The Olympics concluded last week and some of you may have watched the fascinating sport of curling. I don’t know about you, but when I watch curling, I have many questions. Questions such as” “What the heck is going on?” and “How do they keep score?” But the aspect of curling that intrigues me the most is how the curlers communicate. There are moments of silence punctuated by abrupt yelling, and soft talking that becomes full on screaming. It is exciting to watch! But it still begs the questions, what are they communicating and how does this communication help their performance?
Let’s start with some basics. Curling is played on a long, narrow sheet of ice with a marked target area, called the house, at each end. Teams typically consist of four players each and each team takes turns sliding heavy granite stones to the opposite end of the ice. The goal is to get your team’s stones closer to the center button of the “house” by pushing the stone and sweeping the ice in front of the stone to keep it moving at the speed and direction you want. The friction from the “sweepers” sweeping polishes the ice, which makes the stone travel farther and straighter (Reich, 2014). However, for sweepers to know how and when to sweep, effective communication is required from the thrower to the sweepers.
Before the stone is thrown, the skip (the team strategy leader) should communicate the delivery of the stone with the thrower and sweepers. It is key for the delivering player and the sweepers to make sure they understand this guidance from the skip. If needed, they will discuss and confirm with the skip their understanding of the upcoming shot. The thrower and the sweepers will typically discuss the speed of the ice prior to throws as well. Once the stone is moving, constant communication should take place between the sweepers and the thrower. The sweepers will be responsible for judging the weight of the stone and will regularly communicate their estimation to the skip. The thrower is responsible for judging the stone’s course and should regularly inform the sweepers of that course and their need to sweep or not. Various codes and methods of communication exist to describe the path and weight of the stone. Table 1 provides examples of phrases used in curling between the thrower and the sweepers.
So how do we know if a curling team is communicating effectively? We can begin analyzing the communication in terms of an established framework (Jeffcott & Mackenzie, 2008). QIC is currently doing this with Army squad communications during execution of a common battle drill. In this effort, communication between squad members is classified as one of five possible factors: communication quality, leadership, monitoring, cooperation, and coordination. See Table 2 for a description of each factor. Squad scores within each factor are analyzed relative to squad performance metrics.
A similar approach can be applied to curling team communications. Communication Quality can refer to the extent that team members are yelling clearly and sufficiently often. Leadership can be measured through whether the skip is making sound decisions and providing clear direction to the thrower. Monitoring may consist of whether the thrower is constantly monitoring the speed and position of the rock, and if the sweepers are actively listening, responding to, and acknowledging the thrower’s direction. Cooperation can be measured by the degree to which the sweepers are working together. Coordination can refer to the implicit coordination between the sweepers and if the skip is providing direction at the right time.
Once team communications are organized according to the five factors and validated, the formal analysis comparing communications to curling performance can begin. For instance, how does communication within each of the five factors explain differences in curling team’s performance such as points scored, wins and losses, and time to complete a match? With enough data from different curling teams, a predictive model could be developed to better understand how different types of communication, according to the five-factor framework, can predict actual curling performance. This can have major implications for training and team member selection.
What other Olympic sports did you watch where team communications appeared to be an important factor?
Jeffcott, S. A., & Mackenzie, C. F. (2008). Measuring team performance in healthcare: review of research and implications for patient safety. Journal of Critical Care, 23(2), 188-196.
Reich, B. (2014, February 13). Here's everything you ever wanted to know about curling. Mic. Retrieved February 17, 2022, from https://www.mic.com/articles/81947/here-s-everything-you-ever-wanted-to-know-about-curling
Sticking to my exercise regime. Keeping up with those Spanish exercises on DuoLingo. Stop binge-watching “The Office”. Eating healthily. It’s only a few weeks into the new year and l’m already re-thinking my new year’s resolutions.
Most of us would agree that behavioral change is elusive. Two thoughts come to mind, one, “an object at rest stays at rest and an object in motion stays motion, unless it is acted upon by a force” which is Newton’s 1st law of motion (Britannica, 2021). Two, "we are just creatures of habit." Creatures, i.e., driven more by instinct with minimal prefrontal cortex (PFC) action. The PFC being associated with executive functions such as cognitive control, attention, planning, decision-making, impulse inhibition, reasoning, and problem-solving (Fuster, 2015).
So it seems like short of a compelling external force, I can’t help but fall back on old behaviors without some purposeful activation of my higher-order cognitive functions to steer me away from my path of least resistance. It also doesn’t help that in today’s digital age, we all have too many options for things to do at any one time. This means staying on a task requires an intentional decision every time we’re tempted to do something else.
