David Alex Lamb

On Thursday, November 9, 2023 CE, at 10:16 EST (by whatever network server my phone syncs with), I finished the last lecture of my university career. It wasn’t actually “my” lecture, with respect to content: my eldest offspring, Carolyn, was at a convention in Barcelona, and needed me to cover two of their lectures this week. But it was “my” lecture in terms of delivery.

Drawing Connections

You see, it’s never a good idea to just read the slides all the time. You do need to make sure you cover the material on the slide; students can benefit from the combination of visual (the information on the slide) and the verbal (the words someone speaks about the slides). So simply reading the slides still has some benefit, but so does rephrasing the material; some ways of explaining things might click with students, or some students, that other ways.

But what made it “my” lecture was what wasn’t on the slide, or even a paraphrase of it. It was things I could say, from my own experience and knowledge, that were related (at least tangentially), and which might enrich the learning experience of some subset of the students.

I am passionate about leading students to go beyond what they are focusing on in the moment, and open themselves up to a broader set of associations with other material they might already know, or what they might want to learn about once they realize there is a connection. One of my favourite technical examples is that when I teach about the Linux make program (which I have done in several software development courses), I point out the connection with what students learned in their discrete structures class: make performs a topological sort of a bipartite dependency graph and carries out instructions that annotate one of the two distinct kinds of nodes in the graph.

The subject of the lecture in COGS 100 (Introduction to Cognitive Science) was social cognition: how connections with other people affect how we think. This is something I’ve learned tiny bits about by “osmosis” – things I’ve read over the years but never studied in detail. I read the lectures in advance and asked Carolyn for clarification of a few points; I made notes on my phone with the clarifications, and with other things it occurred to me to mention. I told the students I could answer simple questions (though they never asked any, other than whether the slides would be on the learning management system eventually) and that they would have to wait until Carolyn was back for more complex questions. So, I was about as well prepared as a non-expert could be – which to me is the minimal level of competence anyone should expect of a substitute lecturer.

But what I really enjoyed was drawing connections. I don’t recall all of them, since several were things that occurred to me in the moment, but several came from my long experience as an academic. Here are a few of them; afterwards I’ll talk about how I feel about the lecturing experience.

Being a Scholar

In the Tuesday lecture I had alluded to an old article, “Artificial Intelligence Meets Natural Stupidity,” by Drew McDermott, which among other things talked about how, at the time of writing, it was common for researchers to name fairly ordinary data structures after complex pre-existing concepts that the data structure was trying to represent. But there’s a “fundamental principle of data modelling:” the only fully accurate model of the real world is the real world itself. Representing things in any model requires omitting details the creator of the model deems not relevant enough to the purpose of the model. So i cautioned the students to think carefully about how well computing terminology (not just in Cognitive Science) actually matches the pre-existing concepts with similar names. I told them how to find the article with Google Scholar.

In the lecture, I asked how many had looked it up. I didn’t want an answer and told them so, but I led into discussing life-long learning: how, when they left university, they wouldn’t have textbooks and instructors to guide them, and needed to develop the intellectual skills that would help them learn on their own. In particular, they needed to learn to go beyond the content of Wikipedia articles, to the original material on which those articles are based.

Personalizing the Topic

One set of material wasn’t an aside from me directly: Carolyn had, at my request, included a couple of slides about how most research on cognition was for neurotypicals, and autistics like me are considered abnormal. For example, supposedly we don’t have empathy – but more careful research has shown that autistics understand other autistics better than neurotypicals do, and neurotypicals understand other neurotypicals better than autistics do. Well, duh: it makes sense (and should have occurred to the researchers, if not for their bias against autistics) that people of any sort understand people similar to themselves better than people who are dissimilar.

I have become quite willing to tell people I’m autistic (which is not always a good idea), and was very happy to be able to relate something personal to the material of the lecture.

