Computer Programming or Software Development

My friend Pat Yongpradit has a post on LinkedIn that got me thinking. It starts with a key statement “Computer programming (coding) is not equal to software development.” Now I tend to think of those as similar if not identical but Pat points out that “Computer programmers and software developers are codified differently in the BLS data” BLS is the US Bureau of Labor Statistics BTW.

Interesting. So what is the difference? Computer programmers write code. The BLS describes computer programmers:

Computer programmers write, modify, and test code and scripts that allow computer software and applications to function properly.

Software Developers do more. The BLS describes software developers as follows:

Research, design, and develop computer and network software or specialized utility programs. Analyze user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis. Update software or enhance existing software capabilities. May work with computer hardware engineers to integrate hardware and software systems, and develop specifications and performance requirements. May maintain databases within an application area, working individually or coordinating database development as part of a team.

‘A lot more words in that second job description. The BLS projects growth in the need for software developers and a decline in the need for computer programmers. I’m not so optimistic. My read on many of the layoffs in tech companies appear to me to be more about declining numbers of software developers. I could be wrong and maybe there are/were a lot more people just doing computer programming than I think. The industry keeps changing.

In my very first software jobs, back in the late 1970s, I would characterize my work under the software development description. While I did do some programming from specifications and design documents written by others (computer programming) I rapidly moved into meeting with users, analyzing needs, and designing and developing software and utility programs. Job titles may have been different but that was the work.

What may happen is that software development involves less coding than it has in the past because of AI. At least coding by humans. So BLS is probably right about a decline in the need for computer programmers. At the same time, if software developers spend less time doing actual coding they may have more time for higher level (if that is the right term) thinking and involvement in design. Unless AI starts doing more of that. So maybe we will not need more of them. Or perhaps AI will make it possible for more people to be software developers who wouldn’t be that now. We’ll see I guess.

My undergraduate degree is in Systems. One of the goals of the program was to train people to interface between most people and computer systems. In other words, to understand the needs that people/businesses have and translate it into what computer programmers need to know to write software. For a long time, that sort of work involved two sides and sometimes three. That is to say, sometimes there was a user/client, and analyst, and a programmers. Sometimes the latter two roles were one person.

Knowing how to write code was always essential because code is the language of computer science. Not knowing how to code was seriously limiting for someone trying to design software. I think that is always going to be the case at some level. So I think software developers, even those who prompt AIs, will always need to know some coding. More than just coding though, I think that students, anyone who is going to interact with computers and that incudes, of course, software developers, needs to have a background in computer science.

Computer science is not just coding but having an understanding of how computers work. What is computer logic? What is computational anyway? AIs have a lot to learn and people with a computer science understanding are who AI is going to learn from. We need to think of K-12 computer science as computer science – foundational ideas and concepts – and not just a class in how to write code. We need to prepare people to be software developers not computer programmers.

Mike Zamansky has a couple of recent posts on why CS still matters in schools that I think are worth a read:

• Why CS Still Matters
• More on why teaching CS matters

Interested in seeing what the BLS thinks of employment changes because of AI? Check out Incorporating AI impacts in BLS employment projections: occupational case studies

Selling AI Before It’s Time

Artificial Intelligence has been big in the news the last few days. A lot of the talk has been about the Trump administration designating Anthropic a supply chain risk. The US  Department of Defense (its official legal name) was unable to agree to contract terms with Anthropic. You can read Anthropic’s statement here. Statement on the comments from Secretary of War Pete Hegseth

There are apparently two sticking points. 

The use of Anthropic’s AI model, Claude:for:

• the mass domestic surveillance of Americans
• fully autonomous weapons.

The first on general principal. The second because Anthropic does not believe that AI is ready for handling fully autonomous weapons. I’m surprised (OK not really) that the first is an issue because the DoD says that using it for mass domestic surveillance would be illegal (probably true) and that they would not do it. Well, some of us remember the CIA snarfing up data on Americans by getting data from overseas so I can see why Anthropic might want more assurances than “trust me.”

The fully autonomous weapon control is potentially even more concerning. Anthropic doesn’t believe their AI is ready for that. I wonder if it ever will be ready. There are reports that OpenAI’s tools took part in mission planning for the recent strikes against Iran. There are also credible reports that those attacks hit a school and killed over 80 school children.  Did AI pick the targets alone? Was there human oversite? I have no idea but clearly things were missed. At least I hope they were missed. I’d hate to think that event was intentional. Dare we let AI make these decisions?

