Homework is for using every tool at your disposal to learn. Tests are for proving you actually learned. Grading homework for credit and not giving feedback until after the test is a pattern I have seen too many times in higher ed, and it is a sorry excuse for education."},"story_title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["ai"],"value":"University Suspends Students for AI Tool It Gave Them $10k Prize to Make"},"story_url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["ai","homework"],"value":"https://www.404media.co/university-suspends-students-for-ai-homework-tool-it-paid-them-10-000-to-make/"}},"_tags":["comment","author_deckar01","story_40429229"],"author":"deckar01","comment_text":"You can get a tutor to check your homework and highlight your errors. Sometimes they just tell you answers in the process of teaching. AI can be a tutor if that is what you ask for.
Homework is for using every tool at your disposal to learn. Tests are for proving you actually learned. Grading homework for credit and not giving feedback until after the test is a pattern I have seen too many times in higher ed, and it is a sorry excuse for education.","created_at":"2024-05-21T16:01:30Z","created_at_i":1716307290,"objectID":"40430208","parent_id":40429229,"story_id":40429229,"story_title":"University Suspends Students for AI Tool It Gave Them $10k Prize to Make","story_url":"https://www.404media.co/university-suspends-students-for-ai-homework-tool-it-paid-them-10-000-to-make/","updated_at":"2024-09-20T17:02:31Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"fnordpiglet"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ai","homework","grading","education"],"value":"Competing with what? Homework is usually the minority of grade weight in almost every course and college entrance is largely based on entrance exams. Using AI to cheat on homework only cheats the students ability to complete and exam, let alone an entrance exam.
People act as if cheating on homework is new with LLms. It\u2019s not. The homework is there to guide you towards the exam, and exams are generally proctored to prevent cheating in ways homework is explicitly not. Generally teachers grade homework to create an incentive for students to practice rigorously for the in course and final exams. Any student who doesn\u2019t avail themselves of that practice invariably flunks their exams. Your homework grade won\u2019t help you then.
So who cares? Sooner or later the cheating student either learns why it doesn\u2019t pay to cheat or suffers the life consequences of not learning in school. This isn\u2019t new with LLMs.
What is new is you have a tool that you can get advice from on topics that are difficult or even get up front grading and advice on homework before turning it in that helps you master the material better. Students who use this will be able to master the material faster, even if their parents both work and can\u2019t invest the time to tutor their children at night.
(N.b., The threads here imply every parent works at a cushy tech job and has plenty of time to be invested in their kids education and any parent who isn\u2019t is negligent - while the truth is many are just struggling to make ends meet - as my parents did \u2026 I didn\u2019t get the investment my daughter gets not because they didn\u2019t care but because they were busy feeding me and keeping us from being homeless. I would have loved to have ChatGPT help me as a kid)"},"story_title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["homework"],"value":"My little sister's use of ChatGPT for homework is heartbreaking"},"story_url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["homework"],"value":"https://old.reddit.com/r/ChatGPT/comments/1hun3e4/my_little_sisters_use_of_chatgpt_for_homework_is/"}},"_tags":["comment","author_fnordpiglet","story_42611844"],"author":"fnordpiglet","children":[42618434],"comment_text":"Competing with what? Homework is usually the minority of grade weight in almost every course and college entrance is largely based on entrance exams. Using AI to cheat on homework only cheats the students ability to complete and exam, let alone an entrance exam.
People act as if cheating on homework is new with LLms. It\u2019s not. The homework is there to guide you towards the exam, and exams are generally proctored to prevent cheating in ways homework is explicitly not. Generally teachers grade homework to create an incentive for students to practice rigorously for the in course and final exams. Any student who doesn\u2019t avail themselves of that practice invariably flunks their exams. Your homework grade won\u2019t help you then.
So who cares? Sooner or later the cheating student either learns why it doesn\u2019t pay to cheat or suffers the life consequences of not learning in school. This isn\u2019t new with LLMs.
What is new is you have a tool that you can get advice from on topics that are difficult or even get up front grading and advice on homework before turning it in that helps you master the material better. Students who use this will be able to master the material faster, even if their parents both work and can\u2019t invest the time to tutor their children at night.
(N.b., The threads here imply every parent works at a cushy tech job and has plenty of time to be invested in their kids education and any parent who isn\u2019t is negligent - while the truth is many are just struggling to make ends meet - as my parents did \u2026 I didn\u2019t get the investment my daughter gets not because they didn\u2019t care but because they were busy feeding me and keeping us from being homeless. I would have loved to have ChatGPT help me as a kid)","created_at":"2025-01-07T01:41:17Z","created_at_i":1736214077,"objectID":"42618279","parent_id":42612322,"story_id":42611844,"story_title":"My little sister's use of ChatGPT for homework is heartbreaking","story_url":"https://old.reddit.com/r/ChatGPT/comments/1hun3e4/my_little_sisters_use_of_chatgpt_for_homework_is/","updated_at":"2025-01-07T02:39:25Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"vkou"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ai","homework","grading","education"],"value":"A few thoughts that immediately spring to mind:
Starting school at 7:30 has negative academic value, because half the students aren't even awake yet.
