Miracle-dz/UniFAR-FTUs huggingface dataset:
Merging SaaS Products In A User-Centered Way — A Case Study of Overleaf and ShareLaTeX

Mergers and acquisitions pose complex organizational and technical challenges. A user-centered approach can help ensure the success of a merger. By prioritizing the management of user expectations, by addressing change aversion and by ensuring users feel heard, a merger cannot only be made more successful, but also be perceived as a positive change by end users. This case study describes and discusses the user-centered approach taken to successfully merge two established online LaTeX editors: Overleaf and ShareLaTeX. A mixed methods approach was used to simultaneously ensure broad coverage of the user base (quantitative; relevant because these were established products) and also in-depth understanding of their issues, opinions and motivations (qualitative; relevant to making informed design decisions). This user-centered approach was successful in helping the company to set a path for the merger, to adapt in the face of new data, and to create the foundation for sustained growth.
BunCho: AI Supported Story Co-Creation via Unsupervised Multitask Learning to Increase Writers’ Creativity in Japanese

Co-creation with artificial intelligence (AI) is an upcoming trend. However, less attention has been given to the construction of systems for Japanese novelists. In this study, we built “BunCho”, an AI supported story co-creation system in Japanese. BunCho’s AI is GPT-2 (an unsupervised multitask language model) trained using a large-scale dataset of Japanese web texts and novels. With BunCho, users can generate titles and synopses from keywords. Furthermore, we propose an interactive story co-creation AI system as a tabletop role-playing game. According to summative studies of writers (N=16) and readers (N=32), 69% writers enjoyed writing synopses with BunCho more than by themselves, and at least one of five common metrics were improved at objective evaluation, including creativity. In addition, 63% writers indicated that BunCho broadened their stories. BunCho showed paths to assist Japanese novelists in creating high-level and creative writing.
Explainable Automatic Evaluation of the Trail Making Test for Dementia Screening

The Trail Making Test (TMT) is a frequently used neuropsychological test for assessing cognitive performance. The subject connects a sequence of numbered nodes by using a pen on normal paper. We present an automatic cognitive assessment tool that analyzes samples of the TMT which we record using a digital pen. This enables us to analyze digital pen features that are difficult or impossible to evaluate manually. Our system automatically measures several pen features, including the completion time which is the main performance indicator used by clinicians to score the TMT in practice. In addition, our system provides a structured report of the analysis of the test, for example indicating missed or erroneously connected nodes, thereby offering more objective, transparent and explainable results to the clinician. We evaluate our system with 40 elderly subjects from a geriatrics daycare clinic of a large hospital.
Context-Aware Wearables: The Last Thing We Need is a Pandemic of Stray Cats

We present Connected Companion (CoCo), a health tracking wearable that provides users with timely, context-relevant notifications aimed at improving wellness. Traditionally, self-tracking wearables report basic health data such as resting heart rate; these data are visualised and positive behaviours (e.g. exercising often) are encouraged with rudimentary gamification (e.g. award badges) and notification systems. CoCo is the first wearable to combine caffeine, alcohol and cortisol sensors, a context network (which predicts user context), and a wellness model (which establishes per-user wellness measures). Working in tandem these provide users with notifications that encourage discrete behaviours intended to optimise user-wellness per very specific biological and social contexts. The paper describes the (sometimes unexpected) results of a user-study intended to evaluate CoCo's efficacy and we conclude with a discussion about the power and responsibility that comes with attempts to build context-aware computing systems.
A Multichannel Pneumatic Analog Control System for Haptic Displays: Multichannel Pneumatic Analog Control System (MPACS)

Soft robotics use in haptic devices continues to grow, with pneumatic control being a common actuation source. Typical control systems used, however, rely on a digital on/off control allowing only inflation/deflation at a set rate. This limits the degrees of freedom available when designing haptic experiences. We present an alternative system to allow the use of analog control of the pneumatic waveform profiles to design and experiment with haptic devices, and to determine the optimum wave profile for the desired experience. Using a combination of off-the-shelf components and a user interface, our system allows for rapid experimentation with various pressure levels, and the ability to control waveform profiles in a common format such as attack-sustain-release. In this paper, we demonstrate that by altering the attack and release profiles we can create a more pleasant pulsing sensation on the wrist, and a more continuous sensation for communicating movement around the wrist.
Learning from Healthcare Providers’ Strategies: Designing Technology to Support Effective Child Patient-Provider Communication