There have been some studies of AI used in war games. These studies have resulted in headlines like “AI simulations constantly opting for nuclear strikes, terrifying study shows” AI models do not have human sensibilities or share human ideas of going too far. Apparently, these AI tools have not been trained to follow Asimov's Three  Rules of Robotics. I wonder if the people developing AI today are aware of them. I doubt that many government officials are. Nor do they really understand the risks of AI controlling weapons.. No one really does but if the developers behind a tool say it isn’t ready perhaps we should believe them!

I was reminded of the old Paul Masson advertisements where Orson Wells would dramatically declare “We will sell no wine before its time.” The point was not to rush things and to let the process complete until the wine was completely ready. It appears that some people are pushing AI in places where AI is not ready to perform adequately. That is very unlikely to give a good result.

Who Is Driving Changes to Computer Science Education

There are a lot of Changes happening at code dot org The Slashdot article linked there lists several of them. While the changes include a number of people changes including President Cameron Wilson stepping aside, Chief Academic Officer Pat Yongpradit leaving to join Microsoft, and some staff layoffs the change in direction, to AI, may be the most concerning. From Hour of Code to Hour of AI? Some interesting comments follow that post.

The questions top of my mind are "who is driving the direction of CS education" and "is CS education moving in the right direction?" A lot of people believe that industry is pushing CS education in the direction of being vocational. The new focus on Artificial Intelligence often feels like a vocational direction.

My involvement with computer science education predates code.org and even CSTA so I have seen a lot of changes. In my first teaching days computer science teachers were pretty isolated. There was SIGCSE which accepted K12 teachers though welcomed sometimes felt like aspirational rather than actual. ACM, of which SIGCSE was and is still a part, was doing some support for CS education. Cameron Wilson was a huge part of that and worked policy.

CSTA was developed by some wonderful people in and around ACM. This started the real movement towards expanding K12 CS education. CSTA helped train and organize teachers to push for more more CS education. Code,org came a bit later and brought something new to the effort.

Code.org brought money and industrial production values. From the first set of videos that went viral to some very good curriculum resources as well as connections to industry and political leaders. Getting policymakers to push for CS education stepped up.

We’ve come a long way.

Coming back to my earlier questions. Is industry driving the directions that CS education is moving? A lot of people think they are. Industry has money and it has funded a lot of the work by code.org and CSTA. The modern Golden Rule is that the people with the gold make the rules after all.

Industry has some motivation here. I spent a few years working at Microsoft myself where my job was to promote the use of Microsoft tools for teaching. I didn’t get much in the direction of what to teach. I always felt that teachers should decide what to teach and I just wanted to help teachers find ways to use tools to teach those concepts. Teaching computer science as vocation was always there though. Senior mangers often told me that industry needed more people to know CS because there were jobs that needed to be filled.

CS as vocation has always been a selling point for CS education of course. It’s what helped sell school boards and other elected officials. Among teachers that was usually a secondary motivation. For a lot of teachers, including me over time, CS education became more about understanding how the world works. We don;t teach physics because we want to make more physicist. We teach it so that students understand the world around them.

People who are not working for tech companies often have to use computers and make decisions about computing. From spreadsheets to databases to internet searches. And now AI. People in all walks of life use computers. Understanding computer science can make those people more efficient. Computers are an important part of our world.

It seems like all the big tech companies are betting huge sums of money on AI. There is a lot of pressure to move the direction of CS education into AI. Is the industry push vocational in intent? Is is all about helping these companies to make money? CSTA and code.org are both pushing AI these days. Is this because of industry (gold making the rules?) or would it be happening independently?

That leads to the second question – are we moving in the right direction? I think that question may be different for K12 and for university. Personally, I still think CS education in K12 should be about understanding and not vocational. Someone else can address higher education but K12 should be about preparation for life and not for vocation at least in comprehensive schools.

So is AI the right direction? I think it is indisputable that AI is important to learn. Students should learn prompting and they should learn what AI can and cannot do, They should also learn how to think about what AI should not do. They need to know something about how AI works and that is core computer science.

I think that computer science, in the old analogy, is the dog and AI is the tail. The tail should not wag the dog. Making AI the focus at the expense of basic  computer science would be a huge mistake. We do have to teach the basics that make AI possible. Students need to understand where AI comes from and where it might go. Understanding code is an essential part of that understanding.  There is always going to be more to CS than just AI. We didn’t stop teaching arithmetic when calculators were invented. We should not assume that AI code writers mean we don’t have to stop teaching basic computer science.

