It’s been a while since I wrote about my teaching experience at Kenyatta University in Nairobi, Kenya. Here is a summary, a report card of sorts, on what I tried and what worked:
Face time with students: 22.5 hours
Classes have ended for the Spring 2012 semester. I provided nine 2.5 hour lectures totaling 22.5 hours for an entire course. On paper the semester runs from January 10th until March 27th, but I wasn’t given the green light until January 23rd.
That same day I rounded up students and started lecturing. In fact, I gave a full 2 hour lecture on neuroscience and important figures in the history of science and the scientific method without any preparation. Most other professors would have taken the day off, but that was already the third lecture, so I couldn’t.
On paper, students could have received a maximum of 12 * 3 hour lectures = 36 hours. They told me a standard course is 34 hours when I asked. But I feel pretty good about my 22.5 hours. I couldn’t have squeezed more in because (1) administrators were leaving campus around 6:30pm (hence why my lectures were 2.5 hours and not 3 hours each week, as I needed to return the projector.), and (2) classes did not really start until 2 weeks into the semester and I was strongly discouraged from providing a lecture this week (would have been week 10).
Last week I chose not to lecture on new material because the students deserve to have a review session (originally planned for this week). So they burn the candle /semester short at both ends. At the same time, when I asked students on campus whether they remembered ever having a college course to which their professor attended every class that he scheduled, they said no. So mine was the first class to offer 9 consecutive weeks of lectures without exception, as far as I can tell.
From my observations I would expect that most 34 hour classes are actually only 20 hours of instruction. Not because of any external influences – but merely because class scheduling is not given the same urgency as, say, an emergency 4 hour meeting at the ministry of health to discuss vision 2030 strategic aims. Yet I consider this university to be much better than many I’ve seen in Africa.
Most students I met there had 1 or 2 exams, squeezed in the back half of the semester, when professors realized they’d been teaching for two months and forgot to test their students. (How can it come as a surprise that semesters go fast if you’ve taught before?)
I on the other hand offered a quiz every week from lecture 3 through lecture 8, with a literature research / review paper due on week 9. Each quiz had 4 questions in various formats and took 15-20 minutes to complete. Not a lot given our 3 hour time slot.
Many of my quiz questions exposed students to different ways of testing.
Typically they had been exposed to True / False, Matching, Fill in the Blank, short answer, and essays. I introduced multiple choice questions, and several different types of short answer questions. For example, I’d present a plot from a paper and ask them a question that requires one to interpret data. I would provide them with 12 parts of brain anatomy involved in a function like learning or vision and ask them to pick 3 to describe in detail. It’s odd when given the option that people still pick stuff they don’t know well. And I would ask them calculation questions, descriptive questions, and questions that bridge two concepts.
Choice: individual or collective grades?
Sir Ken Robinson suggests that a more natural form of school assessment is to give groups of people a task and grade the collective product. I offered my students the option on one quiz of individual grades or collaborating on one shared problem. Each person would receive the same grade, and grades would depend on whether the problem was solved. They declined the group grading.
Case Study of a real life situation for a health scientist in Kenya
What I wished I did more of (every week!) was use case studies and hypothetical science policy dilemmas to facilitate group discussion and apply material to a real world problem. I devoted 20 minutes to a detailed problem based on a real situation where a pharmaceutical company approached an African country government for support in conducting a phase 3 clinical trial. Only as the students ask more questions more about the company’s ulterior motives are revealed. Only if they ask the right questions and dig for clues, that is.
Many of my students will find themselves consulting on health policy and yet have never had any questions like this posed. So I am preparing them to question information and not assume that what is provided is sufficient information to protect the rights and the health of Kenya’s people. They must think and work harder, or other suffer.
Incorporating inspirational TED talks and brief illustrations
Early in the course one of my major battles was to convince my students that their university wasn’t suffering from a lack of lab equipment and funding; it was suffering from a lack of creativity.
True, their labs were not as nice as those at Penn State or Tulane, but do to any of the experiments I was lecturing about in neuroscience would easily take an investment of $50,000-250,000. Realistically, universities don’t demonstrate calcium imaging or electrophysiology, or make a knockout mouse – they present movies about it.
And so I did. For every lecture, I downloaded 10-30 minutes of illustrations from youtube and presented them on our LCD projector.
Weekly TED talks of scientists solving the world’s problems were also essential. This one from an NASA bio-engineer was especially good on several levels:
Why so good?
- Every solution could have come from Kenya.
- Solutions were / had to be cheap, low tech, scalable, and sustainable.
- African American scientist as role model
- He’s really excited about science!
Using an online textbook seemed ideal at a university where they had only one copy of the “official” textbook. I declined to lecture from that book, though I had used it in a US Neurochemistry course. Instead I build my lectures from web material. All of my students refused to use the free online and interactive neuroscience textbook. Why? Because it was based on FLASH multimedia – not smart phone compatible – and not PDF-downloadable. Let this be a lesson that flash and Africa go together like oil and sugar in your gas tank.
As much as I think my students made a poor choice, I let them download and print out my inferior powerpoint lecture notes.
Final Exam Format
I’d been told by the admin that I could design a different final exam based on typical American college courses in Neuroscience. My teaching here was partly to spread innovative ideas and methods, though this is one area where the university hierarchy exerted rigid control of my classroom. After being told my exam needed to be submitted for review with just a day’s notice, I wrote a comprehensive one with 52 multiple choice questions and 12 short answer questions.