Effective patient-provider communication is critical to promote patient satisfaction, encourage patient involvement in care, and improve health outcomes. Although prior HCI works aim to enhance the dyadic communication by improving patients’ communication skills, little is known about healthcare providers’ communication work to facilitate effective communication with their child patients. Through semi-structured interviews with 10 healthcare providers and clinic observations, our study identified four strategies that providers used in their communication with patients: building rapport, developing familiarity with care settings, respecting patients’ communication modes and preferences, and delegating small decision-making and directing questions to patients. Based on these strategies, we discuss three key elements that providers value and work toward to achieve effective communication in pediatric care practice. Our study also uncovers the detailed process of how the providers develop their strategies to tailor their communication to the patients’ specific needs and preferences, and we describe design opportunities for communication technology.
How Design Researchers Interpret Probes: Understanding the Critical Intentions of a Designerly Approach to Research

Since entering the HCI lexicon in the 1990s, Probes have been interpreted and used in divergent ways as a designerly approach to research. While originally positioned as a critique of dominant user-research methods, literature on Probes rarely reflects on such critical dimensions nor explicitly articulates the intents of using Probes as research artifacts. We conducted interviews with 12 design researchers who have worked with Probes within diverse Research through Design projects, exploring direct accounts of how and why Probes are used in practice. Our interviews brought to the fore the critical concerns behind Probe practices in relation to the language of Probing, relationships with participants, and motivations to challenge normative practices. While the pluralistic interpretations of Probes offered by our participants brings challenges, we discuss how making visible the critical motivations of our research opens up new ways of practicing and disseminating Probes.
Aiki - Turning Online Procrastination into Microlearning

This paper presents and evaluates Aiki, a simple browser extension designed to redirect a user to a learning platform for a fixed amount of time before accessing websites defined as ’procrastination’ or ’time-wasting’ websites. The goal of the extension is to enable the user to exchange time spent on pages they believe contribute less to their own productivity for microlearning activities, defined as small or short-term learning activities. The paper describes the design and development of Aiki and evaluates the extension with a group of n = 10 participants studying the Danish language. Based on a two-week study, we conclude that this type of extension, even in its preliminary version, has the potential to improve language skills in a lightweight manner and that redirection is an important alternative to blocking for procrastination management.
Designing and Evaluating Intelligent Agents’ Interaction Mechanisms for Assisting Human in High-Level Thinking Tasks

In the twenty-first century, people need to learn and apply high-level thinking skills, such as decision-making, problem-solving, and critical thinking, in their daily lives. Traditionally when in need, people can get help from human assistants to complete these thinking tasks, yet, such human experts are not always accessible. Intelligent agents, such as physical robots and virtual chatbots, are promising alternatives to the human assistants in these tasks. My doctoral research focuses on designing intelligent agents to assist human users and evaluating the impact of their interaction mechanisms (i.e., way of behaving) on user experience. Specifically, my works surround this theme by proposing: 1) an anticipation-autonomy framework that models the service robot’s proactivity in decision-making support contexts (decision-making); 2) a bot assistant that helps users to solve the problem of writing poor-quality comments in online mental health communities either by assessing the writing performance or recommending writing examples (problem-solving); and 3) a chatbot in comparison to a non-conversational tool for facilitating people to read academic papers critically (critical thinking). My dissertation contributes to the design of intelligent agents for helping people in high-level thinking tasks and insights for developing appropriate interaction mechanisms for these agents in the future.
Perverse Downstream Consequences of Debunking: Being Corrected by Another User for Posting False Political News Increases Subsequent Sharing of Low Quality, Partisan, and Toxic Content in a Twitter Field Experiment

A prominent approach to combating online misinformation is to debunk false content. Here we investigate downstream consequences of social corrections on users’ subsequent sharing of other content. Being corrected might make users more attentive to accuracy, thus improving their subsequent sharing. Alternatively, corrections might not improve subsequent sharing - or even backfire - by making users feel defensive, or by shifting their attention away from accuracy (e.g., towards various social factors). We identified N=2,000 users who shared false political news on Twitter, and replied to their false tweets with links to fact-checking websites. We find causal evidence that being corrected decreases the quality, and increases the partisan slant and language toxicity, of the users’ subsequent retweets (but has no significant effect on primary tweets). This suggests that being publicly corrected by another user shifts one's attention away from accuracy - presenting an important challenge for social correction approaches.
HoloBar: Rapid Command Execution for Head-Worn AR Exploiting Around the Field-of-View Interaction

