Equipping young people to engage with media driven science experiences: beyond science knowledge to science literacy and discerning consumers of news.

This paper reports on a study of a curricular intervention for pupils (age 10-13 years) in the UK aimed at supporting critical engagement with science based media reports. In particular the study focused on core elements of knowledge, skills and attitudes identified in previous studies that characterize critical consumers of science presented as news. This was an empirical study based on classroom observation. Data included responses from individual pupils, in addition video recording of group activity and intentional conversations between pupils and teachers were scrutinised. Analysis focused on core tasks relating to different elements of critical reading. Pupils demonstrated a grasp of questioning and evaluating text, however the capacity to translate this experience in support of a critical response to a media report with a science component is limited in assessing the credibility of text and as an element in critical reading.

Towards a knowledge-based approach for effective decision-making in railway safety

Purpose – This paper aims to contribute towards understanding how safety knowledge can be elicited from railway experts for the purposes of supporting effective decision-making. Design/methodology/approach – A consortium of safety experts from across the British railway industry is formed. Collaborative modelling of the knowledge domain is used as an approach to the elicitation of safety knowledge from experts. From this, a series of knowledge models is derived to inform decision-making. This is achieved by using Bayesian networks as a knowledge modelling scheme, underpinning a Safety Prognosis tool to serve meaningful prognostics information and visualise such information to predict safety violations. Findings – Collaborative modelling of safety-critical knowledge is a valid approach to knowledge elicitation and its sharing across the railway industry. This approach overcomes some of the key limitations of existing approaches to knowledge elicitation. Such models become an effective tool for prediction of safety cases by using railway data. This is demonstrated using passenger–train interaction safety data. Practical implications – This study contributes to practice in two main directions: by documenting an effective approach to knowledge elicitation and knowledge sharing, while also helping the transport industry to understand safety. Social implications – By supporting the railway industry in their efforts to understand safety, this research has the potential to benefit railway passengers, staff and communities in general, which is a priority for the transport sector. Originality/value – This research applies a knowledge elicitation approach to understanding safety based on collaborative modelling, which is a novel approach in the context of transport.