SIAT - Theses, Dissertations, and other Required Graduate Degree Essays

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Data-informed collaboration in evaluating design alternatives

File(s): 
Date created: 
2021-08-11
Supervisor(s): 
Halil Erhan
Department: 
Communication, Art & Technology: School of Interactive Arts and Technology
Thesis type: 
(Thesis) M.Sc.
Abstract: 

Evaluation of design ideas is an integral part of designing built environments. It involves multiple stakeholders with diverse backgrounds reviewing design solutions by studying their form and performance data. Although there are computational systems for supporting evaluation tasks, they are either highly specialized for designers or configured for a particular workflow with limited functions. I developed a Design Analytics method aiming at a collaborative and data-driven evaluation of alternatives in the design-evaluate-feedback cycle. Adopting this approach, I introduce D-ART as a prototype system composed of customizable Web interfaces for presenting design alternatives, enabling stakeholders to participate in data-informed discourse on alternatives and providing feedback to the design team. Its system design considers requirements gathered through literature review, critical analysis of the existing systems and collaboration with our industry partners. Finally, I assessed D-ART's design through an expert review evaluation, which generally reported positive results on the system's utility.

Document type: 
Thesis

Measuring self-regulatory phases with multi-channel trace data in open-ended learning technology

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Date created: 
2021-11-05
Supervisor(s): 
Marek Hatala
Department: 
Communication, Art & Technology: School of Interactive Arts and Technology
Thesis type: 
(Thesis) Ph.D.
Abstract: 

Research has emphasized that self-regulated learning (SRL) is critically important for learning. Students have different capabilities of regulating their learning processes and individual needs. To help students improve their SRL capabilities, we need to identify students’ current behaviors. Specifically, I used learning design to create visible and meaningful markers of student progress through SRL in an open-ended technology, a Learning Management System (LMS). I applied knowledge engineering to develop a framework of proximal indicators representing SRL phases and evaluated them in quasi-experiments in four different learning activities. I developed an embedded tool to collect real-time students’ self-reports in the LMS. Comparing two SRL measures, i.e., behavioral and self-reported measures, revealed a relatively high agreement between two measures (weighted kappa, κ = .62 - .74). However, our indicators did not always discriminate adjacent SRL phases, particularly for enactment and adapting phases, compared with students’ real-time self-reported behaviors. Our behavioral indicators also were comparably successful at classifying SRL phases for different students’ cohorts. The revised indicators incorporating SRL temporal features improved the convergence of behavioral and self-reported measures. However, the findings revealed that the SRL temporal feature is task-specific and requires customization for a specific task type. The findings also suggested that the task type may influence how students progress through SRL processes. Overall, this thesis demonstrated how the triangulation of multiple sources of students’ self-regulatory data could help unravel the complex nature of SRL phases. Additionally, this thesis highlighted the importance of learning design in open-ended learning technology to support students and track their progress through SRL phases for personalized scaffolds.

Document type: 
Thesis

Design and development of interactive systems for integration of visual analytics in design workflow

Author: 
File(s): 
Paper URL: http://papers.cumincad.org/cgi-bin/works/paper/caadria2021_405; Video URL: https://youtu.be/_-DtXfgEo2w
Paper URL: http://papers.cumincad.org/cgi-bin/works/paper/caadria2020_423; Video URL: https://youtu.be/9KGB2nbDwAo
Date created: 
2021-08-10
Supervisor(s): 
Halil Erhan
Department: 
Communication, Art & Technology: School of Interactive Arts and Technology
Thesis type: 
(Thesis) M.Sc.
Abstract: 

Data-driven processes are increasingly being used in architectural design to create, evaluate, and select design options. Multiple design-aid systems for supporting such processes exist. Despite this, many systems primarily support parametric modelling or lack sufficient support for simultaneously organizing, scanning, and comparing multiple alternatives in the design and development process, taking their forms and performance data into account. In this research project, I argue that interactive data visualizations can provide real-time feedback about the performance of design alternatives. This data visualization should be incorporated in the design process from the early design stages. Moreover, evaluating and selecting potential alternatives must occur in the same context in which they are created and explored. The design environment also must enable detailed comparison of a few design alternatives as an integral part of the directly interactive design modelling workflow. We call our approach Design Analytics which aims to identify, develop, and validate practical key features of visualization tools for assisting designers in evaluating (e.g. analyzing, comparing, and selecting) multiple solutions with their data. I present Design Flow User Interface (D-FlowUI) and Design Comparative Analytics Tool (D-CAT) as visualization prototype systems integrated into an existing Computer-Aided Design application. D-FlowUI and D-CAT act as platforms for generating knowledge about using interactive data visualization to evaluate and compare design alternatives. Finally, I conducted a formative qualitative evaluation with design professionals, which revealed the tool’s potential and highlighted future directions. This research aims to transfer the findings from studying and evaluating these interfaces to the development of practical applications for real-world use.