Inefficient menu interfaces lead to system and application commands being tedious to execute in Immersive Environments. HoloBar is a novel approach to ease the interaction with multi-level menus in immersive environments: with HoloBar, the hierarchical menu splits between the field of view (FoV) of the Head Mounted Display and the smartphone (SP). Command execution is based on around-the-FoV interaction with the SP, and touch input on the SP display. The HoloBar offers a unique combination of features, namely rapid mid-air activation, implicit selection of top-level items and preview of second-level items on the SP, ensuring rapid access to commands. In a first study we validate its activation method, which consists in bringing the SP within an activation distance from the FoV. In a second study, we compare the HoloBar to two alternatives, including the standard HoloLens menu. Results show that the HoloBar shortens each step of a multi-level menu interaction (menu activation, top-level item selection, second-level item selection and validation), with a high success rate. A follow-up study confirms that these results remain valid when compared with the two validation mechanisms of HoloLens (Air-Tap and clicker).
FingerMapper: Enabling Arm Interaction in Confined Spaces for Virtual Reality through Finger Mappings

As Virtual Reality (VR) headsets become more mobile, people can interact in public spaces with applications often requiring large arm movements. However, using these open gestures is often uncomfortable and sometimes impossible in confined and public spaces (e.g., commuting in a bus). We present FingerMapper, a mapping technique that maps small and energy-efficient finger motions onto virtual arms so that users have less physical motions while maintaining presence and partially virtual body ownership. FingerMapper works as an alternative function while the environment is not allowed for full arm interaction and enables users to interact inside a small physical, but larger virtual space. We present one example application, FingerSaber that allows the user to perform the large arm swinging movement using FingerMapper.
Facilitating Change: A Study of Supporting Teacher Learning

: This article examines efforts to implement the Scratch Educator Meetup model in order to accommodate the growing number of teachers involved in supporting computing education. Scratch Educator Meetups are focused on supporting teacher co-construction and participatory learning using a professional learning community approach. Previous literature on teacher professional development suggests that professional learning communities play a key role in promoting instructional improvement, and that facilitators are central to this process. Following this theoretical orientation, we share an ethnographic case study that details the tensions, contradictions, and possibilities that can arise when a professional development facilitator eschews familiar models of supporting teacher learning in favor of a novel approach. We argue that implementing instructional improvement initiatives demands careful attention to the qualitative dimensions of change, change that occurs as facilitators learn to think and act in new ways.
Pervasive Intelligent Models to Predict the Outcome of COVID-19 Patients

Nowadays, there is an increasing need to understand the behavior of COVID-19. After the Directorate-General of Health of Portugal made available the infected patient’s data, it became possible to analyze it and gather some conclusions, obtaining a better understanding of the matter. In this context, the project developed—ioCOVID19—Intelligent Decision Support Platform aims to identify patterns and develop intelligent models to predict and support clinical decisions. This article explores which typologies are associated with different outcomes to help clinicians fight the virus with a decision support system. So, to achieve this purpose, classification algorithms were used, and one target was studied—Patients outcome, that is, to predict if the patient will die or recover. Regarding the obtained results, the model that stood out is composed of scenario s4 (composed of all comorbidities, symptoms, and age), the decision tree algorithm, and the oversampling sampling method. The obtained results by the studied metrics were (in order of importance): Sensitivity of 95.20%, Accuracy of 90.67%, and Specificity of 86.08%. The models were deployed as a service, and they are part of a clinical decision support system that is available for authorized users anywhere and anytime.
Developing AI into Explanatory Supporting Models: An Explanation-visualized Deep Learning Prototype for Computer Supported Collaborative Learning

: Using Artificial Intelligence (AI) and machine learning technologies to automatically mine latent patterns from educational data holds great potential to inform teaching and learning practices. However, the current AI technology mostly works as “black box” - only the inputs and the corresponding outputs are available, which largely impedes researchers from gaining access to explainable feedback. This interdisciplinary work presents an explainable AI prototype with visualized explanations as feedback for computer-supported collaborative learning (CSCL). This research study seeks to provide interpretable insights with machine learning technologies for multimodal learning analytics (MMLA) by introducing two different explanatory machine learning-based models (neural network and Bayesian network) in different manners (end-to-end learning and probabilistic analysis) and for the same goal - provide explainable and actionable feedback. The prototype is applied to the real-world collaborative learning scenario with data-driven learning based on sensor-data from multiple modalities which can assess collaborative learning processes and render explanatory real-time feedback.
Characterising Shared Epistemic Agency in a Knowledge Building Learning Environment

: This study examined the role of Knowledge Building (KB), enriched with Virtual Reality (VR) technologies, in supporting students' understanding of scientific practices and ecosystem concepts. Students’ shared epistemic agency were characterized to examine the different patterns of strategies that students deployed while engaging in knowledge building. Twenty students of a Hong Kong middle school engaged in progressive theory-building as they mimic scientists to investigate its decrease in animal population within a virtual world. Knowledge Forum (KF) served as the platform for collaborative knowledge building and collective discourse. Key findings of this study include 1) improvement in understanding of concepts on ecology; 2) characterising shared epistemic agency as progressive levels. The implications of engaging students with KB to promote shared epistemic agency are discussed.
Learning From Design Failure, Collaboratively

