Assumed: 1 plus 1 is 2

What assumptions do we make on a regular basis? Should we question those assumptions? If we learn a fact, can we assume it will always be true, or should we re-validate it at some point? Let’s explore these questions a bit by considering some examples.

Some things we learn early in our life journeys that often appear to be facts; once we learn them, it seams reasonable to assume they will always be true. For example, 1 plus 1 gives us 2, and the sun will rise each morning and set each evening, regardless of whether we’re able to see it or not throughout the day.

The sun does appear to rise and set every day, and we understand that to be true due to the rotation of the earth, and its orbit around our sun. There may be clouds that prohibit us from seeing it, but it does rise, nonetheless and brings with it daylight, which goes away when it sets. That is a fact. There's no need to question it, right? As long as the earth continues to rotate and orbit the sun, the sun is going to rise and set each day. But is this a Midwestern US viewpoint. Would someone living on the Arctic Circle make the same assumption? Or might they assume it will rise and set most days, but that there are times when they assume the sun will never rise, and other times it will never set—daylight never arrives, or leaves? Maybe perspective has something to do with the accuracy of assumptions.

Recently, I had an opportunity to interact with an unsophisticated chatbot program, and the conversation started out like this. (My responses to the chatbot are shown in italics.)

Enter your name:  Dave
Hi, Dave! I am Francie. I love studying about women in tech because they inspire me!
Year you were born: 1957
Did you know that Intel built the first microprocessor in 1971?
It happened -14 year(s) before you were born!

Negative 14 years before I was born?!?  Did the chatbot author assume users of their program would be born after 1972? Seems like they ignored nearly half of the population. Maybe knowing our audience has something to do with the accuracy of assumptions.

A decade ago, when I started teaching at the university level, all I knew to do was lecture, so that’s what I did. That is all I had experienced in my many years of undergraduate and graduate courses, and I assumed that is what university teachers did. I assumed it must be the best way for students to learn, because if there was a better way, professors would use that approach, rather than lecture. After teaching a semester or two, I started adding some activities to my class time, and discovered that students responded well to them, and seemed to better learn the material. That started me down a path to discover active learning and the flipped learning environment, and I’ve never gone back to lecturing.

Similarly, all grading I’d experienced had been point based, so I had assumed that was the best (and maybe only) way of tracking and establishing grades. A few years ago, a fellow faculty member introduced me to specifications grading. After trying it in a course one semester, then two courses the next, I’ve been using specifications grading in all of the courses I have taught since that time. Using points to determine grades no longer adds up for me. (Previous posts about specifications grading s are here and here.)

I recently tweeted the following, which perhaps gives some insight as to why many teachers don't change.

I was recently accused of being a boat rocker, based on the following quote from Stephen Brookfield’s "Becoming a Critically Reflective Teacher". I'm taking it as a good thing.

"Teachers who are seen to be reinventing themselves and their practice can commit cultural suicide without even being aware that it is happening. As they speak about how they’re questioning and reevaluating their practice or how they’re doing things differently, they run a real risk that colleagues will see them as engaged in an act of betrayal. They are whistle-blowers on the culture of stasis—the collective agreement not to rock the boat by asking awkward questions or doing things differently."

Maybe past experiences help develop assumptions, but there is a real need to consider altering those assumptions based on new experiences and knowledge.

And in case you’re wondering why I’d question the assumption that 1 plus 1 will always give us 2, you made an assumption, and likely were not even aware if it. You assumed that the math being discussed was being performed in an integer base greater than 2. Obviously (at least for us computer people), the correct answer to 1 plus 1 could be 10, if we’re performing the math in base 2, rather than base 10. Both 2 and 10 are valid answers, depending on the base being used.

What assumptions have you made in the last day, week, or year that perhaps you should have questioned, or sought clarification? Did you know what “base” you were supposed to be using, or should you have confirmed that before spending time and effort, and then having a disagreement with someone who arrived at a different answer because they were using a different base? Was it you who were “off base”, or them—or both of you? Maybe context has something to do with the accuracy of assumptions.

Have I titled this blog post incorrectly? Is this a better title?

Assumed: We should always be willing to check our assumptions and seek clarification, because 1 plus 1 is not always 2.

Based on these examples, it appears that perspective, our audience, past and current experiences, and context are all helpful ways for us to check the validity of our assumptions. Or have I made a wrong assumption?

Image credit: http://www.publicdomainpictures.net

Creativity as expressed in HONR 296 final projects (spring 2020 edition)

Back in March, I wrote about the 68 ways learners in my Honors College course shared as ways to exhibit and document knowledge and understanding. I also described the course final project, which, in summary, was to create a tangible artifact that recorded their responses to the course’s essential questions, as it related to their chosen major(s) and/or minor(s).

The learners ended up creating visual art (2), making bread, creating collages (2), writing computer programs (2), doing a demonstration, writing an essay or report (2), creating a GIS map, creating infographics (2), writing a journal article, creating music (2), recording a podcast, writing poems, creating a poster, developing a PowerPoint presentation (2), and recording videos (2). I asked all of the students if they were willing for me to share their work. Eighteen of them responded positively, and the rest of this post is devoted to showcasing what they produced.