Resolutions can either be approach-oriented goals such as eating more vegetables and keeping up with exercise, or avoidance-oriented goals such as spending less or quitting a bad habit. Studies show that approach-oriented goals are more effective than avoidance-oriented ones (Oscarsson, Carlbring, Andersson, & Rozental, 2020), suggesting that when possible, we should perhaps reframe those “quit” goals as new habits to be formed instead. Another consideration for forming resolutions is applying one of the seven principles of highly effective people: begin with the end in mind (Covey, 2020). This means I shouldn’t just resolve simply to exercise more or eat more healthily. The goals need to be specific and tied to a realistic vision of what the end looks like. For the exercise goal, this could be an ongoing one like jogging 2 miles three times a week.
Here are some commonly cited pointers to help us new year resolvers along:
1. Watch those cues and lower the bar for the good habit to form
Many of our behaviors are based on and triggered by cues which can be an event, emotion, place or person. For instance, when I come home after work and turn on the TV, this is the end-of-the-day signal to wind down, and for me, it is a cue to take a trip to the fridge or pantry and reach for that bag of chips. Feelings of boredom can also cue mindless snacking. To counter this, I’ll need the cues to signal the new behavior. Instead of turning on the TV the minute I get home, I should do something else that takes me away from the TV, e.g., go out for a walk or tend to my plants. Cues should also be used to encourage us to form good habits. Some suggest putting running shoes by the bed as a cue to exercise early the next day. I’d also suggest lowering the bar for the new habit and wearing my running socks to bed, or replace the chips with readily accessible healthy snacks, so I don’t quit snacking, but snack more healthily.
2. Use frequent reinforcements and immediate feedback
Once we have started on the behavior, we need frequent reinforcements to see it through to completion. In the midst of my jog, I’m always tempted to quit and so must be fueled by frequent reinforcements such as encouraging self-talk, or immediate feedback of my incremental gains provided by the upward count of the number of steps or distance displayed on my fitness app. Listening to music to distract from the monotony of the jog also works well. The feeling of accomplishment at the end of the exercise can also be rewarding.
3. Get support or make a social commitment.
Sometimes we all need an extra push to stay on top of our resolutions. This is where others come in. In a large study conducted on new year’s resolutions, participants who had more support with their goals were more successful in attaining them. Compared to the no support group, these supported participants named at least one person that would support their progress and were given support in the form of follow-up emails and information and exercises on how to cope with potential hurdles when working towards their goals (Oscarsson, Carlbring, Andersson, & Rozental, 2020). If you can’t find anyone to exercise with, then at least create a social contract by letting a friend or family member know of your goals. This will count as support if you feel obliged to keep our word and follow through.
4. Just keep on keeping on, there is no fail
It is inevitable that we’ll have bad days, so we shouldn’t ditch the resolution just because we failed once, or twice, or thrice, or however many times. The important thing to do is just to keep moving. Besides, there are benefits in making new year’s resolutions:
So if you haven’t done so but still want to, it’s not too late to make some resolutions. Let us know how you're doing with your resolutions!
Britannica, T. Editors of Encyclopaedia (2021, July 23). Newton's laws of motion. Encyclopedia Britannica. https://www.britannica.com/science/Newtons-laws-of-motion
Covey, S. R., & Covey, S. (2020). The 7 habits of highly effective people. Simon & Schuster.
Dai, H., Milkman, K. L., & Riis, J. (2014). The fresh start effect: Temporal landmarks motivate aspirational behavior. Management Science, 60(10), 2563-2582.
Dai, H., Milkman, K. L., & Riis, J. (2015). Put your imperfections behind you: Temporal landmarks spur goal initiation when they signal new beginnings. Psychological science, 26(12), 1927-1936.
Fuster, J. (2015). The prefrontal cortex. Academic Press.
Oscarsson, M., Carlbring, P., Andersson, G., & Rozental, A. (2020). A large-scale experiment on New Year’s resolutions: Approach-oriented goals are more successful than avoidance-oriented goals. PLoS One, 15(12), e0234097.
While failure is no fun, it is a part of life. Whether summitting mountains or managing projects, there are times when one must recognize the signs of failure, make the tough decision to call it a day, and learn from the experience to return smarter and stronger next time.
This past summer, I took a vacation to Colorado which was a blast. Three days on the agenda consisted of backpacking into the Chicago Basin, camping, and summiting 14ers (mountains over 14,000 feet). I had no prior mountaineering experience though was with someone who did, and we planned extensively. I had the right gear, was in good shape, and the conditions were ideal; I was feeling confident. On the second day, as I attempted a second summit, I began feeling fatigued, making mental errors, and falling behind. Though I tried to press on, I was aware that poor decisions and continued mistakes, especially near the summit, could be catastrophic (see Wickens, Keller, & Shaw, 2015).
