This document provides an overview of prototyping and evaluation for an Intelligent Interfaces course. It discusses using the Processing programming environment for visual interface prototyping. It then covers the interaction design process, different evaluation paradigms including usability testing and field studies, and how to plan an evaluation. Finally, it discusses some prototyping techniques like using classes and objects, importing libraries, and adding graphical controls and interface elements.
This document outlines the syllabus for a course on intelligent interfaces and human-computer interaction. The course aims to help students reason about user models, design adaptive systems, and evaluate interfaces that maintain interactions using innovative technologies. Over 12 weeks, topics will include theoretical frameworks, input technologies, visual design, natural language interfaces, and case studies. Students will complete a group project involving iterative interface design, online discussions, and a final presentation. The project consists of 6 milestones involving analysis, paper and computer prototyping, implementation, and user testing.
This document discusses different methods for testing and evaluating user interfaces, including expert reviews, heuristic evaluations, cognitive walkthroughs, usability testing, and surveys. It describes the following key points:
- Expert reviews involve having experts examine an interface and provide feedback, while heuristic evaluations involve having experts evaluate an interface against established usability principles or heuristics.
- Usability testing involves observing real users interacting with an interface to identify usability issues. Different types of usability testing are discussed, including discount usability testing and competitive usability testing.
- Surveys can be used to collect feedback from users on their experiences, preferences, and satisfaction. Common survey methods include questionnaires with Likert scales and bipolar
This document provides an overview of a university course on visual design for user interfaces. It discusses key topics that will be covered in the course including the differences between UX and UI design, best practices in UI design, and designing for inclusive practices. The course aims to help students describe case studies of intelligent interface design, differentiate between UX and UI design approaches, list basic UI design principles, and review models for inclusive user interface design.
This document provides an overview of Week 4 of an HCI course, covering input and output devices. The key points are:
- It discusses various types of input devices like pointing devices, audio input, and visual input devices. Properties and categories of input devices are described.
- Information processing models for choice reaction tasks are explained. Stages like stimulus identification and response selection are covered.
- Output devices like displays are introduced. Characteristics of selecting the right input devices for users and tasks are outlined.
- Evaluation methods for input devices like Fitt's Law are summarized. The future of input with ubiquitous computing is briefly discussed.
This document outlines the aims, learning outcomes, syllabus, modality, assessment, and project requirements for an Intelligent Interfaces course. The course aims to teach students how to reason about user models, design adaptive systems, and evaluate interfaces using technologies like AI. It is a blended course consisting of lectures, online sessions, and a group project to design, implement and evaluate a user interface in iterations. Students will be assessed based on their project, online postings, and a final group presentation.
The document discusses the design of multimodal interfaces. It provides an overview of a course on intelligent interfaces that includes a week focused on multimodal interactions. It defines key concepts such as multimodal vs multimedia, describes various input and output modalities, and provides guidelines for designing effective multimodal interfaces. Examples of challenges and research areas in multimodal interfaces are also presented.
This document provides an overview of week 5 of an intelligent interfaces course. It discusses input devices, design guidelines for interfaces, adaptive user interfaces, and designing for human information processing. The learning outcomes are to understand visual design principles, intelligent interface design case studies, and how to design interfaces that consider metaphors and navigation. It also discusses evaluating input devices, mapping input signals, feedback, and future trends in input technologies.
This document provides an overview of the topics to be covered in Week 5 of the course ICS3211 - Intelligent Interfaces II. The week will cover input devices, design guidelines for interfaces, designing interfaces, adaptive user interfaces, and designing interactions for specific audiences. Students will learn about visual design principles, comparing interfaces and intelligent interfaces, case studies of intelligent user interface design, and how to design interfaces that consider metaphors, mental models, navigation and interaction. Learning outcomes include being able to list design principles, describe intelligent interface case studies, and draw inferences about designing interfaces that account for various user factors.
This document outlines the syllabus for a course on intelligent interfaces and human-computer interaction. The course aims to help students reason about user models, design adaptive systems, and evaluate interfaces that maintain interactions using innovative technologies. Over 12 weeks, topics will include theoretical frameworks, input technologies, visual design, natural language interfaces, and case studies. Students will complete a group project involving iterative interface design, online discussions, and a final presentation. The project consists of 6 milestones involving analysis, paper and computer prototyping, implementation, and user testing.
This document discusses different methods for testing and evaluating user interfaces, including expert reviews, heuristic evaluations, cognitive walkthroughs, usability testing, and surveys. It describes the following key points:
- Expert reviews involve having experts examine an interface and provide feedback, while heuristic evaluations involve having experts evaluate an interface against established usability principles or heuristics.
- Usability testing involves observing real users interacting with an interface to identify usability issues. Different types of usability testing are discussed, including discount usability testing and competitive usability testing.
- Surveys can be used to collect feedback from users on their experiences, preferences, and satisfaction. Common survey methods include questionnaires with Likert scales and bipolar
This document provides an overview of a university course on visual design for user interfaces. It discusses key topics that will be covered in the course including the differences between UX and UI design, best practices in UI design, and designing for inclusive practices. The course aims to help students describe case studies of intelligent interface design, differentiate between UX and UI design approaches, list basic UI design principles, and review models for inclusive user interface design.
This document provides an overview of Week 4 of an HCI course, covering input and output devices. The key points are:
- It discusses various types of input devices like pointing devices, audio input, and visual input devices. Properties and categories of input devices are described.