Document type: 
Thesis

Improving spatial orientation in virtual reality with leaning-based interfaces

Author: 
File(s): 
Date created: 
2021-04-13
Supervisor(s): 
Bernhard Riecke
Department: 
Communication, Art & Technology: School of Interactive Arts and Technology
Thesis type: 
(Thesis) M.Sc.
Abstract: 

Advancement in technology has made Virtual Reality (VR) increasingly portable, affordable and accessible to a broad audience. However, large scale VR locomotion still faces major challenges in the form of spatial disorientation and motion sickness. While spatial updating is automatic and even obligatory in real world walking, using VR controllers to travel can cause disorientation. This dissertation presents two experiments that explore ways of improving spatial updating and spatial orientation in VR locomotion while minimizing cybersickness. In the first study, we compared a hand-held controller with HeadJoystick, a leaning-based interface, in a 3D navigational search task. The results showed that leaning-based interface helped participant spatially update more effectively than when using the controller. In the second study, we designed a "HyperJump" locomotion paradigm which allows to travel faster while limiting its optical flow. Not having any optical flow (as in traditional teleport paradigms) has been shown to help reduce cybersickness, but can also cause disorientation. By interlacing continuous locomotion with teleportation we showed that user can travel faster without compromising spatial updating.

Document type: 
Thesis

Gray areas inside black boxes: Tracing actor-networks and ethics in professional design practice

Author: 
File(s): 
Date created: 
2021-08-17
Supervisor(s): 
Ron Wakkary
Department: 
Communication, Art & Technology: School of Interactive Arts and Technology
Thesis type: 
(Thesis) M.A.
Abstract: 

In this study, I analyze professional designers’ experiences of exercising agency and enacting ethics in design practice. This research is based on a focus group and a series of individual interviews with design and technology practitioners at technology companies and design consultancies. First, based on grounded theory analysis, I present a thematic analysis of ethical issues in professional design practice and the mitigating strategies used by designers. Second, based on actor-network theory (ANT), I present three vignettes to describe the human and nonhuman networks of professional designers and how they increase agency and ethics in design. The contributions of this work include an application of actor-network theory to professional design practice, an empirical account of the human and nonhuman networks of professional design practice, and descriptions of how agency and ethical responsibility are distributed and shared across humans and nonhumans.

Document type: 
Thesis

Adaptive and learning-based formation control of swarm robots

Author: 
File(s): 
Date created: 
2021-10-14
Supervisor(s): 
Philippe Pasquier
Department: 
Communication, Art & Technology: School of Interactive Arts and Technology
Thesis type: 
(Thesis) Ph.D.
Abstract: 

Autonomous aerial and wheeled mobile robots play a major role in tasks such as search and rescue, transportation, monitoring, and inspection. However, these operations are faced with a few open challenges including robust autonomy, and adaptive coordination based on the environment and operating conditions, particularly in swarm robots with limited communication and perception capabilities. Furthermore, the computational complexity increases exponentially with the number of robots in the swarm. This thesis examines two different aspects of the formation control problem. On the one hand, we investigate how formation could be performed by swarm robots with limited communication and perception (e.g., Crazyflie nano quadrotor). On the other hand, we explore human-swarm interaction (HSI) and different shared-control mechanisms between human and swarm robots (e.g., BristleBot) for artistic creation. In particular, we combine bio-inspired (i.e., flocking, foraging) techniques with learning-based control strategies (using artificial neural networks) for adaptive control of multi- robots. We first review how learning-based control and networked dynamical systems can be used to assign distributed and decentralized policies to individual robots such that the desired formation emerges from their collective behavior. We proceed by presenting a novel flocking control for UAV swarm using deep reinforcement learning. We formulate the flocking formation problem as a partially observable Markov decision process (POMDP), and consider a leader-follower configuration, where consensus among all UAVs is used to train a shared control policy, and each UAV performs actions based on the local information it collects. In addition, to avoid collision among UAVs and guarantee flocking and navigation, a reward function is added with the global flocking maintenance, mutual reward, and a collision penalty. We adapt deep deterministic policy gradient (DDPG) with centralized training and decentralized execution to obtain the flocking control policy using actor-critic networks and a global state space matrix. In the context of swarm robotics in arts, we investigate how the formation paradigm can serve as an interaction modality for artists to aesthetically utilize swarms. In particular, we explore particle swarm optimization (PSO) and random walk to control the communication between a team of robots with swarming behavior for musical creation.

