative guidance