It's done because it's convenient for parents, who have to drop their kids off, who, for some reason, are 'incapable' of walking to school like their parents did.
A class of 32-35 students per teacher has no positive academic value. It is purely a cost-saving measure, that leaves everyone with a half-assed education.
Having to ask permission to piss, hall passes, limits on the number of students allowed to use the restroom at a time (typically 1/class) has more in common with a prison, or maybe boot camp, than a school. And, of course, there's no time in the 5-minute between class break for everyone who needs to, to both use the facilities, and get to their class, on time. It is done purely for social control reasons.
The expectation that teachers also do the job of social workers results in a lot of anti-academic outcomes. When your teacher, in a class of 30, is more concerned about how to deal with behaviour problems for a kid whose parents are, say, raging, shitty alcoholics, is not particularly conductive to the academic development of their peers. But that's not the school's, or the teacher's fault, so I can give that a pass.
AI essay grading (which is a more modern development, and works about as well as asking a monkey to grade essays) is the new thing that's popular to complain about. Negative academic value, but it saves time for teachers, who don't want to spend hours grading the hours of homework they assign. I don't blame them for preferring to have a 10-hour workday, instead of a 15-hour one, but still..."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Under digital surveillance: how American schools spy on millions of kids"},"story_url":{"matchLevel":"none","matchedWords":[],"value":"https://www.theguardian.com/world/2019/oct/22/school-student-surveillance-bark-gaggle"}},"_tags":["comment","author_vkou","story_21324133"],"author":"vkou","children":[21336610,21337591],"comment_text":"A few thoughts that immediately spring to mind:
Starting school at 7:30 has negative academic value, because half the students aren't even awake yet.
It's done because it's convenient for parents, who have to drop their kids off, who, for some reason, are 'incapable' of walking to school like their parents did.
A class of 32-35 students per teacher has no positive academic value. It is purely a cost-saving measure, that leaves everyone with a half-assed education.
Having to ask permission to piss, hall passes, limits on the number of students allowed to use the restroom at a time (typically 1/class) has more in common with a prison, or maybe boot camp, than a school. And, of course, there's no time in the 5-minute between class break for everyone who needs to, to both use the facilities, and get to their class, on time. It is done purely for social control reasons.
The expectation that teachers also do the job of social workers results in a lot of anti-academic outcomes. When your teacher, in a class of 30, is more concerned about how to deal with behaviour problems for a kid whose parents are, say, raging, shitty alcoholics, is not particularly conductive to the academic development of their peers. But that's not the school's, or the teacher's fault, so I can give that a pass.
AI essay grading (which is a more modern development, and works about as well as asking a monkey to grade essays) is the new thing that's popular to complain about. Negative academic value, but it saves time for teachers, who don't want to spend hours grading the hours of homework they assign. I don't blame them for preferring to have a 10-hour workday, instead of a 15-hour one, but still...","created_at":"2019-10-23T15:40:14Z","created_at_i":1571845214,"objectID":"21335740","parent_id":21333485,"story_id":21324133,"story_title":"Under digital surveillance: how American schools spy on millions of kids","story_url":"https://www.theguardian.com/world/2019/oct/22/school-student-surveillance-bark-gaggle","updated_at":"2024-09-20T05:07:40Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"ryanmercer"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ai","homework","grading","education"],"value":"Am I the only one that doesn't care about software beating humans at video games?
I'm sure there's some sort of useful learning being done here by the people that created the software that might some day help them create software that can better predict what is needed for a specific application but to me it just feels like entities like OpenAI and Google researching this predictive software are just wasting obscene amounts of money.
How about train the stuff on better typed OCR? Better handwriting OCR? This will have actual commercial application.
Why not make something for grading papers. English papers, math homework, etc? Start at a first grade level and as you train the software up move on to higher levels of education. My fiance is a high school teacher, she currently only teaches math but previously has done math and English, she sits there grading papers off the clock while watching television in the evenings and on the weekends... MANY high school teachers are in this situation, think of how much free time could be reclaimed by training this instead of teaching software how to beat humans in video games!!!