- Information processing models for choice reaction tasks are explained. Stages like stimulus identification and response selection are covered.
- Output devices like displays are introduced. Characteristics of selecting the right input devices for users and tasks are outlined.
- Evaluation methods for input devices like Fitt's Law are summarized. The future of input with ubiquitous computing is briefly discussed.
This document outlines the aims, learning outcomes, syllabus, modality, assessment, and project requirements for an Intelligent Interfaces course. The course aims to teach students how to reason about user models, design adaptive systems, and evaluate interfaces using technologies like AI. It is a blended course consisting of lectures, online sessions, and a group project to design, implement and evaluate a user interface in iterations. Students will be assessed based on their project, online postings, and a final group presentation.
The document discusses the design of multimodal interfaces. It provides an overview of a course on intelligent interfaces that includes a week focused on multimodal interactions. It defines key concepts such as multimodal vs multimedia, describes various input and output modalities, and provides guidelines for designing effective multimodal interfaces. Examples of challenges and research areas in multimodal interfaces are also presented.
This document provides an overview of week 5 of an intelligent interfaces course. It discusses input devices, design guidelines for interfaces, adaptive user interfaces, and designing for human information processing. The learning outcomes are to understand visual design principles, intelligent interface design case studies, and how to design interfaces that consider metaphors and navigation. It also discusses evaluating input devices, mapping input signals, feedback, and future trends in input technologies.
This document provides an overview of the topics to be covered in Week 5 of the course ICS3211 - Intelligent Interfaces II. The week will cover input devices, design guidelines for interfaces, designing interfaces, adaptive user interfaces, and designing interactions for specific audiences. Students will learn about visual design principles, comparing interfaces and intelligent interfaces, case studies of intelligent user interface design, and how to design interfaces that consider metaphors, mental models, navigation and interaction. Learning outcomes include being able to list design principles, describe intelligent interface case studies, and draw inferences about designing interfaces that account for various user factors.
This document provides an overview of a university course on intelligent user interfaces and input/output devices. It discusses various types of input devices like keyboards, mice, microphones, and digital cameras. It covers properties of input devices, how to select the appropriate devices based on tasks and users, and how to evaluate device performance. The document also discusses trends in user interfaces like sensor-based interactions and affective computing, as well as challenges. It introduces concepts like Fitt's Law for comparing pointing devices and feedback methods. The goal is for students to understand input/output devices and how to design interfaces around user needs.
This document summarizes Week 3 of an Intelligent Interfaces course. It discusses preferential choices and decision making, including defining preferential choices, the difference between decisions and choices, and factors that influence decision making like goals, anticipation of consequences, reuse of previous choices, and social influence. It provides guidelines for designing interfaces to support decision making and discusses how interfaces can influence users' choices without their awareness.
This document provides an overview of advanced interface technology topics covered in week 8 of an intelligent interfaces course, including wearable computing, augmented reality, virtual reality, invisible interfaces, environment sensing, and physiological sensing. The learning outcomes are to explore programming for visual design, compare interfaces for different applications, discuss research issues in AR/VR, and describe current AR/VR research projects. Examples of technologies discussed include Google Glass, Oculus Rift, augmented reality, invisible gesture interfaces, environmental sensors like Kinect and Tango, and physiological sensors like eye trackers. Research problems mentioned involve hardware, user interaction, social acceptance, and novel applications.
This document provides an overview of the topic "Theoretical Frameworks in HCI" that is part of the course "ICS3211 - Intelligent Interfaces II". It discusses intelligent interfaces, their need and components. It also describes different theories and models of human information processing as they relate to HCI, including GOMS model, stages of information processing in choice-reaction tasks, and various attention models. The learning outcomes are to understand intelligent interfaces and the difference between intelligent interfaces and interfaces for intelligent systems.
This document provides an overview of week 6 of the ICS3211 course on intelligent interfaces. It discusses visual design for user interfaces, including a recap of case studies, the differences between UX and UI design, best practices in UI design, evolutionary design principles, and designing for inclusive practices. The learning outcomes are also outlined.
This document summarizes a course on intelligent interfaces and decision making. It discusses interface types, preferential choices versus decisions, goals and values in decision making, anticipating consequences of choices, reusing previous choices, and social influences on decision making. Key learning outcomes are listed, including explaining how preferential choices relate to other areas of human-computer interaction and synthesizing a framework for supporting user decision making. Guidelines for interaction design to support decision making are also outlined.
This document discusses various methods for testing and evaluating user interfaces, including:
1) Expert review involves having design experts evaluate the interface against guidelines. Heuristic evaluation involves experts evaluating it based on established heuristics like Nielsen's.
2) Usability testing observes real users performing tasks while thinking aloud. It is conducted in labs and can use remote or discount testing.
3) Surveys collect user feedback through questionnaires with Likert scales.
4) Field studies and logging actual usage after release provide continuous evaluation of how users interact with the system in natural settings.
This document provides an overview of the topics to be covered in Week 2 of an Intelligent Interfaces course. It discusses the need for intelligent interfaces and the difference between intelligent interfaces and interfaces for intelligent systems. It describes the components of intelligent interfaces and various theories of human information processing, including methods and models. Learning outcomes focus on describing intelligent interfaces, explaining the difference between intelligent interfaces and interfaces for intelligent systems, listing intelligent interface components, and comparing information processing theories.