This was quickly rejected, and I played phone tag / appealed. Eventually I had to submit a final exam in the only allowed format. It must have 8 short answer and 4 essay questions, regardless of the subject. Imagine covering 1000 pages of material with only 12 questions? It’s not possible to be comprehensive or even representative of the subject.
Unless of course I only have 5 lectures… hmm… why did I think of that? Then the final exam would fit my half-ass devotion to covering the subject.
(Unfortunately I believe science education will transform Africa into the world’s center for clever innovation, so teaching like it doesn’t matter is out of the question.)
I would teach again, even for free, because my students clearly appreciated having a professor who took their future careers more seriously than his own.
I know they appreciated it because I have full attendance for every lecture except the last one (which might have coincided with a ton of other tests and papers assigned by all the other procrastinating professors).
- Introduction (Jan 23) Science fundamentals
- Scientific method applied to real world
- Four influential scientific thinkers (Newton, Kuhn, Popper, Feynman)
- How scientific theories evolve
- Molecular machinery of neurons (Jan 30)
- Ion channels (non-ligand gated)
- Types of receptors (ionotropic / metabotropic = ligand gated channels)
- Neurotransmitter receptors (glutamate, GABA so far)
- Biogenic amine neurotransmitters – synthesis, structure
- Ion pumps (Na/K pump, Na/Ca exchanger)
- Resting membrane potential Reuptake on neurotransmitters P
- resynaptic plasticity – amperometry – vesicle pools
- Kinesin and vesicular transport
- Fluoescent tracer analysis examples
- Molecular machinery continued and Neuroanatomy (Feb 6)
- 2nd messenger systems Intracellular signaling and homeostasis
- Neuronal communication – neural circuit types
- Nernst Equation – calculating resting potential
- Electrophysiology – vclamp, I-clamp, patch-clamp Feedback looping systems
- Neuroanatomy by function – Kandel section IV: Neural Basis of Cognition
- Broca’s areas
- Aphasias that reveal function
- Blood brain barrier
- “Love, Sex, and Reward” Neurotransmitters, drugs of abuse, and the brain’s reward system (Feb 13)
- Criteria for substance to be classified as a neurotransmitter
- Outdated “nucleus accumbens / ventral striatum theory of reward”
- Dopamine Norepinephrine / Epinephrine
- Anti-depressants Opioids, Morphine, Heroine Psychadelics (LSD, DMT, psylocybin, mescaline) Marijuana Alcohol, GHB PCP (angel dust) Methamphetamine (Csytal meth)
- Sex, orgasm, pregnancy – neuroendocrine – oxytocin
- Learning and Memory (Feb 20)
- Hippocampus Circuits – electrophysiological recordings of learning Experiments that reveal the mechanisms CREB Cfos / cjun / Ca imaging Amygdala & sham rage
- NMDA receptors, synaptic plasticity Role of newsynapses & subventricular zone
- Forgetting and PTSD – mechanisms, treatments
- Rehavioral learning paradigms & molecular mechanisms Classical “pavlovian” conditioning Operant conditioning Memory storage, retrieval
- Memory encoding: “Grandmother” cells in visual cortex? Watching learning in free moving rats – 2-photo microscopy Applysia: extinction and sensitization
- Diseases of the brain (Feb 27)
- Parkinsons Alzheimers Epilepsy Depression & Mania Sleep disorders Schizophrenia Drug Addiction
- Neuroendocrinology and the Sleeping Brain, Behavioral homeostasis (Mar 5)
- Hypothalamic-pituitary-adrenal axis
- Hormones, structure, function, synthesis, breakdown
- Pharmacology Pregnancy / birth control and endocrinology
- Senses: Vision, hearing, smell, touch, & taste (Mar 12)
- Visual processing Hearing Smell Touch Taste Smell – drosophila is a good model HeroRats – practical application Cerebellum – and motor control Brain stem – and body homeostasis Balance – vestibular system
- Complexity, Emergence, and Intelligence (Mar 19)
- Human Crowd-sourcing
- Social networks as tool for knowledge-based emergence Chaos, complexity, and the hidden order emergence phenomenon
- Neural Networks as prediction machines Prediction markets (InTrade) vs. Opinion polling
- Predicting future epidemics using the friends paradox to map social networks (TED).
- Rigorous error analysis of a complex system
- Iterative systems Fractals as an iterative math function (Douglas Hoffstadler)
- Recursion & Self-replicating sentences – cluster algorithm
- System Dynamics and causal-loop diagrams of complex processes
- The basis of intelligence: “Turing test” game Self-referential systems and mathematical recursion (why human intelligence cannot be programmed by a computer yet.)
- Computers vs human intelligence (serial vs parallel processing)
- Developmental neuroscience (Mar 26) & Course Review
- GABA / chloride flip in development
- Sonic hedgehog and the organization of the brain Similarities across species
- Human embryos reveal earlier animal types
30% – 5 announced quizzes + 1 unannounced quiz. A quiz is a 4-5 question “continuous assessment” test. Answers will be either written short answers, drawing a diagram to explain, or full essay explanations of a broad concept.
70% – Final exam – about 70 questions. Mixture of multiple choice, essay, diagram drawing & labeling, outlining how one would thinking like a scientist in a scenario, and problem solving.