This would even help teachers have more time during school hours to help struggling students, if you aren't trying to grade papers in class while students are doing work you free up time that you could actively be assisting one or more students. Instead, these "AI" researchers keep training software to be the best at video games... facepalm
Then take that and apply it to something like my job. I clear international freight through customs for a living, I look at paperwork all day and then have to determine what tariff number I should use for something (cell phone 8517120050, silver ring over 1.50 USD 7113115000) and classify every single line on an invoice by using familiarity with the tariff schedule/description(s) on the invoice/any other supporting documentation/customer profiles for customers that have paid to have product databases on file with us. My employer, we do thousands of these things a day and have to keep everything for several years (5 IIRC) in the evening CBP or any other OGA wants to see it during that time period.
So take that huge, pre-existing, data set like that, identify which shipments were classified correctly and which were not, and then let the software have a stab at trying to do it with that better OCR you created.
Then, you know, actually get rid of (or drastically reduce) soul crushing, mind-numbing, highly repetitive digital paperwork jobs like mine."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Grandmaster level in StarCraft II using multi-agent reinforcement learning"},"story_url":{"matchLevel":"none","matchedWords":[],"value":"https://deepmind.com/blog/article/AlphaStar-Grandmaster-level-in-StarCraft-II-using-multi-agent-reinforcement-learning"}},"_tags":["comment","author_ryanmercer","story_21405188"],"author":"ryanmercer","comment_text":"Am I the only one that doesn't care about software beating humans at video games?
I'm sure there's some sort of useful learning being done here by the people that created the software that might some day help them create software that can better predict what is needed for a specific application but to me it just feels like entities like OpenAI and Google researching this predictive software are just wasting obscene amounts of money.
How about train the stuff on better typed OCR? Better handwriting OCR? This will have actual commercial application.
Why not make something for grading papers. English papers, math homework, etc? Start at a first grade level and as you train the software up move on to higher levels of education. My fiance is a high school teacher, she currently only teaches math but previously has done math and English, she sits there grading papers off the clock while watching television in the evenings and on the weekends... MANY high school teachers are in this situation, think of how much free time could be reclaimed by training this instead of teaching software how to beat humans in video games!!!
This would even help teachers have more time during school hours to help struggling students, if you aren't trying to grade papers in class while students are doing work you free up time that you could actively be assisting one or more students. Instead, these "AI" researchers keep training software to be the best at video games... facepalm
Then take that and apply it to something like my job. I clear international freight through customs for a living, I look at paperwork all day and then have to determine what tariff number I should use for something (cell phone 8517120050, silver ring over 1.50 USD 7113115000) and classify every single line on an invoice by using familiarity with the tariff schedule/description(s) on the invoice/any other supporting documentation/customer profiles for customers that have paid to have product databases on file with us. My employer, we do thousands of these things a day and have to keep everything for several years (5 IIRC) in the evening CBP or any other OGA wants to see it during that time period.
So take that huge, pre-existing, data set like that, identify which shipments were classified correctly and which were not, and then let the software have a stab at trying to do it with that better OCR you created.
Then, you know, actually get rid of (or drastically reduce) soul crushing, mind-numbing, highly repetitive digital paperwork jobs like mine.","created_at":"2019-10-31T14:18:57Z","created_at_i":1572531537,"objectID":"21409062","parent_id":21405188,"story_id":21405188,"story_title":"Grandmaster level in StarCraft II using multi-agent reinforcement learning","story_url":"https://deepmind.com/blog/article/AlphaStar-Grandmaster-level-in-StarCraft-II-using-multi-agent-reinforcement-learning","updated_at":"2024-09-20T05:06:05Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"istjohn"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ai","homework","grading","education"],"value":"I believe conversation is a one of the best ways to really learn a topic, so long as it is used deliberately.
My folk theory of education is that there is a sequence you need to complete to truly master a topic.
Step 1: You start with receptive learning where you take in information provided to you by a teacher, book, AI or other resource. This doesn't have to be totally passive. For examble, it could take the form of Socratic questioning to guide you towards an understanding.
Step 2: Then you digest the material. You connect it to what you already know. You play with the ideas. This can happen in an internal monologue as you read a textbook, in a question and answer period after a lecture, in a study group conversation, when you review your notes, or as you complete homework questions.
Step 3: Finally, you practice applying the knowledge. At this stage, you are testing the understanding and intuition you developed during digestion. This is where homework assignments, quizes, and tests are key.
This cycle can occur over a full semester, but it can also occur as you read a single textbook paragraph. First, you read (step 1). Then you stop and think about what this means and how it connects to what you previously read. You make up an imaginary situation and think about what it implies (step 2). Then you work out a practice problem (step 3).
Note that it is iterative. If you discover in step 3 a misunderstanding, you may repeat the loop with an emphasis on your confusion.
