Tootfinder

Robots and Children that Learn Together : Improving Knowledge Retention by Teaching Peer-Like Interactive Robots
Imene Tarakli, Samuele Vinanzi, Richard Moore, Alessandro Di Nuovo
https://arxiv.org/abs/2506.18365

Robots and Children that Learn Together : Improving Knowledge Retention by Teaching Peer-Like Interactive Robots
Despite growing interest in Learning-by-Teaching (LbT), few studies have explored how this paradigm can be implemented with autonomous, peer-like social robots in real classrooms. Most prior work has relied on scripted or Wizard-of-Oz behaviors, limiting our understanding of how real-time, interactive learning can be supported by artificial agents. This study addresses this gap by introducing Interactive Reinforcement Learning (RL) as a cognitive model for teachable social robots. We conducted …

Do What? Teaching Vision-Language-Action Models to Reject the Impossible
Wen-Han Hsieh, Elvis Hsieh, Dantong Niu, Trevor Darrell, Roei Herzig, David M. Chan
https://arxiv.org/abs/2508.16292

Do What? Teaching Vision-Language-Action Models to Reject the Impossible
Recently, Vision-Language-Action (VLA) models have demonstrated strong performance on a range of robotic tasks. These models rely on multimodal inputs, with language instructions playing a crucial role -- not only in predicting actions, but also in robustly interpreting user intent, even when the requests are impossible to fulfill. In this work, we investigate how VLAs can recognize, interpret, and respond to false-premise instructions: natural language commands that reference objects or condit…

"A new state law forbids education increasing ‘awareness’ of issues relating to race. How are educators supposed to teach history?"
Teaching the Holocaust Just Got Harder in Mississippi
https://www.thebulwark.com/p/teaching-the-holocaust-just-got-harder-in-mississippi-hb-1193-dei-slavery-tate-reeves

If I were teaching a Con Law or Criminal Procedure class I would put up this video and ask the students to identify how many Constitutional violations are occurring.
(The first one to hit me was the violation, right at the start of the video of the 5th amendment's right of non self-incrimination.)
https://www.

If you’re wondering how to get a toddler to brush their teeth, I can recommend teaching them the words to “Witchdoctor”, by Cartoonies.
ooooh-eeee (brush fronts of teeth)
ooh-aah-aah (brush backs)
ting-tang (brush tops and bottoms of molars)
walla-walla-bing-bang (brush tongue)
And repeat.
Under no circumstances should you let them hear the actual song, which is awful.

A Large-Scale Real-World Evaluation of LLM-Based Virtual Teaching Assistant
Sunjun Kweon, Sooyohn Nam, Hyunseung Lim, Hwajung Hong, Edward Choi
https://arxiv.org/abs/2506.17363

A Large-Scale Real-World Evaluation of LLM-Based Virtual Teaching Assistant
Virtual Teaching Assistants (VTAs) powered by Large Language Models (LLMs) have the potential to enhance student learning by providing instant feedback and facilitating multi-turn interactions. However, empirical studies on their effectiveness and acceptance in real-world classrooms are limited, leaving their practical impact uncertain. In this study, we develop an LLM-based VTA and deploy it in an introductory AI programming course with 477 graduate students. To assess how student perceptions …

Stranger Danger was never the answer.
https://www.huffpost.com/entry/teaching-kids-safety-awareness_l_68a61241e4b0da9c591c73ff

'Stranger Danger' Doesn't Cut It Anymore. Safety Experts Want Parents To Teach This Instead.
Kids need situational awareness — from crossing the street to navigating the internet. But many parents don't know how to teach it.

