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Incorporating evolutionary adaptions into the cognitive fit model for data visualization
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2023 | Decision Support Systems | Citations: 0
Authors: Bina, Saman; Kaskela, Timothy; Jones, Donald R.; Walden, Eric; Graue, William B.

Abstract: With the proliferation of data has arisen an array of information visualization ... Expand

Abstract: With the proliferation of data has arisen an array of information visualization tools to help humans convert data to information for better decision-making. This ever-expanding visualization toolset has outrun the development of theories of data visualization usage for decision support. In the current research, we contribute to the development of visualization theories in two ways. First, we incorporate our understanding of evolutionary adaptations into the cognitive fit theory to explain why 3-D surface graphs often outperform traditional 2-D graphs in various sensemaking tasks. Drawing on geon theory to interpret the 3-D advantage, we develop the concept of geonic/non-geonic information representations and tasks. We tested and found support for our hy potheses that geonic representations have a speed advantage for the tasks we studied, derived from the human evolved capacity for geographic orienteering, but accuracy depends on the match of representation and task, as geonic or non-geonic. Our experiment compared the geonic representation (3-D surface graph) to non-geonic planar representations (cluster bar, heat map, and line) in geonic (integration, proportion) and non-geonic atomic (acquisition, comparison) tasks. For our second contribution, we build on this result to expand the cognitive fit model to incorporate classic human information processes and evolutionary adaptations. We suggest that the cognitive fit model can expand to include new advances in neuroscience. We discuss the theoretical and practical implications of our experiment and our expanded model. Collapse

Semantic filters: cognitive fit theory

Topics: data visualization sensemaking decision making spreadsheet Python

Methods: experiment parametric test ANOVA exploratory data analysis descriptive statistic

Theories: cognitive fit theory
Explainable artificial intelligence in information systems: A review of the status quo and future research directions
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2023 | Electronic Markets | Citations: 4
Authors: Brasse, Julia; Broder, Hanna Rebecca; Förster, Maximilian; Klier, Mathias; Sigler, Irina

Abstract: The quest to open black box artificial intelligence (AI) systems evolved into an ... Expand

Abstract: The quest to open black box artificial intelligence (AI) systems evolved into an emerging phenomenon of global interest for academia, business, and society and brought about the rise of the research field of explainable artificial intelligence (XAI). With its pluralistic view, information systems (IS) research is predestined to contribute to this emerging field; thus, it is not surprising that the number of publications on XAI has been rising significantly in IS research. This paper aims to provide a comprehensive overview of XAI research in IS in general and electronic markets in particular using a structured literature review. Based on a literature search resulting in 180 research papers, this work provides an overview of the most receptive outlets, the development of the academic discussion, and the most relevant underlying concepts and methodologies. Furthermore, eight research areas with varying maturity in electronic markets are carved out. Finally, directions for a research agenda of XAI in IS are presented. Collapse

Semantic filters: cognitive fit theory

Topics: explainable artificial intelligence artificial intelligence user requirement electronic market user experience

Methods: literature study literature sample cluster analysis synthesis machine learning

Theories: information systems theory activity theory agency theory attribution theory cognitive fit theory
How Novices and Experts Understand Hierarchies in Business Process Modeling

2023 | International Conference on Information Systems | Citations: 0
Authors: Stark, Jeannette; Neubauer, Maria; Greiffenberg, Steffen

Abstract: Conceptual models are essential for successful IT implementation, as they conci ... Expand

Abstract: Conceptual models are essential for successful IT implementation, as they concisely represent the system's component structures, behavior, and relationships. However, for conceptual models to fully realize their potential, they must be understood. To this end, hierarchy has been employed in business process modeling to enhance understanding of complex models. Prior research has proposed a two-component framework to explain the effects of hierarchy on understanding. Drawing on empirical data, this work extends this framework by investigating the influence of expertise on the understanding of hierarchical business process models. Our findings indicate that experts and novices benefit from hiding task-irrelevant information in subprocesses, with experts benefiting significantly more than novices. Additionally, experts profit more from recognizing familiar patterns in subprocesses than novices. Based on our results, we propose two principles for designing hierarchy and suggest future research avenues. Collapse

Semantic filters: cognitive fit theory

Topics: business process management

Methods: business process modeling experiment Student's t-test parametric test design science

Theories: cognitive fit theory
Improving Performance by Encouraging Users to Consider Different Levels of Action Identification (LAI)

2023 | International Conference on Information Systems | Citations: 0
Authors: Tzur, Aviram; Te’Eni, Dov; Zalmanson, Lior

Abstract: Action Identification Theory proposes that individuals perceive their actions a ... Expand

