On the Mental Workload Assessment of Uplift Mapping Representations in Linked Data

Self-reporting procedures have been largely employed in literature to measure the mental workload experienced by users when executing a specific task. This research proposes the adoption of these mental workload assessment techniques to the task of creating uplift mappings in Linked Data. A user study has been performed to compare the mental workload of “manually” creating such mappings, using a formal mapping language and a text editor, to the use of a visual representation, based on the block metaphor, that generate these mappings. Two subjective mental workload instruments, namely the NASA Task Load Index and the Workload Profile, were applied in this study. Preliminary results show the reliability of these instruments in measuring the perceived mental workload for the task of creating uplift mappings. Results also indicate that participants using the visual representation achieved smaller and more consistent scores of mental workload

Taxonomic models of individual differences: A guide to transdisciplinary approaches

Models and constructs of individual differences are numerous and diverse. But detecting commonalities, differences and interrelations is hindered by the common abstract terms (e.g. ‘personality’, ‘temperament’, ‘traits’) that do not reveal the particular phenomena denoted. This article applies a transdisciplinary paradigm for research on individuals that builds on complexity theory and epistemological complementarity. Its philosophical, metatheoretical and methodological frameworks provide concepts to differentiate various kinds of phenomena (e.g. physiology, behaviour, psyche, language). They are used to scrutinize the field's basic concepts and to elaborate methodological foundations for taxonomizing individual variations in humans and other species. This guide to developing comprehensive and representative models explores the decisions taxonomists must make about which individual variations to include, which to retain and how to model them. Selection and reduction approaches from various disciplines are classified by their underlying rationales, pinpointing possibilities and limitations. Analyses highlight that individuals' complexity cannot be captured by one universal model. Instead, multiple models phenotypically taxonomizing different kinds of variability in different kinds of phenomena are needed to explore their causal and functional interrelations and ontogenetic development that are then modelled in integrative and explanatory taxonomies. This research agenda requires the expertise of many disciplines and is inherently transdisciplinary

Biosignals reflect pair-dynamics in collaborative work : EDA and ECG study of pair-programming in a classroom environment

Collaboration is a complex phenomenon, where intersubjective dynamics can greatly affect the productive outcome. Evaluation of collaboration is thus of great interest, and can potentially help achieve better outcomes and performance. However, quantitative measurement of collaboration is difficult, because much of the interaction occurs in the intersubjective space between collaborators. Manual observation and/or self-reports are subjective, laborious, and have a poor temporal resolution. The problem is compounded in natural settings where task-activity and response-compliance cannot be controlled. Physiological signals provide an objective mean to quantify intersubjective rapport (as synchrony), but require novel methods to support broad deployment outside the lab. We studied 28 student dyads during a self-directed classroom pair-programming exercise. Sympathetic and parasympathetic nervous system activation was measured during task performance using electrodermal activity and electrocardiography. Results suggest that (a) we can isolate cognitive processes (mental workload) from confounding environmental effects, and (b) electrodermal signals show role-specific but correlated affective response profiles. We demonstrate the potential for social physiological compliance to quantify pair-work in natural settings, with no experimental manipulation of participants required. Our objective approach has a high temporal resolution, is scalable, non-intrusive, and robust.Peer reviewe

Spirals of Spirituality: A Qualitative Study Exploring Dynamic Patterns of Spirituality in Turkish Organizations

This paper explores organizational spirituality, uncovers it as spiralling dynamics of both positive and negative potentialities, and proposes how leaders can shape these dynamics to improve the human conditions at the workplace. Based on case study of five Turkish organizations and drawing on the emerging discourse on spirituality in organizations literature, this study provides a deeper understanding of how dynamic patterns of spirituality operate in organizations. Insights from participant observation, organizational data, and semi-structured interviews yield three key themes of organizational spirituality: reflexivity, connectivity, and responsibility. Each of these themes has been found to be connected to upward spirals (inspiration, engagement, and calling) and downward spirals (incivility, silence, and fatigue). The study provides a detailed and holistic account of the individual and organizational processes through which spirituality is enacted both positively and negatively, exploring its dynamic and dualistic nature, as embodied in the fabric of everyday life and culture

Advanced Modeling Methods for Studying Individual Differences and Dynamics in Organizations: Introduction to the Special Issue

It is likely that computer simulations will assume a greater role in the next future to investigate and understand reality (Rand & Rust, 2011). Particularly, agent-based models (ABMs) represent a method of investigation of social phenomena that blend the knowledge of social sciences with the advantages of virtual simulations. Within this context, the development of algorithms able to recreate the reasoning engine of autonomous virtual agents represents one of the most fragile aspects and it is indeed crucial to establish such models on well-supported psychological theoretical frameworks. For this reason, the present work discusses the application case of the theory of planned behavior (TPB; Ajzen, 1991) in the context of agent-based modeling: It is argued that this framework might be helpful more than others to develop a valid representation of human behavior in computer simulations. Accordingly, the current contribution considers issues related with the application of the model proposed by the TPB inside computer simulations and suggests potential solutions with the hope to contribute to shorten the distance between the fields of psychology and computer science

Determining Optimization-Risk Profiles for Individual Decision Makers

Investment funds typically vary with regard to the emphasis that the managers place on acceptable risk and expected returns on investment. This chapter highlight a nonlinear analytic strategy, orbital decomposition (ORBDE) for identifying and extracting patterns of categorical events from time series data. The contributing constructs from symbolic dynamics, chaos, and entropy are described in conjunction with the central ORBDE algorithm. A study in task switching, which can alleviate or induce cognitive fatigue, is used an illustrative example of the basic mode of analysis. The aggregate more of ORBDE allows category codes from multiple variables to be assigned to each event in a time series. An illustrative example of the aggregate mode is presented for risk profile analysis in financial decisions. The results open up many possibilities for studying sequences of decisions made by fund managers and individual investors to determine profiles of risk acceptance, expected returns, and other features of portfolio management