This blog was started as my reflections on the 2011 Change MOOC. It is now an on going journal of my thoughts on Higher Education, specifically teaching Biology.

Sunday, October 16, 2011

Goals #change11

Last weeks discussions regarding David Wiley's challenges to the MOOC participants, and Tony Bates webinar today, have really encouraged me to sit down and reflect on what I want to do in my classes.  Next semester I am presenting a Hybrid online/F2F class in biology.  This project is based upon an internal grant sponsored by our Center for Instructional Innovation.  Since joining the #change11 MOOC, I've had a lot of ideas about how to handle this class, and a lot of inspiration for other projects.  What follows is the basic ideas about the class.  This is still a work in progress.  But first, this class.

The Course:
The course is the first semester biology for our biology majors.  This is a heavy content class, with much of the content being required for later classes.  Students who do not take the time to incorporate foundational concepts tend to do poorly in later classes.

The Goal:
  • Encourage students to become active, independent learners.
  • Encourage students to learn the foundational concepts of biology.
  • Encourage retention of the foundational concepts of biology.
  • Encourage students to see the connections between different concepts of biology; to build in their mind a picture of the systems of living organisms.
The majority of students in this class are use to directive styles of instruction, and do not see themselves as independent learners.  The instructional management of this course will start off heavy, with additional resources provided to the students.  These resources will included online presentations, notes, links, and helpful hints.  As the semester continues, fewer instructor notes will be made available. Students will be asked instead to contribute notes, interpretations and content to the course wiki.

The class is hybrid online/face-2-face, meaning that each week, students will come to the lecture hall for face-2-face time, but then the remaining time will be online work. 
Online work
  • ePortfolio of work including a blog of daily activities.
  • Comments on the blogs of other students.
  • Access to online tutorials.
  • Online quizzes based in a learning management system.
  • Papers submitted for calibrated online review.
  • Participation in webinars, online help sessions, and discussion boards.
  • End of semester reflective paper (based on Prior Learning Assessments)
In class work
  • Time in class will be mainly devoted to question and answers, mini-lectures (5 minutes on a specific topic), case studies, and activities (such as working with molecular models).
  • There will be two assessments to determine comprehension and synthesis of information.
Student Assessment:
  • 1/3 of the student's final grade is determined by the performance in lab.  The instructor has very little influence over lab, so this is something I will have very little control over.
  • Students will receive points for daily blog activity starting during the first week and proceeding through the 15 weeks of he semester.  I should note that points are awarded on "sound participation."  What this means is that the student has posted a reflection on the topic, the post is intelligible and logical.
  • Students will receive points for the completion of online quizzes.
  • Students will receive points on in class assessments.
  • Students will receive points for the end of the semester reflective paper and all calibrated peer reviewed papers.
Course Assessment:
Qualitative studies have never been my strong suit, so I'm working on ways to evaluate the effectiveness of the course.  Some of the assessments will include:
  • Survey of Student Satisfaction
  • Review of Student Participation and Survey by external observer
  • Comparison of results of standard departmental questions between sections.

This is the current scheme of the course.  Comments welcome.

Tuesday, October 11, 2011

Opening statements on Open Content #change11

The work of David Wiley as an innovator and advocate are impressive, especially his current work on open textbooks.  The expense of textbooks is a topic that is dear to my heart, for as a science educator, I see the burden placed on students.  I guess it is one of the reasons I provide all of the lab materials to the students free of charge.  Of course, this makes me consider about opening up this material as open content.

I have yet to get through all of the sources provided, but my first concern regarding open content would be the quality of the material.  What is the review process?  Who are the reviewers?  What is the review criteria?  These would be my first questions (which of course may already be answered in the sources provided by David Wiley).

As to the challenge put before us, I would say that is two fold.  First is to provide and help students find open source material to further their biology education.  Even with a starting point provided, students often explore links and other sources when reviewing materials online.  As such, they become actively engaged in the material, which is a positive result.  For example, online games that allow you to look up answers through search engines provides a great example of becoming actively engaged in learning.

The second part is to encourage students to produce open content of what they have learned, be it a video, blog, song, or whatever creative outlet sparks their interest.  With varying levels of success, I have had students prepare videos on specific topics.  The greatest success was with a group of medical microbiology students who made videos on the immune system (some of their content is still available on our campus iTunesU site, if you can find it).  In the future, I would like to let them work through their own creative outlets, but still convey some accumulated knowledge.

