Publications
A complete list of publications can be found through one of my researcher IDs (Google Scholar, ORCID, Semantic Scholar).
The publications below are a selected set, tagged with my current research themes.
LLMs integration in software engineering team projects: Roles, impact, and a pedagogical design space for AI tools in computing education
2026 | ACM Transactions on Computing Education
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Abstract: This work takes a pedagogical lens to explore the implications of generative AI (GenAI) models and tools, such as ChatGPT and GitHub Copilot, in a semester-long 2nd-year undergraduate software engineering team project. Qualitative findings from a survey (39 students) and interviews (eight students) provide insights into the students' views on the impact of GenAI use on their coding experience, learning, and self-efficacy. Our results address a particular gap in understanding the role and implications of GenAI on teamwork, team-efficacy, and team dynamics. The analysis of the learning aspects is distinguished by the application of learning- and pedagogy-informed lenses to discuss the data. We propose a preliminary design space for GenAI-based programming learning tools highlighting the importance of considering the roles that GenAI can play during the learning process, the scaffolding support that can be applied to each role, and the importance of supporting transparency in GenAI for team members and students in addition to educators.
LLMs integration in software engineering team projects: Roles, impact, and a pedagogical design space for AI tools in computing education
2026 | ACM Transactions on Computing Education
Abstract: This work takes a pedagogical lens to explore the implications of generative AI (GenAI) models and tools, such as ChatGPT and GitHub Copilot, in a semester-long 2nd-year undergraduate software engineering team project. Qualitative findings from a survey (39 students) and interviews (eight students) provide insights into the students' views on the impact of GenAI use on their coding experience, learning, and self-efficacy. Our results address a particular gap in understanding the role and implications of GenAI on teamwork, team-efficacy, and team dynamics. The analysis of the learning aspects is distinguished by the application of learning- and pedagogy-informed lenses to discuss the data. We propose a preliminary design space for GenAI-based programming learning tools highlighting the importance of considering the roles that GenAI can play during the learning process, the scaffolding support that can be applied to each role, and the importance of supporting transparency in GenAI for team members and students in addition to educators.
Role of Augmented Reality in Tertiary Care: Qualitative Investigation Using Thematic Analysis
2025 | JMIR XR and Spatial Computing (JMXR)
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Abstract
Background: While augmented reality (AR) as a concept is not new, it is still an emerging technology with a wide range of applications that it could provide value for. In the medical field, AR is becoming ever more prevalent, but while it has been applied to various medical tasks, it is far from commonplace. Radiological imaging has been suggested as one of these applications, and the radiology workflow capacity crisis the United Kingdom’s National Health Service is experiencing is a potential opportunity for technology to alleviate pressure. Understanding clinical stakeholders and current systems is important for identifying design opportunities for developing AR to enhance interactions and gain more from radiological images.
Objective: This study had 3 key aims. First, to build an understanding of the field in the context of AR; second, to understand the stakeholders and workflows surrounding radiological images; and finally, to suggest how AR could integrate within these workflows and current practices in order to provide value.
Methods: We conducted 14 interviews with hospital-based consultants in a range of specialties and then completed a thematic analysis on the transcripts in order to find trends that suggest what value AR could add to radiological imaging, where that value could be added, and who would benefit. We implemented reflexive thematic analysis to develop themes from across the interviews, which were then built on to suggest design implications.
Results: We find that the need for efficiency in image evaluation is present across many roles, regardless of the clinical question, but consultants can be resistant to new technology. Additionally, we find that the current capability of AR technology could be of greater benefit to radiologists as opposed to surgeons or other practitioners. We discuss these findings for the development of AR applications and present 3 design implications that stand as our core contribution.
Conclusions: We conclude with 3 design implications for the application of AR within radiological imaging based on the results of our thematic analysis and frame them within the Human-Computer Interaction and medical fields. The first design implication highlights efficiency and how AR has the potential to allow for quicker comprehension and measurements. Second, we suggest that the capability of AR tools should complement existing techniques and not simply replicate current ability in 3 dimensions. Finally, the integration of AR tools with existing workflows is crucial in the uptake of the technology in order not to negatively disrupt practice.