Document type: 
Thesis

Bodily resonance: Exploring the effects of virtual embodiment on pain modulation and the fostering of empathy toward pain sufferers

Author: 
File(s): 
Date created: 
2021-04-15
Supervisor(s): 
Diane Gromala
Chris D. Shaw
Department: 
Communication, Art & Technology: School of Interactive Arts and Technology
Thesis type: 
(Thesis) Ph.D.
Abstract: 

Globally, around 20% of people suffer from chronic pain, an illness that cannot be cured and has been linked to numerous physical and mental conditions. According to the BioPsychoSocial model of pain, chronic pain presents patients with biological, psychological, and social challenges and difficulties. Immersive virtual reality (VR) has shown great promise in helping people manage acute and chronic pain, and facilitating empathy of vulnerable populations. Therefore, the first research trajectory of this dissertation targets chronic pain patients’ biological and psychological sufferings to provide VR analgesia, and the second research trajectory targets healthy people to build empathy and reduce patients’ social stigma. Researchers have taken the attention distraction approach to study how acute pain patients can manage their condition in VR, while the virtual embodiment approach has mostly been studied with healthy people exposed to pain stimulus. My first research trajectory aimed to understand how embodied characteristics affect users’ sense of embodiment and pain. Three studies have been carried out with healthy people under heat pain, complex regional pain syndrome patients, and phantom limb pain patients. My findings indicate that for all three studies, when users see a healthy or intact virtual body or body parts, they experience significant reductions in their self-reported pain ratings. Additionally, I found that the appearance of a virtual body has a significant impact on pain, whereas the virtual body’s motions do not. Despite the prevalence of chronic pain, public awareness of it is remarkably low, and pain patients commonly experience social stigma. Thus, having an embodied perspective of chronic pain patients is critical to understand their social stigma. Although there is a growing interest in using embodied VR to foster empathy towards gender or racial bias, few studies have focused on people with chronic pain. My second trajectory explored how researchers can foster empathy towards pain patients in embodied VR. To conclude, this dissertation uncovers the role of VR embodiment and dissects embodied characteristics in pain modulation and empathy generation. Finally, I summarized a novel conceptual design framework for embodied VR applications with design recommendations and future research directions.

Document type: 
Thesis

Expressive movement generation with machine learning

Author: 
Date created: 
2021-03-25
Supervisor(s): 
Philippe Pasquier
Department: 
Communication, Art & Technology: School of Interactive Arts and Technology
Thesis type: 
(Thesis) Ph.D.
Abstract: 

Movement is an essential aspect of our lives. Not only do we move to interact with our physical environment, but we also express ourselves and communicate with others through our movements. In an increasingly computerized world where various technologies and devices surround us, our movements are essential parts of our interaction with and consumption of computational devices and artifacts. In this context, incorporating an understanding of our movements within the design of the technologies surrounding us can significantly improve our daily experiences. This need has given rise to the field of movement computing – developing computational models of movement that can perceive, manipulate, and generate movements. In this thesis, we contribute to the field of movement computing by building machine-learning-based solutions for automatic movement generation. In particular, we focus on using machine learning techniques and motion capture data to create controllable, generative movement models. We also contribute to the field by creating datasets, tools, and libraries that we have developed during our research. We start our research by reviewing the works on building automatic movement generation systems using machine learning techniques and motion capture data. Our review covers background topics such as high-level movement characterization, training data, features representation, machine learning models, and evaluation methods. Building on our literature review, we present WalkNet, an interactive agent walking movement controller based on neural networks. The expressivity of virtual, animated agents plays an essential role in their believability. Therefore, WalkNet integrates controlling the expressive qualities of movement with the goal-oriented behaviour of an animated virtual agent. It allows us to control the generation based on the valence and arousal levels of affect, the movement’s walking direction, and the mover’s movement signature in real-time. Following WalkNet, we look at controlling movement generation using more complex stimuli such as music represented by audio signals (i.e., non-symbolic music). Music-driven dance generation involves a highly non-linear mapping between temporally dense stimuli (i.e., the audio signal) and movements, which renders a more challenging modelling movement problem. To this end, we present GrooveNet, a real-time machine learning model for music-driven dance generation.

