Museums actively researching visitors experiences and learning (MARVEL): a methodological study

Abstract

The MARVEL project (Museums Actively Researching Visitor Experience and Learning) has developed a set of strategies for measuring aspects of learning in museums. The project was a partnership between the University of Technology Sydney, the Australian Museum, Environmetrics Pty Ltd and the Royal Botanic Gardens, Sydney. The strategies were designed to enable their use by museum staff who may not have evaluation experience. The project aimed to find appropriate ways to: • assess the degree of learning that takes place in an exhibition/museum • understand the nature of learning that takes place in an exhibition/museum • establish benchmarks for learning outcomes • compare the learning outcomes for different exhibitions • share data with others and make comparisons with them. Three strategies for uncovering visitor learning were developed: Personal declarations of learning (based on a set of statements about their learning) Looking for understanding of the big ideas of an exhibition (open ended questions) Looking for behaviours that indicate learning is happening. (through observing visitors and listening to their conversations). The tools were tested and developed at the Australian Museum and the Royal Botanic Gardens, Sydney. The aspects of the project that are reported in this paper include determining each tool’s effectiveness in uncovering the extent and nature of learning; developing the most appropriate and effective use of each strategy; investigating the relationships between the learning revealed by combinations of the strategies, and determining the appropriate application of sets of combinations. The findings showed that the strategies are complementary, each providing a different insight into visitor learning and together providing a rich portrait of visitors’ experiences. In summary, visual observation data tells us that people are learning and aspects of how they are learning. It gives a good indication of the extent and nature of visitors’ use of hands-on exhibits. It also provides information on a number of behaviours that do not involve talking, such as reading, manipulating, looking at objects etc. Listening data tells us more about how they are learning as well as some information about what they are learning. It gives a much deeper understanding of the learning that is taking place, how visitors are relating what they see to other experiences, how the exhibits stimulate discussion which is not always directly related to what they see. Only from the listening data were we able to get a good picture of the emotive responses to the exhibitions. At the same time the listening data also gave a more accurate picture of non-learning behaviour as much of this was revealed by hearing what they were talking about. Exit survey data tells us what visitors are learning and if they know they are learning. They give good comparisons with the listening data regarding emotive responses, interest and curiosity. We found that surveys were the best way to determine understanding of the main messages. Visitor’s views about the exhibit itself are revealed in the surveys as well as the listening data. It was found that while each strategy could provide useful information they also each were missing out on some aspects of the visitors’ learning – an important discovery for museum evaluators. The information gathered will prove invaluable to exhibition developers and designers, as there were clear differences in the types of learning that was taking place in different exhibitions. Understanding the learning process and providing measurable learning outcomes will be vital for museums in the future to enable them to demonstrate to external bodies the value of museum visiting, show how museum learning fits within a broader educational infrastructure and to assist them in providing better learning experiences for visitors.