I made the difficult call to abandon the summit bid and hiked down to lower elevation. Watching the beautiful sunrise over the basin lakes, I began to reflect on the failure, thinking about it in terms of project management given a summit bid, like a project, is “a temporary endeavor undertaken to create a unique…result” (Project Management Institute, 2008, p. 5). Though a project manager (PM) never plans to fail, they do identify the risks and notice the potential signs of failure so that they can correct course. As a last resort, a responsible PM may decide it is best to call it quits before stakeholder and company losses become too great.
Recognizing the Signs
In a Project Management Institute (PMI) published article "Managing Troubled Projects", Alaskar (2013) outlines signs that a project may be in jeopardy. Several of these apply to my summit bid:
Learning from Failure
In another PMI published article, Ranganath (2006) presents a learning from experience (LifE) cycle for project management that applies to dealing with project failure. The cycle involves:
Though it may be a bit painful, tell us about a project failure whether work related or not. If you like to climb mountains, tell us about that too!
Alaskar, A. H. (2013). Managing troubled projects. Paper presented at PMI® Global Congress 2013—North America, New Orleans, LA. Newtown Square, PA: Project Management Institute.
Project Management Institute. (2008). A guide to the project management body of knowledge (PMBOK guide) (4th ed.). Project Management Institute.
Ranganath, P. G. (2006). LIfE—learning and improving from experience. Paper presented at PMI® Global Congress 2006—North America, Seattle, WA. Newtown Square, PA: Project Management Institute.
Wickens, Christopher D.; Keller, John W.; and Shaw, Christopher (2015) "Human Factors in High-Altitude Mountaineering," Journal of Human Performance in Extreme Environments: Vol. 12 : Iss. 1 , Article 1.
This semester QIC welcomes Natalie Paquette as a Human Factors Intern! Natalie is a Ph.D. student in the Human Factors and Cognitive Psychology program at the University of Central Florida (UCF). Natalie earned her MA in Applied Experimental and Human Factors Psychology in 2020 at UCF and her MA in Psychology focused on Cognitive and Behavioral Neuroscience at George Mason University in 2017. Her work has examined performance issues related to mismatched expectations, reliance on visual working memory, and the effect of restricted time intervals on error processing. Natalie’s interests include examining the neurophysiological and perceptual aspects of cognition and performance in various environments to determine optimal parameters for successful task completion.
This semester QIC welcomes Nicolas Uszak as a Human Factors Intern! Nicolas is a Ph.D. student at the University of Central Florida’s Human Factors and Cognitive Psychology Program. Nicolas has a Master’s in Applied Experimental Human Factors and a graduate certificate for Design Usability in Industrial Engineering, both from UCF. Previously he graduated summa cum laude with his B.A. in Psychology from Cleveland State University. His interests lie in motivation, situational awareness, automation, multi-tasking, vigilance, and machine learning. Nicolas is currently working on his dissertation involving situational awareness while operating automated vehicles.
I've attended and presented at several conferences this year, such as the Human Systems Digital Experience, World Aviation Training Summit (WATS), and Applied Human Factors and Ergonomics (AHFE), and have noticed a simple yet powerful construct appearing over and over again…self-efficacy. Self-efficacy is "concerned with people’s beliefs in their capabilities to produce given attainments" (Bandura, 2006). In other words, it's the confidence in the ability to exert control over one's own motivation, behavior, and social environment (Carey & Forsyth, 2009). Extensive evidence has shown self-efficacy to be a significant predictor across a variety of contexts and domains, such as college academic performance (Choi, 2005), pre-career pilot performance (Wilson, 2021), weight loss success (Armitage et al., 2014), health management (Arslan, 2012), second language skills (Raoofi, Tan, & Chan, 2012), and work burnout and engagement (Ventura, Salanova, & Lloren, 2015). While there are a host of other areas that have explored the role of self-efficacy, one of particular interest to me that has been gaining more attention is usability.
Usability assessments typically focus on effectiveness, efficiency, and satisfaction, but research suggests the integration of self-efficacy can provide a robust assessment (Martin, 2007). As the preponderance of technological solutions continuously diffuses across all aspects of our personal and work lives, our dependency on them will impact our ability to complete tasks. Therefore, belief in our ability to complete a task with a technological solution should impact the way in which these solutions are designed. Plenty of evidence exists indicating the role of self-efficacy in the adoption of technology, such as mobile learning solutions (Bettayeb, Alshurideh, Al Kurdi, 2020), desktop virtual environments for learning (Makransky & Petersen, 2019), fitness devices (Rupp, Michaelis, McConnel, Smither, 2018), and medical support tools (Lindblom, Gregory, Wilson, Flight, & Zajac, 2012).
