Student Perspectives on Changing Requirements for Human Factors Engineering Education

2021 ◽  
Vol 65 (1) ◽  
pp. 1579-1583
Author(s):  
Bella Yigong Zhang ◽  
Esa M. Rantanen ◽  
Mark Chignell
Keyword(s):  
Human Factors ◽  
Data Science ◽  
Real Life ◽  
Early Career ◽  
Human Factors Engineering ◽  
Everyday Objects ◽  
Hands On ◽  
Challenges And Opportunities ◽  
Survey Results ◽  
Industry Trends

In today’s digital economy, the Internet of Things (IoT) has connected devices, humans, and everyday objects to each other in ways that were unimaginable before. Vast amounts of data are collected everywhere and disrupting how we design systems and products. Data science and emerging technologies offer challenges and opportunities for early-career human factors professionals who are looking to grow their careers and their human factors practice. In this paper, we report on a survey to assess the perspectives of students currently studying human factors. The survey items examined shortfalls in current human factors education with re-spect to relevance to industry trends. The survey results show that students see a need to include more relevant subjects in data science, as well as opportunities to learn trending industry problems, hands-on experience with real-life projects, prior to graduation.

A Pre-Prototyping Framework to Explore Human-Centered Prototyping Strategies During Early Design

2020 ◽  
Author(s):  
Salman Ahmed ◽  
H. Onan Demirel
Keyword(s):  
Human Factors ◽  
Product Development Process ◽  
Extensive Literature ◽  
Human Factors Engineering ◽  
Design Strategies ◽  
Key Factors ◽  
Hands On ◽  
The Right

Abstract Current prototyping frameworks are often prompt-based and heavily rely on designers’ experience. The lack of systematic guidelines in prototyping activities causes unwanted variation in the quality of the prototype. Notably, there is limited, or no prototyping framework exists that enables human factors engineering (HFE) guidelines be part of the early product development process. In this paper, a pre-prototyping framework is proposed to render human-centered design strategies to guide designers before the hands-on prototyping activity starts. The methodology consists of extracting key factors related to prototyping and human factors engineering principles based on an extensive literature review. The key elements are then combined to form the prototyping categories, dimensions (theory), and tools (practice). The resulting prototyping framework can be used to develop prototyping strategies consist of theoretical guidelines and practical tools that are needed during the prototyping of human-centered products. The framework provides systematic guidance to designers in the early stages of the design process so that designers, in particular novices in ergonomics and human factors, can have a head start in building the prototypes in the right direction. Finally, a case study is presented to demonstrate a walk-through and efficacy of the proposed pre-prototyping framework.

scholarly journals A Human Factors Engineering Education Perspective on Data Science, Machine Learning and Automation

2019 ◽  
Vol 63 (1) ◽  
pp. 488-492
Author(s):  
Daniel Hannon ◽  
Esa Rantanen ◽  
Ben Sawyer ◽  
Raymond Ptucha ◽  
Ashley Hughes ◽  
...  
Keyword(s):  
Machine Learning ◽  
Human Factors ◽  
Engineering Education ◽  
Data Science ◽  
Human Factors Engineering ◽  
Automated Systems ◽  
Learning Techniques ◽  
Black Boxes ◽  
Model Training ◽  
Novel Applications

The explosion of data science (DS) in all areas of technology coupled with the rapid growth of machine learning (ML) techniques in the last decade create novel applications in automation. Many working with DS techniques rely on the concept of “black boxes” to explain how ML works, noting that algorithms find patterns in the data that humans might not. While the mathematics are still being developed, the implications for the application of ML, specifically to questions of automation, also are being studied, but still remain poorly understood. The decisions made by ML practitioners with respect to data selection, model training and testing, data visualization, and model applications remain relatively unconstrained and have the potential to yield unexpected results at the systems level. Unfortunately, human factors engineers concerned with automation often have limited training and awareness of DS and ML applications and are unable to provide the meaningful guidance that is needed to ensure the future safety of these newly emerging automated systems. Moreover, undergraduate and graduate programs in human factors engineering (HFE) have not kept pace with these developments and future HFEs may continue to find themselves unable to contribute meaningfully to the development of automated systems based on algorithms derived from ML. In this paper, human factors engineers and educators explore some of the challenges to our understanding of automation posed by specific ML techniques and contrast this with an outline of some of the historical work in HFE that has contributed to our understanding of safe and effective automation. Examples are provided from more conventional applications using both supervised and unsupervised learning techniques, that are explored with respect to implications for algorithm performance, use in system automation, and the potential for unintended results. Implications for human factors engineering education are discussed.