I think AI can be extremely helpful in all three stages of learning--in particular, for steps 2 and 3. It's invaluable to have quick feedback at step 3 to understand if you are on the right trail. It doesn't make sense to wait for feedback until a teacher's aid gets around to grading your HW if you can get feedback right now with AI.
The danger is if you don't give yourself a chance to struggle through step 3 before getting feedback. The amount of struggle that is appropriate will vary and is a subtle question.
Philosophers, mathematicians, and physicists in training obviously need to learn to be comfortable finding their way through hairy problems without any external source of truth to guide them. But this is a useful muscle that arguably everyone should exercise to some extent. On the other hand, the majority of learning for the majority of students is arguably more about mastering a body of knowledge than developing sheer brain power.
Ultimately, you have to take charge of your own learning. AI is a wonderful learning tool if used thoughtfully and with discipline."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"How University Students Use Claude"},"story_url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["education"],"value":"https://www.anthropic.com/news/anthropic-education-report-how-university-students-use-claude"}},"_tags":["comment","author_istjohn","story_43633383"],"author":"istjohn","comment_text":"I believe conversation is a one of the best ways to really learn a topic, so long as it is used deliberately.
My folk theory of education is that there is a sequence you need to complete to truly master a topic.
Step 1: You start with receptive learning where you take in information provided to you by a teacher, book, AI or other resource. This doesn't have to be totally passive. For examble, it could take the form of Socratic questioning to guide you towards an understanding.
Step 2: Then you digest the material. You connect it to what you already know. You play with the ideas. This can happen in an internal monologue as you read a textbook, in a question and answer period after a lecture, in a study group conversation, when you review your notes, or as you complete homework questions.
Step 3: Finally, you practice applying the knowledge. At this stage, you are testing the understanding and intuition you developed during digestion. This is where homework assignments, quizes, and tests are key.
This cycle can occur over a full semester, but it can also occur as you read a single textbook paragraph. First, you read (step 1). Then you stop and think about what this means and how it connects to what you previously read. You make up an imaginary situation and think about what it implies (step 2). Then you work out a practice problem (step 3).
Note that it is iterative. If you discover in step 3 a misunderstanding, you may repeat the loop with an emphasis on your confusion.
I think AI can be extremely helpful in all three stages of learning--in particular, for steps 2 and 3. It's invaluable to have quick feedback at step 3 to understand if you are on the right trail. It doesn't make sense to wait for feedback until a teacher's aid gets around to grading your HW if you can get feedback right now with AI.
The danger is if you don't give yourself a chance to struggle through step 3 before getting feedback. The amount of struggle that is appropriate will vary and is a subtle question.
Philosophers, mathematicians, and physicists in training obviously need to learn to be comfortable finding their way through hairy problems without any external source of truth to guide them. But this is a useful muscle that arguably everyone should exercise to some extent. On the other hand, the majority of learning for the majority of students is arguably more about mastering a body of knowledge than developing sheer brain power.
Ultimately, you have to take charge of your own learning. AI is a wonderful learning tool if used thoughtfully and with discipline.","created_at":"2025-04-10T18:52:17Z","created_at_i":1744311137,"objectID":"43646990","parent_id":43634527,"story_id":43633383,"story_title":"How University Students Use Claude","story_url":"https://www.anthropic.com/news/anthropic-education-report-how-university-students-use-claude","updated_at":"2025-04-10T20:56:20Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"6SixTy"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ai","homework","grading","education"],"value":"In the US, this is not how things are done. Grades are literally everything within the education system. Learning how the system works and playing how your final grading is weighted including but not limited in regard to tests, assignments, and homework is a gigantic portion of how a student's aptitude is determined.
A lot of the system is based off of memorization and paperwork anyways. Something an AI can do all day, every day."},"story_title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["homework"],"value":"My little sister's use of ChatGPT for homework is heartbreaking"},"story_url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["homework"],"value":"https://old.reddit.com/r/ChatGPT/comments/1hun3e4/my_little_sisters_use_of_chatgpt_for_homework_is/"}},"_tags":["comment","author_6SixTy","story_42611844"],"author":"6SixTy","comment_text":"In the US, this is not how things are done. Grades are literally everything within the education system. Learning how the system works and playing how your final grading is weighted including but not limited in regard to tests, assignments, and homework is a gigantic portion of how a student's aptitude is determined.