Right And Wrong Answers

There were a couple of places where technology could have made the lecture more interactive. There are systems (a mix of hardware and software) that can present a list of choices, gather answers from the audience, and show how many people picked each answer. Then the instructor can ask people to discuss with their neighbours, whether that convinces anyone wants to change their answer, and take a second poll. I mentioned the technology and said that it is useful to take the position that there are no wrong answers: that “wrong” answer is often a sign of a misconception that can be discovered, leading to a change of learning materials to guide people away from the misconception. And sometimes it isn’t even a misconception: when I teach the part of the Universal Modelling Language (UML) about relationships between classes, then ask people to group together and create a poster for a model of a specific problem, I commonly get some (perhaps most) add attributes to classes that actually represent one choice for a representation of a relationship. The real issue is that learning UML involves taking programmers at a particular level of learning to a new level requiring more abstract thinking. I needed to change my teaching approach to point that out, show an example of the ‘error,” and show them how the community of people using UML expects to represent that situation.

Feelings

I have alexithymia, common among autistics: difficulty recognizing emotions, both our own and those of others. So introspection about how I feel is difficult, and has a strong element of trying to interpret physical feelings and glimmers of mental ones, substituting analysis for intuition. But I’m fairly sure about a few of my reactions during and after the lecture.

I felt fairly comfortable and confident in the second lecture; in the first I had been a bit rusty. My lecturing skills have never been great but rarely bad. For most of my career I expect my lectures would have been described as fairly easy to understand but a little boring. There may have been a few flashes of brilliance – a few former students have told me of some – but for the most part I wasn’t as inspiring a lecturer as some of my colleagues (though perhaps a little better than a very few of them). It felt good that I hadn’t declined much in skill over the COVID gap.

I felt a little sad about leaving lecturing, but not a lot. I’ve always enjoyed finding good ways of explaining things, and I can keep doing that, in textual form. I can write short blog entries, and may be able to write long books now that I’m freer to do so.

I’m glad Carolyn gave me this one last opportunity.

On Monday, October 30, 2023, my friend and colleague Bill Kamphuis died, after a 3-year struggle with Alzheimer’s. The funeral home’s obituary was brief, and the only others I could find were essentially copies. So I felt moved to write a personal reflection about how he influenced my own life and career.

I likely met Bill sometime in late 1997, when my family and I started attending First Christian Reformed Church in Kingston, Ontario. I likely first saw him when he was playing the church organ, an unpaid role shared by several parishioners. I’m not especially social, so I didn’t interact with him much, but I do recall a general impression that he was a kind and thoughtful man.

I didn’t really get to know him until the late 2010’s, when my wife and I stayed at the same bed-and-breakfast a couple of years in a row for the Stratford Festival. In between attending performances, we would chat about a wide variety of things, but what I remember most clearly are his thoughts about Queen’s and his career there.

Bill’s subject was coastal engineering (which strikes me as wonderfully apt, for someone born in the Netherlands). Some of his academic accomplishments are listed at his Queen’s web page, but the thing that influenced me the most was that he wrote a textbook, Introduction To Coastal Engineering And Management. The first edition was published in 2000, the second in 2010, and the third in 2020. Bill told me that when he had taught the material for several years, one of his students encouraged him to write a book about it. I found his thoughts about textbook-writing to be inspirational. I had published one on Software Engineering back in 1988, but a senior Computing professor discouraged me from following up with revisions; it was a “poor choice of priorities,” apparently. He may have been right; within a few years massive tomes would replace the kind of concise work I preferred to write. Bill re-affirmed the idea that writing textbooks is a valuable contribution, and inspired me to start a monograph that maybe I can actually complete now that I’m about to retire.

If it’s every published, I’m going to dedicate it to Bill.

On Monday I sent in my official notice of retirement from the School of Computing at Queen’s University; December 31 will be my last day. At age 69 and after 39 years there (depending on how you count my 15 years of disability leave), it was time to accept that my mental health status is something Queen’s can’t accommodate. They’ve done fairly well by me in that regard since I returned to work in 2014, but the stress of being a professor at a university has become too much for me.