I encourage you to read to the end of this post, and click on all the images and links to experience the full breadth of how these students understood computer science and algorithms to impact their current and future lives. In the interest of brevity, I have not provided any commentary on them, but rather have provided a very brief description and an image or link for you to investigate further. They are not listed in any particular order.

Dan Council (left) created a GIS map of the US (along with a report), showing the correlation between education level and internet access.

Julia Steele wrote and recorded an informative podcast about her experience with computer science and algorithms, which you can listen to here.

Michaela Cox (right) created an infographic providing a variety of statistics and information about how algorithms impact us daily, ending with "continue saved game?"

Ally Swank (left) created a piece of art using nails and yarn to produce an image of a manta ray. She provided a report which described how the art represented a computer system, our inter-connectedness, algorithms, and the use of computing technology in marine biology research.

Eliza Roark (right) created a series of drawings and then used a program to convert them into ASCII art. Shown here is her drawing of Katherine Johnson of NASA fame.

Kurtis Stuckey explored the differences between live and computer generated music by writing a brief piece of music, playing it himself, and then having a computer play the same music. He recorded a video demonstrating this, along with a bit of commentary.

Ben Eger (left) wrote a simple Python program to display ASCII art and respond to the course essential questions. A brief snippet of code and sample output from the program are provided.

Nick Burrell wrote a report wherein he responded to the course essential questions. He ended with the observation that computer scientists "might be facing job insecurity in a decade or two as we develop more and more algorithms that are supposed to be self-learning. These algorithms could one day potentially write code that is so similar to human code that companies could just use these new algorithms to write programs for customers and cut out the original coders in the process."

Tauri Hagemann wrote a set of poems to address the course essential questions. Here is one of them.

we praise technology for the services it provides,
easier access, easier operation, easier life.
humans are so focused on progress,
there’s no thought of the consequence.

remote learning makes professors more available,
allows things to go on as normal amidst crisis.
except for the student who’s paying through scholarships and loans,
who can’t afford his own computer or laptop
and who doesn’t have internet at home.
he doesn’t know how he’s going to do schoolwork now.
he fears for his future and how he’ll keep up.

social media helps us stay in touch over time and distance.
but we think not of the girl who stands in her room,
crying to herself while she stares daggers at the mirror,
pinching at her stomach even though she hasn’t eaten in days.
she starves herself and curses her reflection because
she doesn’t look like the girls on her Instagram feed.

self-driving cars make travel faster and easier,
except when something goes wrong.
if they crash, who is at fault?
the passenger? the car dealer? the manufacturers?
either way, an accident has killed someone.

we praise technology for the services it provides,
but we give no thought to the consequence.

Ben Smith wrote out his responses to the course essential questions, and then took those words and fed them into an algorithm he developed which converted them into music. A portion of the music score and audio resulting from his efforts is available. After you click on the link, click on the small triangle play button in the top left of the page to listen to his creation.

Lauren Andrews (left) created a poster relating various computer science concepts to the human body. You can view a portion of her report and poster, where she discusses caching, in the provided image.

Drew Thomas (right) created a PowerPoint presentation titled "Coding for non-programmers" wherein he described in simple terms what he does as a computer scientists. A sample slide is provided.

Emma Staicer (left) created a collage to visually represent how business analytics and the course essential questions relate to everyday life. The background, person with hypnosis glasses, phone, things swirling out of the person’s head, and the  hand reaching for the person all represent different aspects of this relationship.

Genevieve Risner (right) baked bread. She observed that Amish friendship bread starter could be used in a variety of recipes, and it made her think that it could be a computer. The code would be the recipe itself and the variety of ingredients added would be its data. An example of a successful algorithm is shown. There were a couple of less than successful attempts that needed further debugging.

Autumn Auxier provided responses to the course essential questions in the form of a scientific journal article. The opening paragraph of the discussion section is provided here.

I am coming out of this class better understanding more about myself, my career, and life than I ever would have expected in a computer science course. Because I took this class, I have a better understanding of my own career in biology and I can answer the four essential questions of this class in reference to my career. Because most of my career has been dedicated to learning how to write scientifically, I chose to write this paper in the format that I would a scientific article as part of relating this class to my major. Further, because I have focused much of my academic career on research, I have been able to apply what I have learned about computer science to how I will continue to use it in my career as a researcher, no matter where or what I might be researching.

Chloe Wineinger created a compilation of SpongeBob SquarePants video clips in response to the course essential questions. I didn't know cartoons could be so educational. You can watch her compilation here.

Lexy Scheele (left) created a collage in response to the course essential questions. The brains, chickens, girl, black and white graphic, buildings, watch, and car all symbolize different parts of her response.

Jonathan Le (right) created visual organizers describing how video entertainment tropes work by using algorithms to simplify many aspects of our life for maximum effectiveness and efficiency, even when it is considered to be an art form as compared to a practice that follows a rigid logic structure. His organizer for the algorithm for the progression of weapon effectiveness is provided here.

So, there you have it. Eighteen different responses to the same prompt. Leaving an assignment open (as opposed to strictly defined)  provides the learner an opportunity to explore their passions, and thus they are likely to more fully engage with the assignment. It also makes the evaluation of the assignment a lot more interesting, since they are not cookie cutters of each other. Learner-centered teaching for the win.

What interesting assignments have you had? Describe it in a comment below.

Image credits:All images were provided by their creators.