This is just a brief introduction.  I need to consider this weeks challenge in more detail before I start building a map or other resource.

Monday, October 10, 2011

Collective Learning - Final Thoughts #change11

After my epiphany regarding collective learning, I've taken a chance to rethink my views on the topic and Professor Littlejohn's work.  Due to meetings, I was unable to attend the presentation on Friday, and hope to view it later this week.

First, collective knowledge is a reality.  No human holds the sum total of all knowledge, so we have to use external sources of knowledge to supplement our understanding of topics.  In the sciences, collective knowledge has been tapped for centuries, as can be seen with the correspondences between intellectuals and scientists since the 1600s (and earlier if you keep going).  In our modern world though, there seems to be disparity between academic disciplines in how, when, or even if, collective knowledge is tapped.

During a meeting on Friday, I had an opportunity to talk to people from English and Art about collective learning.  It was agreed among them that they preferred to work alone.  Collective learning, if any, was relegated to conferences and meetings.  From reading Professor Littlejohn's work, it seems that this is also the case in business and corporate collective knowledge.  I also realized that in academic settings, this can also be the case.  It can be amazing how many faculty members (both new and older) don't know how a university is administered.  There are at times some strange misconceptions that could be solved simply by asking.

This brings us to my first key in Collective Learning:  ask questions.  I feel we have built a culture that really does not like to ask questions, that it is seen as some type of weakness to look for knowledge from those around you.  Even my students are at first hesitant to ask questions, but it is the fastest way to access collective knowledge.  If one person doesn't know, they may at least know someone or some reference that can provide the information.  Does asking a question show a lack of knowledge, yes, but it also shows that you are cognizant of your lack of knowledge and are actively trying to correct that lack of knowledge.

My second key in Collective Learning: ask for feedback.  Culturally, we are also afraid of criticism, and this leads us to the self-destructive path of trying to be a lone wolf in our work.  Instead of going over to a colleague and saying "could you look this over for me?", we will sit alone and go over the work again and again until we convince ourselves that it is perfect.  This comes for a meeting I just had (about an hour ago) with a student over a lab paper, and then another about a test.  Instead of getting feedback from an external source, both just convinced themselves that their work or knowledge was perfect only to find out that it was not at the expected level.  We tap into collective knowledge when we get feedback.

The third key in Collective Learning is be open to new ideasI was at a meeting with other faculty members from around the university working on a new idea for the college.  What I discovered was that the older faculty members mainly focused on "tried and true" methods of doing things, while younger faculty members wanted to do projects that would carry with it name recognition (making a name for themselves).  None of the ideas were new, none were revolutionary, none were going to go to that mythical "next level."  Would they work?  In their own way, but there was limited openness to anything untested, untried, or innovative.  Collective knowledge is not stagnant, it is not codified and unchanging.  It grows as individuals and organizations grow, and you should experiment.  That is why being open to new ideas is so critical.  New ideas allow collective knowledge to adapt and expand.

Finally, be willing to answer questions and give feedback.  The worst thing for an eager learner is to come face to face with someone who won't help them.  Always take time to answer questions and to give feedback.  This is the only way for collective learning to be provided to the next generation.

Yes, I have focused on person-to-person communication of knowledge, but that is because people will know where to go for the information.  You could do a Google searches for information, and get back 1,000 sites of varying degrees of relevance.  Instead, you could go to someone in the "know" and ask them where they would start looking for the information.  In general, you'll get a better way of finding a useful site, and you will be a connection in your individual learning network.

Thursday, October 6, 2011

The Phenomena of Emergence (Collective Learning #change11 )

Yesterday, I joined the CIDER meeting Emergent Learning and Learning Ecologies in Web 2.0.  One of the other audience members made a comment to me that got me thinking.  We were talking about emergence, and I made mention of mathematical complexity.  The response was that we were discussing social emergence, and that math was just a metaphor.  That is what got me thinking.

