Like almost everything else, Thanksgiving this year will be far from normal thanks to the COVID-19 pandemic. No doubt most of us are still keen to carry on with the activities that characterize the season. My goal this Thanksgiving is modest: to have a safe, enjoyable, delicious, Thanksgiving where I get to catch up with family and friends, recounting fond memories, dodging embarrassing questions, enduring rude remarks and avoiding arguments. Yes, a good Thanksgiving.

COVID has definitely added concerns to my travel plans, as it has with others (Sarmiento & Wamsley, 2020). Should I fly or drive? What are the COVID risks from being at the airport? Is it enough that the airline mandates masks to be worn at all times? What should be my route if I’m driving and what are the COVID risks from that?

Leading a QIC project that is employing Goal Directed Task Analysis (GDTA; Endsley, Bolte, & Jones, 2003), I decided to apply it in the context of my travel conundrum. A GDTA documents a task in terms of the goals to be achieved, the key decisions that determine the extent which the goals are met, and the information requirements needed to make those decisions. The GDTA has been used to describe complex unstructured tasks that can involve ill-defined processes and outcomes such as maritime navigation (Sharma, 2019), critical monitoring tasks (Rummukainen, 2016), paramedics’ tasks (Abd Hamid & Waterson, 2010), supervisory control tasks (Kaber et al., 2006), and command and control decision making (Bolstad et al., 2000), so of course it is capable of helping to resolve my problem. Applying the GDTA methodology to my overall goal is to make travel arrangements for Thanksgiving this year, I defined the main and subgoals in the following Goal Hierarchy (Endsley, 1993) (see Figure 1).

According to Endsley and Garland (2000), the GDTA information required can be further categorized as that which enables the decision maker to: 

• Perceive and obtain awareness of the situation (Level 1)
• Comprehend and derive meaning about the situation (Level 2)
• Project future states and events (Level 3)

 
After identifying the above goals and subgoals, I identified the decisions that are associated with these goals as well as the information I needed to make those decisions at various levels. The result is a Relational Hierarchy (Figure 2). 

So, have I made my decision yet? Well, no… but thanks to the GDTA process I have systematically determined the information needed to make that decision. As new information becomes available, I can apply it to this framework. If another viable transportation mode is suddenly invented (e.g. teleportation), I can expand the analysis to include that mode of transportation. Has the COVID pandemic changed the way you are making your travel plans this Thanksgiving? Try doing your own GDTA to see if that helps. 

At its core, coaching is a form of individual and team development in which the coach helps to bring out the potential of the learner. The coach does this in a manner which supports, encourages, and most importantly, places responsibility for development with the learner (Dembkowski, 2006). There are four core qualities that make up every effective coach, no matter the style by which they lead.

1. Building Rapport and Relationships 
Rapport is the presence of a close and trusting relationship in which the learner and the coach understand each other’s ideas and communicate well. Rapport building involves getting to know one another, understanding where each other come from and what their background is, and most importantly spending time with one another.

2. Asking Questions and Listening
Where are you now, and where do you want to go? Helping learners gain insight through self-evaluation is a key part to coaching. Good coaches listen carefully, are open to learners’ perspectives, and allow learners to vent thoughts and emotions without judgement.

3. Providing Effective Feedback
Coaches that provide effective feedback focus on facts and observed actions, rather than personal reflections of what they think about the learner or team (Dembkowski, 2006). Feedback should be honest, but not judgmental. Good coaches recognize that an important part of their role is to challenge the learner, and giving feedback is a good way to deliver this.

4. Setting Goals and Delivering Results
Effective coaching is about achieving goals. The coach helps the learner set meaningful targets and identify specific behaviors for meeting them. The coach helps to clarify milestones or measures of success and holds the learner accountable for them (Forbes, 2010). Goals are much more likely to be accomplished if they are specific, and clearly defined (Dembkowski, 2006).

A Tale of Two Coaches
Bobby Knight, nicknamed “The General”, was the head men’s basketball coach for the Indiana Hoosiers from 1971-2000, and for Texas Tech from 2001-2008. While at Indiana, Knight let his teams to three NCAA championships and 11 Big Ten Conference championships. He also coached the 1984 USA men’s Olympic team to a gold medal, and has the third most wins in NCAA coaching history. Though we was highly successful, innovative coach, Knight is probably best known for his short temper, angry outbursts, and for throwing a chair across the floor during one of his more famous tirades.

Phil Jackson, nicknamed the “The Zen Master”, was the head basketball coach for the Chicago Bulls from 1987-1998, and for the Los Angeles Lakers from 1999-2004 (and again from 2005-2011). Phil Jackson coached his teams to eleven (11!) NBA championships, an NBA record. Jackson studied human psychology, native American philosophy, and Zen meditation to help him inform coaching strategies. He taught players mindfulness, selflessness, and would lead breathing exercises while burning sage in the locker room.

Technology and Coaching
The importance of coaching is evident, regardless of the style of coaching. However, finding a coach is not exactly an easy task. Until recently, the idea of going to the store and buying a coach for an activity that you are trying to improve on or become an expert in, would have seemed ridiculous. Technology has changed this. There is an endless number of apps on Google Play and Apple’s App Store that boast unique automated coaching experiences. Some of these apps can provide this unique coaching experience through artificial intelligence (AI), which is allowing for a more individualized coaching experience without human intervention. But, how can technology accomplish the four core qualities discussed earlier? Is it possible for AI to achieve features such as rapport building, and asking questions and listening? Even more complex, how does it account for different styles of coaching, that get results in different situations? How does it account for the General vs. Zen Master problem. A big part of this challenge is analyzing behavior based on understanding the learner and the performance environment. In my next installment, I will talk about how technology, and specifically AI, is beginning to overcome this challenge. What are your thoughts?


