I know, a lot of faculty are disgusted with the trend of taking business ideas and applying them to educational principles. After all, in a business model, are the students our customers or our product? And what of the companies who are hiring our students, should we be striving to make sure they are satisfied?

Nonetheless, just like the field of information processing developed countless useful and sustaining theories through using the computer as a metaphor, we can certain look to other disciplines outside of education for learning about how to be better professors.

Today, I wanted to look at the six pillars of Steve Jobs, http://technolog.msnbc.msn.com/_news/2011/11/11/8758769-the-6-pillars-of-steve-jobs-design-philosophy, as a means of identifying what each statistics professor should be striving toward.

Pillar 1: Craft Above All Else

I know I can’t be alone in thinking about teaching as my “craft.” As stated in prior weeks and in future weeks, there is no substitute for a faculty members formally studying how students learn and to truly focus on the craft of pedagogy.

Pillar 2: Empathy

Steve Jobs felt that the designers at Apple needed to have Empathy for the needs and desires of its consumers. For the professor, we have to be empathetic to the needs of our students. This some times means being tough. We do our students no favors if we “kind heart” our ways into letting them through the class without mastering the material. Moreover, we must hold our students to a high level of success, including time spent studying. Currently, the typical college student in the US is studying 14 or so hours a week, meanwhile they are socializing 60 hours or so a week. I encourage you to look at your institutions most recent NSSE data (National Survey of Student Engagement) as it will give you an indication of how many hours your students are actually studying. Nonetheless, a little bit of empathy to the challenges facing our students can go a long way to getting them to that next level.

For my students, here is how I show empathy.

- I recognize their schedules are tight, so I keep the homework assignment s consistent at about 1 hour a day, 6 days a week. This level of consistency makes it easier for students to schedule their time.
- I recognize that some of my students have weak math backgrounds, and I provide them with links to visual demonstration (e.g., Mathematica) and for math practice problems (e.g., Khan Academy), so they can build up their skills.
- I am always sympathetic to deaths, unexpected pregnancies, and money problems, however, I tell them my sympathy will not equal academic success. Sometime students simply have to retake a class, as though I care greatly about my students, I am giving them no favors by letting them through the class without the knowledge.

Pillar 3: Focus

This part should be easy … stay focused on helping students to master the critical concepts of applied statistics, and that they master the skills of answering questions using statistics.

Pillar 4: Impute

This is a trickier one, as Impute has two definitions. Interestingly, they both are relevant to the teaching of statistics. Impute is to focus on attributes. Great statistics professors help students to focus on the attributes they need to possess to be successful in statistics. Thus, great teachers should take the focus off of them and put it on the students’ behaviors. Students then recognize that their success is directly linked to behavior. This translates into first helping students development a sense of academic self efficacy, a belief in their own personal success, coupled with a belief that through effort they can get smarter in statistics (incremental view of intelligence). Once these beliefs are securely in place, the right kind of studying behavior (e.g., daily involving self testing) should follow. And though this won’t guarantee appropriate student behavior, students who do not believe that their behavior can make a difference will most certainly fail to be successful in applied statistics.

The other definition of Impute seems to be very business focused in that it view people possess about a particular product. However, as it relates to statistics, great professors help students understand the importance of statistics in answering important questions in their field. Thus, their view of the “quality” of applied statistics must be nurtured, particularly in an age where there is so much anti statistics sentiment.

Pillar 5: Friendliness

There is a Dunkin’ Donuts near my house. The workers there are not particularly friendly. If I had a choice between getting my tea there or going without tea, I’m selecting the latter. Meanwhile, there is a Dunkin Donuts about 15 minutes from my house. It is never “on the way” to any where I might be going. However, no matter what time of day I visit, no matter how busy they are, I’m always greeted with such friendliness. These pleasantries assure that I will go out of my way just to get my tea.

Why wouldn’t that be true with students? If we are friendly, do you think they might go out of their way for us, by coming to class or visiting us with questions during our office hours? Think back to your favorite teachers. Sure, I’d be annoyed with that sicken sweet friendliness, I’m guessing many statistics professor would be. But isn’t part of what made this professor among your favorites because he or she was happy to see you and friendly (sometimes in a cranky sort of way)?

Pillar 6: Finding simplicity for the future in metaphors from the past.

Steve Jobs used this Pillar for technology design, but doesn’t it work in teaching statistics as well? Being parsimonious is what we teach is paramount. This helps students to build solid foundations and continue to build upon them as they learn. Unlike the Piagetian idea that the initial schemata formed by children ceases to exist when new and different information come s into play, by us presenting information parsimonious, making sure students master each component, we can continue to build their schemata throughout the semester, and if done properly, they will continue to grow and develop long after they leave our classes. One of the ways we can help students with this cognitive foundation is through the use of metaphors from their past.

Some common metaphors I use are:

For estimating the standard deviation and variance from a sample to a population, I use the fruit bowl example. With the small bowl (sample) taken from the Large Serving Bowl (population) ever be more varied? Less varied? Equally varied? This concrete metaphor is something students can grasp and understand, and build the knowledge of a biased estimate upon it.

For Power, the metaphor is the missing shoe. What is the probability of finding the missing shoe given it is stored in your closet? What if there is little mess (variability) in your closet. What if it’s very messy (high in variability)? What if more than one person was helping you look? Of course, we would never even waste on time on such an endeavor if we knew the shoe wasn’t there in the first place.

As I write this, I am thinking to myself … having a month where we talk about metaphors we use in teaching applied statistics seems like a good future topic. Though we will be sticking to the topic of what makes a great applied statistics professor for the remainder of this academic year.

Conclusion:

Statistics are the tools of business, science, health care, and education. It is the one discipline that can have a home in every college of every university, as it functions as a basis for helping us to find the consistency in what is otherwise a sea of variability. In the shadow of the death of Steve Jobs, it seems fitting to take his perspective of greatness in product design and applying it to greatness in the classroom. Craft above all else, empathy, focus, impute, Friendliness, and Finding simplicity for the future in metaphors of the past, are attributes and behaviors clearly seen in great applied statistics professors.

Yet, I end with a reminder … though using analogies and metaphors are a critical way to advance our understanding, including in the teaching of applied statistics, the business metaphor and education can only go so far, as often what it the most fiscally expedient and what is the most educationally sound could be at odds. In the end, if we do not train our students to think and reason and use the tools of epistemological development, of which applied statistics is one, it is safe to say our economy will not grow … thus I end with a common but critical quote, we must all be careful in education to learn from all great minds, but never be, “Penny Wise and Pound Foolish!”

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