Poison to Protection

If you’re paranoid of being poisoned, one possibility is to build immunity. Folklore suggests one king Mithridates of Pontus did just that. He’d take small doses of arsenic amongst other poisons and build up to larger doses, all while fighting Pompey and the Roman empire. An internet search for “arsenic eaters” will lead you to several articles about the famed Styrian arsenic eaters, a small community of Austrian peasants who were tested by consuming arsenic on food and seemed not to suffer any ill effects.

 

If you’re interested in the history, there is a very readable and relatively short article available on JSTOR by John Parascandola: “Pharmacology and Folkore: The Arsenic Eaters of Styria” (Pharmacy in History, 2015, vol. 57, no.1-2, pp. 3-16). I learned that arsenic was considered a possible medicine and cosmetic. I suppose that in low doses it would kill pathogenic bacteria and other microbes that might cause skin blemishes. I learned that the “Styrian defense” was used in murder trials: claiming that the victim regularly consumed arsenic, and perhaps took too much in a fatal dose. I learned that some indigenous populations in the Andes had an arsenic-metabolizing gene, likely from long-term generational exposure to higher arsenic concentrations in the water. And folklore-wise, I learned about a legend of “poison maidens” from India – assassins who could kill you with a kiss, having been “fed poisonous plants and venomous snakes form infancy, becoming immune…”

 

Since I’m interested in the origin of life, and I taught a special topics class on “Metals and Biochemistry” last spring semester, I now pay attention to chemical evolution arguments on why certain substances arrived “later” on the scene. New signaling pathways came into play as eukaryotes and multicellularity came into the story of life on Earth. Why is Mg²⁺ mainly internal and associated with phosphates and nucleic acids, while Ca²⁺ is mainly involved in extracellular signaling? Why are zinc and copper latecomers in various enzymes, nickel and iron are early, and molybdenum shows up somewhere in between? One of the reference books I used in class was The Biological Chemistry of the Elements by R. J. P. Williams and J. J. R. Frausto da Silva. So, I decided to read selections from their companion book, The Natural Selection of the Chemical Elements.

 

While skimming the book, I started to be intrigued by the idea that certain substances that were poisonous and deleterious to early organisms, eventually became incorporated into living systems. This popped up throughout the book, but comes together in the final summary chapter in a section (16.3) on “The environment and evolution”. The authors pose the question: “Did the change in environment drive the evolution or was there just random searching?” They provide a compromise answer in two parts: “(1) a poison, of necessity, gives rise to protection from it; (2) a protection can give rise to functional use so as to increase survival.”

 

Here's my summary of their argument using quotes from the text: “The protection against the poison involves at first greater production of the protein system most useful in handling this poison…” Inorganic poisons result in “sequestration and rejection” by pumping out the bad stuff. Organic poisons are destroyed by enzymes. “Thus, a poison increases the turnover of certain RNA (and proteins) and therefore of exposure of local regions of DNA.” This “exposed” DNA is “more liable to mutation, [thus] selection could drive improved protection… [locally] within that short section of the code… with little effect elsewhere on the DNA. The step from protection to functional use follows the same pattern since protection involves handling the elements and requires knowledge of poisons within the cell. The obvious step is to make the poison an extracellular messenger or part of an enzyme.”

 

As I’ve studied autocatalytic cycles to understand how proto-metabolism arises, I had mainly focused on what substances are favorably incorporated and why. I’ve thought about evolution and system expansion from the point of view of protometabolites acting as catalysts, crummy at first but with increased selection better catalysts persist. I had considered molecular parasites – things that reduce the stoichiometric factor to maintain autocatalysis – but I hadn’t thought about the role of molecular poisons. What if certain nitrogenous compounds were initially “poisonous” in some way (as many are still today)? Perhaps some of these compounds, as they were recognized as such, were then turned into messenger-type molecules which catalyze other reactions to allow system expansion? This is an interesting idea fomenting at the edges of my thought process. I’m not quite sure whether this idea will lead to something concrete I can test, but I’m now reciting the mantra “poison to protection”. And now I get to do more research!

