Computing and Information Systems - Research Publications
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Item“Keeping the Program Going”: Technology Use by Community Organizations to Support the Social Connectedness of Older Adults During the COVID-19 Pandemic(Association for Computing Machinery (ACM), 2023-03-06)Social programs run by community organizations provide an important outlet for social connectedness among older adults. However, these programs were disrupted by the COVID-19 pandemic restrictions. In this study, we aimed to understand how community organizations used digital technologies to continue running social programs online for older adults during COVID-19. We conducted semi-structured interviews with 12 staff members from local councils, libraries, community groups and care providers. We found that the use of technology benefited organizations by revealing new program delivery opportunities, and by strengthening their social bonds with older adults. However, organizations experienced challenges when transitioning social programs online. Some organizations lacked financial and human resources to support online programs; staff needed to upskill themselves and put significant effort into transferring older adults online; and it was difficult to replicate in-person experiences in online settings. Staff developed ad-hoc strategies to help older adults participate by providing extra guidance and training to increase digital literacy, and by offering accessible technical support. We discuss the significance of continuing online social programs beyond the pandemic and the importance of scaffolding to enable the online participation of older people in social programs. We outline design considerations for technology-mediated social programs run by community organizations.
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ItemUncovering Students’ Learning Pathways: A Process Mining Perspective( 2023)This paper presents an approach to discovering students’ pathways when accessing a Learning Management System (LMS). These pathways reflect students’ compliance with the subject design and/or alternate ways of learning. Discovering such routines can enable the early detection of students at risk of not achieving the intended learning outcomes, as well as informing academics about students’ understanding of their progression in the subject. While LMSs report on aggregate data, they do not report on the order in which students follow the subject design. This information can reveal undesirable situations, such as students responding to the quizzes before completing the prerequisite activities (e.g., watching videos or completing the readings).
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ItemDusting for fingerprints: Revealing patterns of online students’ behaviour( 2023-09-01)Hybrid learning strategies combine face-to-face instruction with online components. These hybrid environments rely heavily on online Learning Management Systems (LMSs) that serve as central hubs for learning materials. Depending on the adopted instructional strategy, students may be expected to complete certain tasks in the LMS. For instance, when adopting a flipped classroom strategy, students must watch videos, read material or complete quizzes prior the classroom time. Then, during classroom time, students focus on performing hands-on exercises. Students consistently engaging in the adopted strategy is key, as failing to do so can decrease the effectiveness of the adopted strategy. This paper presents an approach to monitor the changes of students’ behaviour over time. Using variants analysis, the method analyses data captured in an LMS and finds significant differences between time windows (e.g., two academic weeks). This can inform educators about changes in students’ engagement in the instructional strategy (e.g., students not completing some tasks). To showcase our method, we analyse a semester’s worth of data for a master’s subject implementing flipped classroom strategy.
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ItemStatistical Modelling for Simulating and Interpreting an Egg Packaging Process for Giveaway Mitigation(AIS, 2022)Giveaway, the excess product being packed into orders, contributes to revenue loss that pre-packaged food manufacturers care about the most. In collaboration with an egg packaging company, this study aims to discover operation rules to mitigate the giveaway in egg orders. For that, two variables have been raised as potential controllable factors of the giveaway. One statistical model has been developed to better interpret the experimental results by understanding the underlying rules of the egg grading machine. The experiments have been accurately reproduced by a simulation using the estimated model parameters, indicating the model's success. Based on the experiment results, we claim that the number of accepted egg grades significantly influences the final giveaway ratio. Limitations and further potentials of the statistical model have also been discussed.
