Statistical models should accurately reflect analysts' domain knowledge about variables and their relationships. While recent tools let analysts express these assumptions and use them to produce a resulting statis...
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ISBN:
(纸本)9798400703300
Statistical models should accurately reflect analysts' domain knowledge about variables and their relationships. While recent tools let analysts express these assumptions and use them to produce a resulting statistical model, it remains unclear what analysts want to express and how externalization impacts statistical model quality. This paper addresses these gaps. We first conduct an exploratory study of analysts using a domain-specific language (DSL) to express conceptual models. We observe a preference for detailing how variables relate and a desire to allow, and then later resolve, ambiguity in their conceptual models. We leverage these findings to develop rTisane, a DSL for expressing conceptual models augmented with an interactive disambiguation process. In a controlled evaluation, we find that analysts reconsidered their assumptions, self-reported externalizing their assumptions accurately, and maintained analysis intent with rTisane. Additionally, rTisane enabled some analysts to author statistical models they were unable to specify manually. For others, rTisane resulted in models that better fit the data or enabled iterative improvement.
This paper proposes an architecture that makes programming of robot behavior of an arbitrary complexity possible for end-users and shows the technical solutions in a way that is easy to understand and generalize to di...
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This paper proposes an architecture that makes programming of robot behavior of an arbitrary complexity possible for end-users and shows the technical solutions in a way that is easy to understand and generalize to different situations. It aims to facilitate the uptake and actual use of robot technologies in therapies for training social skills to autistic children. However, the framework is easy to generalize for an arbitrary human robot interaction application, where users with no technical background need to program robots, i.e. in various assistive robotics applications. We identified the main needs of end-user programming of robots as a basic prerequisite for the uptake of robots in assistive applications. These are reusability, modularity, affordances for natural interaction and the ease of use. After reviewing the shortcomings of the existing architectures, we developed an initial architecture according to these principles and embedded it in a robot platform. Further, we used a co-creation process to develop and concretize the architecture to facilitate solutions and create affordances for robot specialists and therapists. Several pilot tests showed that different user groups, including therapists with general computer skills and adolescents with autism could make simple training or general behavioral scenarios within 1 h, by connecting existing behavioral blocks and by typing textual robot commands for fine-tuning the behaviors. In addition, this paper explains the basic concepts behind the TiViPE based robot control platform, and gives guidelines for choosing the robot programming tool and designing end-user platforms for robots. (C) 2012 Elsevier B.V. All rights reserved.
We reflect on our experiences in improving the diversity of participants in our research, focusing on geographic diversity and countering WEIRDness. Our reflections are grounded in four studies conducted over two year...
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ISBN:
(纸本)9798350376920;9798350366136
We reflect on our experiences in improving the diversity of participants in our research, focusing on geographic diversity and countering WEIRDness. Our reflections are grounded in four studies conducted over two years, with more than 100 total participant engagements across more than 100 hours of user studies. Our samples included participants from the UK and the USA, but also from the Republic of Ireland, the Netherlands, Kenya, Nigeria, Ghana, Armenia, Israel, and Japan. We reflect on some of the challenges we encountered and what we have learnt about the benefits of geographic diversity. Finally, we discuss the scientific ideal of "representativeness" and consider whether it is possible, or appropriate, in small sample studies (n similar to 20). We propose that representativeness is antagonised by the ideal of diversity. We seek alternative ways of understanding and articulating the epistemic value of diversity in Human-Computer Interaction (HCI) research.
Despite significant advances in machine learning (ML) applications within science, there is a notable gap in its integration into K-12 education to enhance data literacy and scientific inquiry (SI) skills. To address ...
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ISBN:
(纸本)9798400703317
Despite significant advances in machine learning (ML) applications within science, there is a notable gap in its integration into K-12 education to enhance data literacy and scientific inquiry (SI) skills. To address this gap, we enable K-12 teachers with limited technical expertise to apply ML for pattern discovery and explore how ML can empower educators in teaching SI. We design a web-based tool, ML4SI, for teachers to create ML-supported SI learning activities. This tool can also facilitate collecting data about the interaction between ML techniques and SI learning. A pilot study with three K-12 teachers provides insights to prepare the next generation for the era of big data through ML-supported SI learning.
Computer programming typically requires people to describe operations in a formally specified textual language. Unfortunately, working with syntax is a significant cognitive load, making programming difficult for begi...
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ISBN:
(纸本)9781450399098
Computer programming typically requires people to describe operations in a formally specified textual language. Unfortunately, working with syntax is a significant cognitive load, making programming difficult for beginners and time-consuming for professional developers. In response to this, contemporary research often focuses on abstracting or improving the process of composing code. We believe, however, that one fundamental reason why programming is difficult is the disconnect between the symbols and metaphors used in code and the mechanics they represent. programming languages use abstractions whose superficial similarities to natural language neither effectively help users understand programs nor enable them to work creatively. To tackle this fundamental limitation, this paper introduces a new language based on a novel programming-by-demonstration paradigm that (i) enables users to experiment and test their programs, (ii) allows describing complex operations without the need to learn any syntax, and (iii) always displays an approximation of the program state while programming a new operation. We explain the rationales behind our new approach and present our design and implementation using illustrative examples and a supplemental video recording.
