huashen218/convxai-cia-dataset huggingface dataset:
Title: Improving Instruction of Programming Patterns with Faded Parsons Problems
Authors: family: Weinman
given: Nathaniel; family: Fox
given: Armando; family: Hearst
given: Marti A.
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Programming Patterns, Computing Education, CS1, Parsons Problems

Abstract: Learning to recognize and apply programming patterns — reusable abstractions of code — is critical to becoming a proficient computer scientist. However, many introductory Computer Science courses do not teach patterns, in part because teaching these concepts requires significant curriculum changes. As an alternative, we explore how a novel user interface for practicing coding — Faded Parsons Problems — can support introductory Computer Science students in learning to apply programming patterns. We ran a classroom-based study with 237 students which found that Faded Parsons Problems, or rearranging and completing partially blank lines of code into a valid program, are an effective exercise interface for teaching programming patterns, significantly surpassing the performance of the more standard approaches of code writing and code tracing exercises. Faded Parsons Problems also improve overall code writing ability at a comparable level to code writing exercises, but are preferred by students.
Title: StoryCoder: Teaching Computational Thinking Concepts Through Storytelling in a Voice-Guided App for Children
Authors: family: Dietz
given: Griffin; family: Le
given: Jimmy K; family: Tamer
given: Nadin; family: Han
given: Jenny; family: Gweon
given: Hyowon; family: Murnane
given: Elizabeth L; family: Landay
given: James A.
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: computational thinking, children, storytelling, voice user interface

Abstract: Computational thinking (CT) education reaches only a fraction of young children, in part because CT learning tools often require expensive hardware or fluent literacy. Informed by needfinding interviews, we developed a voice-guided smartphone application leveraging storytelling as a creative activity by which to teach CT concepts to 5- to 8-year-old children. The app includes two storytelling games where users create and listen to stories as well as four CT games where users then modify those stories to learn about sequences, loops, events, and variables. We improved upon the app design through wizard-of-oz testing (N = 28) and iterative design testing (N = 22) before conducting an evaluation study (N = 22). Children were successfully able to navigate the app, effectively learn about the target computing concepts, and, after using the app, children demonstrated above-chance performance on a near transfer CT concept recognition task.
Title: On Designing Programming Error Messages for Novices: Readability and its Constituent Factors
Authors: family: Denny
given: Paul; family: Prather
given: James; family: Becker
given: Brett A.; family: Mooney
given: Catherine; family: Homer
given: John; family: Albrecht
given: Zachary C; family: Powell
given: Garrett B.
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: readability, introductory programming, HCI, students, human computer interaction, compiler error messages, programming error messages, compiler design and implementation, novice programmers, CS1

Abstract: Programming error messages play an important role in learning to program. The cycle of program input and error message response completes a loop between the programmer and the compiler/interpreter and is a fundamental interaction between human and computer. However, error messages are notoriously problematic, especially for novices. Despite numerous guidelines citing the importance of message readability, there is little empirical research dedicated to understanding and assessing it. We report three related experiments investigating factors that influence programming error message readability. In the first two experiments we identify possible factors, and in the third we ask novice programmers to rate messages using scales derived from these factors. We find evidence that several key factors significantly affect message readability: message length, jargon use, sentence structure, and vocabulary. This provides novel empirical support for previously untested long-standing guidelines on message design, and informs future efforts to create readability metrics for programming error messages.
Title: The Role of Working Memory in Program Tracing
Authors: family: Crichton
given: Will; family: Agrawala
given: Maneesh; family: Hanrahan
given: Pat
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Program tracing, restricted focus viewing, program comprehension, working memory

Abstract: Program tracing, or mentally simulating a program on concrete inputs, is an important part of general program comprehension. Programs involve many kinds of virtual state that must be held in memory, such as variable/value pairs and a call stack. In this work, we examine the influence of short-term working memory (WM) on a person’s ability to remember program state during tracing. We first confirm that previous findings in cognitive psychology transfer to the programming domain: people can keep about 7 variable/value pairs in WM, and people will accidentally swap associations between variables due to WM load. We use a restricted focus viewing interface to further analyze the strategies people use to trace through programs, and the relationship of tracing strategy to WM. Given a straight-line program, we find half of our participants traced a program from the top-down line-by-line (linearly), and the other half start at the bottom and trace upward based on data dependencies (on-demand). Participants with an on-demand strategy made more WM errors while tracing straight-line code than with a linear strategy, but the two strategies contained an equal number of WM errors when tracing code with functions. We conclude with the implications of these findings for the design of programming tools: first, programs should be analyzed to identify and refactor human-memory-intensive sections of code. Second, programming environments should interactively visualize variable metadata to reduce WM load in accordance with a person’s tracing strategy. Third, tools for program comprehension should enable externalizing program state while tracing.
Title: Diagramming Working Field Theories for Design in the HCI Classroom
Authors: family: Ploderer
given: Bernd; family: Lawrence Taylor
given: Jennyfer; family: Muñoz
given: Diego; family: Bircanin
given: Filip; family: Brereton
given: Margot
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: sensitizing concept, design research, HCI education, fieldwork, visual thinking