A lot of the system is based off of memorization and paperwork anyways. Something an AI can do all day, every day.","created_at":"2025-01-06T17:55:35Z","created_at_i":1736186135,"objectID":"42613067","parent_id":42612488,"story_id":42611844,"story_title":"My little sister's use of ChatGPT for homework is heartbreaking","story_url":"https://old.reddit.com/r/ChatGPT/comments/1hun3e4/my_little_sisters_use_of_chatgpt_for_homework_is/","updated_at":"2025-01-06T22:18:39Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"throwawaygh"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ai","homework","grading","education"],"value":"Yes to everything about the US system having some serious problems and being fairly unique relative to the rest of the world.
> Software will eventually be able to read an essay and provide feedback on how well the argument was made, as well as the nuts and bolts of how sentences are put together... Imagine for example the task is to convince an AI to buy you a pony. You have to write a persuasive essay as to why you should have a pony. The AI can...
No, it can't.
Giving good feedback on essays in high school English or History courses is AI-complete.
"Some type of feedback" is already possible (you can go buy essay graders today -- go try one), but if we go that route we'll mostly just be teaching people how to optimize for a (very broken) grading algorithm.
"'The AI' will then <do thing that we spend years teaching people how to do well>" is exactly how you end up with horribly shitty ML code destroying people's lives.
TBH we're not even there with high school math yet, which is a lot easier than high school essays.
I have a CS PhD, publish in AI conferences, and have taught high school. I am fundamentally absolutely certain that high-quality grading of high school English/History essays is not possible. I'm also certain that we could build "something" that "grades essays" and will have catastrophic negative outcomes for a generation of students if adopted. Students will learn how to write for one really dumb algorithm, and then there will be years of cleanup at universities and workplaces afterward teaching them how to actually write for humans.
> but to be clear, _almost all_ motivation in education is extrinsic now. Nobody is doing their math homework because its fun. They do it so they won't "fail".
My classroom experience suggests that a) this isn't true, and b) there are lots of different types of extrinsic motivation; grades are actually not the most important motivator for most students. People are really complex, and everyone has different motivators."},"story_title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["education"],"value":"Video Games Are the Future of Education"},"story_url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["education"],"value":"https://nabeelqu.co/education"}},"_tags":["comment","author_throwawaygh","story_23593872"],"author":"throwawaygh","children":[23596085,23597205],"comment_text":"Yes to everything about the US system having some serious problems and being fairly unique relative to the rest of the world.
> Software will eventually be able to read an essay and provide feedback on how well the argument was made, as well as the nuts and bolts of how sentences are put together... Imagine for example the task is to convince an AI to buy you a pony. You have to write a persuasive essay as to why you should have a pony. The AI can...
No, it can't.
Giving good feedback on essays in high school English or History courses is AI-complete.
"Some type of feedback" is already possible (you can go buy essay graders today -- go try one), but if we go that route we'll mostly just be teaching people how to optimize for a (very broken) grading algorithm.
"'The AI' will then <do thing that we spend years teaching people how to do well>" is exactly how you end up with horribly shitty ML code destroying people's lives.
TBH we're not even there with high school math yet, which is a lot easier than high school essays.
I have a CS PhD, publish in AI conferences, and have taught high school. I am fundamentally absolutely certain that high-quality grading of high school English/History essays is not possible. I'm also certain that we could build "something" that "grades essays" and will have catastrophic negative outcomes for a generation of students if adopted. Students will learn how to write for one really dumb algorithm, and then there will be years of cleanup at universities and workplaces afterward teaching them how to actually write for humans.
> but to be clear, _almost all_ motivation in education is extrinsic now. Nobody is doing their math homework because its fun. They do it so they won't "fail".
My classroom experience suggests that a) this isn't true, and b) there are lots of different types of extrinsic motivation; grades are actually not the most important motivator for most students. People are really complex, and everyone has different motivators.","created_at":"2020-06-21T22:29:44Z","created_at_i":1592778584,"objectID":"23595890","parent_id":23595729,"story_id":23593872,"story_title":"Video Games Are the Future of Education","story_url":"https://nabeelqu.co/education","updated_at":"2024-09-20T06:30:00Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"erlkonig"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ai","homework","grading","education"],"value":"Each of your 3 foundational knowledge points will never be used by certain branches of computing. There are scenarios where none of them will be used, so it's hard to truly call them foundational. Filesystems are a key discipline you left out, for example, but it, too, isn't quite foundational.