Volume, Velocity, Virality

Soon we will be like ants. Seemingly mindless. Living as if we were in eusocial colonies. At least that’s what an extraterrestial observing Earth might surmise by looking at the largest growing entity on our planet. What is this entity? The Meganet. Huh… what? We’ll be looking at the features of a meganet from the point of view of David Auerbach, author of Meganets – subtitled “How Digital Forces Beyond Our Control Commandeer Our Daily Lives and Inner Realities”.

 

Let’s begin with Auerbach’s concise definition: “A meganet is a persistent, evolving, and opaque data network that controls how we see the world.” And why these three qualities?

·      “persistent because its value comes from it never being offline and never being reset… there is no way to restart or even pause a meganet without destroying it.”

·      “evolving because thousands if not millions of entities, whether user or programmers or AIs, are constantly modifying it.”

·      “opaque because it is difficult and frequently impossible to gauge why the meganet behaved in a particular way.”

 

The meganet is a complex system – more than the sum of its parts. It is tightly integrated with a tangle of feedback loops that make it impossible to predict what will happen next. Global weather and climate change are also complex systems. You can’t turn them off. Tiny entities, atoms and molecules, in the gazillions, contribute to macroscale effects that we can only partially model. And that’s even when we understand a lot of what’s going on from the physical sciences. Any large scale modern A.I. today? It’s mostly a black box to even the best computational scientists.

 

Why are meganets complex? Auerbach stresses the three V’s: Volume, Velocity, Virality. What makes a tweet go viral? Re-tweeting. A lot. Like spreading a virus. It’s an exponential increase. Even if every person that received a tweet echoed it to two other individuals who hadn’t yet, you’d reach over a billion people in just thirty steps. That’s a high-volume tweet. And thanks to fiber optics, it literally moves at close to light-speed. High-velocity! Humans might be slow, a botnet wouldn’t wait for us.

 

Auerbach provides plenty of examples: An Elon Musk tweet. Gamestonk. FarmVille. FaceBook. Those are some that I’d heard of. I learned more about the underbelly of the meganet, things previously unknown to me. And one thing stands out: the meganet essentially takes a life of its own. The original person who started the cascade has very little control of what happens next. Hiring an army of content moderators can’t stop evolution at such speed. You could shut the system down entirely. But then you simply have nothing. Auerbach delves into the insidious integrated relationship between meganet-gaming and money, from Farmville gold-mining operations to the “Corrupted Blood” phenomenon in World of Warcraft. I found his chapter on cryptocurrency and forced forks was particularly eye-opening.

 

We’re awash in fake news, fake pictures, fake videos. Or should that be AI-generated news, pictures, videos? Is it just the same difference? The problem, Auerbach argues in three pithy statements, is that:

·      “It is far easier to put information into the meganet than to remove information from it.”

·      “It is far easier for information to spread across meganets than for it to be contained.”

·      “It is far easier for information to be wrong than to be right.”

 

And it’s unclear if there are good solutions. Auerbach suggests a few in his final chapter on “taming the meganet”. But it’s unclear if they will work or if there is the will to even implement them. Perhaps the meganet is alive. Life finds a way. Living systems have evolved to be remarkably robust. But it is possible to kill them to extinction. Maybe that’s what happened on Mars. Or maybe if we dig deep enough we’ll find some microbes hanging out, waiting for us to provide them a flourishing environment. Could we pull the plug to kill the meganet? I don’t think there’s any going backward at this point. Will AI terminator-bots evolve? I think this less likely unless we’re remarkably stupid. But as we rely more and more on the meganet, it will reduce us humans to simpler modes of processing information. The curtain for humanity is when the machines reduce us down to its level.

Test Taking: Student Edition

If I were to recommend a book to students who are apprehensive about their math and science classes and want to succeed, it would be A Mind for Numbers by Barbara Oakley. Subtitled “How to Excel at Math and Science (even if you flunked algebra)”, it’s full of good advice, practical tips, uplifting anecdotes, and incorporates evidence-based learning theory. Will the students be willing to pick up a 250-page book? I hope so. It’s engaging, not difficult to read, and Oakley aims (I think) at the right level. Given that she flunked math and only became a scientist later in life, she knows what she’s talking about.