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ItemNo Preview AvailableUnderstanding What Drives Long-term Engagement in Digital Mental Health Interventions: Secondary Causal Analysis of the Relationship Between Social Networking and Therapy Engagement(JMIR PUBLICATIONS, INC, 2023)BACKGROUND: Low engagement rates with digital mental health interventions are a major challenge in the field. Multicomponent digital interventions aim to improve engagement by adding components such as social networks. Although social networks may be engaging, they may not be sufficient to improve clinical outcomes or lead users to engage with key therapeutic components. Therefore, we need to understand what components drive engagement with digital mental health interventions overall and what drives engagement with key therapeutic components. OBJECTIVE: Horyzons was an 18-month digital mental health intervention for young people recovering from first-episode psychosis, incorporating therapeutic content and a private social network. However, it is unclear whether use of the social network leads to subsequent use of therapeutic content or vice versa. This study aimed to determine the causal relationship between the social networking and therapeutic components of Horyzons. METHODS: Participants comprised 82 young people (16-27 years) recovering from first-episode psychosis. Multiple convergent cross mapping was used to test causality, as a secondary analysis of the Horyzons intervention. Multiple convergent cross mapping tested the direction of the relationship between each pair of social and therapeutic system usage variables on Horyzons, using longitudinal usage data. RESULTS: Results indicated that the social networking aspects of Horyzons were most engaging. Posting on the social network drove engagement with all therapeutic components (r=0.06-0.36). Reacting to social network posts drove engagement with all therapeutic components (r=0.39-0.65). Commenting on social network posts drove engagement with most therapeutic components (r=0.11-0.18). Liking social network posts drove engagement with most therapeutic components (r=0.09-0.17). However, starting a therapy pathway led to commenting on social network posts (r=0.05) and liking social network posts (r=0.06), and completing a therapy action led to commenting on social network posts (r=0.14) and liking social network posts (r=0.15). CONCLUSIONS: The online social network was a key driver of long-term engagement with the Horyzons intervention and fostered engagement with key therapeutic components and ingredients of the intervention. Online social networks can be further leveraged to engage young people with therapeutic content to ensure treatment effects are maintained and to create virtuous cycles between all intervention components to maintain engagement. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12614000009617; https://www.australianclinicaltrials.gov.au/anzctr/trial/ACTRN12614000009617.
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ItemContent development and validation for a mobile application designed to train family caregivers in the use of music to support care of people living with dementia(FRONTIERS MEDIA SA, 2023-05-12)BACKGROUND: Music therapy is increasingly recognized as an effective support for people living with dementia. However, with incidences of dementia increasing, and limited availability of music therapists, there is a need for affordable and accessible ways that caregivers can learn to use music-therapy based strategies to support the people they care for. The MATCH project aims to address this by creating a mobile application that can train family caregivers in the use of music to support people living with dementia. METHODS: This study details the development and validation of training material for the MATCH mobile application. Training modules developed based on existing research were assessed by 10 experienced music therapist clinician-researchers, and seven family caregivers who had previously completed personalized training in music therapy strategies via the HOMESIDE project. Participants reviewed the content and scored each training module based on content (music therapists) and face (caregivers) validity scales. Descriptive statistics were used to calculate scores on the scales, while thematic analysis was used to analyze short-answer feedback. RESULTS: Participants scored the content as valid and relevant, however, they provided additional suggestions for improvement via short-answer feedback. CONCLUSION: The content developed for the MATCH application is valid and will be trailed by family caregivers and people living with dementia in a future study.
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ItemMarket-inspired framework for securing assets in cloud computing environments(WILEY, 2022-06-07)Abstract Self‐adaptive security methods have been extensively leveraged for securing software systems and users from runtime threats in online and elastic environments, such as the cloud. The existing solutions treat security as an aggregated quality by enforcing “one service for all” without considering the explicit security requirements of each asset or the costs associated with security. Dealing with the security of assets in ultra‐large environments calls for rethinking the way we select and compose services—considering not only the services but the underlying supporting computational resources in the process. We motivate the need for an asset‐centric, self‐adaptive security framework that selects and allocates services and underlying resources in the cloud. The solution leverages learning algorithms and market‐inspired approaches to dynamically manage changes in the runtime security goals/requirements of assets with the provision of suitable services and resources, while catering for monetary and computational constraints. The proposed framework aims to inform the self‐adaptive security efforts of security researchers and practitioners operating in dynamic large‐scale environments, such as the Cloud. To illustrate the utility of the proposed framework it is evaluated using simulation on an application based scenario, involving cloud‐based storage and security services.