Abstract: Action Identification Theory proposes that individuals perceive their actions at different levels of abstraction and how this perception can significantly impact their behavior. The paper argues that prompting users to shift between different levels of action identification during their interaction with an information system can improve their performance. The experimental work includes a laboratory experiment and a think-aloud study that explores the effect of users' attention to different levels of action identification and the cognitive fit between on-screen representation and mental models on performance improvement. The discussion analyzes the results and outlines future research plans and expected contributions to the field. This study highlights the importance of considering the user's cognitive processes when designing information systems and suggests potential ways to enhance their performance. Collapse

Semantic filters: cognitive fit theory

Topics: human computer interaction usability decision making problem solving

Methods: experimental group experiment cognitive walkthrough laboratory experiment statistical hypothesis test

Theories: cognitive fit theory
Advancing our understanding and assessment of cognitive effort in the cognitive fit theory and data visualization context: Eye tracking-based approach
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2022 | Decision Support Systems | Citations: 0
Authors: Bačić, Dinko; Henry, Raymond

Abstract: In Cognitive Fit Theory (CFT) based research, there is a consensus about cogniti ... Expand

Abstract: In Cognitive Fit Theory (CFT) based research, there is a consensus about cognitive effort as the underlying mechanism impacting performance. Although critical to the theory, cognitive effort and its direct empirical assessment remain a challenge. In this repeated measures experimental study, we introduce a research model and develop hypotheses based on the fundamental relationships underlying CFT while integrating eye tracking as an approach for assessing cognitive effort. Our study finds that eye tracking technology, specifically fixation-based metrics, can be used in the understanding of cognitive processes initiated by our data representation choices. Specifically, we find that in all tasks except the complex-symbolic task, users experience meaningful change in the physiological assessment of cognitive effort based on the condition of cognitive fit. We contrast our findings to existing research and find that physiological indicators of cognitive effort can provide critical insights often missed in traditional CFT research. Collapse

Semantic filters: cognitive fit theory

Topics: task complexity data visualization decision making individual impact usability

Methods: oculometry experiment post-hoc analysis parametric test experimental task

Theories: cognitive fit theory
The role of design patterns in the development and legal assessment of lawful technologies
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2022 | Electronic Markets | Citations: 2
Authors: Dickhaut, Ernestine; Li, Mahei Manhai; Janson, Andreas; Leimeister, Jan Marco

Abstract: Novel technologies such as smart personal assistants integrate digital services ... Expand

Abstract: Novel technologies such as smart personal assistants integrate digital services into everyday life. These services use personal data to offer personalized services. While they are subject to special data protection regulations at the time of development, there are few guidelines describing the transition from legal requirements to implementation. To reduce risks, services depend on external legal assessments. With developers and legal experts often missing either legal or technical knowledge, the challenge lies in bridging this gap. We observe that design patterns support both developers and legal experts, and we present an approach in which design patterns are leveraged to provide twofold value for both developers and legal experts when dealing with novel technologies. We conducted a revelatory case study for smart personal assistants and scaffolded the case interpretation through cognitive fit theory. On the basis of the findings, we develop a theoretical model to explain and predict the twofold value of design patterns to develop and assess lawful technologies. Collapse

Semantic filters: cognitive fit theory

Topics: systems development problem solving legal context General Data Protection Regulation legal information system

Methods: design pattern case study simulation theory development qualitative interview

Theories: cognitive fit theory
Digital Sludging in the Privacy Context: Evidence of a Multigroup Analysis

2022 | Americas Conference on Information Systems | Citations: 3
Authors: Kollmer, Tim

Abstract: Organizations apply aggressive tactics to harvest and exhaust data from individ ... Expand

Abstract: Organizations apply aggressive tactics to harvest and exhaust data from individuals. These tactics exploit human psychology to manipulate individuals' behavior through user interface design characteristics. Because governmental regulations for data collection were introduced recently, organizations make use of digital sludging to prevent individuals from refusing the consent for the data collection -most commonly within the cookie consent. Digital sludging is characterized as excessive and unjustified frictions that increase the effort and decrease the attention of a specific choice. Hence, we conducted a vignette study to investigate digital sludging in the privacy context further. Overall, we contribute to existing research by demonstrating how privacy concerns affect the perception and interaction with the cookie consent. In addition, we outline how manipulative practices such as digital sludging influence individuals' decisionmaking. Collapse

Semantic filters: cognitive fit theory

Topics: information privacy concern privacy decision making mobile application

Methods: experiment partial least squares regression usability testing PLS tool survey

Theories: cognitive fit theory
Voice Assistant vs. Chatbot – Examining the Fit Between Conversational Agents’ Interaction Modalities and Information Search Tasks
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2022 | Information Systems Frontiers | Citations: 0
Authors: Rzepka, Christine; Berger, Benedikt; Hess, Thomas

Abstract: Owing to technological advancements in artificial intelligence, voice assistants ... Expand