 

Learning science and math requires effort and perseverance. There’s no Matrix connection that can deliver the knowledge straight into your brain. This baseline assumption runs through Oakley’s book. Why is it so effortful? For one thing, we haven’t evolved those skills biologically. And also, these subjects have a higher level of abstraction and encryptedness. Her example: “You can point to a real-life cow chewing its cud in a pasture and equate it with the letters c-o-w… but you can’t point to a real live plus sign that the symbol ‘+’ is modeled after – the idea underlying the plus sign is more abstract. By encryptedness, I mean that one symbol can stand for a number of different operations or ideas, just as the multiplication sign symbolizes repeated addition.”

 

The practical suggestions in her book will have two underpinning theoretical concepts so it’s worth describing them briefly.

 

First, our brain is constantly switching between two types of thinking process: the focused mode and diffuse mode. Oakley says: “Focused-mode thinking is essential… [because] it involves a direct approach to solving problems using rational, sequential, analytical approaches… Turn your attention to something and bam – the focused mode is on, like the tight, penetrating beam of a flashlight.” In contrast: “Diffuse-mode thinking is also essential… [because] allows us to suddenly gain a new insight on a problem… and is associated with ‘big-picture’ perspectives. Diffuse-mode thinking is what happens when you relax your attention and let your mind wander… [its] insights often flow from preliminary thinking that’s been done in the focused mode.”

 

Second is the Einstellung effect. Oakley writes: “In this phenomenon, an idea you already have in mind, or your simple initial thought, prevents a better idea or solution from being found… [think of it] as installing a roadblock because of the way you are initially looking at something. This kind of wrong approach is especially easy to do in science because sometimes your initial intuition about what’s happening is misleading… sometimes it’s tough even figuring out where to begin, as when tackling a homework problem. You bumble about… your thoughts far from the actual solution…” I bet students looking at a problem set will find this feeling very familiar. It’s part of the process of learning science. I’ve certainly experienced it in spades.

 

Expert learners switch back and form efficiently between the two modes and avoid getting stuck. They also take the time to commit basic things to memory so that they can build on those foundational blocks (without having to look them up) and digest more complex material. Oakley devotes a few chapters to why, what and how you should memorize. She also has great tips to help get out of the black hole of procrastination. Memory and self-discipline are muscles, and it’s good to exercise them.

 

But let’s get to the meat and what students care most about (as if their grade depended on it!): Exams. In Chapter 17, Oakley writes (in bold): “Testing is itself an extraordinarily powerful learning experience. The effort you put into test taking, including the preliminary mini-tests of your recall and your ability to problem-solve during your preparation, is of fundamental importance… [Testing] has a wonderful way of concentrating the mind.”

 

Oakley provides a “Test Preparation Checklist” (with credit to Richard Felder). It’s a series of Yes/No questions. The instructions read: “Answer ‘Yes’ only if you usually did the things described (as opposed to occasionally or never).” I think this is a crucial distinction! And the more ‘Yes’, the better. Now on to the list. These are mostly verbatim from the book except I left out one repetitive statement and made minor truncations.

 

1.     Did you make a serious effort to understand the text? (Just hunting for relevant worked-out examples doesn’t count.)

2.     Did you work with classmates on homework problems, or at least check your solutions with others?

3.     Did you attempt to outlined every homework problem solution before working with classmates?

4.     Did you consult with the instructor when you were stuck on something?

5.     Did you understand ALL of your homework problem solutions when you submitted them?

6.     Did you ask for explanations of homework problem solutions that weren’t clear to you?

7.     If you had a study guide, did you carefully go through it before the test and convince yourself that you could do everything on it?

8.     Did you attempt to outline lots of problem solutions quickly, without spending time on the algebra and calculations?

9.     With your classmates, did you go quiz one another on the study guide and problems?

10. If there was a review session, did you attend and ask questions about anything you weren’t sure about?

 

And the final key one: Did you get a reasonable night’s sleep before the test?

 

My “Advice for Success” on my course pages covers this ground in the form of statements. I like phrasing them as questions and I might do so next semester.

 

Yes, I know this post is getting long but I wanted to cover one more thing that Oakley discusses. It’s counter-intuitive. She calls it the Hard-Start-Jump-to-Easy technique. I’ve never used it myself although I do a variant of it. Oakley first describes the ‘classic’ approach: tackle the easiest problems first so that you gain confidence in doing the more difficult ones later. I’ve never given this advice to students because I don’t do it myself. Oakley acknowledges that “this approach works for some people, mostly because anything works for some people. Unfortunately, however, for most people it’s counterproductive. Tough problems often need lots of time, meaning you’d want to start on them first thing on a test. Difficult problems also scream for the creative powers of the diffuse mode.”