Abstract: HCI has historically provided little support for moving from fieldwork insights or theories to design outcomes. Having witnessed many students struggle and then justify their designs with a form of marketing hype, we developed a supporting approach of “field theories”. A field theory is a working theory about salient interactions in a particular domain and sensitizing concepts in order to frame design investigations. It is presented visually in a field theory diagram to support succinct communication and critique. Studying use of design prototypes that have been informed by a field theory helps to reflect upon and refine the theory. In this paper we present examples from our HCI classes and reflections based on interviews with students. We discuss how field theories offer an orientation in the spirit of a ‘bricoleur’ who harnesses elements of theory and practice to produce deeper understandings and more fitting outcomes for the task at hand.
Title: Effective Interfaces for Student-Driven Revision Sessions for Argumentative Writing
Authors: family: Afrin
given: Tazin; family: Kashefi
given: Omid; family: Olshefski
given: Christopher; family: Litman
given: Diane; family: Hwa
given: Rebecca; family: Godley
given: Amanda
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Academic writing, intelligent interface, argumentative writing, revision, wizard of oz

Abstract: We present the design and evaluation of a web-based intelligent writing assistant that helps students recognize their revisions of argumentative essays. To understand how our revision assistant can best support students, we have implemented four versions of our system with differences in the unit span (sentence versus sub-sentence) of revision analysis and the level of feedback provided (none, binary, or detailed revision purpose categorization). We first discuss the design decisions behind relevant components of the system, then analyze the efficacy of the different versions through a Wizard of Oz study with university students. Our results show that while a simple interface with no revision feedback is easier to use, an interface that provides a detailed categorization of sentence-level revisions is the most helpful based on user survey data, as well as the most effective based on improvement in writing outcomes.
Title: EvalMe: Exploring the Value of New Technologies for In Situ Evaluation of Learning Experiences
Authors: family: Lechelt
given: Susan; family: Brudy
given: Frederik; family: Marquardt
given: Nicolai; family: Rogers
given: Yvonne
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Educational Setting, Education/learning, Children/Parents, Tangible, Schools

Abstract: Tangible interfaces have much potential for engendering shared interaction and reflection, as well as for promoting playful experiences. How can their properties be capitalised on to enable students to reflect on their learning, both individually and together, throughout learning sessions? This Research through Design paper describes our development of EvalMe, a flexible, tangible tool aimed at being playful, enjoyable to use and enabling children to reflect on their learning, both in the moment and after a learning session has ended. We discuss the insights gained through the process of designing EvalMe, co-defining its functionality with two groups of collaborators and deploying it in two workshop settings. Through this process, we map key contextual considerations for the design of technologies for in situ evaluation of learning experiences. Finally, we discuss how tangible evaluation technologies deployed throughout a learning session, can positively contribute to students’ reflection about their learning.
Title: Problem-Solving Efficiency and Cognitive Load for Adaptive Parsons Problems vs. Writing the Equivalent Code
Authors: family: Haynes
given: Carl C.; family: Ericson
given: Barbara J.
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Cognitive Load Theory, Parsons Problems, Computing Education, Programming

Abstract: Novice programmers need differentiated assessments (such as adaptive Parsons problems) to maximize their ability to learn how to program. Parsons problems require learners to place mixed-up code blocks in the correct order to solve a problem. We conducted a within-subjects experiment to compare the efficiency and cognitive load of solving adaptive Parsons problems versus writing the equivalent (isomorphic) code. Undergraduates were usually more significantly efficient at solving a Parsons problem than writing the equivalent code, but not when the solution to the Parsons problem was unusual. This has implications for problem creators. This paper also reports on the mean cognitive load ratings of the two problem types and the relationship between efficiency and cognitive load ratings. Lastly, it reports on think-aloud observations of 11 students solving both adaptive Parsons problems and write-code problems and the results from an end-of-course student survey.
Title: Avoiding the Turing Tarpit: Learning Conversational Programming by Starting from Code’s Purpose
Authors: family: Cunningham
given: Kathryn; family: Ericson
given: Barbara J.; family: Agrawal Bejarano
given: Rahul; family: Guzdial
given: Mark
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: conversational programmers, motivation, programming plans, scaffolding, computer-supported instruction

