Human Factors As A Parameter For Improving Interface Usability And User Satisfaction

The endeavour to optimize HCI should integrate a wide array of user characteristics that have an effect throughout users’ interactions with a system. Human factors such as cognitive traits and current state, from a psychological point of view, are undoubtedly significant in the shaping of the perceived and objective quality of interactions with a system. The research that is presented in this paper focuses on identifying human factors that relate to users’ performance in Web applications that involve information processing, and a framework of personalization rules that are expected to increase users’ performance is depicted. The empirical results that are presented are derived from environments both learning and commercial; in the case of e-learning personalization was beneficial, while the interaction with a commercial site needs to be further investigated due to the implicit character of information processing in the Web

ADAPTING mLEARNING ENVIRONMENTS ON LEARNERS’ COGNITIVE STYLES AND VISUAL WORKING MEMORY SPAN

The research that is described in this paper focuses on incorporating theories of individual differences in information processing within the context of mobile hypertext and hypermedia interactive environments. Based on previous findings of the authors in the field of adaptive eLearning, the main purpose was to enhance the quality of information presentation and users’ interactions in the Web by matching their specific needs and preferences. Our more recent experiments, explore how to improve learning process by adapting course content presentation to student cognitive styles and capabilities in mobile environments such as PDA phones. A framework has been developed to comprehensively model student’s cognitive styles and visual working memory span and present the appropriate subject matter, including the content, format, guidance, etc. to suit an individual student by increasing efficiency during interaction. Main aim is to overcome constraints like small screen size and processing/memory capabilities for navigation enhancements that limit the presentation and guidance of the material. An increase on users’ satisfaction as well as more efficient information processing (both in terms of accuracy and task completion time), has been observed in the personalized condition than the original one. Consequently, it is supported that human factors may be used in order to enhance the design of mobile hypertext (or hypermedia) environments in a measurable and meaningful way

Proposing a Perceived Expertise Tool in Business Data Analytics

The business data analytics domain exhibits a particularly diversified and demanding field of interaction for the end-users. It entails complex tasks and actions expressed by multidimensional data visualization and exploration contents that users with different business roles, skills and experiences need to understand and make decisions so to meet their goals. Many times this engagement is proven to be overwhelming for professionals, highlighting the need for adaptive and personalized solutions that would consider their level of expertise towards an enhanced user experience and quality of outcomes. However, measuring adequately the perceived expertise of individuals using standardized means is still an open challenge in the community. As most of the current approaches employ participatory research design practices that are time consuming, costly, difficult to replicate or to produce comparable, unbiased, results for informed interpretations. Hence, this paper proposes a systematic alternative for capturing expertise through a Perceived Expertise Tool (PET) that is devised based on grounded theoretical perspectives and psychometric properties. Preliminary evaluation with 54 professionals in the data analytics domain showed the accepted internal consistency and validity of PET as well as its significant correlation with other affiliated theoretical and domain-specific concepts. Such findings may suggest a good basis for the standardized modeling of users’ perceived expertise that could lead to effective adaptation and personalization

The Role of Emotions in the Design of Personalized Educational Systems

Research on modelling affect and on interfaces adaptation based on affective factors has matured considerably over the past several years, so that designers of educational products are now considering the inclusion of components that take affect into account. Emotions are considered to play a central role in guiding and regulating behaviour by modulating numerous cognitive and physiological activities. This paper1 introduces a new model in the field of adaptive hypermedia, which integrates cognitive and emotional parameters and attempts to apply them on a web-based learning environment. Our purpose is to improve learning performance and, most importantly, to personalize web-content to users’ needs and preferences, eradicating known difficulties that occur in traditional approaches. The specific article emphasizes on the emotional aspect of our model, since it presents results of our efforts to measure and include emotional processing parameters, by constructing a theory that addresses emotion and is feasible in Web-learning environments

EVALUATING THE SIGNIFICANCE OF AFFECTIVE PARAMETERS IN USER LEARNING BEHAVIOR THROUGH DECISION MAKING AND PROBLEM SOLVING PROCESSES

Research on modeling affect has matured considerably over the past several years, so that designers of interfaces and educational products are now considering the inclusion of components that take affect into account. Emotions are considered to play a central role in guiding and regulating behavior by modulating numerous cognitive and physiological activities. This paper introduces a model which integrates personality and emotional parameters and attempts to apply them on web-based appraisal systems. Our purpose is to improve user performance in various tasks and, most importantly, to investigate users’ affective needs and preferences. We present results of our efforts to measure and include emotional processing parameters, by constructing a theory that addresses emotion and personality and is feasible in Web-based learning environments

The role of emotions in the design of personalized educational systems

Research on modelling affect and on interfaces adaptation based on affective factors has matured considerably over the past several years, so that designers of educational products are now considering the inclusion of components that take affect into account. Emotions are considered to play a central role in guiding and regulating behaviour by modulating numerous cognitive and physiological activities. This papers introduces a new model in the field of adaptive hypermedia, which integrates cognitive and emotional parameters and attempts to apply them on a web-based learning environment. Our purpose is to improve learning performance and most importantly, to personalize web-content to users’ needs and preferences, eradicating known difficulties that occur in traditional approaches. The specific article emphasizes on the emotional aspect of our model, since it presents results of our efforts to measure and include emotional processing parameters, by constructing a theory that addresses emotion and is feasible in Web-learning environments

The Role of Affect in Personalized Learning

Research on modelling affect and on interfaces adaptation based on affective factors has matured considerably over the past several years. Emotions are considered to play a central role in guiding and regulating learning, performance, behaviour and decision making, by modulating numerous cognitive and physiological activities. The basic objective of this paper is to analyse the way that individuals process their emotions and how they interact with other elements of their information-processing system. It will further underpin their significance taking into consideration the notion of emotion regulation, based on which users expect to receive the most apt personalized provider’s content. Special emphasis will be given in dispositional trait affect that serves as an overall estimation of an individual’s affective state and statistical evidence will be provided which suggest that affect can have both informational and processing effects on cognition