 

Her advice: “start with the hard problems first – but quickly jump to the easy ones.” The first step: “When the test is handed out to you, first take a quick look to get a sense of what it involves.” (I tell the students they should always do this. I did so when I was a student.) Next: “start with what appears to be the hardest one. But steel yourself to pull away within the first minute or two if you get stuck or get a sense that you might not be on the right track.” The trick is to ‘load’ it into your mind, then “switch attention away from it… turn next to an easy problem, and complete or do as much as you can. Then move next to another difficult-looking problem and try to make a bit of progress.” Rinse, Repeat.

 

When I was a student, I would quickly glance at all pages to get a sense of the length and where the ‘big point’ questions were. Then I’d actually start from the first question and work my way down regardless of perceived difficulty. But I was good at quickly moving to the next one if I got stuck. While I like the logic of picking the hardest problem first, that requires me to waste some time figuring out which it is. And since I was trained to take exams quickly and under high pressure, my method is probably more efficient although not necessarily better. Oakley does point out caveats to her strategy and it’s worth reading Chapter 17 in full. She also discusses how to tackle test anxiety and has some good tips!

 

I very much liked Oakley’s book. I might have persevered further in math if I read it as a student when I was struggling in my college math classes. As an instructor, she reminded me that I can communicate ‘study strategies’ better to my students. I mostly assume that they will read my “advice” and use it, but the reality is probably different and I should make more of an effort to help students as a coach in this area! (I once asked a former student to write a letter to my G-Chem students, and I provide my P-Chem students the comments of previous students.) If you’re a STEM student and you’re reading this post, do read Oakley’s book!

Command Copy

Moving animals do a funny thing. I call it Command Copy. In Chapter 12 of An Immense World, Ed Yong explains: “When an animal decides to move, its nervous system issues a motor command – a set of neural signals that tell its muscles what to do. But on its way to the muscles, this command is duplicated. The copy heads to the sensory systems, which uses it to simulate the consequences of the intended movement. When the movement actually occurs, the senses have already predicted the self-produced signals that they are about to experience. And by comparing that prediction against reality, they can work out which signals are actually coming from the outside world and react to them appropriately. All of this happens unconsciously, and while it isn’t intuitive, it is central to our experience of the world.”

 

This is also why you can’t tickle yourself. Unless you have certain types of schizophrenia that may also predispose you to ‘hearing’ voices and ‘seeing’ delusions. It’s possible that in these cases, something goes wrong with the copy command or with the sensory apparatus. There are two types, as Yong explains: exafference refers to signals from the external world, while reafference refers to signals from the organisms’ own actions; “think of them as other-produced and self-produced”. The crux is that “these signals are the same from the point of view of the sense organs”. Apparently, Command Copy is how pretty much all organisms resolve this dilemma, which is a rather interesting fact.

 

Most of us humans are conscious of the act of making predictions. Our brain seems to have evolved to be an advanced-prediction organ. Consciousness seems to be built, or at least follow analogous rules to Command Copy. One might argue that sensing one’s environment and being able to react in a life-saving way to it (eat food! avoid poison!) is the basis of building a life-form that ‘survives’. To sense one’s environment, it must be able to distinguish self from non-self (the environment). It’s why we think of the simplest organism as a cell with a boundary – a cell membrane at the very least. (These ‘simple’ organisms are biochemically complex when you zoom in and try to elucidate its inner workings.)

 

While organisms have receptors that can respond to single photons or single molecules, by and large organisms react to analog rather than digital signals. Only when a certain threshold concentration of molecules has been ‘detected’ is a response elicited. While response to photon seems digital in that very first detection step, it is almost always coupled to an analog chemical (molecular) signal. Why is this? I’m not sure exactly, but I think it has to do with scale. To complexify, which inevitably involves a division of labor so that different molecular machines carry out different tasks, one has to increase in size. To maintain a certain semblance of stability (to ‘persist’ and not die or be dissembled), you can’t be so sensitive that a single stray molecule or photon disrupts your entire existence. By becoming multiscale, you buffer yourself against such indignities. But by becoming complex, you run the risk of system failure – hard to diagnose because complexity ties things together in circular Gordian knots.