A little background.  Chaos theory was just becoming big when I started my masters.  One of my professors, knowing I had a strong background in math, talked with me about it.  It also came up in a class on modeling ecological systems.  I kept up with complexity and chaos theory off and on since then (but it never became a major calling for me).  As a scientist, I also have been taught the supremacy of mathematics since I was in high school.  So saying that math was just a metaphor was odd, since all complexity theory ultimately originates in mathematics.

The specific thing that was discussed was regarding the imitation of the system, and that small changes at initiation can have a dramatic effect.  My ultimate idea here is that one person could throw the group dynamics into a spin and radically affect the forming social network.  But I sat with the idea of math as a metaphor, and that is when I was struck by an amazing similarity between what is being discussed with collective learning and emergence.  One point I made regarding codifying collective learning is the unpredictability of the initial system.  But it is not just the initial system, it is the individual(s) that make up the collective.

Where did this come from?  What the conversation reminded me of was a work of Science Fiction:  Isaac Asimov's Foundation Series.  If you are not familiar with the series, in the first book, a mathematician develops an algorithm to predict large scale societal trends in the future.  A foundation is built to "oversee" these trends, working for a "better" outcome.  The problem comes in the second book, because the one thing the algorithm can not predict is the actions of an individual, and one individual throws the entire system into chaos.  I know I have left a lot out, but this is just meant as a breif overview.

What is the point?  Ultimately, the individual is the important element in the collective.  How do you maintain a collective when one individual disrupts the collective?  With a large enough population, the collective maybe able to maintain itself, but a small one may not survive.  Think about that one disruptive student in a class.  How much of a problem do they make for the learning of others?  This is not to alienate one person, or to even say one system is better than another, but if you ignore that one individuals actions, it can have a damaging effect on any collective you try to build.  This becomes a question of leadership/management ultimately, but it can not be ignored when trying to build a #collective.

And how does this deal with math...well except for the reference to an algorithm to predict future societal trends by one person, which is in many ways analogous to small changes in initial state altering the behavior of the system, not much. :)

Wednesday, October 5, 2011

Collective Learning Environment - RPG and Fandom

I came home tonight, and while I was sitting and relaxing, a thought occurred to me.  One of the greatest examples of a collective learning environment, and one that has had a fair amount of impact, has been Role Plyaing Games and Fandom.  If your not familiar with these two groups, you might want to look into them.

I first got into role-playing games when I was in elementary school, and my mom thought it was one of the best (and worst) things that happened to me.  She use to tell people that when I got into Dungeons and Draagons, I started to read and study on my own.  I devoured books on medival Europe, became fascinated with classical culture, in high school took Latin, in general, I became a learner.  It didn't stop with me reading; I also talked to people, learned what they knew, got references from them.  I made connections.  Now, that was back in the 70's.  If you look at RPGs now, the idea of collective knowledge has exploded.  I have no idea how many sites exist for D&D alone, but just doing a quick search will find pages and pages of links.  I'll limit myself though to one specific D&D example:  The Forgotten Realms.

The Forgotten Realms is a setting designed for D&D that first appeared in 1987.  Since then it has spawned well over 250 novels, anthologies and graphic novels, as well as at least ten computer games, and a gaming phenomena called living campaigns.  Add to that the official game supplements published, which is well over 200 books, and you have an entire library about a fictional land.  But that is not all, since the advent of the internet, people have been posting their own "rules", ideas, compelations, and other such remixes of ideas.  The Forgotten Realms wiki, founded in 2005, has over 11,000 pages.  The Forgotten Realms General forum, housed at the D&D publishing company, Wizards of the Coast, has 915 thread with a total of 41,288 posts.  The Realms Lore Forum has 2,084 thread with 82,122 posts.  These forums were started approximately 4 years ago.  If you talk to people who play in the Forgotten Realms setting, they know extensive details of the fictional world, including geography, culture, and history.  Strangely, many of these people have along the way picked up a lot about humanity's histories and cultures, as well as real world geographies.

Fandom, groups of people who are fans of a particular author, movie, comic book, or series, are just as knowledgeable of the details of their interest.  Star Trek and Star Wars fans have been lampooned for years about the extensive knowledge that they hold regarding these two fictional worlds, but the point is, these people learned about these worlds.  Fans of Star Trek created a functional Klingon language.  You can even go to the Klingon Language Institute to learn Klingon!