Machine learning-based multimodal prognostic models integrating pathology images and high-throughput omic data for overall survival prediction in cancer: a systematic review
Charlotte Jennings (National Pathology Imaging Cooperative, Leeds Teaching Hospitals NHS Trust, Leeds, UK), Andrew Broad (National Pathology Imaging Cooperative, Leeds Teaching Hospitals NHS Trust, Leeds, UK), Lucy Godson (National Pathology Imaging Cooperative, Leeds Teaching Hospitals NHS Trust, Leeds, UK), Emily…

Machine learning-based multimodal prognostic models integrating pathology images and high-throughput omic data for overall survival prediction in cancer: a systematic review
Multimodal machine learning integrating histopathology and molecular data shows promise for cancer prognostication. We systematically reviewed studies combining whole slide images (WSIs) and high-throughput omics to predict overall survival. Searches of EMBASE, PubMed, and Cochrane CENTRAL (12/08/2024), plus citation screening, identified eligible studies. Data extraction used CHARMS; bias was assessed with PROBAST+AI; synthesis followed SWiM and PRISMA 2020. Protocol: PROSPERO (CRD42024594745)…

I just re-read @… 's manifesto on liberal arts education.
It's really about #education in general, including vocational education, and including the fact that school is a subset of education.
Well worth your time.

Pictorial and Documentary Guide for Research, Teaching, and Education through Astronomy, Physics, and Mathematics Pursued under the Umbrella of the United Nations (1974-2024)
Hans J. Haubold, Arak M. Mathai
https://arxiv.org/abs/2507.17283

Pictorial and Documentary Guide for Research, Teaching, and Education through Astronomy, Physics, and Mathematics Pursued under the Umbrella of the United Nations (1974-2024)
This paper was prepared for Open-Access-only publication as a guide reporting on Education (all aspects of space science and technology), Teaching (remote sensing and GIS, satellite meteorology and global climate, satellite communication, space and atmospheric sciences, global navigation satellite systems), and Research (solar neutrino problem, formation of structure in the Universe) in astronomy (solar physics, cosmology), physics (nuclear physics, neutrino physics), and mathematics (fractiona…

A Comparison of Three Approaches to Teaching Expressiveness
https://bulletproofmusician.com/a-comparison-of-three-approaches-to-teaching-expressiveness/?utm_source=flipb…

A Comparison of Three Approaches to Teaching Expressiveness
A 2006 study compares three different approaches to teaching expressiveness, and identifies some pros and cons of each.

Can the AI bubble please burst next week at the latest?
I'm already done with faculty talk praising AI this and AI that and forcing teaching to fully go tech-bro-style. Next term starts September 15, I just don’t want to set up “AI-safe exams” and having students use AI for everything at the same time
Oh, and don’t be so negative, we’re all using X and Y and the newest Z, it’s awesome! It just hallucinate or lies a bit, but so friendly, the nice bot, don’t you see? Magic!

MAARTA:Multi-Agentic Adaptive Radiology Teaching Assistant
Akash Awasthi, Brandon V. Chang, Anh M. Vu, Ngan Le, Rishi Agrawal, Zhigang Deng, Carol Wu, Hien Van Nguyen
https://arxiv.org/abs/2506.17320

MAARTA:Multi-Agentic Adaptive Radiology Teaching Assistant
Radiology students often struggle to develop perceptual expertise due to limited expert mentorship time, leading to errors in visual search and diagnostic interpretation. These perceptual errors, such as missed fixations, short dwell times, or misinterpretations, are not adequately addressed by current AI systems, which focus on diagnostic accuracy but fail to explain how and why errors occur. To address this gap, we introduce MAARTA (Multi-Agentic Adaptive Radiology Teaching Assistant), a mult…

"Administrators don’t have the guts to ban cellphones but expect teachers to spend every day swinging wildly at the slithering AI tech we’re supposed to embrace"
https://sunny.garden/@himantra/115039571729383600

"I have been teaching classes on #genocide for a quarter of a century. I can recognize one when I see one.
This is not just my conclusion. A growing number of experts in genocide studies and international law have concluded that Israel’s actions in #Gaza can only be defined as genocide. So has …

Opinion | I’m a Genocide Scholar. I Know It When I See It.
A professor of Holocaust and genocide studies comes to a painful conclusion about Israel’s actions in Gaza.