 

As an origins of life researcher who studies protometabolism, this idea of Command Copy is fundamental to autocatalysis. There needs to be stoichiometric increase to grow in size and scale, a necessary ingredient for complexity (and survival). Hence, I’ve been examining reactions that do this at a simpler molecular level in a few steps. And what is exciting to me is that baked into these simple autocatalytic cycles is the potential (perhaps inevitable if an energy source and molecular food sources are available) to expand towards complexity. Command Copy in a sense is the heart of it all, although I’m still struggling to map my chemical level ideas to organismal level responses that Yong describes. There’s likely a continuum that connects these, and it’s what keeps me intrigued with research and the quest for answers to difficult questions!

 

P.S. An Immense World has been a marvelous catalyst for encouraging me to think deeper thoughts. Here are my previous blog posts on Yong’s book.

·      Magnetoreception

·      Body Electrolytic

·      Umwelt

Skills Beyond Content

Following up on my previous post on problem-solving skills related to course content, what other skills should we be teaching students so they will be successful beyond the classroom? Today’s post is on Chapters 10 (“Professional skills”) and 11 (“Teamwork skills”) from Felder & Brent’s Teaching and Learning STEM: A Practical Guide.

 

The five skills that Felder & Brent pick out are:

·      communication

·      creative thinking (finding innovative solutions to problems when existing approaches prove inadequate)

·      critical thinking (making and supporting evidence-based judgments and decisions)

·      self-directed learning (taking the initiative to identify one’s learning needs, finding the resources needed to meet the needs, and doing the learning)

·      teamwork

 

How are these skills developed? (I try to get students to see this process in my resident expert activity.) Felder & Brent provide the following pithy statements:

1.     You did something that required the skill for the first time. It probably didn’t go well.

2.     You reflected on the experience, perhaps got feedback from someone else, and tried again.

3.     The more cycles you went through, the more skillful you became.

 

I readily admit that as instructor, these have not been a bedrock part of most of my “standard” courses such as G-Chem and P-Chem. They sporadically appear usually when I have them in mind for specific but isolated activities. We do emphasize these to varying extents in my department’s Research Methods course, and I also include some of it (albeit a lesser amount) when I teach a special topics elective course. Felder & Brent provide multiple examples of how to incorporate these skills into courses. It reminded me that I should think both strategically and tactically how to build them into G-Chem and P-Chem.

 

Here are my smattering of thoughts.

 

I do call on students regularly in class to provide verbal explanations, often after a quick Think-Pair-Share activity. But I haven’t done much with having them write these out in a broader sense beyond quizzes (low-stakes) and exams (high-stakes). Suggestions from the book include asking students to write a 150-word memo “explaining your calculations and results to your project team leader (who gets upset by poor writing)” or explaining (perhaps verbally through a video assignment) “in terms that an average high school senior could understand”.

 

I could do more is to ask students to suggest why there might be discrepancies might take place in a measurement or a calculation. In G-Chem 1, we discuss this in stoichiometry, but not anywhere else thus far. In G-Chem 2, I have several thinking-discussion exercises where students consider physical and chemical factors that affect fuel efficiency, or the balance between thermodynamic and kinetic factors in an industrial high-throughput reaction. These have mostly been popcorn-style open-class discussions rather than having students work in a focused way in groups – something I should consider. I haven’t done much in the lecture asking students to create or improve an experimental design. (We do so in lab.)

 

Reading these chapters reminded me that getting things wrong is part of learning. I say this in class when the occasion arises, but likely don’t emphasize it enough. I’ve now added this to my “advice for success” page on my course websites. One thing I’ve done sporadically is introduce occasional errors and then ask students what I did wrong. On one occasion or two, I’ve provided several student answers of varying quality and ask students to rank them and justify their rankings. I should do these more; I think students found them helpful. I think the problem is that I’m not strategic about building this into my course as an important skill. Maybe this is the one activity I should strategically build into G-Chem. I’ve put this in bold font so that I remember! (I use my blog as a memory offload.)