CS in K12 should not be just vocational. Is industry driving CS education? I fear they may be. Are we moving in the wrong direction? Maybe. If so, it will be up to educators to provide some course correction. 

AI Tutors and the Human Connection

I  recently shared at quote on Facebook:

Unless our students know that we care, they will not learn from us.

I made the comment that I wondeedr if an AI teacher will get students to think it cares about them. I really believe that a connection between student and educator is important for a good educational experience. Several people on Facebook indicated that they think that an AI tutor will be able to convince students that they (the AI tutor) cares. Is a major concern I have about AI tutors misplaced?

Thinking about this, I recalled variations of the saying:

The secret of success is sincerity. Once you can fake that you’ve got it made.

Can Artificial Intelligence tutors fake caring about students? I wonder.

Initially, I thought, no, not going to happen. Now I am not so sure. I have been thinking of my own interactions with Alexa from Amazon via their smart devices. Attempts to be personal with the AI, for example, saying “thank you.” elicit what feel a lot like personal responses. Alexa wishing me a “good night” or a suggestion to “keep warm out there.”

I recently had a conversation of sorts with Copilot about books I am interested in reading. The conversation felt a lot like taking to a real person.

Also, a friend of mine (Richard Seltzer) recently shared a book he was working on titled “How to Partner with AI: A New Kind of Relationship” (A pre-publication pdf of the entire book is available here for free.) The book reads a lot like a conversation between two real people rather than a person and a computer program. In fact it feels a lot like a conversation among friends.

So maybe AI tutors will get students thinking they care. Whether the program is faking that it cares or really cares is more of a philosophical question than a practical one. It’s a question well worth talking about of course. Just as asking if computers really think or if they can be truly creative. Practically speaking though does it mean that AI tutors can replace human teachers? I think it is more complicated than that.

There is also the matter of what to teach. I read someone recently saying that human teachers teach what they want but that students are not interested in learning and that AI tutors will teach things that students are actually interested in learning. That may be true but is that what we really want? Would that meet the needs of a real education?

What I see often is autodidacts attempting to promote learning that works for them as being the way that everyone should learn. That is decidedly not the case. Many, perhaps most, students need some external motivation and some direction.

I love the idea of students learning more about the things they are interested in knowing. There are things that student need to know though and students are not always interested in learning them all. We have required courses for a reason! Learning all about football at the cost of not learning any mathematics is probably not a good thing. Students are masters of distraction – both of becoming distracted and distracting others. Others includes instructors!

Perhaps that will work out. Perhaps an AI tutor will work mathematics into the football lesson. It could happen but will it?

There is also the question of who is teaching the AI. Will the AI tutors have a good bias or a bad one? Will it be trained to better society or to make it more compliant? Will the students wind up retraining the AI in unhealthy directions? We have seen AI chatbots turn very ugly with help from the internet. Who will monitor these AI tutors? Parents? Not likely.

We’ve also seen AIs get a lot of things wrong. They are not very good at validating sources of information. Human educators are a lot better at that.

I can imagine AI tutors working out very well. I can also imagine them turning out very badly. What I am strongly concerned about is AI tutors for the poor with human educators for the rich. Perhaps the human teacher supplemented with an AI tutor or an AI tutor supplemented with a human supervising instructor. But  it is clear to me that many of the rich are more interested in using AI to save money by replacing people and not as much of making things work better.

Relegating the masses to AI tutors is a high risk proposition with potential of holding the masses back. Autodidacts with high self motivation and a good AI tutor may go far. I am not sure that is the way to bet for most students though.

Reminiscing - When Computers Had Lights

Back before the personal computer age, computers had lights and toggle switches. One could use the switches to program computers and read answers in the lights. All in binary of course. We also used these tools for debugging. One could enter a memory address using the switches and see what was in the location, data or instruction, in the lights.

If a computer program was hung in a loop one could halt the computer and see what address and instruction was part of the loop. It was a useful debugging tool. Similarly if the computer halted for some reason an error code might be displayed in lights.

It wasn’t all seriousness though. Many operating systems would display something in the lights when the computer was idle – not doing real work. Usually this was some sort of animation – lights racing though the strip and rows of lights. Digital Equipment Corporation had a computer type called the PDP-11 that supported a number of different operating systems. Each OS had it’s own idle loop light display. One could walk into a computer lab, typically at night when no one was using the computers, and tell which OS was running on which computer just by watching the lights.

