Immunology from the bedrock

A draft course introduction using a problem-based or non-linear approach to teaching immunology:

google presentation: Immunology from the bedrock

Immunology is non-linear/Immunology from the bedrock/

A draft prezi on building a course in immunology that builds on prior knowledge. I think we also need to consider efficiency, efficacy and motivation. Highly motivated students might learn more effectively under a ‘logical’ or linear mode; less motivated or highly burdened students might benefit more from a non-linear, prior-knowledge approach. Finally, learning styles might also make a difference. Global learners for example might benefit better from a “bottom-up” or logical/linear mode of teaching, while concrete learners might learn better using a “top-down” approach based on prior knowledge. Then again we might see the former as theory based, the second as problem-oriented.
So, crudely, perhaps:
linear non-linear
bottom-up top-down
logical prior knowledge
global concrete
theory-based problem-based

.prezi-player { width: 550px; } .prezi-player-links { text-align: center; }

Teaching Immunology from the Bedrock

Recently I had the opportunity to ß test an introductory lecture for an Immunology course using the guiding principle that students learn by constructing new knowledge (constructivism)  on a bedrock of prior knowledge.  This general notion is supported by studies of long-term potentiation which indicate that new synaptic connections create the substratum for long-term memory best when learning is repeated with rest times between stimulations.  Moreover, long-term memory seems to be firmest when

  • learning is intermittent
  • learning times are relatively short (<15′ per “segment”)
  • learning modes are varied
  • reinforcement requires using knowledge in different ways
  • reinforcement accesses higher order thinking (eg. Bloom models)

The problem for classroom teaching  of the subject of Immunology is, then: how to identify the prior knowledge of students, and how to teach in such a way that new knowledge is constructed so that it is ready as prior knowledge for the next teaching session.

Traditional approaches have used mixed learning strategies such as readings and homework to supplement didactic learning.  Most if not all current textbooks use a similar sequence of chapters, starting with “fundamental immunology” in the first part of the course and ending with “clinical immunology” in the latter part.  A first chapter summarizes the cell types and anatomical structures of the immune system, followed by a chapter on “innate immunity” (moving from the last chapter of the book to the first about 6 years ago).  Then follows a series of chapters which purport to construct knowledge of immunity on the basis of fundamental knowledge: MHC molecules and antigen presentation; T cells and their receptors; B cells and their receptors and so forth. This strategy develops a sequence of topics based on logical categories that more-or-less follow the presumed ontology of the immune response: the sequence of presentation  seeks to  mimic a presumed sequence of events or processes in nature.  Thus we learn that cells respond via innate responses to antigens to stimulate T cells to stimulate B cells to make antibodies, resulting in a variety of functional and dysfunctional effects.

The theoretical advantage of a course built on ontology or on logic is that it is independent of the prior knowledge of students: all we have to do is ensure that students have a minimum competency in the area (using placement strategies, remediation) and then build on the minimum competency.

The disadvantage of this course is that is forces someone else to provide the remediation, or blocks student access to the course.

But ontology has nothing to do with prior knowledge, which is knowledge that we (or our students) happen to have before entering the classroom.  It is like starting a course in macromolecular design with a discussion of quarks, charm and spin.

Can we design a course around “prior epistemology” rather than ontology?    To construct a course of immunity on the basis of prior knowledge, we’d start with what student already know about, which is not likely to be the various types of white cells, anatomy, innate immunity, MHC and antigen presentation, and so forth.  In fact, prior knowledge of immunology is likely to reflect things that the general public knows about: vaccines, transplantation, allergy and autoimmunity, HIV. These are the topics typically taught at the end of a course in immunology.

The proposal:  start the course with clinical cases, examples, things that students already know about and are interested in.  A large fraction of applicants to our PhD program, for example, claim they want a PhD in immunology because a family member has autoimmune disease.   Then, why not start with autoimmunity? Or, most students have or know someone with allergy or asthma.  Then, why not start with allergy?

Here’s the new sequence that might evolve:

Concept map of Immunology (using Tuft University's Visual Understanding Environment). Green: exogenous factors. Pink: human interventions. Blue: endogenous processes.

We might start with any of these major areas, but Type I allergy provides a convenient path that builds on prior knowledge, because it relies to a large degree on a single class of antibody, IgE, with a relatively simple mechanism. Most students will have heard of antibodies and know vaguely what they do. Most students will have heard of anti-histamines. Most students will have heard of anaphylactic shock.

Allergy =>description of mechanism of allergic manifestations (down-stream causation) and treatments of Type I disease (which provides the basis of nearly all other immune pharmacologicals), then efficient causes of allergy (chiefly, IgE). =>treatment of IgE structure and function; B cells, mast cells, anti-inflammatory drugs.

Then generalize from IgE to Ig and the full array of antibody functions: opsonization, complement, neutralization, autoimmune disease,Types II and III hypersensitivity and the efficient causes of class switching. Granulocytes and macrophages.  This is where we first learn about cell trafficking.

This leads to discussion of antigen/antibody diversity => VDJ recombination, somatic hypermutation and affinity maturation,  AID, germinal center reaction, T cell help, CD40.  Hapten-carrier phenomenon.

This leads to discussion of  T cell help: signal 1 vs signal 2, cytokines, TCR and nature of T cell antigens. Th1 vs Th2.  T cell trafficking.

This leads to concept of antigen presentation by MHC molecules and processing; MHC-restriction in the molecular sense.

This leads to concept of MHC polymorphism and MHC-restriction in the genetic sense,  transplantation, matching.

This leads to bone marrow transplantation, thymic education, self tolerance; cytotoxic T cells and virus-resistance.

Finally, we need to understand how T cells are activated, so we reach the end of the course with a discussion of dendritic cells, revisiting antigen presentation, bringing in co-stimulation of T cells, and introducing Toll-like receptors and other innate mechanisms.

IGRa: Introduction to Graduate Research (reading and parsing science)

BCM Term I     IGRa Reading and Parsing Science      Wed 11-12 a.m. Room N901

In this segment of IGR we will learn tools for handling the scientific literature: searching, recording, annotating, reading , interpreting ,critiquing and presenting.   We will analyze one paper in some detail,  Alves-Filho et al. (2010) “Interleukin-33 attenuates sepsis by enhancing neutrophil influx to the site of infection. Nature Medicine 16: 708.

1. Aug 4 Outline of course.  Problem identification. HW: access Pubmed, Endnote,CiteLike, google docs; post 5 citations from Pubmed to CiteUlike; create EndNote .enl file; read OPTEMA chapter (2.2) and send in a 7-bullet OPTEMA analysis of research rotation.

2. Aug 11. OPTEMASM and Reading Strategies; Operations

3. Aug 18  The Typology of Scientific Sentences; students present OPTEMA analyses of figures

4. Aug 25 The One Figure Journal Club;  Instructor presentation  Differentiating Hypotheses and Predictions: students present analyses of text associated with figures

5. Sep 1 (T) Typology of citations      students present analyses of hypotheses

6. Sept 8 .  1 Fig JC   students present analyses of citations

7. Sept 15  1 Fig student presentations (2 presentations)

8 Sept 22  1 Fig JC Student presentations (1 presentations)

Enter your email address to subscribe to this blog and receive notifications of new posts by email.

Join 3 other followers