Effective design requires iterative cycles of learning from failure, where design teams evaluate their designs to identify problems and make iterative improvement. However, existing learning from failure models does not always take the collaborative process, a key aspect of design, into account. The aim of the current study is to design tools that better support young design teams’ collaborative learning from design failure process in an afterschool club with students in grades 4-6. In this article, we examine how teams used discourse to learn from design failure collaboratively by analyzing video data and group artifacts. Our findings suggest that the specific communication process can support or hinder the learning from failure in design contexts and that there's a need to support the team's regulation process so they can benefit from their design failure.
Designing for Playful Math Engagement Across Learning Environments

: This symposium offers considerations for designing playful mathematics learning environments by synthesizing empirical research across four contexts that differ in location, formality, timescale, materials, facilitation, and participation structures. Despite the importance of play across the lifespan, mathematics classrooms are often spaces students feel a void of agency and enjoyment. This has strong implications for students’ sense of competence and their identities as individuals who participate in and enjoy mathematics. Thus, designing playful environments where children enjoy and participate in mathematics as a form of meaning making is a critical issue for equity in education. By putting these four studies in conversation with one another, we hope to develop a refined understanding of how particular design decisions influence learner engagement in mathematics, with an eye towards making mathematical play more accessible both in and out of school.
Advancing Computational Grounded Theory for Audiovisual Data from Mathematics Classrooms

: This poster will discuss early findings from a project that is developing theory-based approaches to combine computational methods and qualitative grounded theory in order to analyze classroom video data of middle school mathematics classrooms. These early findings involve the feasibility of using out-of-the-box implementations of video and audio processing algorithms for analysis of video and audio data, focusing on methods to capture instances of collaboration and student–teacher interactions.
Diameter modulation and integration of vertically aligned single walled carbon nanotubes for understanding of mass transport in carbon nanotubes

Carbon nanotubes (CNTs) are the prototypical one-dimensional nanomaterial that has been highly touted for their superior properties beneficial for a wide range of applications. In particular, a membrane with pores of the CNT interior promises to facilitate and enhance mass transport and poses great potential for applications such as energy-efficient purification, desalination, demineralization and hydroelectric energy generation. Nevertheless, simulations and experiments are not in agreement about the mass transport enhancements. In order to provide indisputable evidence about the flow enhancements in relation to their key physical factors, such as nanotube diameter, it is crucial to establish reliable methodologies for diameter modulation of vertically aligned (VA) CNTs and for membrane manufacturing. Processes that integrate small-diameter, single-walled CNTs (SWCNTs) into a membrane matrix should maintain the original alignment, spatial uniformity, and defect density of the as-grown nanotubes. Here, the precise control of the average diameter of VA-SWCNTs ranging from 1.2 nm, which is the state-of-the-art minimum value for VA-SWCNTs, to 4.67 nm with a 1-3 Å resolution is demonstrated. The two-fold strategies that enabled this wide range and fine average diameter modulation are the rational design of catalyst and the parameter optimization of chemical vapor deposition (CVD) process. The former influences the size distribution of catalyst particles formed from the dewetting process of a thin metal film on a support. First, controlling the nominal deposition thickness of Fe with ~1Å resolution finely tunes the size distribution and number density of nanoparticles. Next, the size matching of Al2O3 support asperities and deposited catalyst particles is found critical to suppress the diffusion and coarsening process. Followingly, Mo deposited between Fe and Al2O3 support is found effective to reduce and narrow the dewetted particle size range and shift CNT formation window to smaller size range, thereby producing smaller diameter CNTs. Lastly, a few-tensof-nm-thick layered Fe/Mo/Al2O3 catalyst is developed that generates dense nanosized bimetallic particles on surface upon a sufficient thermal annealing, which hints weakening of an otherwise strong
Characterizing the Emergence of a Knowledge-Building Community in Online Mathematics Teacher Professional Development

: One factor impacting the effectiveness of online teacher professional development is that teachers primarily share and compare ideas in their discussions. This study aimed to better understand the process by which a knowledge-building community of practice (CoP) emerges in an online mathematics teacher professional development course. We characterized the generativity of teachers’ interactions and employed social network analysis to examine evolution in the pattern of these interactions. We found signs of a knowledge-building CoP, evidenced by a stabilizing and evolving core-periphery structure and consistent increase in the extent to which participants engaged generative interactions to build knowledge with one another. This work has implications for developing technologies that can assist teacher educators in cultivating online knowledge-building CoPs.