Abstract: Conversational programmers want to learn about code primarily to communicate with technical co-workers, not to develop software. However, existing instructional materials don’t meet the needs of conversational programmers because they prioritize syntax and semantics over concepts and applications. This mismatch results in feelings of failure and low self-efficacy. To motivate conversational programmers, we propose purpose-first programming, a new approach that focuses on learning a handful of domain-specific code patterns and assembling them to create authentic and useful programs. We report on the development of a purpose-first programming prototype that teaches five patterns in the domain of web scraping. We show that learning with purpose-first programming is motivating for conversational programmers because it engenders a feeling of success and aligns with these learners’ goals. Purpose-first programming learning enabled novice conversational programmers to complete scaffolded code writing, debugging, and explaining activities after only 30 minutes of instruction.
Title: “You Gotta Watch What You Say”: Surveillance of Communication with Incarcerated People
Authors: family: Owens
given: Kentrell; family: Cobb
given: Camille; family: Cranor
given: Lorrie
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: communication, surveillance, privacy, prison, ICT

Abstract: Surveillance of communication between incarcerated and non-incarcerated people has steadily increased, enabled partly by technological advancements. Third-party vendors control communication tools for most U.S. prisons and jails and offer surveillance capabilities beyond what individual facilities could realistically implement. Frequent communication with family improves mental health and post-carceral outcomes for incarcerated people, but does discomfort about surveillance affect how their relatives communicate with them? To explore this and the understanding, attitudes, and reactions to surveillance, we conducted 16 semi-structured interviews with participants who have incarcerated relatives. Among other findings, we learn that participants communicate despite privacy concerns that they felt helpless to address. We also observe inaccuracies in participants’ beliefs about surveillance practices. We discuss implications of inaccurate understandings of surveillance, misaligned incentives between end-users and vendors, how our findings enhance ongoing conversations about carceral justice, and recommendations for more privacy-sensitive communication tools.
Title: Toggles, Dollar Signs, and Triangles: How to (In)Effectively Convey Privacy Choices with Icons and Link Texts
Authors: family: Habib
given: Hana; family: Zou
given: Yixin; family: Yao
given: Yaxing; family: Acquisti
given: Alessandro; family: Cranor
given: Lorrie; family: Reidenberg
given: Joel; family: Sadeh
given: Norman; family: Schaub
given: Florian
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: icon design, CCPA., choice, Privacy

Abstract: Increasingly, icons are being proposed to concisely convey privacy-related information and choices to users. However, complex privacy concepts can be difficult to communicate. We investigate which icons effectively signal the presence of privacy choices. In a series of user studies, we designed and evaluated icons and accompanying textual descriptions (link texts) conveying choice, opting-out, and sale of personal information — the latter an opt-out mandated by the California Consumer Privacy Act (CCPA). We identified icon-link text pairings that conveyed the presence of privacy choices without creating misconceptions, with a blue stylized toggle icon paired with “Privacy Options” performing best. The two CCPA-mandated link texts (“Do Not Sell My Personal Information” and “Do Not Sell My Info”) accurately communicated the presence of do-not-sell opt-outs with most icons. Our results provide insights for the design of privacy choice indicators and highlight the necessity of incorporating user testing into policy making.
Title: A Design Space for Privacy Choices: Towards Meaningful Privacy Control in the Internet of Things
Authors: family: Feng
given: Yuanyuan; family: Yao
given: Yaxing; family: Sadeh
given: Norman
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: usable privacy, design space, privacy choice, Internet of Things

Abstract: “Notice and choice” is the predominant approach for data privacy protection today. There is considerable user-centered research on providing effective privacy notices but not enough guidance on designing privacy choices. Recent data privacy regulations worldwide established new requirements for privacy choices, but system practitioners struggle to implement legally compliant privacy choices that also provide users meaningful privacy control. We construct a design space for privacy choices based on a user-centered analysis of how people exercise privacy choices in real-world systems. This work contributes a conceptual framework that considers privacy choice as a user-centered process as well as a taxonomy for practitioners to design meaningful privacy choices in their systems. We also present a use case of how we leverage the design space to finalize the design decisions for a real-world privacy choice platform, the Internet of Things (IoT) Assistant, to provide meaningful privacy control in the IoT.
Title: Visual Interactive Privacy Policy: The Better Choice?
Authors: family: Reinhardt
given: Daniel; family: Borchard
given: Johannes; family: Hurtienne
given: Jörn
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Privacy, Privacy Policy Nutrition Label, Privacy Policy