The foundations are things like (this list should not be read as being comprehensive):
* Formalized languages
* The implementation, all the way down to the hardware, underneath those languages and how to bridge between them (this is far too frequently omitted unless it comes up in some 1 hour credit C course - and lately we're seeing C replaced with C++ courses trying to pretend to be abstract, making them pretty pointless to teach at all)
* Algorithms
* Complexity, Big-O notation or equivalent, computatibility in general, and mapping underlying algorithms to different problems
* The reality of just how different an implemented language and platform is from the abstract idea of one - limitations on sizes, errors, failures, etc, all the things that complicate the lives of a theorist trying to do real work
I'm especially annoyed by the C++ classes - said language is a massive cognitive load to inflict on students, and a huge, vocational distraction from the theory and concepts a degree SHOULD be teaching. A better course spread would be some machine language, C, LISP, Smalltalk, some (modern version of a) goal oriented language like Prolog or KL/1, something with intrinsic multiprocessing support, and one that is essentially distributed, and so on. Languages that demonstrate the breadth of what a language can encompass, rather than grinding students into the bottomless pit that C++ has become.
I do agree that these all are relevant: databases (by implementing one, with attention to ACID, but with a lot of assumptions about reliability given and highlighted), concurrency (both with a language that does it intrinsically, and in one that doesn't), and network programming (at least three totally different approaches here: intrinsic to a cluster environment, intrinsic to the language, and implemented via libraries like in C). However, these ideas are not each important enough to count as core.
The point of a non-vocational, classical degree is to be able to understand the field and to be able to create tools - including new ones. The higher the degree, the more important it becomes to be able to extend the field. The objectives (in part) of a classical degree are what I've described, with the goal of producing synthesists and creators within the field of computer science.
In the vocational education, the grads will hit the ground ready to write code using existing libraries and tools, perfect to drop into some project underway to use what they've learned to tie everything together. But they'll be pretty na\u00efve when it comes to creating them, and generally unaware of ideas that fit the tasks better and just need to be pulled in. Have them learn whatever language is the current fad for a couple of years, and train them in all the current things. But they'll have a harder time as the tools shift underfoot.
Some things bridge both the classic and the vocational. Source code control, for one (UTexas CS basically requires knowing git, for example), all the tools' varieties we take for granted to share work, google, communicate, and try to make AI write our homework or job assignments. But the classes for git should be quite different in a vocational versus classical curriculum.
Basically, given what I've heard from former students at various places (and I taught for a decade myself) I see many colleges leaning towards teaching a vocational CS curriculum and pretending it's classical, and this damages the field overall. At the same time, I've seen overly theoretical degrees in CS that I think are also a problem, in a different way, if the students were led to believe they'd be able to actually create software when they were done.
The most pathological example I've seen is a professor at the University of Texas who was trying to teach his students IPC using C and Unix as the demonstration environment (essentially a classical lesson). However, since the professor's awareness of the implementation was too limited, he was using examples with the wrong paradigm - FIFO pipes - instead of sockets. The result being that the examples only worked for processes with a shared parent proc. This undercut the objective so badly that the students were missing the point of IPC, since they could have had a single process produce essentially the same results as the example, and were getting no payoff from the FIFO aspect. The professor's limited vocational grounding was producing students who were failing to understand both the practical AND theoretical.
So it's not just a case of a poor curriculum poorly serving the students, the professors themselves are suffering from the problem of being too polarized between theory and practice. The problem needs to be viewed as endemic in some colleges and I'm not sure anyone's really talking about it enough."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"Ask HN: Why do many CS graduates lack foundational knowledge?"}},"_tags":["comment","author_erlkonig","story_35226887"],"author":"erlkonig","comment_text":"Each of your 3 foundational knowledge points will never be used by certain branches of computing. There are scenarios where none of them will be used, so it's hard to truly call them foundational. Filesystems are a key discipline you left out, for example, but it, too, isn't quite foundational.
The foundations are things like (this list should not be read as being comprehensive):
* Formalized languages
* The implementation, all the way down to the hardware, underneath those languages and how to bridge between them (this is far too frequently omitted unless it comes up in some 1 hour credit C course - and lately we're seeing C replaced with C++ courses trying to pretend to be abstract, making them pretty pointless to teach at all)
* Algorithms
* Complexity, Big-O notation or equivalent, computatibility in general, and mapping underlying algorithms to different problems
* The reality of just how different an implemented language and platform is from the abstract idea of one - limitations on sizes, errors, failures, etc, all the things that complicate the lives of a theorist trying to do real work
I'm especially annoyed by the C++ classes - said language is a massive cognitive load to inflict on students, and a huge, vocational distraction from the theory and concepts a degree SHOULD be teaching. A better course spread would be some machine language, C, LISP, Smalltalk, some (modern version of a) goal oriented language like Prolog or KL/1, something with intrinsic multiprocessing support, and one that is essentially distributed, and so on. Languages that demonstrate the breadth of what a language can encompass, rather than grinding students into the bottomless pit that C++ has become.