I’ve mentioned depression before, and commented how my 15 years’ disability leave for it had made it very difficult to achieve the research standards required for promotion from Associate to Full Professor. I am retiring as an Associate, which, by the Queen’s Board of Trustees’ rules, means I can’t get Emeritus status. But retirees are allowed to keep their professional email addresses, get access to the library, and (subject to resource constraints) share an office with some other members of the School. So I may still do a bit of academic writing from time to time.

Unlike some (former?) workaholics, I’ve been figuring out my post-retirement life for several years now, so I don’t think I’ll be facing the “what do I do now?” problem some of us have. At the moment that seems likely to involve fiction-writing, which has been my main hobby for quite some time. There are some academic books I’ve wanted to write for decades that might now be possible to work on (which is kind of a sad commentary on what my working life was like). There are things I’ve wanted to study for a long time; the last new major technology I learned may have been Java, back in the late 1990’s before I went on disability leave. Maybe I can finally learn how Unity works.

But a life of the mind isn’t the only thing I’m looking forward to. I’ve been working 2/3 time for the last year and a half (a “phased retirement” plan that became possible when the University Pension Plan came in a few years ago), and have come to enjoy being able to live a more spontaneous lifestyle than was possible under the pressures of full-time academic life.

I used to wonder how I’d feel when I finally retired. Since Monday, it’s mostly been relieved, peaceful and hopeful. I welcome this new phased of my life.

I have been offline since mid-April for health reasons, and returned to 450+ comments, almost all of which seem to be spam. I’ve enabled an anti-spam plugin, so hopefully when I’m fully recovered I can respond to comments sooner.

On the plus side (I suppose), it means Google has finally started indexing this site.

Today started off as one of those days where for a couple of hours I couldn’t get my brain out of second gear. First gear is barely enough to get out of bed and accomplish Activities of Daily Living (a phrase I learned from my psychiatrist recently talking about my need to drop one of my antidepressants). I had enough brainpower to safely drive to my morning errands, but not enough to write.

When I got home I sat in front of my “happy light” (a lamp to help combat Seasonal Affective Disorder, S.A.D.) I got out my journal and started writing “Morning Pages” by hand. My writer friends recommended this as a way of connecting one’s subconscious to one’s fingers, and make concrete whatever potentially interesting ideas might be floating around hidden below conscious perception. Mine usually start off as diary entries, and in the past I viewed that as gunk that wasn’t contributing to the “real purpose” of getting subconscious thoughts out in plain view. But this morning I realized that I could look at this as getting that “gunk” out of the way to allow the more interesting stuff out.

After that, I still wasn’t getting any story-related ideas onto the page. All I could think about is how, at the moment, I’m facing about a half-dozen story questions I have to answer before I can summarize the ending of my WIP as part of a synopsis that in theory I’m supposed to submit to my critique group next Tuesday. I have a list of story questions to answer (about 100 in all, for the full novel) and a few alternatives to each, but some alternatives for one don’t fit with some alternatives for others. I decided that what I need to do is look at the story questions and their alternatives in a different way: outline a few different endings, each listing which alternatives lead to that ending. It’s as though story questions and their multiple possible answers are two columns in a table; in essence, I had been focusing on story questions separately, when I should have been focusing on answers to those questions.

That lead to a realization that I was doing meta-meta-storywriting. “Meta” is a prefix that comes from a Greek word for “beyond” but which in Computing has come to mean “a ‘higher’ level that comments on or analyzes a ‘lower’ level of the same kind of thing.” So for data, like an image, there is meta-data, information about that image, like geotags and date it was created. Storywriting is the thing that matters most in the long run. Various kinds of writing preparation, like outlines, worldbuilding, and character sketches are meta-storywriting: writing about the storywriting. Planning how to do the meta-storywriting is meta-meta-storywriting.

So this morning I was two levels removed from what most people think of as writing, but it’s all part of the process a writer has to follow.