A unique selling point for cyber-physical production system manufacturers becomes the easy with which machines and cells can be adapted to new products and production processes. Adaptations, however, are often done by...
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ISBN:
(纸本)9781450393171
A unique selling point for cyber-physical production system manufacturers becomes the easy with which machines and cells can be adapted to new products and production processes. Adaptations, however, are often done by domain experts without in-depth programming know-how. We investigate in this paper, the implications of using a planning-based approach for using a domain expert's knowledge to control the sequences of a robot and injection molding machine (IMM). We find that current engineering support is insufficient to address testing, understanding, and change impact assessment concerns during the evolution of a PDDL/HDDL domain specification.
Trigger-Action programming (TAP) allows end-users to automate IoT devices, social media, and other services. TAP systems typically offer 1) user-friendly, GUI-mediated access to service APIs through "triggers&quo...
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ISBN:
(纸本)9798350376920;9798350366136
Trigger-Action programming (TAP) allows end-users to automate IoT devices, social media, and other services. TAP systems typically offer 1) user-friendly, GUI-mediated access to service APIs through "triggers" and "actions" and 2) a simplified if-this-then-that programming model. While simple, TAP's programming model lacks power and limits what its users can create. We introduce Legato, an automation platform which keeps the convenient trigger and action abstractions from TAP, but allows programmers to connect these triggers and actions with complex logic via JavaScript. Legato piggybacks on IFTTT, taking advantage of IFTTT's mature ecosystem of integrations. Additionally, Legato allows programmers to store and retrieve persistent state, schedule future events, and safely test their programs. Through a two-stage usability study, we found student programmers easily learned Legato and came up with several scenarios requiring Legato's power. Based on feedback and observation, we derive design recommendations for future highly-expressive automation systems and reflect on the role of textual programming for end-user automation.
Boxer suggests a medium that might be used by a computationally literate society. We do not have a computationally literate society, but we do have one where computation is pervasive. Reaching computational literacy w...
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ISBN:
(纸本)9781450396561
Boxer suggests a medium that might be used by a computationally literate society. We do not have a computationally literate society, but we do have one where computation is pervasive. Reaching computational literacy will require us to invent media that reach citizens where they are, so that they can use computation for the kinds of tasks envisioned for Boxer. Teaspoon languages are task-specific languages designed to be highly usable. By developing and disseminating Teaspoon languages, we might move towards creating a computationally literate society.
Internet users have formed a wide array of online communities with diverse community goals and nuanced norms. However, most online platforms only offer a limited set of governance models in their software infrastructu...
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ISBN:
(纸本)9798400703300
Internet users have formed a wide array of online communities with diverse community goals and nuanced norms. However, most online platforms only offer a limited set of governance models in their software infrastructure and leave little room for customization. Consequently, technical proficiency becomes a prerequisite for online communities to build governance policies in code, excluding non-programmers from participation in designing community governance. In this paper, we present Pika, a system that empowers non-programmers to author a wide range of executable governance policies. At its core, Pika incorporates a declarative language that decomposes governance policies into modular components, thereby facilitating expressive policy authoring through a user-friendly, form-based web interface. Our user studies with 10 non-programmers and 7 programmers show that Pika can empower non-programmers to author policies approximately 2.5 times faster than programmers who author in code. We also provide insights about Pika's expressivity in supporting diverse policies online communities want.
Construction firms face challenges in sourcing qualified candidates for enhancing project outcomes through sensor data analytics. There are limited tools for teaching students from construction-related disciplines how...
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Construction firms face challenges in sourcing qualified candidates for enhancing project outcomes through sensor data analytics. There are limited tools for teaching students from construction-related disciplines how to analyze sensor data. By harnessing the potential of block-based programming, this study designed a pedagogical tool, InerSens, to support construction engineering students with no prior programming experience to analyze sensor data and address real-world construction challenges, such as ergonomic risks. Altogether 20 students participated in an experiment comparing InerSens and a traditional platform, Microsoft Excel, for data analytics. Evaluations involved usability, perceived workload, visual attention, verbal feedback using the System Usability Scale, NASA TLX, eye-tracking metrics, and interviews. InerSens was rated as 8.89% more user-friendly than the traditional tool, with a significantly reduced perceived cognitive load by 46.11%, and a more balanced distribution of visual attention during data analytics tasks. Through the evaluation of cognitive and usability factors, this paper extends the applications of the Learning-for-Use and the Cognitive Load theories, emphasizing their applicability in instructional design, revealing learner needs, and the potential to advance the development of pedagogical tools for data analytics.
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