Role of Augmented Reality in Tertiary Care: Qualitative Investigation Using Thematic Analysis
2025 | JMIR XR and Spatial Computing (JMXR)
Abstract
Background: While augmented reality (AR) as a concept is not new, it is still an emerging technology with a wide range of applications that it could provide value for. In the medical field, AR is becoming ever more prevalent, but while it has been applied to various medical tasks, it is far from commonplace. Radiological imaging has been suggested as one of these applications, and the radiology workflow capacity crisis the United Kingdom’s National Health Service is experiencing is a potential opportunity for technology to alleviate pressure. Understanding clinical stakeholders and current systems is important for identifying design opportunities for developing AR to enhance interactions and gain more from radiological images.
Objective: This study had 3 key aims. First, to build an understanding of the field in the context of AR; second, to understand the stakeholders and workflows surrounding radiological images; and finally, to suggest how AR could integrate within these workflows and current practices in order to provide value.
Methods: We conducted 14 interviews with hospital-based consultants in a range of specialties and then completed a thematic analysis on the transcripts in order to find trends that suggest what value AR could add to radiological imaging, where that value could be added, and who would benefit. We implemented reflexive thematic analysis to develop themes from across the interviews, which were then built on to suggest design implications.
Results: We find that the need for efficiency in image evaluation is present across many roles, regardless of the clinical question, but consultants can be resistant to new technology. Additionally, we find that the current capability of AR technology could be of greater benefit to radiologists as opposed to surgeons or other practitioners. We discuss these findings for the development of AR applications and present 3 design implications that stand as our core contribution.
Conclusions: We conclude with 3 design implications for the application of AR within radiological imaging based on the results of our thematic analysis and frame them within the Human-Computer Interaction and medical fields. The first design implication highlights efficiency and how AR has the potential to allow for quicker comprehension and measurements. Second, we suggest that the capability of AR tools should complement existing techniques and not simply replicate current ability in 3 dimensions. Finally, the integration of AR tools with existing workflows is crucial in the uptake of the technology in order not to negatively disrupt practice.
Designs and Interactions for Near-Field Augmented Reality: A Scoping Review
Jacob Hobbs, Christopher Bull
2025 | Informatics
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Abstract: Augmented reality (AR), which overlays digital content within the user’s view, is gaining traction across domains such as education, healthcare, manufacturing, and entertainment. The hardware constraints of commercially available HMDs are well acknowledged, but little work addresses what design or interactions techniques developers can employ or build into experiences to work around these limitations. We conducted a scoping literature review, with the aim of mapping the current landscape of design principles and interaction techniques employed in near-field AR environments. We searched for literature published between 2016 and 2025 across major databases, including the ACM Digital Library and IEEE Xplore. Studies were included if they explicitly employed design or interaction techniques with a commercially available HMD for near-field AR experiences. A total of 780 articles were returned by the search, but just 7 articles met the inclusion criteria. Our review identifies key themes around how existing techniques are employed and the two competing goals of AR experiences, and we highlight the importance of embodiment in interaction efficacy. We present directions for future research based on and justified by our review. The findings offer a comprehensive overview for researchers, designers, and developers aiming to create more intuitive, effective, and context-aware near-field AR experiences. This review also provides a foundation for future research by outlining under-explored areas and recommending research directions for near-field AR interaction design.
Designs and Interactions for Near-Field Augmented Reality: A Scoping Review
Jacob Hobbs, Christopher Bull
2025 | Informatics
Abstract: Augmented reality (AR), which overlays digital content within the user’s view, is gaining traction across domains such as education, healthcare, manufacturing, and entertainment. The hardware constraints of commercially available HMDs are well acknowledged, but little work addresses what design or interactions techniques developers can employ or build into experiences to work around these limitations. We conducted a scoping literature review, with the aim of mapping the current landscape of design principles and interaction techniques employed in near-field AR environments. We searched for literature published between 2016 and 2025 across major databases, including the ACM Digital Library and IEEE Xplore. Studies were included if they explicitly employed design or interaction techniques with a commercially available HMD for near-field AR experiences. A total of 780 articles were returned by the search, but just 7 articles met the inclusion criteria. Our review identifies key themes around how existing techniques are employed and the two competing goals of AR experiences, and we highlight the importance of embodiment in interaction efficacy. We present directions for future research based on and justified by our review. The findings offer a comprehensive overview for researchers, designers, and developers aiming to create more intuitive, effective, and context-aware near-field AR experiences. This review also provides a foundation for future research by outlining under-explored areas and recommending research directions for near-field AR interaction design.