Although some usability measures focus on or integrate the concept of self-efficacy, not all are implemented correctly based on Bandura's guidance (2006). One major flaw is using Likert-type bipolar ratings (e.g., strongly agree to strongly disagree) instead of unipolar ones (e.g., 0 to 10). The issue is if you have zero confidence in your ability to complete a task, then negative ratings below zero make little sense and lead to skewed interpretations of the results. Further, when bipolar ratings are used, the mid-point (usually labeled as neither agree nor disagree) gets converted into a moderate-level of self-efficacy which is incorrect and not a true reflection of the construct (Bandura, 2012). Leveraging self-efficacy as a usability metric can provide valuable insight into the design and evaluation of technology, but it's critical that measures be developed, implemented, and interpreted appropriately.
Bandura (2012) stated that "there is no single all-purpose measure of self-efficacy with a single validity coefficient." This indicates that it's expected for new measures of self-efficacy to be created for, as he puts it, "activity domains." Activity domains are the topic areas in which the tasks under evaluation are performed. For example, evaluating self-efficacy for driving a monster truck. Use these guidelines when developing your measures and scales for usability evaluations (or any evaluation for that matter):
Have you been capturing self-efficacy as part of your usability assessments? Tell us how.
Armitage, C. J., Wright, C. L., Parfitt, G., Pegington, M., Donnelly, L. S., & Harvie, M. N. (2014). Self-efficacy for temptations is a better predictor of weight loss than motivation and global self-efficacy: Evidence from two prospective studies among overweight/obese women at high risk of breast cancer. Patient Education and Counseling, 95(2), 254-258.
Arslan, A. (2012). Predictive power of the sources of primary school students' self-efficacy beliefs on their self-efficacy beliefs for learning and performance. Educational Sciences: Theory and Practice, 12(3), 1915-1920.
Bandura, A. (2006). Guide to the construction of self-efficacy scales. In Pajares, F., Urdan, T. (Eds.), Self-efficacy beliefs of adolescents, Vol. 5: 307-337. Greenwich, CT: Information Age.
Bandura, A. (2012). On the functional properties of perceived self-efficacy revisited. Journal of Management, 38(1), 9–44.
Bettayeb, H., Alshurideh, M. T., & Al Kurdi, B. (2020). The effectiveness of mobile learning in UAE universities: a systematic review of motivation, self-efficacy, usability and usefulness. Control and Automation, 13(2), 1558-1579.
Carey, M.P. & Forsyth, A.D. (2009). Teaching tip sheet: Self-efficacy. American Psychological Association. https://www.apa.org/pi/aids/resources/education/self-efficacy.
Choi, N. (2005). Self‐efficacy and self‐concept as predictors of college students' academic performance. Psychology in the Schools, 42(2), 197-205.
Lindblom, K., Gregory, T., Wilson, C., Flight, I.H.K., & Zajac, I. (2012). The impact of computer self-efficacy, computer anxiety, and perceived usability and acceptability on the efficacy of a decision support tool for colorectal cancer screening, Journal of the American Medical Informatics Association, 19(3), 407–412.
Makransky, G. & Petersen, G. B. (2019). Investigating the process of learning with desktop virtual reality: A structural equation modeling approach. Computers & Education, 134, 15-30.
Martin, C. V. (2007). The Importance of self-efficacy to usability: Grounded theory analysis of a child’s toy assembly task. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 51(14), 865–868.
Raoofi, S., Tan, B. H., & Chan, S. H. (2012). Self-Efficacy in Second/Foreign Language Learning Contexts. English Language Teaching, 5(11), 60-73.
Rupp, M. A., Michaelis, J. R., McConnell, D. S., & Smither, J. A. (2018). The role of individual differences on perceptions of wearable fitness device trust, usability, and motivational impact. Applied Ergonomics, 70, 77-87.
Ventura, M., Salanova, M., & Llorens, S. (2015). Professional self-efficacy as a predictor of burnout and engagement: The role of challenge and hindrance demands. The Journal of Psychology, 149(3), 277-302.
Wilson, N. (2021). Pre-Career Pilots and Motivation – What is the Best Predictor of Performance? 23rd World Aviation Training Summit (WATS), Orlando, FL, June 15-16, 2021.
These posts are written or shared by QIC team members. We find this stuff interesting, exciting, and totally awesome! We hope you do too!