Enhancing reflective learning experiences in museums through interactive installations

In this study we examine the effect that several technological affordances have upon the experiences of children while visiting a museum, focusing upon engagement, discussion and reflection. The museum is the Baba Nyonya Heritage Museum in Malacca, Malaysia. We created a number of public interactive installations designed to facilitate inter-cultural and inter-generational dialogues about cultural identity. The technology employed mixed and augmented reality techniques and gesture recognition to enable visitors to have a multisensory experience with the artefacts on display. Analysis of pre- to post-test knowledge based surveys showed significant learning gains as a result of interacting with the exhibits. Surveys of visitors’ attitudes showed that they felt they had benefitted from the physical interactivity. Qualitative analysis of observational and video data showed that the different interaction techniques provided both benefits and challenges for interaction, which we reflect upon in the paper

Sensing Heritage: Exploring Creative Approaches for Capturing, Experiencing and Safeguarding the Sensorial Aspects of Cultural Heritage

Whilst there is increasing work investigating the role of digital documentation, interpretation, and augmentation of cultural heritage, such interventions have largely focused on visual and sometimes auditory modalities, neglecting the full spectrum of human senses. With this workshop we seek to bring together an interdisciplinary group of researchers, designers, practitioners and community members to explore creative approaches for documenting and experiencing cultural heritage’s rich sensory dimensions extending beyond visual-based approaches to encompass sound, smell, taste, and touch. The workshop directly aligns with the conference’s exploration of "Why Design?" by utilising design as a powerful, empathetic, and participatory tool for safeguarding cultural heritage. Our goal is to extend our understanding of concepts, methods and technologies for capturing and experiencing sensory heritage, advocating for a holistic approach that celebrates and communicates the profound sensory diversity of human cultures, inspiring a shift in how we document, interpret and share cultural heritage

Designing interactive technology for cross-cultural appreciation of intangible cultural heritage: Chinese traditional painting and puppetry

Ph. D. ThesisDigital heritage is becoming a significant component of cultural heritage, and cultural organisations are increasingly using interactive technologies to showcase and safeguard heritage assets. However, few studies focus on using interactive technology to enhance the appreciation of Intangible Cultural Heritage (ICH) amongst cross-cultural audiences. This dissertation explores the design of interactive technologies to support the cultural appreciation, learning, and experience of Chinese ICH. In addition, the research seeks to explore the value of Human-Computer Interaction (HCI) design strategies in supporting the appreciation of ICH. The research uses HCI design strategies to specifically explore how interactive technology might be effectively utilised in two case-study contexts, supporting traditional Chinese painting and traditional Chinese puppetry. To this end, in stage one of the research, a qualitative study involving interviews, workshops, and fieldwork for design was undertaken with potential cross-cultural audiences and both Chinese and international painting and puppetry practitioners. Based on the results of these studies, several suggestions were developed for safeguarding ICH across cultural boundaries. In the next stage of the research, two interactive applications were designed and deployed that supported cross-cultural audiences’ appreciation of traditional of ICH. One application explored Chinese painting, the other Chinese puppetry. Using both qualitative and quantitative methods, studies were conducted that examined the efficacy of both applications and offered suggestions for a holistic approach to cross-cultural appreciation through the use of interactive applications. The analysis focuses on the use of element-based archiving to increase aesthetic appreciation, gestural/tangible interfaces for cultural engagement, and the use of interactive access to inspire self-expression and collaborative appreciation. Finally, this research relies on practical methods to deconstruct cultural elements from the HCI perspective and enhance the cross-cultural appreciation of Chinese ICH. It thus provides a framework for assisting non-Chinese people to better understand the cultural significance of Chinese ICH. The findings have design implications for both HCI researchers and digital heritage researchers

Recalibrating machine learning for social biases: demonstrating a new methodology through a case study classifying gender biases in archival documentation

This thesis proposes a recalibration of Machine Learning for social biases to minimize harms from existing approaches and practices in the field. Prioritizing quality over quantity, accuracy over efficiency, representativeness over convenience, and situated thinking over universal thinking, the thesis demonstrates an alternative approach to creating Machine Learning models. Drawing on GLAM, the Humanities, the Social Sciences, and Design, the thesis focuses on understanding and communicating biases in a specific use case. 11,888 metadata descriptions from the University of Edinburgh Heritage Collections' Archives catalog were manually annotated for gender biases and text classification models were then trained on the resulting dataset of 55,260 annotations. Evaluations of the models' performance demonstrates that annotating gender biases can be automated; however, the subjectivity of bias as a concept complicates the generalizability of any one approach. The contributions are: (1) an interdisciplinary and participatory Bias-Aware Methodology, (2) a Taxonomy of Gendered and Gender Biased Language, (3) data annotated for gender biased language, (4) gender biased text classification models, and (5) a human-centered approach to model evaluation. The contributions have implications for Machine Learning, demonstrating how bias is inherent to all data and models; more specifically for Natural Language Processing, providing an annotation taxonomy, annotated datasets and classification models for analyzing gender biased language at scale; for the Gallery, Library, Archives, and Museum sector, offering guidance to institutions seeking to reconcile with histories of marginalizing communities through their documentation practices; and for historians, who utilize cultural heritage documentation to study and interpret the past. Through a real-world application of the Bias-Aware Methodology in a case study, the thesis illustrates the need to shift away from removing social biases and towards acknowledging them, creating data and models that surface the uncertainty and multiplicity characteristic of human societies