Journal of Cognitive Engineering and Decision Making

Scope & Guideline

Innovating human-centric solutions in engineering.

Introduction

Welcome to the Journal of Cognitive Engineering and Decision Making information hub, where our guidelines provide a wealth of knowledge about the journal’s focus and academic contributions. This page includes an extensive look at the aims and scope of Journal of Cognitive Engineering and Decision Making, highlighting trending and emerging areas of study. We also examine declining topics to offer insight into academic interest shifts. Our curated list of highly cited topics and recent publications is part of our effort to guide scholars, using these guidelines to stay ahead in their research endeavors.
LanguageEnglish
ISSN1555-3434
PublisherSAGE PUBLICATIONS INC
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 2007 to 2024
AbbreviationJ COGN ENG DECIS MAK / J. Cogn. Eng. Decis. Mak.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address2455 TELLER RD, THOUSAND OAKS, CA 91320

Aims and Scopes

The Journal of Cognitive Engineering and Decision Making focuses on the intersection of cognitive engineering principles and decision-making processes across various domains. It emphasizes the integration of human cognition with automated systems, exploring how these interactions can be optimized for improved performance and safety.
  1. Cognitive Engineering in Automated Systems:
    The journal extensively covers the design and evaluation of cognitive systems, particularly how human cognitive processes interact with automated technologies in fields such as transportation, healthcare, and military operations.
  2. Human Factors and Decision-Making:
    Research often examines human decision-making under various conditions, including high-stakes environments, highlighting cognitive biases, communication patterns, and the role of trust in automation.
  3. Automation Failures and Human Response:
    A consistent theme is the investigation of automation failures, focusing on understanding how humans respond to these failures, the implications for system design, and strategies for mitigating risks.
  4. Interdisciplinary Approaches:
    The journal promotes an interdisciplinary perspective, integrating insights from cognitive psychology, human factors, systems engineering, and artificial intelligence to enhance decision-making frameworks.
  5. Training and Skill Development:
    Research also delves into training methodologies and tools designed to improve cognitive skills and situation awareness, particularly in high-stress occupations.
The journal has witnessed the emergence of several important themes that reflect current challenges and innovations in cognitive engineering and decision-making. These trends indicate a shift toward addressing complex sociotechnical systems and the evolving nature of human-automation interactions.
  1. Human-AI Teaming:
    There is a growing emphasis on the dynamics of human-AI collaboration, particularly in high-stakes settings like healthcare and military operations, highlighting the need for better integration of AI capabilities with human decision-making.
  2. Automation Failure and Recovery Strategies:
    Recent publications increasingly address the nuances of automation failures and the strategies for recovery, focusing on how users can regain situation awareness and effectively manage unexpected system behavior.
  3. Cognitive Biases and Decision-Making in Crisis Situations:
    Emerging research is focusing on how cognitive biases affect decision-making during crises, with implications for training and system design to enhance resilience and adaptability.
  4. Ecological Interface Design:
    There is significant interest in ecological interface design principles, which aim to create interfaces that align with human cognitive processes, thereby improving usability and reducing errors in complex systems.
  5. Augmented and Virtual Reality Applications:
    The use of augmented and virtual reality for training and simulation purposes is gaining traction, particularly in high-risk environments, showcasing innovative approaches to enhance cognitive skills and situational awareness.

Declining or Waning

While the journal continues to thrive in many areas, certain themes appear to be declining in frequency or relevance. These waning scopes may reflect broader shifts in research priorities or advancements in technology that render previous inquiries less critical.
  1. Traditional Decision Support Systems (DSS):
    There has been a noticeable decrease in articles focused on traditional DSS frameworks, as the field moves towards more integrated and adaptive systems that incorporate real-time data and AI.
  2. Basic Human-Machine Interaction Studies:
    Research that merely explores basic human-machine interaction without a focus on cognitive implications or advanced automation appears to be less prominent, as the field increasingly demands nuanced understanding of complex interactions.
  3. Static Models of Trust in Automation:
    The exploration of static models of trust, which do not account for dynamic changes in user perceptions or system capabilities, is diminishing as newer, more comprehensive models are developed.

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