Document type: 
Thesis

Audio beacon technologies, surveillance and social order

File(s): 
Date created: 
2021-07-22
Supervisor(s): 
Niranjan Rajah
Department: 
Communication, Art & Technology: School of Interactive Arts and Technology
Thesis type: 
(Thesis) M.A.
Abstract: 

This thesis explores audio beacon technology with the aim of elucidating the implications of this technology for the individual in contemporary society. Audio beacons are hidden inside digital devices. They emit and receive high frequency audio signals which are inaudible to the human ear, thereby generating and transmitting data without our knowledge. The motivation for this research is to raise awareness of the prevalence of audio beacon technologies and to explore their implications for contemporary society. The research takes an interdisciplinary approach involving – 1) a survey of audio beacon technology, 2) a contextualization in terms of contemporary theories of surveillance and control and 3) an interpretation in terms of 20th century dystopian literature. The hidden surveillance and privacy of this technology is examined mainly through the humanistic perspective of George Orwell’s book Nineteen Eighty-Four. The general conclusion formed is that audio beacon technologies can serve as a surveillance method enhancing authoritarian and exploitative regimes. To mitigate the negative impacts of audio beacons, this research proposes two types of solutions – 1) individual actions that will have an immediate effect and 2) governmental legislation that can improve privacy in the longer term. Both of these solutions cannot happen without a raised public awareness, towards which this research hopes to make a contribution. Finally, this research introduces the notion of a 'digital paradox' in which the dystopian worlds of George Orwell and Aldous Huxley are brought together in order to characterize surveillance and control in contemporary society.

Document type: 
Thesis

Sensemaking with learning analytics visualizations: Investigating dashboard comprehension and effects on learning strategy

Author: 
File(s): 
Date created: 
2021-04-07
Supervisor(s): 
Marek Hatala
Department: 
Communication, Art & Technology: School of Interactive Arts and Technology
Thesis type: 
(Thesis) Ph.D.
Abstract: 

In the provision of just-in-time feedback, student-facing learning analytics dashboards (LADs) are meant to aid decision-making during the process of learning. Unlike summative feedback received at its conclusion, this formative feedback may help learners pivot their learning strategies while still engaged in the learning activity. To turn this feedback into actionable insights however, learners must understand LADs well enough to make accurate judgements of learning with them. For these learners, LADs could become an integral part of their self-regulatory learning strategy. This dissertation presents a multifaceted examination of learners’ sensemaking processes with LADs designed to support self-regulatory learning. The in-situ studies detailed therein examine learners’ understanding of the data visualized in LADs and the effects of this understanding on their performance-related mental models. Trace data, surveys, semi-structured in-depth qualitative interviews, and retrospective cued recall methods were used to identify why, when, and how learners used LADs to guide their learning. Learners’ qualitative accounts of their experience explained and contextualized the quantitative data collected from the observed activities. Learners preferred less complex LADs, finding them more useful and aesthetically appealing, despite lower gist recall with simpler visualizations. During an early investigation of how LADs were used to make learning judgments in situ, we observed learners’ tendency to act upon brief LAD interactions. This inspired us to operationalize gist as a form of measurement, describing learners’ ability to make sense of a LAD after a brief visual interrogation. Subsequent comparisons of the accuracy and descriptiveness of learners’ gist estimates to those of laypeople repeatedly showed that laypeople were more apt than learners to produce accurate and complete gist descriptions. This dissertation culminates in a final study examining the evolution of learners’ mental models of their performance due to repeated LAD interaction, followed by a discussion of the contextual factors that contributed to what was observed. Trends observed across this work suggest that learners were more apt to “get the gist” with LAD after repeated interaction. This dissertation contributes a novel method for evaluating learners’ interpretation of LADs, while our findings offer insight into how LADs shape learners’ sensemaking processes.

Document type: 
Thesis