The document provides an overview of a course on intelligent interfaces and multimodal interaction design. It discusses key topics like paper prototyping tasks, characteristics of multimodal interfaces, input and output modalities, challenges in multimodal design, and guidelines for effective multimodal interface design. The goals are to describe multimodal interfaces, compare modalities depending on context, list best practices, and understand multimodal interactions. Examples of speech, gesture, and haptic interactions are provided.
This document discusses two case studies on improving healthcare systems through intelligent user interfaces: 1) An adaptive mobile interface that can adjust to users' changing needs and abilities over time through machine learning. 2) Medical robots used for various purposes like surgery, prosthetics, delivery and disinfection to assist healthcare providers and patients. It also describes scenarios where these interfaces could be used and provides examples of current technologies being developed.
The document introduces Vanessa Camilleri, a lecturer in AI who is interested in computer vision, virtual reality, games, and machine learning education; it then provides an overview of computer vision, discussing how machines capture visual data through cameras, how images are digitized and represented, and the main techniques used to make sense of visual data including object detection, recognition and neural networks.
The document provides a quick overview of human-computer interaction (HCI). It discusses who users are, what constitutes a user interface, the importance of usability, and why good usability and designing user interfaces is difficult. Key challenges include understanding users and their tasks, creating prototypes and iterating designs based on user testing, and analyzing systems to evaluate usability. HCI methods like contextual inquiry, prototyping, iterative design, and usability testing are recommended to develop systems with high usability.
Human computer interaction -Design and software processN.Jagadish Kumar
The document discusses the process of interactive design for human-computer interaction (HCI). It begins by defining design as achieving goals within constraints. It notes that goals for a wireless personal movie player may include young users wanting to watch and share movies on the go, while constraints could be withstanding rain or using existing video standards. The core of HCI design involves understanding users and technology through requirements analysis, prototyping and evaluating designs through iterations to achieve the best possible design within time and budget constraints. The process aims to incorporate user research and usability from the beginning of design through implementation.
This document discusses model-based interface development (MBID) and intelligent user interfaces. It provides an overview of MBID, describing the benefits as reducing gaps between requirements and implementation, coordinating stakeholder involvement, and producing well-structured systems. It also discusses UI models including task, abstract, concrete and final models. Several use cases are presented to illustrate MBID for applications like a car rental system, digital home, and an interactive music sheet using head gestures. Requirements for MBID tools and research gaps are also summarized.
Human Computer Interaction (HCI) is the study of how humans interact with computers and how to design interfaces so that users can interact with systems effectively, efficiently and with satisfaction. HCI aims to make computers more usable by understanding users and designing appropriate input/output devices and interaction styles. The goals of HCI include improving safety, utility, effectiveness and efficiency of computer systems to benefit both users and organizations.
The document discusses human-computer interaction (HCI). It provides an overview of HCI as a discipline concerned with designing interactive computing systems for human use. It also mentions the Association for Computing Machinery's Special Interest Group on Computer-Human Interaction. The document then lists some HCI resources and introduces the main focus of HCI as user interface design. It discusses who typically builds interfaces and why studying user interfaces is important.
This document discusses human-computer interaction (HCI). It defines HCI as the study of how humans interact with computer systems. The history and evolution of HCI is covered, from its origins in the 1970s-1990s to investigate desktop usability, to the modern fields of user experience (UX) design, human-robot interaction, and human data interaction. Key differences between HCI as a field of study and UX as an application of HCI theory are outlined. Finally, potential career paths for HCI graduates such as user researcher, product designer, and interface engineer are presented.
This document provides an overview of the subject of Human-Computer Interaction (HCI). It discusses the historical evolution of HCI from early computers to modern interfaces. It also covers key concepts like interactive system design, usability engineering, and the relationship between HCI and software engineering. The document outlines several topics that are important to HCI like GUI design, prototyping techniques, and research areas in HCI including ubiquitous computing and embedded systems.
Human Computer Interaction (HCI) is an interdisciplinary field that focuses on the design, evaluation and implementation of interactive computing systems for human use, and the study of major phenomena surrounding them. The goal of HCI is to improve the interaction between users and computers by making computers more user-friendly and responsive to user needs. Key aspects of HCI include usability testing interfaces for effectiveness, efficiency and satisfaction. Emerging areas of HCI research include pervasive/ubiquitous computing which embeds technology in everyday objects and ambient intelligence which aims to make technology invisible to users.
COMP 4026 Lecture4: Processing and Advanced Interface TechnologyMark Billinghurst
Lecture 4 from the 2016 COMP 4026 course on Advanced Human Computer Interaction taught at the University of South Australia. Taught by Mark Billinghurst, and containing material about Processing and various advanced Human Computer Interfaces.
COMP 4026 Advanced HCI lecture 6 on OpenFrameworks and Google's Project Soli. Taught by Mark Billinghurst at the University of South Australia on August 25th 2016.
This document provides an overview of a university course on intelligent user interfaces and input/output devices. It discusses various types of input devices like keyboards, mice, microphones, and digital cameras. It covers properties of input devices, how to select the appropriate devices based on tasks and users, and how to evaluate device performance. The document also discusses trends in user interfaces like sensor-based interactions and affective computing, as well as challenges. It introduces concepts like Fitt's Law for comparing pointing devices and feedback methods. The goal is for students to understand input/output devices and how to design interfaces around user needs.