Generative Artificial Intelligence Assistants in Software Development Education: A Vision for Integrating Generative Artificial Intelligence Into Educational Practice, Not Instinctively Defending Against It
Christopher Bull, Ahmed Kharrufa
2024 | IEEE Software
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Abstract: The use of Generative AI in software development is gaining traction. But what are the potentials and implications on software development education? We gathered insights on the use of Generative AI from professional software developers and make some pedagogical recommendations.
Generative Artificial Intelligence Assistants in Software Development Education: A Vision for Integrating Generative Artificial Intelligence Into Educational Practice, Not Instinctively Defending Against It
Christopher Bull, Ahmed Kharrufa
2024 | IEEE Software
Abstract: The use of Generative AI in software development is gaining traction. But what are the potentials and implications on software development education? We gathered insights on the use of Generative AI from professional software developers and make some pedagogical recommendations.
Smartphone Apps for Food Purchase Choices: Scoping Review of Designs, Opportunities, and Challenges
2024 | Journal of Medical Internet Research (JMIR)
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Abstract:
Background: Smartphone apps can aid consumers in making healthier and more sustainable food purchases. However, there is still a limited understanding of the different app design approaches and their impact on food purchase choices. An overview of existing food purchase choice apps and an understanding of common challenges can help speed up effective future developments.
Objective: We examined the academic literature on food purchase choice apps and provided an overview of the design characteristics, opportunities, and challenges for effective implementation. Thus, we contribute to an understanding of how technologies can effectively improve food purchase choice behavior and provide recommendations for future design efforts.
Methods: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we considered peer-reviewed literature on food purchase choice apps within IEEE Xplore, PubMed, Scopus, and ScienceDirect. We inductively coded and summarized design characteristics. Opportunities and challenges were addressed from both quantitative and qualitative perspectives. From the quantitative perspective, we coded and summarized outcomes of comparative evaluation trials. From the qualitative perspective, we performed a qualitative content analysis of commonly discussed opportunities and challenges.
Results: We retrieved 55 articles, identified 46 unique apps, and grouped them into 5 distinct app types. Each app type supports a specific purchase choice stage and shares a common functional design. Most apps support the product selection stage (selection apps; 27/46, 59%), commonly by scanning the barcode and displaying a nutritional rating. In total, 73% (8/11) of the evaluation trials reported significant findings and indicated the potential of food purchase choice apps to support behavior change. However, relatively few evaluations covered the selection app type, and these studies showed mixed results. We found a common opportunity in apps contributing to learning (knowledge gain), whereas infrequent engagement presents a common challenge. The latter was associated with perceived burden of use, trust, and performance as well as with learning. In addition, there were technical challenges in establishing comprehensive product information databases or achieving performance accuracy with advanced identification methods such as image recognition.
Conclusions: Our findings suggest that designs of food purchase choice apps do not encourage repeated use or long-term adoption, compromising the effectiveness of behavior change through nudging. However, we found that smartphone apps can enhance learning, which plays an important role in behavior change. Compared with nudging as a mechanism for behavior change, this mechanism is less dependent on continued use. We argue that designs that optimize for learning within each interaction have a better chance of achieving behavior change. This review concludes with design recommendations, suggesting that food purchase choice app designers anticipate the possibility of early abandonment as part of their design process and design apps that optimize the learning experience.
Smartphone Apps for Food Purchase Choices: Scoping Review of Designs, Opportunities, and Challenges
2024 | Journal of Medical Internet Research (JMIR)
Abstract:
Background: Smartphone apps can aid consumers in making healthier and more sustainable food purchases. However, there is still a limited understanding of the different app design approaches and their impact on food purchase choices. An overview of existing food purchase choice apps and an understanding of common challenges can help speed up effective future developments.
Objective: We examined the academic literature on food purchase choice apps and provided an overview of the design characteristics, opportunities, and challenges for effective implementation. Thus, we contribute to an understanding of how technologies can effectively improve food purchase choice behavior and provide recommendations for future design efforts.
Methods: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we considered peer-reviewed literature on food purchase choice apps within IEEE Xplore, PubMed, Scopus, and ScienceDirect. We inductively coded and summarized design characteristics. Opportunities and challenges were addressed from both quantitative and qualitative perspectives. From the quantitative perspective, we coded and summarized outcomes of comparative evaluation trials. From the qualitative perspective, we performed a qualitative content analysis of commonly discussed opportunities and challenges.