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ItemInvestigating information and communication technology-enabled national development as a multi-level social process(WILEY, 2023-01-01)Are centralised or decentralised strategies more suitable to address a developing nation's socio-economic challenges through information and communication technology (ICT)? We respond to this long-standing question by conceptualising ICT-enabled national development as a multi-level social process and by drawing on empirical findings from a natural experiment set in the context of health information system projects in Indonesia. Our study demonstrates that successful ICT-enabled national development is not contingent on pursuing one strategy or the other but on how micro-level actors interpret, and subsequently respond to, these strategies and the local changes they trigger. Our findings indicate that centralisation and decentralisation are complementary rather than competing strategies to ICT-enabled national development because, if integrated into a hybrid strategy, decentralisation enables local communities to achieve national development outcomes commonly attributed to centralisation. As such, our work provides empirical evidence, explanations and new theoretical insight into the wider ‘centralisation versus decentralisation’ debate, while also outlining avenues for future research and guidelines for policymakers.
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ItemRESCUE: Enabling green healthcare services using integrated IoT-edge-fog-cloud computing environments(WILEY, 2022-02-24)Abstract Internet of Things (IoT) has a pivotal role in developing intelligent and computational solutions to facilitate varied real‐life applications. To execute high‐end computations and data analytics, IoT and cloud‐based solutions play the most significant role. However, frequent communication with long distant cloud servers is not a delay‐aware and energy‐efficient solution while providing time‐critical applications such as healthcare. This article explores the possibilities and opportunities of integrating cloud technology with fog and edge‐based computing to provide healthcare services to users in exigency. Here, we propose an end‐to‐end framework named RESCUE (enabling green healthcare services using integrated iot‐edge‐fog‐cloud computing environments), consisting efficient spatio‐temporal data analytics module for efficient information sharing, spatio‐temporal data analysis to predict the path for users to reach the destination (healthcare center or relief camps) with minimum delay in the time of exigency (say, natural disaster). This module analyzes the collected information through crowd‐sourcing and assists the user by extracting optimal path postdisaster when many regions are nonreachable. Our work is different from the existing literature in varied aspects: it analyses the context and semantics by augmenting real‐time volunteered geographical information (VGI) and refines it. Furthermore, the novel path prediction module incorporates such VGI instances and predicts routes in emergencies avoiding all possible risks. Also, the design of development of a latency‐aware, power‐aware data‐driven analytics system helps to resolve any spatio‐temporal query more efficiently compared to the existing works for any time‐critical application. The experimental and simulation results outperform the baselines in terms of accuracy, delay, and power consumption.
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ItemIoT-Pi: A machine learning-based lightweight framework for cost-effective distributed computing using IoT(JOHN WILEY & SONS LTD, 2022-02-24)It is possible to develop intelligent and self‐adaptive application on the edge nodes with rapid increase in computational capability of Internet of Things (IoT) devices. With the rapid growth of cloud technologies, the demand for hybrid architecture with cloud and IoT has also been boosted as well. To satisfy the critical and comprehensive requirements in the architecture evolution, we proposed a lightweight framework called IoT‐Pi to provide a 3‐phase (sample, learn, adapt) life cycle management of cloud resources with machine learning prediction working on IoT edge nodes using Raspberry Pi device. Compared to the traditional interference by human beings in the field of system administration, the accuracy rate of machine learning prediction in the proposed technique for some algorithms reached over 70%, which demonstrates the feasibility and effectiveness of running cloud resource management on an IoT devices such as Raspberry Pi.