This document summarizes Week 3 of an Intelligent Interfaces course. It discusses preferential choices and decision making, including defining preferential choices, the difference between decisions and choices, and factors that influence decision making like goals, anticipation of consequences, reuse of previous choices, and social influence. It provides guidelines for designing interfaces to support decision making and discusses how interfaces can influence users' choices without their awareness.
This document provides an overview of advanced interface technology topics covered in week 8 of an intelligent interfaces course, including wearable computing, augmented reality, virtual reality, invisible interfaces, environment sensing, and physiological sensing. The learning outcomes are to explore programming for visual design, compare interfaces for different applications, discuss research issues in AR/VR, and describe current AR/VR research projects. Examples of technologies discussed include Google Glass, Oculus Rift, augmented reality, invisible gesture interfaces, environmental sensors like Kinect and Tango, and physiological sensors like eye trackers. Research problems mentioned involve hardware, user interaction, social acceptance, and novel applications.
This document provides an overview of the topic "Theoretical Frameworks in HCI" that is part of the course "ICS3211 - Intelligent Interfaces II". It discusses intelligent interfaces, their need and components. It also describes different theories and models of human information processing as they relate to HCI, including GOMS model, stages of information processing in choice-reaction tasks, and various attention models. The learning outcomes are to understand intelligent interfaces and the difference between intelligent interfaces and interfaces for intelligent systems.
This document provides an overview of week 6 of the ICS3211 course on intelligent interfaces. It discusses visual design for user interfaces, including a recap of case studies, the differences between UX and UI design, best practices in UI design, evolutionary design principles, and designing for inclusive practices. The learning outcomes are also outlined.
This document summarizes a course on intelligent interfaces and decision making. It discusses interface types, preferential choices versus decisions, goals and values in decision making, anticipating consequences of choices, reusing previous choices, and social influences on decision making. Key learning outcomes are listed, including explaining how preferential choices relate to other areas of human-computer interaction and synthesizing a framework for supporting user decision making. Guidelines for interaction design to support decision making are also outlined.
This document discusses various methods for testing and evaluating user interfaces, including:
1) Expert review involves having design experts evaluate the interface against guidelines. Heuristic evaluation involves experts evaluating it based on established heuristics like Nielsen's.
2) Usability testing observes real users performing tasks while thinking aloud. It is conducted in labs and can use remote or discount testing.
3) Surveys collect user feedback through questionnaires with Likert scales.
4) Field studies and logging actual usage after release provide continuous evaluation of how users interact with the system in natural settings.
This document provides an overview of the topics to be covered in Week 2 of an Intelligent Interfaces course. It discusses the need for intelligent interfaces and the difference between intelligent interfaces and interfaces for intelligent systems. It describes the components of intelligent interfaces and various theories of human information processing, including methods and models. Learning outcomes focus on describing intelligent interfaces, explaining the difference between intelligent interfaces and interfaces for intelligent systems, listing intelligent interface components, and comparing information processing theories.
The document provides an overview of a course on intelligent interfaces and multimodal interaction design. It discusses key topics like paper prototyping tasks, characteristics of multimodal interfaces, input and output modalities, challenges in multimodal design, and guidelines for effective multimodal interface design. The goals are to describe multimodal interfaces, compare modalities depending on context, list best practices, and understand multimodal interactions. Examples of speech, gesture, and haptic interactions are provided.
This document discusses two case studies on improving healthcare systems through intelligent user interfaces: 1) An adaptive mobile interface that can adjust to users' changing needs and abilities over time through machine learning. 2) Medical robots used for various purposes like surgery, prosthetics, delivery and disinfection to assist healthcare providers and patients. It also describes scenarios where these interfaces could be used and provides examples of current technologies being developed.
The document introduces Vanessa Camilleri, a lecturer in AI who is interested in computer vision, virtual reality, games, and machine learning education; it then provides an overview of computer vision, discussing how machines capture visual data through cameras, how images are digitized and represented, and the main techniques used to make sense of visual data including object detection, recognition and neural networks.
The document provides a quick overview of human-computer interaction (HCI). It discusses who users are, what constitutes a user interface, the importance of usability, and why good usability and designing user interfaces is difficult. Key challenges include understanding users and their tasks, creating prototypes and iterating designs based on user testing, and analyzing systems to evaluate usability. HCI methods like contextual inquiry, prototyping, iterative design, and usability testing are recommended to develop systems with high usability.
Human computer interaction -Design and software processN.Jagadish Kumar
The document discusses the process of interactive design for human-computer interaction (HCI). It begins by defining design as achieving goals within constraints. It notes that goals for a wireless personal movie player may include young users wanting to watch and share movies on the go, while constraints could be withstanding rain or using existing video standards. The core of HCI design involves understanding users and technology through requirements analysis, prototyping and evaluating designs through iterations to achieve the best possible design within time and budget constraints. The process aims to incorporate user research and usability from the beginning of design through implementation.
This document discusses model-based interface development (MBID) and intelligent user interfaces. It provides an overview of MBID, describing the benefits as reducing gaps between requirements and implementation, coordinating stakeholder involvement, and producing well-structured systems. It also discusses UI models including task, abstract, concrete and final models. Several use cases are presented to illustrate MBID for applications like a car rental system, digital home, and an interactive music sheet using head gestures. Requirements for MBID tools and research gaps are also summarized.