Results: We retrieved 55 articles, identified 46 unique apps, and grouped them into 5 distinct app types. Each app type supports a specific purchase choice stage and shares a common functional design. Most apps support the product selection stage (selection apps; 27/46, 59%), commonly by scanning the barcode and displaying a nutritional rating. In total, 73% (8/11) of the evaluation trials reported significant findings and indicated the potential of food purchase choice apps to support behavior change. However, relatively few evaluations covered the selection app type, and these studies showed mixed results. We found a common opportunity in apps contributing to learning (knowledge gain), whereas infrequent engagement presents a common challenge. The latter was associated with perceived burden of use, trust, and performance as well as with learning. In addition, there were technical challenges in establishing comprehensive product information databases or achieving performance accuracy with advanced identification methods such as image recognition.
Conclusions: Our findings suggest that designs of food purchase choice apps do not encourage repeated use or long-term adoption, compromising the effectiveness of behavior change through nudging. However, we found that smartphone apps can enhance learning, which plays an important role in behavior change. Compared with nudging as a mechanism for behavior change, this mechanism is less dependent on continued use. We argue that designs that optimize for learning within each interaction have a better chance of achieving behavior change. This review concludes with design recommendations, suggesting that food purchase choice app designers anticipate the possibility of early abandonment as part of their design process and design apps that optimize the learning experience.
Reverse Engineering of Digital Measures: Inviting Patients to the Conversation
2023 | Digital Biomarkers
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Abstract:
Background: Digital measures offer an unparalleled opportunity to create a more holistic picture of how people who are patients behave in their real-world environments, thereby establishing a better connection between patients, caregivers, and the clinical evidence used to drive drug development and disease management. Reaching this vision will require achieving a new level of co-creation between the stakeholders who design, develop, use, and make decisions using evidence from digital measures. Summary: In September 2022, the second in a series of meetings hosted by the Swiss Federal Institute of Technology in Zürich, the Foundation for the National Institutes of Health Biomarkers Consortium, and sponsored by Wellcome Trust, entitled "Reverse Engineering of Digital Measures," was held in Zurich, Switzerland, with a broad range of stakeholders sharing their experience across four case studies to examine how patient centricity is essential in shaping development and validation of digital evidence generation tools. Key Messages: In this paper, we discuss progress and the remaining barriers to widespread use of digital measures for evidence generation in clinical development and care delivery. We also present key discussion points and takeaways in order to continue discourse and provide a basis for dissemination and outreach to the wider community and other stakeholders. The work presented here shows us a blueprint for how and why the patient voice can be thoughtfully integrated into digital measure development and that continued multi-stakeholder engagement is critical for further progress.
Reverse Engineering of Digital Measures: Inviting Patients to the Conversation
2023 | Digital Biomarkers
Abstract:
Background: Digital measures offer an unparalleled opportunity to create a more holistic picture of how people who are patients behave in their real-world environments, thereby establishing a better connection between patients, caregivers, and the clinical evidence used to drive drug development and disease management. Reaching this vision will require achieving a new level of co-creation between the stakeholders who design, develop, use, and make decisions using evidence from digital measures. Summary: In September 2022, the second in a series of meetings hosted by the Swiss Federal Institute of Technology in Zürich, the Foundation for the National Institutes of Health Biomarkers Consortium, and sponsored by Wellcome Trust, entitled "Reverse Engineering of Digital Measures," was held in Zurich, Switzerland, with a broad range of stakeholders sharing their experience across four case studies to examine how patient centricity is essential in shaping development and validation of digital evidence generation tools. Key Messages: In this paper, we discuss progress and the remaining barriers to widespread use of digital measures for evidence generation in clinical development and care delivery. We also present key discussion points and takeaways in order to continue discourse and provide a basis for dissemination and outreach to the wider community and other stakeholders. The work presented here shows us a blueprint for how and why the patient voice can be thoughtfully integrated into digital measure development and that continued multi-stakeholder engagement is critical for further progress.