 

Throughout their book, Felder & Brent advise instructors to only focus on one or two changes at most and not try to imagine a complete overhaul – which can be overwhelming. Okay, what’s the one thing I can strategically build into P-Chem? I’m going to pick teamwork in problem-solving. Because the new semester is upon me and I need time to be strategic about this. Felder & Brent suggest that a problem set have both individual and group parts. I could introduce one or two problems in each set that require a group solution. This means I should cut out some of the individual problems and design some actual good group problems. I’ve been telling students for years that learning P-Chem is a team-sport. I’ve introduced (low-stakes) generating mock-exam-question assignments, but I think the quality should be improved. Maybe I can even combine these two ideas so that generating questions is one of the group assignments.

 

I have not done much formally in the area of promoting self-directed learning skills other than my “advice for success” pages. I do have individual discussions with students in my office when they want to know how they can improve (usually after not doing so well on a midterm exam). I think I’ve often assumed that students have baseline skills in figuring out how to diagnose less-than-optimal strategies, but that’s not always the case. While I’ve occasionally implemented a one-off assignment idea, once again I haven’t been strategic about this. The more I think about all the things I don’t do that I could be doing, the more overwhelming it feels. I need to focus on improving one thing at a time and being strategic about it.

 

Felder & Brent anticipate the challenges an instructor might face when trying to introduce skills beyond content. They’ve got some memorable vignettes featuring student discussions outside of class about such assignments. They also emphasize two things that students need to “progress along the intellectual development spectrum: challenge and support. Students are unlikely to change the beliefs that characterize their current levels if those beliefs are not challenged… [When challenged they] are likely to feel threatened and often remain at current levels or retreat to lower ones. To avoid those outcomes, support must accompany challenge.” Much of Felder & Brent’s book is on this theme. Faculty members are characterized as needing to play two contrasting roles: “gatekeeper and coach”. I know I’m good at the first; but I’m still learning how to be better at the second role. Both are needed to help students truly learn.

Problem-Solving Skills

If there was a book I’d recommend to beginning teachers in STEM fields, it would hands down be Teaching and Learning STEM: A Practical Guide by Richard Felder and Rebecca Brent. If such a guide was available when I first started teaching, I would have made fewer mistakes and caused my students less grief. But even if you’re an experienced instructor, it’s still a great book. It was nice to read that many of my current practices are good ones (although I learned them through trial and error). There were also reminders of things I’d forgotten and things I should try out so I get better at teaching.

 

Today’s blog post is on Chapter 9, “Problem-Solving Skills”. There’s an excellent vignette at the beginning contrasting two students: one is methodical, practical, detail-oriented, good at lab, but not so comfortable with abstraction and mathematical models; the other is intuitive, quick, takes leaps (but can be careless and miss details), and very comfortable with abstraction and visualizing mathematical models in the mind’s eye. They are characterized as polar opposites for illustrative purposes; but the reminder (to me, the instructor) is that I need to ensure that my class helps both these archetypes.

 

The main question addressed by Felder & Brent: “What attributes distinguish problem-solving experts from novices? How can I help my students develop those attributes?” They provide a handy table as shown below. Let’s take each of these in turn.

 

Problem Classification. Experts see the deeper (and more abstract) features, novices can’t see pass the superficial ones. How can we help students? First, we should point out these structural aspects or attributes as we walk students through example problems. Get students to practice talking through these when they’re problem-solving; TAPPS could even be helpful here. Second, give students several problems with the same aspect (so they get practice see some variants) and then introduce a problem in which the first methodology fails but another works (so they see when something is not just a variant of the first approach).

 

Metacognition. Experts think about their own thought process while problem solving is taking place. The novice, on encountering a new problem, looks through the textbook or lecture notes, then picks one that seems ‘promising’ and attempts to barrel through using that particular method. How can we help students? Model metacognition. Think aloud while solving the problem. Show what happens when you run into trouble and work your way out of it. (Exam wrappers can also be helpful here.) Break down problems into manageable chunks. Get students to practice, perhaps using TAPPS.

 

Automaticity. Once you’re comfortable driving a car or riding a bike, you no longer need to focus on every single step that you carry out, which the novice has to do. How can we help students? Practice, practice, practice, is what I tell my students. That’s how one builds fluency. (If only I did so more myself when language-learning.) As an instructor we need to build in practice opportunities that are spaced out so that students practice recalling what’s important. Doing something just once and expecting students to “perform” on the exam is a fool’s errand. But be careful not to overload the students; they have other time commitments and other classes to attend to.