Human Computer Interaction (HCI) is the study of how humans interact with computers and how to design interfaces so that users can interact with systems effectively, efficiently and with satisfaction. HCI aims to make computers more usable by understanding users and designing appropriate input/output devices and interaction styles. The goals of HCI include improving safety, utility, effectiveness and efficiency of computer systems to benefit both users and organizations.
The document discusses human-computer interaction (HCI). It provides an overview of HCI as a discipline concerned with designing interactive computing systems for human use. It also mentions the Association for Computing Machinery's Special Interest Group on Computer-Human Interaction. The document then lists some HCI resources and introduces the main focus of HCI as user interface design. It discusses who typically builds interfaces and why studying user interfaces is important.
This document discusses human-computer interaction (HCI). It defines HCI as the study of how humans interact with computer systems. The history and evolution of HCI is covered, from its origins in the 1970s-1990s to investigate desktop usability, to the modern fields of user experience (UX) design, human-robot interaction, and human data interaction. Key differences between HCI as a field of study and UX as an application of HCI theory are outlined. Finally, potential career paths for HCI graduates such as user researcher, product designer, and interface engineer are presented.
This document provides an overview of the subject of Human-Computer Interaction (HCI). It discusses the historical evolution of HCI from early computers to modern interfaces. It also covers key concepts like interactive system design, usability engineering, and the relationship between HCI and software engineering. The document outlines several topics that are important to HCI like GUI design, prototyping techniques, and research areas in HCI including ubiquitous computing and embedded systems.
Human Computer Interaction (HCI) is an interdisciplinary field that focuses on the design, evaluation and implementation of interactive computing systems for human use, and the study of major phenomena surrounding them. The goal of HCI is to improve the interaction between users and computers by making computers more user-friendly and responsive to user needs. Key aspects of HCI include usability testing interfaces for effectiveness, efficiency and satisfaction. Emerging areas of HCI research include pervasive/ubiquitous computing which embeds technology in everyday objects and ambient intelligence which aims to make technology invisible to users.
COMP 4026 Lecture4: Processing and Advanced Interface TechnologyMark Billinghurst
Lecture 4 from the 2016 COMP 4026 course on Advanced Human Computer Interaction taught at the University of South Australia. Taught by Mark Billinghurst, and containing material about Processing and various advanced Human Computer Interfaces.
COMP 4026 Advanced HCI lecture 6 on OpenFrameworks and Google's Project Soli. Taught by Mark Billinghurst at the University of South Australia on August 25th 2016.
The document discusses customization and 3D printing from a software product line perspective. The researchers observed the Thingiverse community to see how they interact and collaborate to customize and produce 3D models. They found that while variability concepts are present, there is no constraints modeling and configuration leads to many issues due to huge complexity with 38 parameters across 8 tabs and 10^28 possible configurations. Software product line engineering techniques like variability modeling and implementation could help address challenges of complexity and cognitive effort for non-software developers customizing 3D models, but may not provide clear benefits for small communities in garages. Future work includes automated techniques to better analyze large datasets and help communities manage complexity.
OpenRepGrid – An Open Source Software for the Analysis of Repertory GridsMark Heckmann
Workshop held at the 11th Biennial Conference of the European Personal Construct Association (EPCA), Dublin, Irland, June 2012.
If you have any questions about OpenRepgrid visit the OpenRepGrid Google group under http://groups.google.com/group/openrepgrid
The document discusses model-driven engineering (MDE) and its advantages. It describes a case study where two development teams, one using traditional development and one using model-driven development (MDA), built a simple e-commerce system. The MDA team achieved a 35% increase in productivity compared to the traditional team. Overall, using MDE approaches can yield an average of 26% savings in development time and costs. MDE promotes higher levels of abstraction, automation, and standards-compliance to help manage increasing demands on modern software.
Transferring Software Testing Tools to PracticeTao Xie
ACM SIGSOFT Webinar co-presented by Nikolai Tillmann (Microsoft), Judith Bishop (Microsoft Research), Pratap Lakshman (Microsoft), Tao Xie (University of Illinois at Urbana-Champaign) http://www.sigsoft.org/resources/webinars.html
MateriApps LIVE! is a virtual machine containing over 270 materials science applications and tools. It can be run on Windows, Mac, or Linux computers to provide a full computational materials science environment without installation. Key features include pre-installed applications for DFT, quantum chemistry, molecular dynamics, and more. It aims to help researchers easily access and use materials simulation software through a centralized portal.
MateriApps LIVE! is a virtual machine image containing over 280 materials science applications and tools. It can be run on Windows, Mac, or Linux computers without installation through VirtualBox. The document provides instructions on downloading MateriApps LIVE!, setting up VirtualBox, importing the virtual machine image, and logging in to begin using the pre-installed materials simulation software. Tips are also included on file sharing, changing display settings, and using commands within the virtual machine.
Here are some potential future interactions and interactivities we could see based on movies, games, or dreams:
- Fully immersive virtual reality worlds we can enter and interact with like in movies like The Matrix or Ready Player One.
- Advanced AI assistants that understand natural language and context like Samantha in Her or the AI helper Clara in the Black Mirror episode "USS Callister."
- Brain-computer interfaces that allow us to control devices and digital worlds with our thoughts like in sci-fi movies where people pilot giant robots or mechs with their minds.