Regulatory Qualification of a Cross-Disease Digital Measure: Benefits and Challenges from the Perspective of IMI Consortium IDEA-FAST
2023 | Digital Biomarkers
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Abstract: Background: Innovative Medicines Initiative (IMI) consortium IDEA-FAST is developing novel digital measures of fatigue, sleep quality, and impact of sleep disturbances for neurodegenerative diseases and immune-mediated inflammatory diseases. In 2022, the consortium met with the European Medicines Agency (EMA) to receive advice on its plans for regulatory qualification of the measures. This viewpoint reviews the IDEA-FAST perspective on developing digital measures for multiple diseases and the advice provided by the EMA. Summary: The EMA considered a cross-disease measure an interesting and arguably feasible concept. Developers should account for the need for a strong rationale that the clinical features to be measured are similar across diseases. In addition, they may expect increased complexity of study design, challenges when managing differences within and between disease populations, and the need for validation in both heterogeneous and homogeneous populations. Key Messages: EMA highlighted the challenges teams may encounter when developing a cross-disease measure, though benefits potentially include reduced resources for the technology developer and health authority, faster access to innovation across different therapeutic fields, and feasibility of cross-disease comparisons. The insights included here can be used by project teams to guide them in the development of cross-disease digital measures intended for regulatory qualification.
Regulatory Qualification of a Cross-Disease Digital Measure: Benefits and Challenges from the Perspective of IMI Consortium IDEA-FAST
2023 | Digital Biomarkers
Abstract: Background: Innovative Medicines Initiative (IMI) consortium IDEA-FAST is developing novel digital measures of fatigue, sleep quality, and impact of sleep disturbances for neurodegenerative diseases and immune-mediated inflammatory diseases. In 2022, the consortium met with the European Medicines Agency (EMA) to receive advice on its plans for regulatory qualification of the measures. This viewpoint reviews the IDEA-FAST perspective on developing digital measures for multiple diseases and the advice provided by the EMA. Summary: The EMA considered a cross-disease measure an interesting and arguably feasible concept. Developers should account for the need for a strong rationale that the clinical features to be measured are similar across diseases. In addition, they may expect increased complexity of study design, challenges when managing differences within and between disease populations, and the need for validation in both heterogeneous and homogeneous populations. Key Messages: EMA highlighted the challenges teams may encounter when developing a cross-disease measure, though benefits potentially include reduced resources for the technology developer and health authority, faster access to innovation across different therapeutic fields, and feasibility of cross-disease comparisons. The insights included here can be used by project teams to guide them in the development of cross-disease digital measures intended for regulatory qualification.
Technology acceptance of digital devices for home use: Qualitative results of a mixed methods study
2023 | DIGITAL HEALTH
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Abstract:
Objective
Digital devices have demonstrated benefits to patients with chronic and neurodegenerative diseases. But when patients use medical devices in their homes, the technologies have to fit into their lives. We investigated the technology acceptance of seven digital devices for home use.
Methods
We conducted 60 semi-structured interviews with participants of a larger device study on their views on the acceptability of seven devices. Transcriptions were analysed using qualitative content analysis.
Results
Based on the unified theory of acceptance and use of technology, we evaluated effort, facilitating conditions, performance expectancy and social influence of each device.
In the effort category, five themes emerged: (a) the hassle to use the device; (b) its usability; (c) comfort; (d) disturbance to daily life; and (e) problems during usage. Facilitating conditions consisted of five themes: (a) expectations regarding a device; (b) quality of the instructions; (c) insecurities with usage; (d) possibilities of optimization; and (e) possibilities to use the device longer. Regarding performance expectancy, we identified three themes: (a) insecurities with the performance of a device; (b) feedback; and (c) motivation for using a device. In the social influence category, three themes emerged: (a) reactions of peers; (b) concerns with the visibility of a device; and (c) concerns regarding data privacy.
Conclusions
We identify key factors that determine the acceptability of medical devices for home use from the participants’ perspective. These include low effort of use, minor disruptions to their daily lives and good support from the study team.
Technology acceptance of digital devices for home use: Qualitative results of a mixed methods study
2023 | DIGITAL HEALTH
Abstract:
Objective Digital devices have demonstrated benefits to patients with chronic and neurodegenerative diseases. But when patients use medical devices in their homes, the technologies have to fit into their lives. We investigated the technology acceptance of seven digital devices for home use.
Methods We conducted 60 semi-structured interviews with participants of a larger device study on their views on the acceptability of seven devices. Transcriptions were analysed using qualitative content analysis.
