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Measuring research’s policy influence is challenging, given the complexity of the policy process, the gradual nature of policy influence, and the time lag between research investment and impact. This paper assesses measurement approaches and discusses their merits and applications to overcome various hurdles.

Relevant articles and studies were selected and analyzed. First, the research-policy interface was revisited to understand their link and how research influences policy making. Second, the most common approaches for measuring policy influence were reviewed based on their features, strengths, and limitations.

The three approaches reviewed — pyramid, influencing, and results chain — have their respective strengths. Thus, research organizations planning to design a program for monitoring and evaluation (M&E) of policy influence have to adopt the best possible features of each approach and develop a customized method depending on their objectives and overall M&E framework.

This paper fosters a deeper understanding of leveraging the three approaches.

The purpose of this paper is to investigate the relationship between preferred choice of school subject and student information behaviour (IB).

Mixed methods were employed. In all, 152 students, teachers and librarians participated in interviews or focus groups. In total, 1,375 students, key stage 3 (11-14 years) to postgraduate, responded to a questionnaire. The research population was drawn from eight schools, two further education colleges and three universities. Insights from the literature review and the qualitative research phase led to a hypothesis which was investigated using the questionnaire: that students studying hard subjects are less likely to engage in deep IB than students studying soft subjects.

Results support the hypothesis that preferences for subjects at school affect choice of university degree. The hypothesis that a preference for hard or soft subjects affects IB is supported by results of an analysis in which like or dislike of maths/ICT is correlated with responses to the survey. Interviewees’ comments led to the proposal that academic subjects can be classified according to whether a subject helps students to acquire a “tool of the Mind” or to apply such a tool. A model suggesting how IB may differ depending on whether intellectual tools are being acquired or applied is proposed.

The “inner logic” of certain subjects and their pedagogies appears closely linked to IB. This should be considered when developing teaching programmes.

The findings offer a new perspective on subject classification and its association with IB, and a new model of the association between IB and tool acquisition or application is proposed, incorporating the perspectives of both teacher and student.