- Augmented reality overlays that blend digital information and interfaces seamlessly into the real world as seen in movies like Iron Man or games like
MateriApps LIVE! is a virtual machine containing over 270 materials science applications and tools that can be run without installation. It aims to promote open source software in computational materials science by forming an online community. Key features include pre-installed applications that can be used for simulations, tutorials, and hands-on sessions. The document provides instructions for setting up MateriApps LIVE! in VirtualBox, sharing files, and accessing resources and applications within the virtual machine.
This guide will help you get started with Innoslate, the full lifecycle systems engineering tool. It will take you through developing your requirements, creating model, simulating your models, and keeping traceability through the entire project.
This document discusses research into integrating software design and space design. The researcher is working on interaction design at mobile, ubiquitous, and urban computing scales. Key projects include CityCompiler, an environment for developing spatial interactive systems, and EnhancedDesk/Table/Movie, which use finger or face tracking to interact with virtual objects over real spaces like desks or walls. The goal is to integrate information systems and software design with physical space design using approaches like model-view-controller frameworks.
C# is an object-oriented programming language developed by Microsoft. The document discusses C# fundamentals including object-oriented programming concepts like classes, objects, encapsulation, inheritance, and polymorphism. It also covers creating a basic "Hello World" C# console application in Visual Studio and debugging and running applications using the Visual Studio integrated development environment.
This document introduces a workshop about the Visual Media Service provided by the ARIADNEplus project. It provides information about the tools offered by the Visual Media Service and invites participants to provide feedback. The workshop will introduce the service and its features like 3D modeling, relightable images, and high resolution images. Participants are asked to comment on useful features and potential improvements.
Coding Like the Wind - Tips and Tricks for the Microsoft Visual Studio 2012 C...Rainer Stropek
Microsoft Visual Studio 2012 contains a bunch of productivity features for C# developers. Rainer Stropek, MVP for Windows Azure, summarizes his top tips for the new VS2012 C# IDE in this presentation
Game Design 2 (2013): Lecture 5 - Game UI PrototypingDavid Farrell
1) Wireframes are visual representations of interfaces used to communicate structure, content, hierarchy, functionality, and behavior to help formalize and test interface design ideas.
2) Paper prototyping allows designers to create inexpensive mockups of interfaces to identify problems and test usability by modeling different interface states that can be handed to users.
3) Usability testing with paper prototypes involves presenting users with paper "screens" and having them perform tasks while designers observe, take notes, and identify required changes based on user feedback and confusion points.
ML in the Browser: Interactive Experiences with Tensorflow.jsC4Media
This document discusses machine learning in the browser using Tensorflow.js. It begins with an introduction and overview of Tensorflow.js, including how it can be used for both authoring models and importing pre-trained models for inference. Examples are provided of using the Ops API to fit a polynomial function and the Layers API to build and train an autoencoder in the browser. Challenges of developing machine learning applications in the browser are also discussed.
This document discusses user experience (UX) in the context of Xtext and diagram editors. It outlines some of the key ingredients of good UX, like usability and consistency. When using diagram frameworks with Xtext, quirks can arise which impact the UX. However, by taking control over UX with tools like FXDiagram, these quirks can be avoided and the user experience improved. The document promotes UX as important for why users like products and advocates taking back control over UX.
Doug McCune - Using Open Source Flex and ActionScript ProjectsDoug McCune
The document summarizes Doug McCune's presentation on riding coattails to the top using open source Flex/ActionScript projects. It discusses finding popular open source projects on sites like Google Code and RIAForge, highlights some hot projects in areas like computer vision, sound, and mapping, and provides demos of projects like Adobe's Open Source Media Framework and the Axiis data visualization framework. It also addresses challenges of staying up to date in this rapidly evolving space.
The document discusses innovative tools for mobile testing including Sikuli for user behavior testing, MonkeyRunner for interacting with device SDKs, ImageMagick for image processing, and MOET for test design patterns. It provides an overview of each tool, how they can be customized for mobile, and demoed automating an address book app on Android and iOS using these open source tools.
This document provides an overview of smart learning environments (SLEs) and discusses key concepts around designing SLEs that promote equity, diversity, and inclusion (EDI). SLEs are physical learning spaces enhanced with digital technologies like sensors and devices. The document outlines several models for SLEs, including centralized and distributed models, and directions for research to focus more on learner experience. It also discusses applying EDI concepts to the design of AI interfaces for SLEs and how AI can be used to create personalized, accessible, and culturally relevant learning experiences. The document proposes activities for groups to discuss scenarios for implementing smart learning environments that address EDI challenges and propose solutions. It concludes by outlining principles for the design of smart classrooms and
This document provides an overview of intelligent user interfaces and interface agents. It discusses agent models and characteristics of agents in complex systems. Environment properties and task environments in AI that affect agent decision making are described. The document also covers intelligent agent models and examples. It discusses how interface agents learn and perceive their environment, including through machine learning algorithms. Challenges of using reinforcement learning for interface agents are also outlined.
ICS2208 Lecture3 2023-2024 - Model Based User InterfacesVanessa Camilleri
Model-based user interface (MBUI) development uses models to capture world knowledge about users, tasks, and systems to develop user interfaces. These models include user models, task models, and system models. MBUIs have benefits like independence, rapid development, flexibility, and automation compared to traditional manual coding approaches. Challenges include complexity, limitations of automatic generation, and integrating adaptation. Example frameworks for MBUI development include Cameleon Reference Framework and MARIA. The future of MBUIs may integrate machine learning techniques like predictive user modeling and natural language processing to develop more adaptive and user-centered intelligent interfaces.