Overly academic/distanced ethical discussions
Had a weird interaction with @/brainwane@social.coop just now. I misinterpreted one of their posts quoting someone else and I think the combination of that plus an interaction pattern where I'd assume their stance on something and respond critically to that ended up with me getting blocked. I don't have hard feelings exactly, and this post is only partly about this particular person, but I noticed something interesting by the end of the conversation that had been bothering me. They repeatedly criticized me for assuming what their position was, but never actually stated their position. They didn't say: "I'm bothered you assumed my position was X, it's actually Y." They just said "I'm bothered you assumed my position was X, please don't assume my position!" I get that it's annoying to have people respond to a straw man version of your argument, but when I in response asked some direct questions about what their position was, they gave some non-answers and then blocked me. It's entirely possible it's a coincidence, and they just happened to run out of patience on that iteration, but it makes me take their critique of my interactions a bit less seriously. I suspect that they just didn't want to hear what I was saying, while at the same time they wanted to feel as if they were someone who values public critique and open discussion of tricky issues (if anyone reading this post also followed our interaction and has a different opinion of my behavior, I'd be glad to hear it; it's possible In effectively being an asshole here and it would be useful to hear that if so).
In any case, the fact that at the end of the entire discussion, I'm realizing I still don't actually know their position on whether they think the AI use case in question is worthwhile feels odd. They praised the system on several occasions, albeit noting some drawbacks while doing so. They said that the system was possibly changing their anti-AI stance, but then got mad at me for assuming this meant that they thought this use-case was justified. Maybe they just haven't made up their mind yet but didn't want to say that?
Interestingly, in one of their own blog posts that got linked in the discussion, they discuss a different AI system, and despite listing a bunch of concrete harms, conclude that it's okay to use it. That's fine; I don't think *every* use of AI is wrong on balance, but what bothered me was that their post dismissed a number of real ethical issues by saying essentially "I haven't seen calls for a boycott over this issue, so it's not a reason to stop use." That's an extremely socially conformist version of ethics that doesn't sit well with me. The discussion also ended up linking this post: https://chelseatroy.com/2024/08/28/does-ai-benefit-the-world/ which bothered me in a related way. In it, Troy describes classroom teaching techniques for introducing and helping students explore the ethics of AI, and they seem mostly great. They avoid prescribing any particular correct stance, which is important when teaching given the power relationship, and they help students understand the limitations of their perspectives regarding global impacts, which is great. But the overall conclusion of the post is that "nobody is qualified to really judge global impacts, so we should focus on ways to improve outcomes instead of trying to judge them." This bothers me because we actually do have a responsibility to make decisive ethical judgments despite limitations of our perspectives. If we never commit to any ethical judgment against a technology because we think our perspective is too limited to know the true impacts (which I'll concede it invariably is) then we'll have to accept every technology without objection, limiting ourselves to trying to improve their impacts without opposing them. Given who currently controls most of the resources that go into exploration for new technologies, this stance is too permissive. Perhaps if our objection to a technology was absolute and instantly effective, I'd buy the argument that objecting without a deep global view of the long-term risks is dangerous. As things stand, I think that objecting to the development/use of certain technologies in certain contexts is necessary, and although there's a lot of uncertainly, I expect strongly enough that the overall outcomes of objection will be positive that I think it's a good thing to do.
The deeper point here I guess is that this kind of "things are too complicated, let's have a nuanced discussion where we don't come to any conclusions because we see a lot of unknowns along with definite harms" really bothers me.