 

Self-efficacy. My PhD in chemistry didn’t teach me how to teach. But it did build self-efficacy because lots of things don’t work in research. It’s rare that the first thing I try works, and the fifth attempt might still fail. Many of my introductory chemistry students did “well” in high school and don’t know what it’s like to fail at something; some had a “bad” experience in high-school chemistry and arrive negatively predisposed. How can we help students? Provide some early wins on assignments; don’t start off with the most difficult thing imaginable to “set the standard” (for failure). Use a diverse suite of pedagogical strategies and mix-it-up in class so that you don’t favor abstract thinkers over ones who would struggle with these challenging concepts. Felder & Brent reminded me to “minimize speed as a factor in determining test grades” (I already use their rule-of-thumb in constructing exams, but my P-Chem exams are probably still too tight time-wise).

 

If you’re a new instructor, most of your brain space is devoted to trying to make sure you get the content “delivered” with as few errors as possible. But it’s worth paying attention to the aspects of teaching that Felder & Brent discuss. Learning STEM is like learning a foreign language, and it requires scaffolding and support for a student to learn problem-solving skills and progress (at least partially) from novice to expert. Much of chemical theory is abstract – we can’t see atoms and molecules, the fundamental building blocks of the discipline! I constantly need to remind myself of the curse of knowledge, that I’ve forgotten what it is like to struggle through learning how to think like a chemist. Mayhap I can help my students get over the barrier with less of a struggle.

Creativity: It's Slippery!

Am I creative? I don’t know. Depends on the definition. Can I and should I try to increase my creativity? Surely yes. Who would say no to that? And there are videos, books, seminars, all ready to help you unleash your creativity to a new you, a better life, or whatever promises are out there. Is creativity a new thing? Or is it just a new name of an old thing? That’s what author Samuel Franklin explores in his new book: The Cult of Creativity, A Surprisingly Recent History.

 

The word creativity turns out to be relatively new, gaining traction in the 1950s and continuing its boom trajectory to the present day. It also tries to occupy a new space. Geniuses are few and far between, but we don’t have to be genii to be creative. Humans are intelligent beings, but that doesn’t mean we’re all creative. But we can be. And that’s a space you should want to be in. So say advertisers hawking their wares. So say businesses looking to hire employees. So say self-help gurus who want to help you reach your potential.

 

Franklin situates the rise of creativity post-WWII in the United States. Business is booming. The menace of the Cold War threatens. Huge investments are made in science and technology. Fears of being conformists in a mass society stuck in a bureaucracy of technocrats rub against Romantic ideas of losing the individual and the narrowing of an open frontier. Psychology pivots into this space, designing tests to identify creative individuals. Ideals of the fine arts are co-opted. Franklin writes that for a “professional to be creative was not simply to be productive, though it was that, but also to model oneself not on the machine but on the artist or poet. It was to pursue work with an intrinsic motivation, a passion for the act of creation. It was to be more human.”

 

Chapter 1 of The Cult of Creativity is titled “Between the Commonplace and the Sublime”. That’s the protean space creativity is attempting to occupy. But it’s slippery. The psychologists were attempting to sort “human resources around a new notion of excellence for the postwar world. Creativity signified something more democratic than genius, yet more heroic than intelligence; more whimsical than mere inventiveness or ingenuity, but more useful than mere imagination or artisticness.” To solve the world’s thorniest issues, creative minds needed to be nurtured. Both art and science were needed to play an integral role in creative acts: to “approach technologies with wisdom”. And now creativity is imbued with moral weight, as if it were an imperative.

 

Franklin discusses and dissects the fad of Brainstorming starting in the 1950s. He then tackles the incorporation of self-actualization promoted by Carl Rogers & Co. Maslow is quoted discussing the freedom of the creative act, to become “our Real Selves”. Then Synectics makes its appearance in the 1960s. This opens the door to the marketing and advertising industries, which Franklin dubs “redeeming the manufacture of desire”. Education isn’t left out of this revolution and the Torrance Tests for Creative Thinking are still with us, even though longitudinal studies indicate a dearth in predictive ability of so-called creative ‘talent’. And thanks to the popularity of Richard Florida’s Rise of the Creative Class, creativity has become an overused word. We still don’t know what it means. The fusion of brainstorming, artisticness, usefulness, technology, has now morphed into “Design Thinking”. We still don’t know what it is, but it occupies that liminal space between the common and the sublime.

