Learning an Interactive Segmentation System

Many successful applications of computer vision to image or video manipulation are interactive by nature. However, parameters of such systems are often trained neglecting the user. Traditionally, interactive systems have been treated in the same manner as their fully automatic counterparts. Their performance is evaluated by computing the accuracy of their solutions under some fixed set of user interactions. This paper proposes a new evaluation and learning method which brings the user in the loop. It is based on the use of an active robot user - a simulated model of a human user. We show how this approach can be used to evaluate and learn parameters of state-of-the-art interactive segmentation systems. We also show how simulated user models can be integrated into the popular max-margin method for parameter learning and propose an algorithm to solve the resulting optimisation problem.Comment: 11 pages, 7 figures, 4 table

Evaluating interactive systems from an emotional perspective

In this paper, we introduce a model that aims to provide guidelines that will strengthen the evaluation of interactive systems by assisting in the identification and analysis of emotions evoked by users during system usage. We briefly discuss related projects that have included emotions in the evaluation of interactive systems. The research presented here is a preliminary work towards the inclusion of emotions during the evaluation of interactive systems. Our model is presented including details of each of its phases. We discussed preliminary results of the application of the model to evaluating a Virtual Learning Environment. Our approach comprises four major phases: Selection of relevant emotions; analysis of relationships between emotions and interactive systems; selection of detection mechanisms; and application of evaluation methods

Genisa: A web-based interactive learning environment for teaching simulation modelling

Intelligent Tutoring Systems (ITS) provide students with adaptive instruction and can facilitate the acquisition of problem solving skills in an interactive environment. This paper discusses the role of pedagogical strategies that have been implemented to facilitate the development of simulation modelling knowledge. The learning environment integrates case-based reasoning with interactive tools to guide tutorial remediation. The evaluation of the system shows that the model for pedagogical activities is a useful method for providing efficient simulation modelling instruction

Heuristic Evaluation of an Institutional E-learning System: A Nigerian Case.

Many African academic institutions have adopted the use of elearning systems, since they enable students to learn at their own pace, time, and without restriction to the classroom. However, evidence of usability evaluation of e-learning systems in Africa is mostly lacking in the literature. This paper reports the experimental heuristic evaluation of the e-learning system of a Nigerian University. The objective is to demonstrate the application of expertbased usability evaluation techniques such as Heuristic evaluation for assessing the attributes of existing e-learning systems. The study revealed that while the e-learning system has strong credentials in terms of support for Web 2.0 activities, good learning content and boasts of useful e-learning features, improvements are necessary in other areas such as interactive learning, assessment and feedback, and quality of learning content. The study adds to the body of extant knowledge in the area of usability evaluation of e-learning systems in African institution

Designing and evaluating the usability of a machine learning API for rapid prototyping music technology

To better support creative software developers and music technologists' needs, and to empower them as machine learning users and innovators, the usability of and developer experience with machine learning tools must be considered and better understood. We review background research on the design and evaluation of application programming interfaces (APIs), with a focus on the domain of machine learning for music technology software development. We present the design rationale for the RAPID-MIX API, an easy-to-use API for rapid prototyping with interactive machine learning, and a usability evaluation study with software developers of music technology. A cognitive dimensions questionnaire was designed and delivered to a group of 12 participants who used the RAPID-MIX API in their software projects, including people who developed systems for personal use and professionals developing software products for music and creative technology companies. The results from the questionnaire indicate that participants found the RAPID-MIX API a machine learning API which is easy to learn and use, fun, and good for rapid prototyping with interactive machine learning. Based on these findings, we present an analysis and characterization of the RAPID-MIX API based on the cognitive dimensions framework, and discuss its design trade-offs and usability issues. We use these insights and our design experience to provide design recommendations for ML APIs for rapid prototyping of music technology. We conclude with a summary of the main insights, a discussion of the merits and challenges of the application of the CDs framework to the evaluation of machine learning APIs, and directions to future work which our research deems valuable

Empirical evaluation of educational interactive systems

[EN ]Educational software systems are usually highly interactive systems that needs to be evaluated from two different perspectives, first as interactive software, mainly using usability and accessibility approaches, and second as an educational product that needs to be evaluated from its learning impact. The empirical evaluation methods may be quantitative, with a more deductive reasoning, or qualitative, with a more inductive reasoning, oriented, however mixed approaches have been used extensively because they combine the both main methods with a more pragmatic knowledge focusing on knowing the consequences or solving problems. The empirical evaluation of interactive educational software due to its own characteristics requires a mixed approach typically. This special issue is devoted to identify, share and valorise best practices and experiences, with a very solid modelling background, that are focused on the empirical evaluation of educational interactive systems with a special emphasis on mixed quantitative and qualitative approaches

Building an interactive simulator on a cloud computing platform to enhance students' understanding of computer systems

Cloud computing technologies have been widely adopted to improve the competitiveness and efficiency of core operations in many enterprises through additional computational resources and/or storage as provided on the underlying cloud platforms. Yet there are relatively few studies on how cloud computing may enhance students' understanding of a specific subject in e-learning systems. In a research project awarded by the Microsoft Research Asia, we successfully developed an interactive simulator aimed to enhance the students' understanding of essential concepts related to computer systems through live animations on a cloud computing platform. Essentially, we propose to integrate the latest technologies of cloud computing and learning objects into an efficient, flexible and interactive simulator to deliver powerful computing services for dynamic simulations of various computer systems specified as 'reactive' models of learning objects on the cloud storage. More importantly, through adopting the IEEE learning object metadata standard to represent each key concept/component in different computer systems, our proposed simulator can readily facilitate the sharing and reuse of relevant concepts for future e-learning applications. The system design and prototype implementation of our cloud-based interactive simulator is carefully considered with a thorough evaluation plan to investigate on how learners may benefit from our interactive simulator in various ways. And there are many directions for future extensions. © 2013 IEEE.published_or_final_versio

The use of Virtual Reality in Enhancing Interdisciplinary Research and Education

Virtual Reality (VR) is increasingly being recognized for its educational potential and as an effective way to convey new knowledge to people, it supports interactive and collaborative activities. Affordable VR powered by mobile technologies is opening a new world of opportunities that can transform the ways in which we learn and engage with others. This paper reports our study regarding the application of VR in stimulating interdisciplinary communication. It investigates the promises of VR in interdisciplinary education and research. The main contributions of this study are (i) literature review of theories of learning underlying the justification of the use of VR systems in education, (ii) taxonomy of the various types and implementations of VR systems and their application in supporting education and research (iii) evaluation of educational applications of VR from a broad range of disciplines, (iv) investigation of how the learning process and learning outcomes are affected by VR systems, and (v) comparative analysis of VR and traditional methods of teaching in terms of quality of learning. This study seeks to inspire and inform interdisciplinary researchers and learners about the ways in which VR might support them and also VR software developers to push the limits of their craft.Comment: 6 Page