I do agree that these all are relevant: databases (by implementing one, with attention to ACID, but with a lot of assumptions about reliability given and highlighted), concurrency (both with a language that does it intrinsically, and in one that doesn't), and network programming (at least three totally different approaches here: intrinsic to a cluster environment, intrinsic to the language, and implemented via libraries like in C). However, these ideas are not each important enough to count as core.
The point of a non-vocational, classical degree is to be able to understand the field and to be able to create tools - including new ones. The higher the degree, the more important it becomes to be able to extend the field. The objectives (in part) of a classical degree are what I've described, with the goal of producing synthesists and creators within the field of computer science.
In the vocational education, the grads will hit the ground ready to write code using existing libraries and tools, perfect to drop into some project underway to use what they've learned to tie everything together. But they'll be pretty na\u00efve when it comes to creating them, and generally unaware of ideas that fit the tasks better and just need to be pulled in. Have them learn whatever language is the current fad for a couple of years, and train them in all the current things. But they'll have a harder time as the tools shift underfoot.
Some things bridge both the classic and the vocational. Source code control, for one (UTexas CS basically requires knowing git, for example), all the tools' varieties we take for granted to share work, google, communicate, and try to make AI write our homework or job assignments. But the classes for git should be quite different in a vocational versus classical curriculum.
Basically, given what I've heard from former students at various places (and I taught for a decade myself) I see many colleges leaning towards teaching a vocational CS curriculum and pretending it's classical, and this damages the field overall. At the same time, I've seen overly theoretical degrees in CS that I think are also a problem, in a different way, if the students were led to believe they'd be able to actually create software when they were done.
The most pathological example I've seen is a professor at the University of Texas who was trying to teach his students IPC using C and Unix as the demonstration environment (essentially a classical lesson). However, since the professor's awareness of the implementation was too limited, he was using examples with the wrong paradigm - FIFO pipes - instead of sockets. The result being that the examples only worked for processes with a shared parent proc. This undercut the objective so badly that the students were missing the point of IPC, since they could have had a single process produce essentially the same results as the example, and were getting no payoff from the FIFO aspect. The professor's limited vocational grounding was producing students who were failing to understand both the practical AND theoretical.
So it's not just a case of a poor curriculum poorly serving the students, the professors themselves are suffering from the problem of being too polarized between theory and practice. The problem needs to be viewed as endemic in some colleges and I'm not sure anyone's really talking about it enough.","created_at":"2023-03-20T09:15:03Z","created_at_i":1679303703,"objectID":"35229042","parent_id":35226887,"story_id":35226887,"story_title":"Ask HN: Why do many CS graduates lack foundational knowledge?","updated_at":"2024-09-20T13:36:12Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"ricardochan319"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ai","homework","grading","education"],"value":"The world of voice-based AI is a symphony of innovation, with emerging trends and future developments shaping its melodious progression. From the rise of Voice ChatGPT to the increasing integration of voice tech in our daily lives, this blog post explores the predictions and trends that are defining the future of voice-based AI.
The Expanding Role of Voice ChatGPT\nVoice ChatGPT, with its ability to understand and generate spoken language, is set to play an increasingly pivotal role in the voice-based AI landscape. It will not only serve as a conversational assistant but also as a tool for content creation, language translation, and personalization.
Voice Commerce\nVoice commerce is set to revolutionize the way we shop. With the integration of voice assistants into e-commerce platforms, users can make purchases and interact with brands using only their voice. The convenience and efficiency of voice commerce will continue to gain traction.
Voice in Healthcare\nVoice-based AI is making inroads in the healthcare industry. Voice assistants can help doctors with documentation, assist patients with medication reminders, and even offer general health information. The future holds the promise of more advanced diagnostic and monitoring capabilities.
Voice Technology in Education\nVoice ChatGPT and similar technologies are transforming the educational landscape. They provide personalized learning experiences, assist with homework, and even serve as virtual tutors. The integration of voice technology in education will continue to grow, catering to diverse learning needs.
Multimodal Experiences\nThe future of voice-based AI is not limited to voice alone. It's about creating multimodal experiences that combine voice with visuals and touch. This approach will enable more holistic and immersive interactions, particularly in the world of augmented and virtual reality.
Smart Homes and IoT\nAs the Internet of Things (IoT) continues to expand, voice-based AI will be at the heart of smart homes. Users will be able to control lighting, heating, security systems, and more through voice commands, creating a more connected and convenient living environment.
Privacy and Security Advances\nWith the growing concerns over data privacy and security, future developments will focus on advanced privacy-preserving AI. This includes techniques that allow voice assistants to function without constantly recording and storing user conversations, bolstering user trust.