This document provides an overview of intelligent user interfaces and user interface design. It discusses key topics such as:
- User interface design models including design models, user models, mental models, and implementation models.
- The user interface design process which includes interface task analysis, design, construction, and validation.
- User interface design evaluation which is an iterative process of building prototypes, getting user feedback, and making modifications to improve the design.
- User-centric characteristics of smart environments which should be embedded, context-aware, personalized, adaptive, anticipatory, unobtrusive, and non-invasive.
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Group Presentation 2 Economics.Ariana Buscigliopptx
ICS3211 Lecture 08 2020
1. ICS3211 - Intelligent
Interfaces II
Combining design with technology for effective human-
computer interaction
Week 8
Department of AI,
University of Malta,
20201
2. Prototyping & Evaluation
Design I
Week 8 overview:
• Using Processing - designing visual interfaces
• The Interaction Design Process
• Evaluation Paradigms
• Planning an Evaluation
• Designing Usability Tests
2
3. Learning Outcomes
At the end of this session you should be able to:
• Explore programming for visual design prototyping;
• Draw inferences about designing for different interfaces;
• Compare and contrast the different interfaces for use on the
same application/game;
• List the research issues/gaps in the design for AR/VR
applications;
• Describe some of the current research projects in AR/VR.
3
4. Experience Prototyping
The experience of evensimple artifacts does not exist in
a vacuumbut, rather, in dynamic relationship with other
people, places andobjects.
Additionally, the quality of people’s experience changes
over time asit is influenced byvariations in these
multiple contextual factors.
4
5. Cover
Download
Exhibition
» ownload Processing
» Play With Examples
» Browse Tutorials
» xhibition
Reference
Libraries
Tools
Environment
Tutorials
Examples
Books
overview
People
Foun dation
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»Forum
»GitHub
»Issues
>•Wild
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>•Twitter
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Processing is a program.ming language, development environment
and online community. Since 2001, Processing has promoted
software literacy within the visual arts and visual literacy within
technology. Initially created to serve as a software sketchbook and
to teach computer program.ming fundamentals within a visual
context, Processing evolved into a development tool for
professionals. Today, there are tens of thousands of students,
artists, designers, researchers, and hobbyists who use Processing
for learning, prototyping, and production.
,. Free to download and open source
,. Interactive programs with 2D,3DorPDFoutput
,. OpenGLintegration for accelerated3D
,. For GNU/Linux, Mac OSX andWindows
,. over 100 libraries extend the core software
,.Well docum ented,with many books available
Keyflies
by MilesPeyton
I
: p
!
Petting Zoo
byMinimaforms
Fragmented Memory
by PhillipSteams
5
7. Processing - Starting Out
• https://processing.org/tutorials/gettingstarted/
• Open Source
• Interactive programs with 2D, 3D or PDF output
• OpenGL integration for accelerated 2D and 3D
• For GNU/Linux, Mac OS X, and Windows
• Over 100 libraries extend the core software
7
8. Basic Parts Of A Sketch
/* Notes comment */!
//set up global variables!
float moveX = 50;!
!
//Initialize the Sketch!
(){!void setup
}!
!
//draw every frame!
void draw(){!
}!
8
9. Sample Drawing
int m = 0;!
float s =
0;!
!
void setup(){!
size(512,512);!
background(255);!
}!
!
void draw (){!
fill(255,0,0);
!
ellipse(mouseX,mouseY,s,s);!
}!
!
void mouseMoved(){!
s = 40 + 20*sin(++m/10.0f);!
}!
9
10. Drawing
• draw() getscalled as fast as possible, unlessa frameRate is specified
• stroke() setscolor of drawing outline
• fill() setsinside color of drawing
• mousePressedis true if mouseis down
• mouseX, mouseY- mouseposition
!void draw() { !
!stroke(255); !
!if(mousePressed) {!
!line(mouseX, mouseY, pmouseX, pmouseY);!
!}!
!
!
!}!
10
11. Processing And Drawing
• BasicShapes
rect(x, y, width, height)!
ellipse(x, y, width, height)!
line(x1, y1, x2, y2), line(x1,y1, x2, y2, z1, z2)!
• Filling shapes- fill( )
fill(int gray), fill(color color), fill(color color, int
alpha)!
• Curve
• Draws curved lines
• Vertex
• Creates shapes (beginShape,endShape)
11
14. Class And Objects
• see http://processing.org/learning/objects/
• Object
• grouping of multiple related properties and
functions
• Objects are defined byObject classes
• EgCarobject
• Data
• colour, location,speed
• Functions
• drive(),draw()
14
18. Class Usage
// Step 1. Declare an object.!
Car myCar;!
!
void setup() { !
// Step 2. Initialize object.!
myCar = new Car();
!
!}
!
on the object. !
void draw() { !
background(255); !
// Step 3. Call methods
myCar.drive(); !
myCar.display(); !
}!
18
19. Constructing Objects
• OneCar
Car myCar= new Car(); !
• TwoCars
!
!
!// Creating
!Car myCar1
!Car myCar2
two car objects
= new
= new
Car();
Car(); !
• One car with initial
values
Car myCar = new Car(color(255,0,0),0,100,2); !