 

I spent a number of years reading the psychology literature on creativity research. I blogged about creativity multiple times. I even attempted to start up a creative cluster with student participants. I didn’t know what I was doing, and I gave up after a while to focus on more mundane concerns. I suspect that I exhibit some of the traits associated with creativity: divergent thinking, coming up with novel yet practical solutions, and I’m a bit of an iconoclast. I can move fluidly between big-picture strategic thinking and localized detailed tactics. I go my own way, in a different direction from the majority, and I’m mostly happy not to be bothered so I can just do my shtick. I’m not an evangelist of my methods (although I will share if asked). I don’t worry about whether I’m living up to my potential – I don’t even know what that means. Am I creative? I still don’t know nor do I care. And maybe it doesn’t matter. But regardless, I appreciated the lens of history that Franklin provides. It goes some way to explain my present nonchalance about creativity.

Pair Problem Solving

I use Think-Pair-Share regularly in my introductory-level general chemistry courses. It’s a nice way to inject a relevant learning activity to ensure students don’t spend too much time being passive sponges in class. It’s important that the question isn’t too easy to answer. And I always tell students ahead of time that I will be calling on them rather than asking for volunteers. That ensures everyone participates because no one wants to ‘look ignorant’ if they’ve been given time in class to think about something and check their explanations with a classmate or two. It’s quick and active!

 

I’ve done group problem solving for things that require some parallel work to generate data which then needs to be put together. Certainly it needs to be something that students cannot do alone easily in a short time period so they have to help each other divide and conquer! I don’t do this very often because it requires the right kind of problem to solve, one that takes a bit more time and resources. It also requires a bit more instruction and organization – I assign the groups to make sure there’s an appropriate ‘balance’ of different technical and communication skills.

 

I’ve participated in Pair Programming one-on-one with research students who are working on a coding project. When I’ve done this, the student is always the ‘pilot’ at the keyboard, and I’m the ‘navigator’ who watches for errors and makes (hopefully) helpful suggestions. I’ve only done this with a student who is experienced writing code and has taken several programming classes. I’ve never tried this as an instructor in a class, but then I don’t teach coding and would probably do a bad job at it.

 

What I haven’t done, but I just stumbled on, is Thinking-Aloud Pair Problem Solving (TAPPS). I’m surprised I hadn’t encountered it before, given that I read about pedagogy regularly and relatively widely. It’s similar to pair programming. Students work in pairs with one being the ‘explainer’ and the other being the ‘questioner’. This could work well if students are provided with a more challenging worked-solution of a mathematically-based problem. The explainer has to go through the solution step-by-step with the questioner asking for clarification if something is not clear or potentially providing some help if the explainer gets stuck. Or the pair could be trying to work out the solution to a problem in which case the ‘explainer’ is akin to the ‘pilot’ or ‘problem-solver’ who writes things out while the ‘questioner’ could function as a ‘navigator’.

 

I think TAPPS could work very well in mathematically-dense physical chemistry courses. I’m starting to look over my course materials for P-Chem 2 this semester to see where I might be able to incorporate TAPPS; or at the very least I will make notes to myself as the semester proceeds of what I can change for the next iteration of the class. It could also work in G-Chem 2 for some of the more-involved problems. I will probably need to experiment a little with the parameters of what works and what doesn’t. I’m sure it will also take some rejiggering of the course content so that sufficient time is given for a TAPPS activity.

 

One potential concern I have is that students may feel uncomfortable with having their working-on-the-fly process be exposed to another student, especially if they are not confident in their understanding of the material. So it might require some other less threatening pair activities earlier in the semester, and then have the same pairs tackle TAPPS activity later on after some trust has been established. To balance things out, maybe TAPPS problems should come in pairs so students take turns being ‘explainer’ and ‘questioner’ even in a single session. Since TAPPS should be aimed at something longer and more challenging than a Think-Pair-Share, different pairs might also work at different speeds so I’ll need to build in something to address this.

 

Anyway, I’m excited to potentially try TAPPS in my classes. Maybe an old dog like me can learn new tricks!