Results Based on the unified theory of acceptance and use of technology, we evaluated effort, facilitating conditions, performance expectancy and social influence of each device. In the effort category, five themes emerged: (a) the hassle to use the device; (b) its usability; (c) comfort; (d) disturbance to daily life; and (e) problems during usage. Facilitating conditions consisted of five themes: (a) expectations regarding a device; (b) quality of the instructions; (c) insecurities with usage; (d) possibilities of optimization; and (e) possibilities to use the device longer. Regarding performance expectancy, we identified three themes: (a) insecurities with the performance of a device; (b) feedback; and (c) motivation for using a device. In the social influence category, three themes emerged: (a) reactions of peers; (b) concerns with the visibility of a device; and (c) concerns regarding data privacy.
Conclusions We identify key factors that determine the acceptability of medical devices for home use from the participants’ perspective. These include low effort of use, minor disruptions to their daily lives and good support from the study team.
Assessment of non-directed computer-use behaviours in the home can indicate early cognitive impairment: A proof of principle longitudinal study
2022 | Aging & Mental Health
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Abstract:
Objectives
Computer-use behaviours can provide useful information about an individual’s cognitive and functional abilities. However, little research has evaluated unaided and non-directed home computer-use. In this proof of principle study, we explored whether computer-use behaviours recorded during routine home computer-use i) could discriminate between individuals with subjective cognitive decline (SCD) and individuals with mild cognitive impairment (MCI); ii) were associated with cognitive and functional scores; and iii) changed over time.
Methods
Thirty-two participants with SCD (n = 18) or MCI (n = 14) (mean age = 72.53 years; female n = 19) participated in a longitudinal study in which their in-home computer-use behaviour was passively recorded over 7–9 months. Cognitive and functional assessments were completed at three time points: baseline; mid-point (4.5 months); and end point (month 7 to 9).
Results
Individuals with MCI had significantly slower keystroke speed and spent less time on the computer than individuals with SCD. More time spent on the computer was associated with better task switching abilities. Faster keystroke speed was associated with better visual attention, recall, recognition, task inhibition, and task switching. No significant change in computer-use behaviour was detected over the study period.
Conclusion
Passive monitoring of computer-use behaviour shows potential as an indicator of cognitive abilities, and can differentiate between people with SCD and MCI. Future studies should attempt to monitor computer-use behaviours over a longer time period to capture the onset of cognitive decline, and thus could inform timely therapeutic interventions.
Assessment of non-directed computer-use behaviours in the home can indicate early cognitive impairment: A proof of principle longitudinal study
2022 | Aging & Mental Health
Abstract:
Objectives Computer-use behaviours can provide useful information about an individual’s cognitive and functional abilities. However, little research has evaluated unaided and non-directed home computer-use. In this proof of principle study, we explored whether computer-use behaviours recorded during routine home computer-use i) could discriminate between individuals with subjective cognitive decline (SCD) and individuals with mild cognitive impairment (MCI); ii) were associated with cognitive and functional scores; and iii) changed over time.
Methods Thirty-two participants with SCD (n = 18) or MCI (n = 14) (mean age = 72.53 years; female n = 19) participated in a longitudinal study in which their in-home computer-use behaviour was passively recorded over 7–9 months. Cognitive and functional assessments were completed at three time points: baseline; mid-point (4.5 months); and end point (month 7 to 9).
Results Individuals with MCI had significantly slower keystroke speed and spent less time on the computer than individuals with SCD. More time spent on the computer was associated with better task switching abilities. Faster keystroke speed was associated with better visual attention, recall, recognition, task inhibition, and task switching. No significant change in computer-use behaviour was detected over the study period.
Conclusion Passive monitoring of computer-use behaviour shows potential as an indicator of cognitive abilities, and can differentiate between people with SCD and MCI. Future studies should attempt to monitor computer-use behaviours over a longer time period to capture the onset of cognitive decline, and thus could inform timely therapeutic interventions.
Known and unknown requirements in healthcare
2020 | Requirements Engineering
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Abstract: We report experience in requirements elicitation of domain knowledge from experts in clinical and cognitive neurosciences. The elicitation target was a causal model for early signs of dementia indicated by changes in user behaviour and errors apparent in logs of computer activity. A Delphi-style process consisting of workshops with experts followed by a questionnaire was adopted. The paper describes how the elicitation process had to be adapted to deal with problems encountered in terminology and limited consensus among the experts. In spite of the difficulties encountered, a partial causal model of user behavioural pathologies and errors was elicited. This informed requirements for configuring data- and text-mining tools to search for the specific data patterns. Lessons learned for elicitation from experts are presented, and the implications for requirements are discussed as “unknown unknowns”, as well as configuration requirements for directing data-/text-mining tools towards refining awareness requirements in healthcare applications.