References
Dembkowski, S. (2006). The seven steps of effective coaching. Thorogood Publishing.
Frankovelgia, C. (2013, June 19). The key to effective coaching. Forbes. https://www.forbes.com/2010/04/28/coaching-talent-development-leadership-managing-ccl.html

Shabnam Mitchell is QIC's new Project Manager! An Agile Certified Practitioner, she has 9 years of experience applying Agile methodologies and frameworks to promote organization efficiency and success. Her experience comes from a wide range of exposures from the banking and financial industries to education and construction managing both large scale and highly critical projects. Shabnam holds an MBA from the University of Phoenix and a B.A. in Economics and Urban Studies from the University of Texas at Austin. Shabnam has led projects from corporate business continuity initiatives and small business change management projects to program and portfolio management through digital disruptions. Shabnam’s professional interests are rooted in simplifying challenging endeavors while engaging and enabling teams to take risks and do their best work, whether in the classroom, at the jobsite, or in the office.

I'll start this out like every blog post in 2020…COVID-19 sucks and has thrown a wrench into everything! From a professional perspective, it has affected us all in different ways, but overall it has forced us to rethink the way we conduct our work. As human factors|UX/UI researchers, this has greatly limited our ability to conduct live field research with human participants. Because of this, methodologies to collect data right now are focused heavily on online or remote approaches. Specifically, web-based surveys may be flooding your inbox. The general use of surveys have been around for quite some time, at a minimum of over a century within the U.S. (Converse, 1987). Web-based methods have been in use since the early days of the internet. Some state it was one of the most significant advances in survey technology within the 20th century (Dillman, 2000). "With great power comes great responsibility" (I'll attribute this quote to the late and great Stan Lee). Okay, so survey writing may not be a superpower, but it is a powerful tool for collecting quantitative and qualitative data when implemented correctly. Actually, if I can understand a person's behavioral patterns based on collected data, then that kind of gives me the power to predict the future. I guess I do have superpowers!

Despite the longevity and broad applications of surveys, I constantly come across poorly designed online surveys and it hurts my human factors brain. This is likely because anyone can create a survey if they want, especially web-based, but this doesn't mean you should. So what should you do? Work with professionals who are trained to extract valuable information from participants or respondents. It may seem like an easy task to do on your own, but being able to generate a valid and effective survey is as much of an art as it is a science. You don't become a great scientist or artist overnight, it takes time and experience to hone those skills. 

Think about it this way, if you're planning to use the data collected from a survey to drive decisions about a product design, an event, or whatever, don't you think it's important to gather the most informative data possible? Especially if these products or events cost hundreds of thousands to millions of dollars to develop. I'll answer for you…YES! So why are there still so many issues with online surveys? I say it's probably because people don't know what they don't know. They aren't aware or trained how to create appropriately worded questions, or organize the flow, or understand the factors that might influence a person's response to a question. And therefore, they end up drawing conclusions that don't accurately reflect respondents' views, behaviors, or beliefs. The end result may be a poorly designed product that no one wants to use.

​This is what the form looks like when you choose an answer. See any other issues with how it's designed? Maybe a color selection issue?

​Rating scales should align with the questions and be consistent. First, the scale should make sense when associated with a question. When Likert-type scales are used to gather responses, the lower end of the scale usually refers to less agreement, frequency, importance, likelihood, or quality. Do you see an issue with the scale below? Second, anchor labels could be used to show the extreme ends of the scale, but should still have an associated value (although it's best to have labels and values for every level of the scale to avoid confusion). Third, a label for the center of the scale should be provided because the middle may be assumed to be a neutral response. Fourth, the scales should be consistent as much as possible throughout the survey. Meaning, if you're using a 10-point scale, the don't make the next question a five- or seven-point as seen in the images below. This just makes answering questions more challenging for the respondents.

Avoid double barreled questions. The questions above are also designed poorly because there are multiple items in the questions that the respondents might not agree with. Asking the respondents if they prefer "workshops, panels, and training" to be online is taking away the ability for respondents to agree with one of those only. It may seem tedious, but these types of questions need to be reworded or broken out into separate questions.

Avoid leading and loaded questions. Do not force respondents to provide answers that don't truly reflect their sentiment. Below it asks respondents to select up to four, but what if respondents only agreed with one or two items? Now you're forcing respondents to provide biased answers that don't truly reflect how they feel or would behave. See a problem with this? Rephrasing the question to say they could choose up to four is different than saying they have to choose them.

Make sure the question wording is clear and well defined. Don't leave the wording of questions open for interpretation (unless that is intentional). Every included word should be chosen with a clear purpose. If you asked different respondents what "long run" meant, you would probably receive many different answers.

These are just some examples to highlight the challenges with creating a valid survey, although there are many other issues that can arise. It may not be obvious until you sit down to analyze the data that you have a complex data set and it's difficult (or impossible) to generate appropriate conclusions for decision-making. Don't waste your time and resources collecting worthless data when you can do it correctly the first time. You'll be happy, your boss will be happy, your customers will be happy, and the respondents will be happy to know their opinions matter. Contact us if you have any questions (no pun intended) or need support with your data collection efforts.