While many may see these as anomolous, or fringe groups, even classify them with some form of psycological disorder even, the fact remains that people in these groups possess a collective knowledge, share that knowledge, experience collective learning, and even create new objects (even languages) from this collective expereince.

The question becomes, why would someone learn the history of the forgotten realms and not the history of Europe? 

My main answer would be that you are expected to learn the history of Europe, it is mandated by your school, by your parents, and by your society.  In essence, all the life has been sucked out of it.  The forgotten realms on the other hand is exciting, new, something that you can explore.  There is no expectation for you to learn what someone has decided is an important date or an important leader (even if the date or leader is important).  The keywords for this is explore, imagine, create

Now I need a period of reflection (and dinner).  I'm going to come back to this idea of explore, imagine and create a little later.

Collective Learning part 3 (Ah-Ha moment) #change11

This morning in my email box, there was a note that there was a comment in Jeff Merrell's Learning. Change. By Design. blog.  Allison Littlejohn had left a link to some of the presentation papers she and her colleagues have given.  I want to thank her for those links because they have helped to give me more clarity on her concept of Collective Learning.

As I have mentioned before, I don't see the concept of collective knowledge and learning as radically new.  The presentation paper entitled Charting Collective Knowledge: Supporting Self-regulated Learning in the Workplace, and some comments from John, are helping me to see Professor Littlejohn's position paper in more light.  And that light?  I'm not part of the intended audience.

I know it sounds simple, but a quote from Jeff really hammered this point home: "So the usefulness of Littlejon's work is in many ways as a framework for describing the environment and getting practitioners to reframe their thinking."  The practitioners mentioned are trainers.

This immediately sent me back to a day long workshop when I was teaching at a community college.  The President of the college decided that the faculty needed to learn better people skills, and he hired a firm to come in and train the faculty with "best practices."  These trainers faced a group of academics, and tried to "teach" lessons on how to handle phone calls and other "people skills."  I really don't remember anything after the first fifteen minutes of how to answer a phone; that is because the psychology faculty got into an argument with the trainers about why they were using 30 year old physiological tactics in managing people on the phone when these same tactics were shown ineffective 15 years previously.  I remember the ensuing debate, the psychologics, sociologists and most of the business faculty leaving (save for their chair).  I just went to my happy place and zoned out through the workshop.  OK, it was a bad mix all around, but I do remember that the trainers had no idea what they were in for when they came to the college that day (and the president had no idea that the faculty backlash would be so harsh...we all worked it out though).  One lesson learned, never put a group of academics into a remedial training class because one person has a bad phone presence.  The second, know your audience.

So, now in light of my new realization of audience, I can look over Professor Littlejohn's work with a fresh eye!  Therefore, it is back to the drawing board on Collective Learning.

Tuesday, October 4, 2011

Collective Learning Part 2 #change11

Yesterday, I posted my first response to the Collective Learning concept that is being discussed in #change11.   I mentioned that that I was missing a peice of the puzzle to Collective Learning, and I discussed how in science this does not seem like a new concept.  I was reading Jeff Merrell's post on Collective Learning at Learning.Change. By Design., and I think I found that missing peice.

I started to realize that the difference is in discipline training.  Not all scientists learn collaborative skills.  In my department there are some Principle Investigators that actually pit their grad students against each other.  Most labs work in a model where there is a collective knowledge pool, and it is shared, used, and built upon by each generation of grad student.  In addition, there is the collaboration between labs, that leads to even more growth in the collective knowledge of both labs (see yesterday's post for more details). 

What Jeff Merrell showed me was that in the model of business education, this lesson of pooling knowledge is not learned.  One quick tangent, I've actually taken some KM training courses through element K since it is free for the students, faculty and staff of our university.  I didn't make the connection until now, but there is a lot of jargon in KM.  This was another peice of the Collective Learning puzzle for me.  I could be completely off base, but it seems that KM wants to strongly codify learning so that it can be packaged for corporate entities.  This is where my issue with Collective Learning starts.  Not because it is about corporate entities, but about packaging.

The building and dispersing of collective knowledge in a lab or even between labs is not a cut an dry process.  It is an organic process that occurs based upon social interactions.  Like any social interaction, the initial steps can be hard to predict.  If you have a young grad student that is not confident in their knowledge or ability, they may not speak up when they actually have a valuable peice of information.  A worst case scenerio is when you have someone speak up before they have reflected or considered the question (or the person who just repeats what has already been said).  You can actually have people who actively resist participation in the collective, for example, the person who thinks that they are a lone wolf (but then feeds off of everyone else). 

