Ситуативно-інформаційне моделювання у англомовному дискурсі програмного забезпечення

В статье очерчены новые перспективы лингвистического моделирования, а именно ситуативно-информационное моделирование для обеспечения более эффективного взаимодействия человека и компьютера. Коммуникативные и когнитивные особенности ситуативно-информационного моделирования исследуются на материале англоязычного дискурса программного обеспечения. Ситуативно-информационное моделирование рассматривается как особый вид коммуникативной стратегии, призванной обеспечить эффективное взаимодействие человека и машины.The article represents a new perspective of linguistic modeling, i.e. sutuation-information modeling, and its implementation in human-computer interaction. Various aspects of communicative and cognitive modeling are represented on the material of the English software discourse. Sutuation-information modeling is regarded as a specific communicative strategy used to facilitate effective human-computer speech communication

Human-Computer Interaction in Mobile Context : A Cognitive Resources Perspective

Human-computer interaction is currently shifting its focus from desktop-based interaction to interaction with "beyond the desktop", which is embedded into everyday activities. In order to support users more elegantly, these mobile, wearable, and ubiquitous computing devices are envisioned to adapt inte lligently to their context. Thus far, however, the mobile use contexts per se have received attention, as most research has been technology-driven. Drawing from cognitive psychology, user modeling in human-computer interaction, and ethnomethodology, a framework is put forward here to analyse mobile use situations from the point of view of resource competition. The framework assumes that mobility is inherently multitasking and easily leads to competition for cognitive and other human resources. This "cognitive resource competition" framework is elaborated and associated with the psychological principles of capacity and multitasking. It looks at the typical social, interactional, cognitive, and physical tasks in mobility, relates them to the typical cognitive resources they compete for, and, based on known capacities of cognitive faculties, pinpoints restrictions and resources for action that can emerge in a given mobile situation. It is argued that the approach is useful for identifying the perceptual, attentional, and cognitive capabilities of a user in a mobile situation. The approach has implications for the design and innovation of intelligent, context-sensitive user interfaces and services. Furthermore, a practical method for making human resources visible in a design session is proposed and evaluated

Negative Results in Computer Vision: A Perspective

A negative result is when the outcome of an experiment or a model is not what is expected or when a hypothesis does not hold. Despite being often overlooked in the scientific community, negative results are results and they carry value. While this topic has been extensively discussed in other fields such as social sciences and biosciences, less attention has been paid to it in the computer vision community. The unique characteristics of computer vision, particularly its experimental aspect, call for a special treatment of this matter. In this paper, I will address what makes negative results important, how they should be disseminated and incentivized, and what lessons can be learned from cognitive vision research in this regard. Further, I will discuss issues such as computer vision and human vision interaction, experimental design and statistical hypothesis testing, explanatory versus predictive modeling, performance evaluation, model comparison, as well as computer vision research culture

Improved Teaching of Database Schema Modeling by Visualizing Changes in Levels of Abstraction

Conceptual modeling of databases is a complex cognitive activity, particularly for novice database designers. The current research empirically tests a new pedagogy for this activity. It examines an instructional approach that stresses visualizing gradual transitions between levels of abstraction in different hierarchic levels of a relational database schema. The new approach builds on a four-level TSSL model from the field of human-computer interaction. TSSL, an acronym for the Task, Semantics, Syntax, and Lexical levels, is applied here to describe the levels of conceptual database modeling and to explain how improved instructional design can help minimize extraneous cognitive load during the design of database schemas. We tested the effectiveness of the proposed instructional approach via a controlled experiment carried out on IS students. We divided students into two groups, those exposed to a visual emphasis on the syntax of gradual transitions in a schema structure and those not exposed to it. We then measured performance in terms of errors in students’ solutions while also recording their perceptions and attitudes toward the instructional approach and the activity of database modeling. Our results show that the new approach is an effective tool for teaching database modeling

Field dependence–independence and instructional-design effects on learners’ performance with a computer-modeling tool

Angeli, C., Valanides, N., & Kirschner, P. A. (2009). Field dependence–independence and instructional-design effects on learners’ performance with a computer-modeling tool. Computers in Human Behavior, 25, 1355–1366.The study investigated the extent to which two types of instructional materials and learner field dependence– independence affected learners’ cognitive load, time spent on task, and problem-solving performance in a complex system with a computer-modeling tool. One hundred and one primary student teachers were initially categorized into field dependent, field mixed, and field-independent learners based on their performance on the Hidden Figures Test, and were then randomly assigned to two experimental conditions. One group received a static diagram and a textual description in a split format, and the second group received the same static diagram and textual description in an integrated format. MANOVA revealed that the split-format materials contributed to higher cognitive load, higher time spent on task, and lower problem-solving performance than the integrated-format materials. There was also an interaction effect, only in terms of students’ problem-solving performance, between field dependence– independence and instructional materials, indicating that the facilitating effect of the integrated-format materials was restricted to the field-independent learners. Conclusions are drawn in terms of how the well-documented split-attention effect manifests itself irrespective of students’ field dependence-independence. Implications of the effects of reduced extraneous cognitive load on students’ problem-solving performance are also discussed

