A B s T R A c T It has been argued that visitors' pre-visit "agendas" directly influence visits.This study attempted to directly test the effects of different museum visit agendas on visitor learning. Two new tools were developed for this purpose:(1) a tool for measuring visitor agendas; and (2) a tool for measuring visitor learning (Personal Meaning Mapping). Visitor agenda was defined as having two dimensions: motivations and strategies. Personal Meaning Mapping is a constructivist approach that measures change in understanding along four semi-independent dimensions: extent, breadth, depth, and mastery. The study looked at 40 randomly-selected adults who were visiting the National Museum of Natural History's Geology, Gems and Minerals exhibition. Visitor agendas did significantly impact how, what, and how much individuals learned. Results are discussed in terms of the current debate about education vs. entertainment.
The cloudUPDRS app is a Class I medical device, namely an active transient non-invasive instrument, certified by the Medicines and Healthcare products Regulatory Agency in the UK for the clinical assessment of the motor symptoms of Parkinson's Disease. The app follows closely the Unified Parkinson's Disease Rating Scale which is the most commonly used protocol in the clinical study of PD; can be used by patients and their carers at home or in the community; and, requires the user to perform a sequence of iterated movements which are recorded by the phone sensors. This paper discusses how the cloudUPDRS system addresses two key challenges towards meeting essential consistency and efficiency requirements, namely: (i) How to ensure high-quality data collection especially considering the unsupervised nature of the test, in particular, how to achieve firm user adherence to the prescribed movements; and (ii) How to reduce test duration from approximately 25 minutes typically required by an experienced patient, to below 4 minutes, a threshold identified as critical to obtain significant improvements in clinical compliance. To address the former, we combine a bespoke design of the user experience tailored so as to constrain context, with a deep learning approach used to identify failures to follow the movement protocol while at the same time limiting false positives to avoid unnecessary repetition. We address the latter by developing a machine learning approach to personalise assessments by selecting those elements of the UPDRS protocol that most closely match individual symptom profiles and thus offer the highest inferential power hence closely estimating the patent's overall UPRDS score. • Personalised tests reducing the time required to carry out an assessment to less than 4 minutes. These so-called quick tests are created using machine learning to select a subset of UPDRS observations that closely estimate the motor performance of a particular patient.
Museum exhibition environment provides experiential learning through its messages to influence knowledge, attitudes and learning behaviours of visitors. Connections in visitors' cognitive, affective, emotional and physiological responses play a beneficial role in museum visits. The research focuses on how science centre as part of a museum discusses various practical methods to inspire visitor into having a response. The review features multiple theories of learning advocating how visitors learn and how these theories influence a museum's exhibition design endeavors. Using the experience of selected Science Centres as primary case-studies, this article analyses various perspectives and
Parkinson's Disease is a neurological condition distinguished by characteristic motor symptoms including tremor and slowness of movement. To enable the frequent assessment of PD patients, this paper introduces the cloudUPDRS app, a Class I medical device that is an active transient non-invasive instrument, certified by the Medicines and Healthcare products Regulatory Agency in the UK. The app follows closely Part III of the Unified Parkinson's Disease Rating Scale which is the most commonly used protocol in the clinical study of PD; can be used by patients and their carers at home or in the community unsupervised; and, requires the user to perform a sequence of iterated movements which are recorded by the phone sensors. The cloudUPDRS system addresses two key challenges towards meeting essential consistency and efficiency requirements, namely: (i) How to ensure high-quality data collection especially considering the unsupervised nature of the test, in particular, how to achieve firm user adherence to the prescribed movements; and (ii) How to reduce test duration from approximately 25 minutes typically required by an experienced patient, to below 4 minutes, a threshold identified as critical to obtain significant improvements in clinical compliance. To address the former, we combine a bespoke design of the user experience tailored so as to constrain context, with a deep learning approach based on Recurrent Convolutional Neural Networks, to identify failures
This paper presents findings from a study carried out as part of BigPicnic, a European Commission's Horizon 2020 project. BigPicnic brought together members of the public, scientists, policy-makers and industry representatives to develop exhibitions and science cafés. Across 12 European and one Ugandan botanic gardens participating in the study, we surveyed 1189 respondents on factors and motives affecting their food choices. The study highlights the importance that cultural knowledge holds for understanding food choices and consumer preferences. The findings of this study are discussed in the wider context of food security issues related to sustainable food choice, and the role of food as a form of cultural heritage. Specifically, the findings underline the importance of the impact of food preferences and choices on achieving sustainability, but also indicate that heritage is a key parameter that has to be more explicitly considered in definitions of food security and relevant policies on a European and global level.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.