19
29. When toevaluate?
• Once the product has been developed
• pros : rapid development, small evaluation cost
• cons : rectifying problems
• During design and development
• pros : find and rectify problems early
• cons : higher evaluation cost, longer development
design implementation
evaluation
redesign &
reimplementation
design implementation
29
31. Quick and dirty
• ‘quick & dirty’ evaluation describes the
common practice in which designers informally
get feedback from users or consultants to
confirm that their ideas are in-line with users’
needs and are liked.
• Quick & dirty evaluations are done any time.
• The emphasis is on fast input to the design
process rather than carefully documented
findings.
32. Usability testing
• Usability testing involves recording typical users’
performance on typical tasks in controlled settings.
Field observations may also be used.
• As the users perform these tasks they are watched &
recorded on video & their key presses are logged.
• This data is used to calculate performance times,
identify errors & help explain why the users did what
they did.
• User satisfaction questionnaires & interviews are
used to elicit users’ opinions.
33. Usability Engineering
• Term coined by staff at Digital Equipment Corp.
around 1986
• Concerned with:
– Techniques for planning, achieving and verifying objectives for
system usability
– Measurable goals must be defined early
– Goals must be assessed repeatedly
• Note verification above
• Definition by Christine Faulkner (2000):
– “UE is an approach to the development of software and
systems which involves user participation from the outset and
guarantees the usefulness of the product through the use of a
usability specification and metrics.”
34. Field studies
• Field studies are done in natural settings
• The aim is to understand what users do naturally
and how technology impacts them.
• In product design field studies can be used to:
- identify opportunities for new technology
- determine design requirements
- decide how best to introduce new technology
- evaluate technology in use.
35. Predictive evaluation
• Experts apply their knowledge of typical users, often
guided by heuristics, to predict usability problems.
– Heuristic evaluation
– Walkthroughs
• Another approach involves theoretically based
models.
– Predicting time, errors:
– GOMS and Fitts’ Law formula
• A key feature of predictive evaluation is that users
need not be present
• Relatively quick & inexpensive
36. Evaluation approaches andmethods
Method Usability
testing
Field
studies
Predictive
Observing x x
Asking
users
x x
Asking
experts
x x
Testing x
Modeling x
36
38. How to Plan an Evaluation?
• Preece, Roger & Sharp - DECIDE
framework
– captures many important practical issues
– works with all categories of study
39. DECIDE:
A framework to guide evaluation
• Determine the goals the evaluation addresses.
• Explore the specific questions to be answered.
• Choose the evaluation paradigm and techniques to
answer the questions.
• Identify the practical issues.
• Decide how to deal with the ethical issues.
• Evaluate, interpret and present the data.
40. Determine the goals
• What are the high-level goals of the evaluation?
• Who wants it and why?
The goals influence the paradigm for the study
• Some examples of goals:
− Identify the best metaphor on which to base the design.
− Check to ensure that the final interface is consistent.
− Investigate how technology affects working practices.
− Improve the usability of an existing product .
41. Explore the questions
• All evaluations need goals & questions to guide them
so time is not wasted on ill-defined studies.
• For example, the goal of finding out why many
customers prefer to purchase paper airline tickets
rather than e-tickets can be broken down into sub-
questions:
- What are customers’ attitudes to these new tickets?
- Are they concerned about security?
- Is the interface for obtaining them poor?
• What questions might you ask about the design of a cell
phone?
42. Choose the evaluation paradigm &
techniques
• The evaluation paradigm strongly
influences the techniques used, how data
is analyzed and presented.
• E.g. field studies do not involve testing or
modeling
43. Identify practical issues
For example, how to:
• select users
• stay on budget
• staying on schedule
• find evaluators
• select equipment
44. Decide on ethical issues
• Develop an informed consent form
– See example(s) in text, Web site, etc.
• Participants have a right to:
- know the goals of the study
- what will happen to the findings
- privacy of personal information
- not to be quoted without their agreement
- leave when they wish
- be treated politely
• “Informed consent” agreement
45. Evaluate, interpret & present data
• How data is analyzed & presented depends on the
paradigm and techniques used.
• The following also need to be considered:
- Reliability: can the study be replicated?
- Validity: is it measuring what you thought?
- Biases: is the process creating biases?
- Scope: can the findings be generalized?
- Ecological validity: is the environment of the
study influencing it - e.g. Hawthorn effect
46. Developing Usability Tests
• Goals and Usability Concerns
• Observations from Tasks
• Triangulation
• Test Plan and Scenarios
• Questionnaires and Interviews
47. Observing and Recording Tests
• Notes
• Audio Recording
• Still photos
• Video
• Event Logging Software
48. Conducting Usability Tests
• Prepare test room
• Pre-test Questionnaire
• Brief user (explain UI, scenario, etc.)
• Post-test Questionnaire
• Thank user and organise findings
49. Pilot studies
• A small trial run of the main study.
• The aim is to make sure your plan is viable.
• Pilot studies check:
- that you can conduct the procedure
- that interview scripts, questionnaires,
experiments, etc. work appropriately
• It’s worth doing several to iron out problems before
doing the main study.
• Ask colleagues if you can’t spare real users.
50. Key points
• An evaluation paradigm is an approach that is influenced by
particular theories and philosophies.
• Five categories of techniques were identified: observing
users, asking users, asking experts, user testing, modeling
users.
• The DECIDE framework has six parts:
- Determine the overall goals
- Explore the questions that satisfy the goals
- Choose the paradigm and techniques
- Identify the practical issues
- Decide on the ethical issues
- Evaluate ways to analyze & present data
• Do a pilot study