Then there are the interpersonal issues:  from personal experience there were some people when I was a grad student that I actively disliked, usually because I had gone over the same protocol over twenty times and they were still doing it wrong.  Yes, these are based on face to face interactions, but the same is true in social networks.  How many times have you started to ignore someones post because they annoyed you?  What will you miss because of that annoyance?

My gut feeling is that codifying a process that can be described as an emergent learning system based on social network and personal interaction is a process doomed from the start.  The idea of codifying such a community construction, or a collective and dispersive knowledge pool, is based on an assumption that you can predict and control the initial interactions. 

Now, Jeff Merrell brought up two concepts that I'm going to end with:  Charting and the concept of individual  “practices, literacies and mindsets”.  Charting is a framework that I find questionable, because it is trying to establish a framework for an emergent system to follow.  The four C's of charting are a great alliteration, but it really feels like forcing a condition on an interaction.  In my mind I keep seeing the image of a group of people sitting around a table with straight jackets and ball gags trying to share knowledge.  It looks great on paper, but again it seems like your trying to fit a natural dialog into a report.

The concept of individual  “practices, literacies and mindsets” though is something I believe all of us are looking at when we start to incorporate new technologies into our teaching and learning.  This is the area of Allison Littlejohn's work that sparks new ideas, specifically the mindsets.

BTW:  If you have not read Jeff's post, I recommend it.  He provides a great summary of Allison Littlejohn's position paper.  It really helped me see her concept of Collective Learning in a new light.  Still not convinced it is really a new idea.  I'm looking forward though to the presentation later this week.  I'm still open to seeing if there is more to the puzzle of Collective Learning that I'm missing.

Epiphany...eLearning and Student Maturity Levels #change11

Inspiration comes when you least expect it!  If you followed some of my earlier posts, you may remember that I have had a problem trying to figure out how much direction and assessment to give students, verses the amount of independence provided to build their own learning environment and sense-making systems.  Last night, an old model presented its self to me.  My partner went back to school for a nursing degree and is currently in a leadership class.  He asked me if I could explain a leadership model presented in his book.  After a few minutes trying to figure out what he was talking about, I realized that it was the situational leadership model.  If I remember correctly, this came into vogue around the early 70's; I first came across it in the late 80's.  My partner's textbook did a horrible job explaining the principles (very bizarre and negative examples), so I started talking him through the basics.  Bill has a master's degree in English literature, so he is very familiar with education, so I started building a model of situational leadership between a teacher and a student.  That is when inspiration struck!

I'm not sure how familiar readers may be with the model of situational leadership, so I'll go through a part of it, and provide a few links to help explain it further.  The core idea is that the relationship between a leader and a follower (in this case teacher and student) is situational, meaning that it is based upon the level of maturity, skill and responsibility of the follower.  There are two metrics:  Task and Relationship.  The task is how much direction the leader must provide for the follower to complete the task.  The relationship is the amount of two-way communication needed in the course of the task.  Two metrics combined, provides four situations and four development/maturity levels.

The S1 condition is one where you have a person whose skill level is low for task competition (D1).  So the leader has to provide detailed direction and oversight.  In education (US), the equivalent would be an elementary school or middle school teacher helping a student learn how to write or do math.  You have to direct their learning.

The S2 condition is one where the person has growing skill, but they may not have the confidence in their ability and/or need refinement of their skills (D2).  In this case, the leader has to develop a two way communication with the follower, and take on a coaching role to build their confidence and skills.  In education (US), this would be high school and early college (hopefully).  This would be where you have the transition of a lecturer becoming a mentor, as you leave the directive and enter into communication.

The S3 condition is one where the person has the skill, but still needs some oversight.  It may be an issue of confidence, but I think of this situation as more of refinement (D3).  In this case you don't have to worry about the skill, it is more about the final product.  While the diagram above calls it supporting, I see it more as a collaboration.  In education, this would be graduate school, where the student has the knowledge and skills, but needs to refine their work to a higher academic standard.  That is where the major professor and graduate committee come in.  Their role is give the student the room to grow, but be there as needed.