Abstract: Online privacy policies should enable users to make informed decisions. Current text policies, however, lack usability: users often miss crucial information and consent to them without reading. Visual representation formats may increase comprehension, but are rarely used in practice. In an iterative design process we gathered qualitative feedback on typical policy contents and on existing and newly designed representation formats. We developed design guidelines and a Visual Interactive Privacy Policy based on the Privacy Policy Nutrition Label enriched with control options and further interactive elements. In an empirical evaluation, both visual representations received higher ratings of attractiveness, stimulation, novelty and transparency compared to a standard policy long text. Interactivity improved time spent with the policy. There were no effects on conversion rate, perceived control or perceived trust, efficiency and perspicuity. More research is needed, especially with regard to the cost-benefit ratio of visual privacy policies.
Title: Bolder is Better: Raising User Awareness through Salient and Concise Privacy Notices
Authors: family: Ebert
given: Nico; family: Alexander Ackermann
given: Kurt; family: Scheppler
given: Björn
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: information systems, information saliency, privacy awareness, privacy communication, experimental design, Privacy notices

Abstract: This paper addresses the question whether the recently proposed approach of concise privacy notices in apps and on websites is effective in raising user awareness. To assess the effectiveness in a realistic setting, we included concise notices in a fictitious but realistic fitness tracking app and asked participants recruited from an online panel to provide their feedback on the usability of the app as a cover story. Importantly, after giving feedback, users were also asked to recall the data practices described in the notices. The experimental setup included the variation of different levels of saliency and riskiness of the privacy notices. Based on a total sample of 2,274 participants, our findings indicate that concise privacy notices are indeed a promising approach to raise user awareness for privacy information when displayed in a salient way, especially in case the notices describe risky data practices. Our results may be helpful for regulators, user advocates and transparency-oriented companies in creating or enforcing better privacy transparency towards average users that do not read traditional privacy policies.
Title: Exploring Design and Governance Challenges in the Development of Privacy-Preserving Computation
Authors: family: Agrawal
given: Nitin; family: Binns
given: Reuben; family: Van Kleek
given: Max; family: Laine
given: Kim; family: Shadbolt
given: Nigel
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: policy, privacy-enhancing technologies, expert interview, cryptography

Abstract: Homomorphic encryption, secure multi-party computation, and differential privacy are part of an emerging class of Privacy Enhancing Technologies which share a common promise: to preserve privacy whilst also obtaining the benefits of computational analysis. Due to their relative novelty, complexity, and opacity, these technologies provoke a variety of novel questions for design and governance. We interviewed researchers, developers, industry leaders, policymakers, and designers involved in their deployment to explore motivations, expectations, perceived opportunities and barriers to adoption. This provided insight into several pertinent challenges facing the adoption of these technologies, including: how they might make a nebulous concept like privacy computationally tractable; how to make them more usable by developers; and how they could be explained and made accountable to stakeholders and wider society. We conclude with implications for the development, deployment, and responsible governance of these privacy-preserving computation techniques.
Title: PriView– Exploring Visualisations to Support Users’ Privacy Awareness
Authors: family: Prange
given: Sarah; family: Shams
given: Ahmed; family: Piening
given: Robin; family: Abdelrahman
given: Yomna; family: Alt
given: Florian
Venue: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Keywords: Smart Home, Privacy, Mobile Application, Visualisation, Thermal Camera, Smart Devices, IoT, VR, AR, Smart Environments

Abstract: We present PriView, a concept that allows privacy-invasive devices in the users’ vicinity to be visualised. PriView is motivated by an ever-increasing number of sensors in our environments tracking potentially sensitive data (e.g., audio and video). At the same time, users are oftentimes unaware of this, which violates their privacy. Knowledge about potential recording would enable users to avoid accessing such areas or not to disclose certain information. We built two prototypes: a) a mobile application capable of detecting smart devices in the environment using a thermal camera, and b) VR mockups of six scenarios where PriView might be useful (e.g., a rental apartment). In both, we included several types of visualisation. Results of our lab study (N=24) indicate that users prefer simple, permanent indicators while wishing for detailed visualisations on demand. Our exploration is meant to support future designs of privacy visualisations for varying smart environments.