Known and unknown requirements in healthcare
2020 | Requirements Engineering
Abstract: We report experience in requirements elicitation of domain knowledge from experts in clinical and cognitive neurosciences. The elicitation target was a causal model for early signs of dementia indicated by changes in user behaviour and errors apparent in logs of computer activity. A Delphi-style process consisting of workshops with experts followed by a questionnaire was adopted. The paper describes how the elicitation process had to be adapted to deal with problems encountered in terminology and limited consensus among the experts. In spite of the difficulties encountered, a partial causal model of user behavioural pathologies and errors was elicited. This informed requirements for configuring data- and text-mining tools to search for the specific data patterns. Lessons learned for elicitation from experts are presented, and the implications for requirements are discussed as “unknown unknowns”, as well as configuration requirements for directing data-/text-mining tools towards refining awareness requirements in healthcare applications.
StammerApp: Designing a Mobile Application to Support Self-Reflection and Goal Setting for People Who Stammer
2018 | CHI Conference on Human Factors in Computing Systems
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Abstract: Stammering is a speech disorder affecting approximately 1% of the worldwide population. It can have associated impacts on daily life, such as loss of confidence in social situations and increased anxiety levels (particularly when speaking to strangers). Work exploring the development of digital tools to support people who stammer (PwS) is emerging. However, there is a paucity of research engaging PwS in the design process, with participation being facilitated mainly in testing phases. In this paper, we describe the user-centered design, development and evaluation of StammerApp, a mobile application to support PwS. We contribute insights into the challenges and barriers that PwS experience day-to-day and reflect on the complexities of designing with this diverse group. Finally, we present a set of design recommendations for the development of tools to support PwS in their everyday interactions, and provide an example of how these might be envisioned through the StammerApp prototype.
StammerApp: Designing a Mobile Application to Support Self-Reflection and Goal Setting for People Who Stammer
2018 | CHI Conference on Human Factors in Computing Systems
Abstract: Stammering is a speech disorder affecting approximately 1% of the worldwide population. It can have associated impacts on daily life, such as loss of confidence in social situations and increased anxiety levels (particularly when speaking to strangers). Work exploring the development of digital tools to support people who stammer (PwS) is emerging. However, there is a paucity of research engaging PwS in the design process, with participation being facilitated mainly in testing phases. In this paper, we describe the user-centered design, development and evaluation of StammerApp, a mobile application to support PwS. We contribute insights into the challenges and barriers that PwS experience day-to-day and reflect on the complexities of designing with this diverse group. Finally, we present a set of design recommendations for the development of tools to support PwS in their everyday interactions, and provide an example of how these might be envisioned through the StammerApp prototype.
Combining data mining and text mining for detection of early stage dementia: the SAMS framework
2016 | Resources and ProcessIng of linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric impairments (RaPID '16)
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Abstract: In this paper, we describe the open-source SAMS framework whose novelty lies in bringing together both data collection (keystrokes, mouse movements, application pathways) and text collection (email, documents, diaries) and analysis methodologies. The aim of SAMS is to provide a non-invasive method for large scale collection, secure storage, retrieval and analysis of an individual's computer usage for the detection of cognitive decline, and to infer whether this decline is consistent with the early stages of dementia. The framework will allow evaluation and study by medical professionals in which data and textual features can be linked to deficits in cognitive domains that are characteristic of dementia. Having described requirements gathering and ethical concerns in previous papers, here we focus on the implementation of the data and text collection components.
Combining data mining and text mining for detection of early stage dementia: the SAMS framework
2016 | Resources and ProcessIng of linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric impairments (RaPID '16)
Abstract: In this paper, we describe the open-source SAMS framework whose novelty lies in bringing together both data collection (keystrokes, mouse movements, application pathways) and text collection (email, documents, diaries) and analysis methodologies. The aim of SAMS is to provide a non-invasive method for large scale collection, secure storage, retrieval and analysis of an individual's computer usage for the detection of cognitive decline, and to infer whether this decline is consistent with the early stages of dementia. The framework will allow evaluation and study by medical professionals in which data and textual features can be linked to deficits in cognitive domains that are characteristic of dementia. Having described requirements gathering and ethical concerns in previous papers, here we focus on the implementation of the data and text collection components.