Regulatory Frameworks\nAs the voice-based AI landscape matures, regulatory frameworks will become increasingly important. Governments and organizations will need to establish clear guidelines to ensure ethical AI development and use while protecting user privacy.
User-Centric Design\nFuture developments will emphasize user-centric design. AI solutions will be more adaptable to individual user preferences, making interactions more intuitive and personalized.
Ethical AI\nEthical AI practices will continue to be at the forefront of voice-based AI development. Ensuring fairness, transparency, and the responsible use of AI technology will remain a cornerstone of future trends.
In conclusion, the world of voice-based AI is set for an exciting and transformative future. From advanced language understanding to multimodal experiences, voice-based AI will continue to enhance various aspects of our lives. The key to its successful evolution lies in responsible development, user-centric design, and ethical considerations. As we navigate this evolving landscape, one thing is clear: the symphony of voices in AI is only beginning to play its most exciting and melodious tunes."},"story_title":{"matchLevel":"none","matchedWords":[],"value":"[dead]"}},"_tags":["comment","author_ricardochan319","story_37873920"],"author":"ricardochan319","comment_text":"The world of voice-based AI is a symphony of innovation, with emerging trends and future developments shaping its melodious progression. From the rise of Voice ChatGPT to the increasing integration of voice tech in our daily lives, this blog post explores the predictions and trends that are defining the future of voice-based AI.
The Expanding Role of Voice ChatGPT\nVoice ChatGPT, with its ability to understand and generate spoken language, is set to play an increasingly pivotal role in the voice-based AI landscape. It will not only serve as a conversational assistant but also as a tool for content creation, language translation, and personalization.
Voice Commerce\nVoice commerce is set to revolutionize the way we shop. With the integration of voice assistants into e-commerce platforms, users can make purchases and interact with brands using only their voice. The convenience and efficiency of voice commerce will continue to gain traction.
Voice in Healthcare\nVoice-based AI is making inroads in the healthcare industry. Voice assistants can help doctors with documentation, assist patients with medication reminders, and even offer general health information. The future holds the promise of more advanced diagnostic and monitoring capabilities.
Voice Technology in Education\nVoice ChatGPT and similar technologies are transforming the educational landscape. They provide personalized learning experiences, assist with homework, and even serve as virtual tutors. The integration of voice technology in education will continue to grow, catering to diverse learning needs.
Multimodal Experiences\nThe future of voice-based AI is not limited to voice alone. It's about creating multimodal experiences that combine voice with visuals and touch. This approach will enable more holistic and immersive interactions, particularly in the world of augmented and virtual reality.
Smart Homes and IoT\nAs the Internet of Things (IoT) continues to expand, voice-based AI will be at the heart of smart homes. Users will be able to control lighting, heating, security systems, and more through voice commands, creating a more connected and convenient living environment.
Privacy and Security Advances\nWith the growing concerns over data privacy and security, future developments will focus on advanced privacy-preserving AI. This includes techniques that allow voice assistants to function without constantly recording and storing user conversations, bolstering user trust.
Regulatory Frameworks\nAs the voice-based AI landscape matures, regulatory frameworks will become increasingly important. Governments and organizations will need to establish clear guidelines to ensure ethical AI development and use while protecting user privacy.
User-Centric Design\nFuture developments will emphasize user-centric design. AI solutions will be more adaptable to individual user preferences, making interactions more intuitive and personalized.
Ethical AI\nEthical AI practices will continue to be at the forefront of voice-based AI development. Ensuring fairness, transparency, and the responsible use of AI technology will remain a cornerstone of future trends.
In conclusion, the world of voice-based AI is set for an exciting and transformative future. From advanced language understanding to multimodal experiences, voice-based AI will continue to enhance various aspects of our lives. The key to its successful evolution lies in responsible development, user-centric design, and ethical considerations. As we navigate this evolving landscape, one thing is clear: the symphony of voices in AI is only beginning to play its most exciting and melodious tunes.","created_at":"2023-10-13T18:34:47Z","created_at_i":1697222087,"objectID":"37873921","parent_id":37873920,"story_id":37873920,"story_title":"[dead]","updated_at":"2024-09-20T15:27:24Z"}],"hitsPerPage":20,"nbHits":9,"nbPages":1,"page":0,"params":"query=AI+homework+grading+education&advancedSyntax=true&analyticsTags=backend","processingTimeMS":34,"processingTimingsMS":{"_request":{"queue":7,"roundTrip":26},"afterFetch":{"format":{"highlighting":1,"total":1},"merge":{"mergeLoop":{"prepareNextHit":4,"total":4},"total":6},"total":6},"fetch":{"query":17,"scanning":9,"total":27},"total":34},"query":"AI homework grading education","serverTimeMS":43}