Abstract: Owing to technological advancements in artificial intelligence, voice assistants (VAs) offer speech as a new interaction modality. Compared to text-based interaction, speech is natural and intuitive, which is why companies use VAs in customer service. However, we do not yet know for which kinds of tasks speech is beneficial. Drawing on task-technology fit theory, we present a research model to examine the applicability of VAs to different tasks. To test this model, we conducted a laboratory experiment with 116 participants who had to complete an information search task with a VA or a chatbot. The results show that speech exhibits higher perceived efficiency, lower cognitive effort, higher enjoyment, and higher service satisfaction than text-based interaction. We also find that these effects depend on the task’s goal-directedness. These findings extend task-technology fit theory to customers’ choice of interaction modalities and inform practitioners about the use of VAs for information search tasks. Collapse

Semantic filters: cognitive fit theory

Topics: information storage and retrieval system task characteristic Google+ human computer interaction smart speaker

Methods: experiment laboratory experiment survey factor analysis data transformation

Theories: cognitive fit theory theory of task technology fit cognitive load theory
Adaptive cognitive fit: Artificial intelligence augmented management of information facets and representations
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2022 | International Journal of Information Management | Citations: 2
Authors: Samuel, Jim; Kashyap, Rajiv; Samuel, Yana; Pelaez, Alexander

Abstract: Explosive growth in big data technologies and artificial intelligence (AI) appli ... Expand

Abstract: Explosive growth in big data technologies and artificial intelligence (AI) applications have led to increasing pervasiveness of information facets and a rapidly growing array of information representations. Information facets, such as equivocality and veracity, can dominate and significantly influence human perceptions of in formation and consequently affect human performance. Extant research in cognitive fit, which preceded the big data and AI era, focused on the effects of aligning information representation and task on performance, without sufficient consideration to information facets and attendant cognitive challenges. Therefore, there is a compelling need to understand the interplay of these dominant information facets with information representations and tasks, and their influence on human performance. We suggest that artificially intelligent technologies that can adapt information representations to overcome cognitive limitations are necessary for these complex information environments. To this end, we propose and test a novel “Adaptive Cognitive Fit” (ACF) framework that explains the influence of information facets and AI-augmented information representations on human performance. We draw on information processing theory and cognitive dissonance theory to advance the ACF framework and a set of propositions. We empirically validate the ACF propositions with an economic experiment that demonstrates the influence of information facets, and a machine learning simulation that establishes the viability of using AI to improve human performance. Collapse

Semantic filters: cognitive fit theory

Topics: artificial intelligence website digital ecosystem big data decision support

Methods: experiment simulation machine learning parametric test ANOVA

Theories: cognitive fit theory cognitive dissonance theory information processing theory information systems theory behavioral economics
Animation as a dynamic visualization technique for improving process model comprehension
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2021 | Information & Management | Citations: 2
Authors: Aysolmaz, Banu; Reijers, Hajo A.

Abstract: Process models are widely used for various system analysis and design activities ... Expand

Abstract: Process models are widely used for various system analysis and design activities, but it is challenging for stakeholders to understand these complex artifacts. In this work, we focus on the use of dynamic visualization techniques, in particular animation, to help reduce users’ cognitive load when making sense of process models. We built on the principles of the cognitive theory of multimedia learning, cognitive load theory, and cognitive dimensions framework to develop an adaptive animation solution. Our experiments suggested that process model comprehension improves when users of process models are provided with animation features; the effect is moderated by process modeling expertise according to a U-shape. Our study contributes to the field of conceptual modeling by making a strong case for the use of animation to support complex problem-solving tasks. Moreover, our animation solution offers ample opportunities for being integrated into industrial modeling tools. Collapse

Semantic filters: cognitive fit theory

Topics: problem solving perceived usefulness online learning system PHP website

Methods: business process modeling experiment conceptual modelling descriptive statistic chi squared test

Theories: cognitive load theory cognitive theory of multimedia learning cognitive fit theory

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Found 140 articles

Incorporating evolutionary adaptions into the cognitive fit model for data visualization

Explainable artificial intelligence in information systems: A review of the status quo and future research directions

How Novices and Experts Understand Hierarchies in Business Process Modeling

Improving Performance by Encouraging Users to Consider Different Levels of Action Identification (LAI)

Advancing our understanding and assessment of cognitive effort in the cognitive fit theory and data visualization context: Eye tracking-based approach

The role of design patterns in the development and legal assessment of lawful technologies

Digital Sludging in the Privacy Context: Evidence of a Multigroup Analysis

Voice Assistant vs. Chatbot – Examining the Fit Between Conversational Agents’ Interaction Modalities and Information Search Tasks

Adaptive cognitive fit: Artificial intelligence augmented management of information facets and representations

Animation as a dynamic visualization technique for improving process model comprehension