Teaching Human Factors Principles Through Design of an EXIT Sign

2007 ◽  
Vol 51 (18) ◽  
pp. 1168-1170 ◽  
Author(s):  
Jennifer L. Dyck
Keyword(s):  
Environmental Factors ◽  
Human Factors ◽  
Visual Display ◽  
Specific Design ◽  
Display Design ◽  
Everyday Objects ◽  
Class Comparison ◽  
Hands On

A hands-on, specific design assignment is described, for use in a graduate or undergraduate human factors course. The assignment requires students to re-design an EXIT sign, taking into account principles of visual display design, and environmental factors, which may reduce visibility of the sign. Assigning a particular object to re-design allows for in-class comparison and discussion, and additionally, is easier for students when first beginning to identify human factors deficiencies in everyday objects. Students consistently rate this assignment positively, and especially enjoy the creative aspect of the assignment.

Reshaping Human Factors Education in Times of Big Data: Practitioner Perspectives

2021 ◽  
Vol 65 (1) ◽  
pp. 1574-1578
Author(s):  
Bella Yigong Zhang ◽  
Mark Chignell
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Human Factors ◽  
Task Analysis ◽  
Data Science ◽  
Data Sets ◽  
Human Factors Engineering ◽  
Design Data ◽  
Wide Range ◽  
Human Use

Human Factors Engineering (HFE) is an applied discipline that uses a wide range of methodologies to better the design of systems and devices for human use. Underpinning all human factors design is the maxim to fit the human to the task/machine/system rather than vice versa. While some HFE methods such as task analysis and anthropometrics remain relatively fixed over time, areas such as human-technology interaction are strongly influenced by the fast-evolving technological trend. In times of big data, human factors engineers need to have a good understanding of topics like machine learning, advanced data analytics, and data visualization so that they can design data-driven products that involve big data sets. There is a natural lag between industrial trends and HFE curricula, leading to gaps between what people are taught and what they will need to know. In this paper, we present the results of a survey involving HFE practitioners (N=101) and we demonstrate the need for including data science and machine learning components in HFE curricula.

Enhancing Learning of Human Factors with Web-Based Technology Applications

1998 ◽  
Vol 42 (7) ◽  
pp. 602-605
Author(s):  
Joseph C. Hickox ◽  
Stuart L. Turner ◽  
Anthony J. Aretz
Keyword(s):  
Human Factors ◽  
United States Air Force ◽  
The United States ◽  
Human Factors Engineering ◽  
Web Based ◽  
Institutional Goals ◽  
Technology Applications ◽  
Survey Results ◽  
Initial Resistance ◽  
Descriptive Survey

This paper describes a case study of two senior-level undergraduate courses in the Human Factors Engineering curriculum at the United States Air Force Academy. These courses were modified extensively to employ World Wide Web (WWW) and internet technologies as an assist to standard pedagogies. The modifications were made in response to multiple institutional goals and student needs. Descriptive survey data were collected to gauge student receptivity to these changes. Results suggest initial resistance, followed by a bimodal response of either strongly embracing the technology, or mildly rejecting it. Additional survey results are discussed along with instructor impressions of effectiveness.

Teaching an Introductory Course in Human Factors Engineering: A Successful Learning Experience

1993 ◽  
Vol 37 (6) ◽  
pp. 456-460 ◽  
Author(s):  
Russell J. Sojourner ◽  
Anthony J. Aretz ◽  
Kristen M. Vance
Keyword(s):  
Critical Thinking ◽  
Human Factors ◽  
Learning Experience ◽  
The United States ◽  
Thinking Skills ◽  
Learning Material ◽  
Human Factors Engineering ◽  
Introductory Course ◽  
Hands On ◽  
Hands On Learning

The ideal structure for an introductory human factors engineering course has received widespread interest. A common issue involves the need to supply students with hands-on experience in design and applications. Such experience was provided by a recently revised course at the United States Air Force Academy. Course objectives stressed critical thinking through collaborative and interactive learning. Material was taught at a general conceptual level, and in-class exercises were extensively incorporated. To facilitate hands-on learning and critical thinking, the course was structured around a series of design projects, performed both individually and in groups. To measure success, standardized student critique data were collected and compared with the previous year. Results showed strong student agreement in the belief that the course stimulated both human factors knowledge and thinking skills. In addition, there was a significant increase in overall student evaluations from the previous year. These findings appear to validate the use of hands-on collaborative learning to augment the teaching of human factors concepts and theory.

Creative Design Solutions as a Class Exercise

2009 ◽  
Vol 17 (1) ◽  
pp. 6-7 ◽  
Author(s):  
Jennifer L. Dyck
Keyword(s):  
Environmental Factors ◽  
Human Factors ◽  
Visual Display ◽  
Creative Design ◽  
Display Design ◽  
Everyday Objects ◽  
Class Comparison ◽  
Hands On ◽  
Psychology Course

This article describes a case study I use as a hands-on design assignment in a human factors psychology course. The assignment is to redesign an exit sign, taking into account principles of visual display design and environmental factors that could reduce the sign's visibility. Assigning a particular object to redesign allows in-class comparison and discussion, and it is relatively easy for students when they begin to identify human factors deficiencies in everyday objects. Students consistently rate this assignment positively, and they especially enjoy its creative aspects.

Sign in / Sign up

Export Citation Format

Share Document