Progress towards Automated Human Factors Evaluation

Cao, S. (2015). Progress towards Automated Human Factors Evaluation. 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015) and the Affiliated Conferences, AHFE 2015, 3, 4266–4272. https://doi.org/10.1016/j.promfg.2015.07.414 This work is made available through a CC-BY-NC-ND 4.0 license. The licensor is not represented as endorsing the use made of this work. https://creativecommons.org/licenses/by-nc-nd/4.0/Human factors tests are important components of systems design. Designers need to evaluate users’ performance and workload while using a system and compare different design options to determine the optimal design choice. Currently, human factors evaluation and tests mainly rely on empirical user studies, which add a heavy cost to the design process. In addition, it is difficult to conduct comprehensive user tests at early design stages when no physical interfaces have been implemented. To address these issues, I develop computational human performance modeling techniques that can simulate users’ interaction with machine systems. This method uses a general cognitive architecture to computationally represent human cognitive capabilities and constraints. Task-specific models can be built with the specifications of user knowledge, user strategies, and user group differences. The simulation results include performance measures such as task completion time and error rate as well as workload measures. Completed studies have modeled multitasking scenarios in a wide range of domains, including transportation, healthcare, and human-computer interaction. The success of these studies demonstrated the modeling capabilities of this method. Cognitive-architecture-based models are useful, but building a cognitive model itself can be difficult to learn and master. It usually requires at least medium-level programming skills to understand and use the language and syntaxes that specify the task. For example, to build a model that simulates a driving task, a modeler needs to build a driving simulation environment so that the model can interact with the simulated vehicle. In order to simply this process, I have conducted preliminary programming work that directly connects the mental model to existing task environment simulation programs. The model will be able to directly obtain perceptual information from the task program and send control commands to the task program. With cognitive model-based tools, designers will be able to see the model performing the tasks in real-time and obtain a report of the evaluation. Automated human factors evaluation methods have tremendous value to support systems design and evaluatio

Factors That Enhance Consumer Trust in Human-Computer Interaction: An Examination of Interface Factors and Moderating Influences

The Internet coupled with agent technology presents a unique setting to examine consumer trust. Since the Internet is a relatively new, technically complex environment where human-computer interaction (HCI) is the basic communication modality, there is greater perception of risk facing consumers and hence a greater need for trust. In this dissertation, the notion of consumer trust was revisited and conceptually redefined adopting an integrative perspective. A critical test of trust theory revealed its cognitive (i.e., competence, information credibility), affective (i.e., benevolence), and intentional (i.e., trusting intention) constructs. The theoretical relationships among these trust constructs were confirmed through confirmatory factor analysis and structural equation modeling. The primary purpose of this dissertation was to investigate antecedent and moderating factors affecting consumer trust in HCI. This dissertation focused on interface-based antecedents of trust in the agent-assisted shopping context aiming at discovering potential interface strategies as a means to enhance consumer trust in the computer agent. The effects of certain interface design factors including face human-likeliness, script social presence, information richness, and price increase associated with upgrade recommendation by the computer agent were examined for their usefulness in enhancing the affective and cognitive bases for consumer trust. In addition, the role of individual difference factors and situational factors in moderating the relationship between specific types of computer interfaces and consumer trust perceptions was examined. Two experiments were conducted employing a computer agent, Agent John, which was created using MacroMedia Authorware. The results of the two experiments showed that certain interface factors including face and script could affect the affective trust perception. Information richness did not enhance consumers’ cognitive trust perceptions; instead, the percentage of price increase associated with Agent John’s upgrade recommendation affected individuals’ cognitive trust perceptions. Interestingly, the moderating influence of consumer personality (especially feminine orientation) on trust perceptions was significant. The consequences of enhanced consumer trust included increased conversion behavior, satisfaction and retention, and to a lesser extent, self-disclosure behavior. Finally, theoretical and managerial implications as well as future research directions were discussed

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

Комп’ютерне моделювання когнітивного аспекту обробки природної мови на основі природно-мовної бази знань

У даній роботі розглядається проблема взаємодії «людина-комп’ютер» у форматі дослідження засобів реалізації природно-мовної комунікації у технічних системах, зокрема проблеми розуміння природної мови. Пропонується підхід до вирішення цієї проблеми шляхом моделювання когнітивного аспекту мовленнєвої діяльності людини на основі природно-мовної бази знань. Оцінка моделі проводиться шляхом експериментальної перевірки наявності окремих ключових проявів, пов’язаних з розумінням тексту, в роботі бази знань.This paper deals with human-computer interaction at the level of examination of methods of implementation of natural language communication in technical systems, in particular of natural language understanding. An approach to solving this problem is proposed which is centered around modeling the cognitive aspect of human speech activity on the basis of the natural language knowledge base. The model evaluation is conducted by executing an experimental test of occurrence of certain essential manifestations, linked to the understanding of natural language text, in the operation of knowledge base