Supporting Reflective Practice in Software Engineering Education through a Studio-Based Approach
Christopher Bull, Jon Whittle
2014 | IEEE Software
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Abstract: Learning is a lifelong process, especially in the fast-paced software industry. In addition to formal training courses, good software developers continually learn by reflecting on what they've done in the past. However, reflective practice is rarely taught explicitly in university software engineering education. One way to teach reflective techniques from the start is through studio-based learning.
Supporting Reflective Practice in Software Engineering Education through a Studio-Based Approach
Christopher Bull, Jon Whittle
2014 | IEEE Software
Abstract: Learning is a lifelong process, especially in the fast-paced software industry. In addition to formal training courses, good software developers continually learn by reflecting on what they've done in the past. However, reflective practice is rarely taught explicitly in university software engineering education. One way to teach reflective techniques from the start is through studio-based learning.
Observations of a Software Engineering Studio: Reflecting with the Studio Framework
Christopher Bull, Jon Whittle
2014 | Conference on Software Engineering Education and Training (CSEE&T '14)
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Abstract: Studio-based learning for software engineering is a well-received concept, despite its apparent lack of uptake across institutions worldwide. Studio education affords a variety of highly desirable benefits, and is also popular amongst its students. This paper presents Lancaster University's software engineering studio, details of its implementation, observations made throughout its first year, evidence of its successes, and reflections against the recently defined studio framework. This paper aims to provide useful information for anyone that is considering utilizing a studio-based approach.
Observations of a Software Engineering Studio: Reflecting with the Studio Framework
Christopher Bull, Jon Whittle
2014 | Conference on Software Engineering Education and Training (CSEE&T '14)
Abstract: Studio-based learning for software engineering is a well-received concept, despite its apparent lack of uptake across institutions worldwide. Studio education affords a variety of highly desirable benefits, and is also popular amongst its students. This paper presents Lancaster University's software engineering studio, details of its implementation, observations made throughout its first year, evidence of its successes, and reflections against the recently defined studio framework. This paper aims to provide useful information for anyone that is considering utilizing a studio-based approach.
Studios in Software Engineering Education: Towards an Evaluable Model
2013 | International Conference on Software Engineering (ICSE '13)
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Abstract: Studio-based teaching is a method commonly used in arts and design that emphasizes a physical "home" for students, problem-based and peer-based learning, and mentoring by academic staff rather than formal lectures. There have been some attempts to transfer studio-based teaching to software engineering education. In many ways, this is natural as software engineering has significant practical elements. However, attempts at software studios have usually ignored experiences and theory from arts and design studio teaching. There is therefore a lack of understanding of what "studio" really means, how well the concepts transfer to software engineering, and how effective studios are in practice. Without a clear definition of "studio", software studios cannot be properly evaluated for their impact on student learning nor can best and worst practices be shared between those who run studios. In this paper, we address this problem head-on by conducting a qualitative analysis of what "studio" really means in both arts and design. We carried out 15 interviews with a range of people with studio experiences and present an analysis and model for evaluation here. Our results suggest that there are many intertwined aspects that define studio education, but it is primarily the people and the culture that make a studio. Digital technology on the other hand can have an adverse effect on studios, unless properly recognised.
Studios in Software Engineering Education: Towards an Evaluable Model
2013 | International Conference on Software Engineering (ICSE '13)
Abstract: Studio-based teaching is a method commonly used in arts and design that emphasizes a physical "home" for students, problem-based and peer-based learning, and mentoring by academic staff rather than formal lectures. There have been some attempts to transfer studio-based teaching to software engineering education. In many ways, this is natural as software engineering has significant practical elements. However, attempts at software studios have usually ignored experiences and theory from arts and design studio teaching. There is therefore a lack of understanding of what "studio" really means, how well the concepts transfer to software engineering, and how effective studios are in practice. Without a clear definition of "studio", software studios cannot be properly evaluated for their impact on student learning nor can best and worst practices be shared between those who run studios. In this paper, we address this problem head-on by conducting a qualitative analysis of what "studio" really means in both arts and design. We carried out 15 interviews with a range of people with studio experiences and present an analysis and model for evaluation here. Our results suggest that there are many intertwined aspects that define studio education, but it is primarily the people and the culture that make a studio. Digital technology on the other hand can have an adverse effect on studios, unless properly recognised.