Emotions in Information Systems Research – A Five Component View

Many scientific viewpoints and research streams occurred over the last decades with the objective to create structure and common understanding on a more abstract level how emotions affect human behavior (e.g. constructivist or appraisal theories). As a consequence, Information Systems (IS) researchers have adopted diverse mixed up theoretical foundations about emotions. This brings the need for a more structured way to study emotions in the IS field. Thus, within this research a five component view on emotions is developed, based on appraisal theories of emotions and the 3-emotions´ nomological network by Gregor et al. (2014). The new view provides better guidance for IS researchers studying the occurrence or effect of human emotions in terms of a better understanding of the emotion concept and an easier transfer of theoretical considerations from psychology to the IS field, especially the adaptation of emotional constructs and their subjective and objective measurement

EMPATH: A Neural Network that Categorizes Facial Expressions

There are two competing theories of facial expression recognition. Some researchers have suggested that it is an example of "categorical perception." In this view, expression categories are considered to be discrete entities with sharp boundaries, and discrimination of nearby pairs of expressive faces is enhanced near those boundaries. Other researchers, however, suggest that facial expression perception is more graded and that facial expressions are best thought of as points in a continuous, low-dimensional space, where, for instance, "surprise" expressions lie between "happiness" and "fear" expressions due to their perceptual similarity. In this article, we show that a simple yet biologically plausible neural network model, trained to classify facial expressions into six basic emotions, predicts data used to support both of these theories. Without any parameter tuning, the model matches a variety of psychological data on categorization, similarity, reaction times, discrimination, and recognition difficulty, both qualitatively and quantitatively. We thus explain many of the seemingly complex psychological phenomena related to facial expression perception as natural consequences of the tasks' implementations in the brain

The Perceptions of Teacher Evaluation by Teachers and Campus Administrators in a Suburban Texas District

The purpose of this research is to examine the perceptions of campus administrators and teachers of the new Texas Teacher Evaluation and Support System (T-TESS) in a suburban Texas school district. Historically, teacher evaluation systems have failed to reach the intended outcome of serving as a tool to improve teaching practices. When campus administrators and teachers perceive teacher evaluation as primarily a tool to document poor performers, the growth aspect of the evaluation process is not maximized. This research seeks to identify the perceptions of both campus administrators and teachers on the evaluation system. District leaders will be able to determine if the perceptions of one or both groups is aligned with the intended outcomes of the evaluation process

Using Noninvasive Brain Measurement to Explore the Psychological Effects of Computer Malfunctions on Users during Human-Computer Interactions

In today’s technologically driven world, there is a need to better understand the ways that common computer malfunctions affect computer users. These malfunctions may have measurable influences on computer user’s cognitive, emotional, and behavioral responses. An experiment was conducted where participants conducted a series of web search tasks while wearing functional nearinfrared spectroscopy (fNIRS) and galvanic skin response sensors. Two computer malfunctions were introduced during the sessions which had the potential to influence correlates of user trust and suspicion. Surveys were given after each session to measure user’s perceived emotional state, cognitive load, and perceived trust. Results suggest that fNIRS can be used to measure the different cognitive and emotional responses associated with computer malfunctions. These cognitive and emotional changes were correlated with users’ self-report levels of suspicion and trust, and they in turn suggest future work that further explores the capability of fNIRS for the measurement of user experience during human-computer interactions

Anticipating user eXperience with a desired product: The AUX framework

Positive user experience (UX) has become a key factor in designing interactive products. It acts as a differentiator which can determine a product’s success on the mature market. However, current UX frameworks and methods do not fully support the early stages of product design and development. During these phases, assessment of UX is challenging as no actual user-product interaction can be tested. This qualitative study investigated anticipated user experience (AUX) to address this problem. Using the co-discovery method, participants were asked to imagine a desired product, anticipate experiences with it, and discuss their views with another participant. Fourteen sub-categories emerged from the data, and relationships among them were defined through co-occurrence analysis. These data formed the basis of the AUX framework which consists of two networks which elucidate 1) how users imagine a desired product and 2) how they anticipate positive experiences with that product. Through this AUX framework, important factors in the process of imagining future products and experiences were learnt, including the way in which these factors interrelate. Focusing on and exploring each component of the two networks in the framework will allow designers to obtain a deeper understanding of the required pragmatic and hedonic qualities of product, intended uses of product, user characteristics, potential contexts of experience, and anticipated emotions embedded within the experience. This understanding, in turn, will help designers to better foresee users’ underlying needs and to focus on the most important aspects of their positive experience. Therefore, the use of the AUX framework in the early stages of product development will contribute to the design for pleasurable UX

Mapping a multi-sensory identity territory at the early design stage

This article presents a kansei design methodology. It is placed at the very beginning of the design process and aims to influence the following steps in order to improve the user's understanding and experiencing of the designed product. The experimentation combines in a subtle way the design thinking approach of learning by doing and the kansei engineering quantitative approach. The research presented is based on the results of a previous study that defined the semantic and emotional scope of future hybrid cars for European using visual stimuli. This kansei design methodology creates and assesses multi-sensory atmospheres is order to provide tangible direction composed of vision, touch, hearing and smell stimuli. From the cognitive and affective responses of the 42 participants we were able to detail 3 directions for future cars interiors that aim to enrich the styling design briefs and to influence the design strategies such as the management of the different grades. The research presented here was supported by the Kansei Design department from Toyota Motor Europe (TME-KD). This collaboration also brought an industrial context to it.SUPPORTED BY TOYOTA EUROP