The difference between S2 and S3:  In S2, the leader/teacher is the one who initiates the two way communication.  In S3, it is the follower/student that initiates the communication; this shows a growing independence.

In S4, the follower has the skills and confidence required to be handed a project by the leader, and the leader knows that the project will be completed to specifications (D4).  In education, this is where you have your academics.

The following is a quote from Situational Leadership®.

  Once a task is defined, each individual on the team is objectively assessed for Performance Readiness®, giving the leader the ability to fully optimize each individual’s contribution to the team effort. Situational leaders lead individuals who happen to be part of a team, rather than leading a team that happens to contain individuals.

This quote was when I had my moment of inspiration:  "To lead students who happen to be part of a class, rather than leading a class that happens to contain students."

A simple transition, but a powerful one for me to consider.  Added to that is the idea that I am looking at students who start out at different developmental levels.  Most of my students in Principles of Biology will be at the D2 stage, but I will have some D3 students.  Noting that, I can prepare and distribute a lot of supplemental resources, assess students and proscribe learning modules that will help them (coaching).  For the students that are already motivated, I can work with them on a more collaborative/supportive level.

Where do MOOCs fall?  I put them firmly in S4, where you have D4 participants.  I don't think we can expect this level from college freshmen and sophomores just yet.  Some junior classes, and most senior levels classes though could fit into the MOOC model.

Oh, almost forgot the link for a good overview of situational leadership: http://www.12manage.com/methods_blanchard_situational_leadership.html

Monday, October 3, 2011

Collective Learning #change11

I've read over the position paper posted by Allison Littlejohn, and listened to the interview points she posted on her blog site Little by Littlejohn.  After going through this, I feel like I am missing something.  I am left wondering if the author and her colleagues are trying to codify a process that could be better described as fuzzy or emergent.  It seemed an unnecessary complication with a lot of jargon that describes something that has been going on for years.  I know that it is looking at Web2.0 technologies, but for over 50 years this concept has been tried and true in the sciences, long before digital social networking.

In science graduate programs, when you start, you are coming into an environment where there is a strong pool of knowledge.  This collective knowledge is not only about your chosen discipline, but the research in the lab and all of the lab protocols.  As an example, when I first started my Ph.D. research, I needed to learn Gas Chromatography (GC).  I learned from the person currently using the instrument, then I read the manual and article pertaining to what I wanted to do, and eventually I became the expert.  So I started teaching others as they came into the lab.

It was also not uncommon to start corresponding to people in other labs who worked on similar projects, or who were doing things (procedures) that would help in your research (which I had to do during my Masters).  With email, the response time became quicker.  With a stronger internet, companies started putting documents on line.  We shared bookmarks and links between members of our lab, and with other labs.  Now with social bookmarking the process is faster.  If we really needed to learn a new protocol, it was not uncommon to visit the lab of someone who was doing that work.  Now we they can show the technique via skype.  While you may be taking classes, most of the education at the graduate level is done through networking.  So, I would have to say that based upon the model of collective learning, this is something that has been done for a long time in science; it's just now faster and broader.  Now with labs building websites with demonstration videos, blogs, and access to papers, we have broader access.  Still, you may never know about these resources unless you first talk to people in these labs.  (Even my major professor talked about correspondence and visits with colleagues back during his graduate experience...hence the 50 years or so of doing this type of work).

This is why I'm saying that I am missing something in the current discussion of collective learning.  I am not sure why the attempt to codify an emergent social process save to make it more marketable for the masses.  Even then, as a teacher, I'm not sure I can sell it to my students as a canned package.  It seems better to set up a baseline system and then with monitoring, let the interaction develop.

I'm going to continue reading, and I'm looking forward to Allison Littlejohn's presentation.  As I've said, I just feel like I'm missing something about the idea of collective learning.


Over the last week, I've been looking at digital scholarship (#change11) and reading through papers on a variety of eLearning  topics.  One thing that kept hitting me is the use of terminology.  One of the classes I frequently teach is an introductory biology course to our majors, and I spend a great deal of time trying to untangle misconceptions.  A common thread that I have seen in elearning papers and blogs deals with ensuring that students utilize resources that are valid (i.e., not some fringe knowledge that does not apply to the topic).  Well, this brought me to a pet peeve I have about certain words that I regularly have to disentangle from my student's thinking.