Some manifaxine computers had a lit of lights. A company called Burroughs had one large computer that would display the company logo in the lights when it was idle. Now you never really want to see that display if you owned that computer. It was frightfully expensive to buy and operate so you really wanted it to be doing real work 24/7. One potential buyer wanted their company logo to display when the computer was idle. Vanity perhaps? Anyway, silly as it was, as I recall, the program change was made and the sale went though.

Today, those sorts of lights are an unwanted, and generally unneeded, expense. I do sometimes miss those simpler days though.

CS Teacher Improvement Through Observation

I remember the first time I was observed by a principal. Brilliant man with two masters degrees and ABD PhD. He told me that he didn't understand much of what I was teaching but the students seemed to be getting it and the class ran smoothly. Not much in there to help me improve.

I believe that teaching CS is different from teaching most subjects. But each subject probably has its own nuances. That's why I think that teachers need specific training in teaching their particular subject. I know that there are MS degree programs in teaching reading and, I think, math. Probably more than those as well

There is limited training in how to teach CS though. There are some degree and certificate programs in teaching CS. As states increasingly require certification to teach computer science there will be more I am sure. Most CS teachers have to figure it out on their own though.

I think we have a lot to learn about how to teach CS well. There are a few people doing research in CS education. A lot of it gets disseminated at SIGCSE which can be hard for K-12 CS teachers to attend. That is both because of cost and because it happens during the school year. A lot of teachers have very limited options for missing school days. If nothing else it is a lot of work to create good sub plans!

Many teachers are resistant to sessions that are research based. That is often because they have had too many professional development sessions that year after year replace the previous research based methods without giving any one method a fair chance. Or worse, having failed.

It would be nice is teachers had more opportunity to observe experience CS teachers teach. (Both Mark Guzdial and Mike Zamansky have blogged about that recently – blog post links below) BTW if you ever get a chance to hear Mark Guzdial present I recommend that you do. Especially if the topic is how to teach.

In an ideal world, CS teachers would get to observe teachers in the building where they teach. For a variety of reasons, not the least of which is that many K-12 CS teachers are the only CS teacher in the building, that is often not possible.

CS conferences are a mixed bag. Yes, there are some great presenters. Many of them do try to model good teaching practice. There are not a lot of talks on how to teach though. I gave one at CSTA Online six years ago. (How is it that long ago?) It was well received but we could use a lot more that talk about and modeled how to teach CS.

I think we could use more talk sessions on the conference “hallway track” that informal, unscheduled time when teachers find themselves sharing ideas with like minded people.

At the heart of the issue is that teachers have to be about constant improvement. There is a difference between five years of experience and one year of experience five times.

Anyway, please read the posts linked below. Smarter people than me.

• Learning to teach better by observation: What I did on my sabbatical – Mark Guzdial

• Improving Instruction - College and K12 – Mike Zamansky

Are AI Code Assistants Getting Better or Worse

A friend of mine sent me a link to an opinion piece in the IEEE Spectrum - AI Coding Assistants Are Getting Worse –> Newer models are more prone to silent but deadly failure modes

Are AI code generators getting worse? The tl;dr  in this article is “Yes” because companies are letting poor programmers train the AI. You should read the article though.

It’s not deliberate of course. It’s just the way the internet works. AI software is not checking to see if the information it is getting is good in absolute terms. It is just checking to see if the user is happy. In the user is happy because they don’t realize that what they have is bad how is the AI to know?

The term GIGO - Garbage In, Garbage Out may not be repeated as often as it used to be but it is still true! We have to be careful about who and how artificial intelligence is trained. Do an internet search for “Chatbot goes bad” sometime and you’ll find a large number of cases where AI chatbots have been trained badly. Sometimes trained maliciously. Sometimes just trained on poor data sets.

TO me this trend points out a couple of things that we need to teach beginners. In the words of Ronald Regan, “Trust but verify.” Students need to test their code. Students need to be able to read and understand code. Programmers have to be able to determine if AI it taking shortcuts like leaving out error handling, data validation, and other errors of omission.

We also need to prepare students to think about how AIs are being trained so that they learn how to train AIs well themselves. Even if coding is dead, as one of my former students claims, people will still have to train AI, ask AI good questions, and be able to understand if they are getting the value from AI that they want, need, and think they are getting.