I'm going to start with one that most people are familiar with: Theory.  There are two main ways people define this word: one colloquial, the other strict. When I first ask students to define a theory, over 90% will tell me that it is a conjecture or a guess.  This is the colloquial definition, and one held by may people.  Yet, to a scientist, the word theory has a much stronger meaning, and one that is counter to the idea of a guess.  For a scientist, a theory is an idea that is supported by a large, and often growing, body of evidence.  A theory is an idea that is so robustly supported by data, that we consider it a good working model of the universe.  Another idea that people have a hard time with is that science can not provide Universal Truths, instead, we build models of how the universe works.  The more we can predict and control with these models, the stronger we see their value.  A theory is not a guess, but a model that is robustly supported.  It takes students a while to change their mode of thinking on this word, and it is one reason that there are so many disputes between scientists and non-scientists regarding scientific theories, like evolution.

Evolution is the next word that has to be disentangled.  When I first ask students to define the term, before we even go into the theories, I get two main responses:  it is about the origin of life and it talks about how organisms change.  While there is a fringe of evolutionary science that focuses on how life began, most work is actually done with existent species.  Now comes the big challenge; evolution describes how traits within a population changes over generations.  It is not about how an individual changes.  A common misconception is that individual organisms change over the course of their life, and that is what evolution describes.  In evolutionary theory, you are born with your adaptation range (your ability to survive), and you will life within that range, breed, pass your adaptation range to your children, and then you die.  Unless your gametic genes (egg or sperm) mutate, none of your life experiences will go to the next generation (if you know anything about epigenetics, then you will know that there is some flexibility in this).  As I often say to my students:  "you do not evolve, the human population in an area evolves."  Of course, we have the concept of psychological evolution, self-help gurus tell you of personal evolution, and new-age groups will tell of spiritual evolution.  The meaning of the word has degraded to a colloquial definition of change, but it misleads and detracts from the beauty of the strict meaning (and there is a great deal of beauty in evolutionary theory).  Even the concept of co-evolution, which again can be a truly astonishing event, is considered an individual alteration.

The last word of this pet peeve is ecology.  As an ecologist, there is a strict meaning of the word to me, but I know that colloquially, it represents relationships between organisms and other organisms, or organisms and their environment.  Sometimes, it is degraded to just being a mere habitat (or virtual habitat).  Ecology though has become a power word, symbolizing something new.  If you want to give a new spin, an intellectually inclusive spin, you tack on the word ecology.  Instead of dealing with urban blight or inner city social injustice, you deal with Urban Ecology.  Now, don't get me wrong, there are studies in Urban Ecology that are amazing and beautiful, but like so many thing, people use this umbrella term too broadly.  My pet peeve around the use of ecology is that once it is used, people then start to add in systems theories, complexity theories, and community theories.  Why is that a pet peeve?  Because they are already explicit in the word ecology.  When I see the word, and as I try to get my student's to see, my mind shifts immediately in to systems thinking; complexity is just another component of systems.  Modern community and ecosystem analysis, and even good population ecology, relies on systems and complexity.  As I've read papers over the last week, sometimes I feel as though I could not find why the author used the phrase learning ecology (more to the point, why ecology was used).

Now, I understand that terms change meanings over time, and that misconceptions are rampant.  I also acknowledge that different disciplines have co-opted terms with varying degrees of success; social sciences for instance have numerous human ecology sub-disciplines (many of which really look at the ecology of the interactions).  Most of the time, I find myself trying to figure out what an author means when they use a term.  For example, are they using evolution to say that individuals change to a stimulus, or that over time there is a change in the group?  Is ecology being used as a place holder for higher order relationships, or is it describing the complex dynamics of the overall system?

Ultimately, these are terms that many students have misconceptions about.  It's a pet peeve because every semester I have to disentangle the colloquial from the strict meaning of these terms.  So, more than anything, this post is about getting this pet peeve off my chest.

One final note:  Though I may have a pet peeve when I see these terms, I have to say that all the papers I've read over the last week have been enjoyable and educational.  There is something I have gotten from each of them, and my evernotes is growing with the ideas stimulated.  So, please do not take what I've written as a pejorative.