Programming by Backprop: LLMs Acquire Reusable Algorithmic Abstractions During Code Training
Jonathan Cook, Silvia Sapora, Arash Ahmadian, Akbir Khan, Tim Rocktaschel, Jakob Foerster, Laura Ruis
https://arxiv.org/abs/2506.18777

Programming by Backprop: LLMs Acquire Reusable Algorithmic Abstractions During Code Training
Training large language models (LLMs) on source code significantly enhances their general-purpose reasoning abilities, but the mechanisms underlying this generalisation are poorly understood. In this paper, we propose Programming by Backprop (PBB) as a potential driver of this effect - teaching a model to evaluate a program for inputs by training on its source code alone, without ever seeing I/O examples. To explore this idea, we finetune LLMs on two sets of programs representing simple maths p…

Similarly, hostility to education cloaks itself as support by saying that education should be useful, should be practical, should be focused only on what students need, should be narrowed to what students need, should narrow students, should narrow students into being only what capitalism needs.
I wrote extensively about this dangerous line of thought here:
https://innig.net/teaching/liberal-arts-manifesto
6/

Agile and Student-Centred Teaching of Agile/Scrum Concepts
Maria Spichkova
https://arxiv.org/abs/2506.14369 https://arxiv.org/pdf/250…

Agile and Student-Centred Teaching of Agile/Scrum Concepts
In this paper, we discuss our experience in designing and teaching a course on Software Engineering Project Management, where the focus is on Agile/Scrum development and Requirement Engineering activities. The course has undergone fundamental changes since 2020 to make the teaching approach more student-centred and flexible. As many universities abandoned having face-to-face exams at the end of the semester, authentic assessments now play an even more important role than before. This makes asse…

A "watch your replay videos" reflection assignment on comparing programming without versus with generative AI: learning about programming, critical AI use and limitations, and reflection
Sarah "Magz" Fernandez, Greg L Nelson
https://arxiv.org/abs/2507.17226

A "watch your replay videos" reflection assignment on comparing programming without versus with generative AI: learning about programming, critical AI use and limitations, and reflection
Generative AI is disrupting computing education. Most interventions focus on teaching GenAI use rather than helping students understand how AI changes their programming process. We designed and deployed a novel comparative video reflection assignment adapting the Describe, Examine, then Articulate Learning (DEAL) framework. In an introductory software engineering course, students recorded themselves programming during their team project two times: first without, then with using generative AI. S…

At #AIED2025 we are getting a preview of the report of the #EuropeanDigitalEducationHub, providing practical examples of how XAI-Ed could be used

Explainable AI in education: Fostering human oversight and shared responsibility - Knowledge Innovation Centre
Explainable AI in education is essential for maintaining human oversight as AI tools become more prevalent in teaching and learning. This report examines how transparency and explainability foster trust, ensure legal compliance, and preserve human agency.

Im having a mental battle of cheap vs lazy. I have an old Thinkpad laptop i use for teaching. (T40?) Circa 2015ish. But it works just fine, no issues with Fedora, and giving Garuda a try for now on it. Its a good laptop. Problem is that its heavy. And I have to carry a work laptop (MS Surface, win11) as well. And two laptops in the bag is a bit of weight. So I am debating getting a refurb X1 Carbon. But the cheap part of me is going "NOOOO". Ugh, internal conflicts.

Most educators have moved from denial about AI to cautious use, but the real cutting-edge is creators misusing it, twisting it, revealing off-label uses and glitches. At least that's what I claim in this U of T podcast https://edtech.engineering.utoronto.ca/made-for-u-o…

Talking to Dragons
#teaching #ai I was talking with Jennifer Fletcher about the perils of AI for education and one of the points she made was that we should be careful not to anthropomorphize AI. I think that is true, but difficult. Humans anthropomorphize EVERYTHING, from pets, to cars, to …

Teaching Complex Systems based on Microservices
Renato Cordeiro Ferreira (University of S\~ao Paulo), Thatiane de Oliveira Rosa (University of S\~ao Paulo, Federal Institute of Tocantins), Alfredo Goldman (University of S\~ao Paulo), Eduardo Guerra (Free University of Bozen-Bolzano)
https://arxiv.org/abs/2506.16492

Teaching Complex Systems based on Microservices
Developing complex systems using microservices is a current challenge. In this paper, we present our experience with teaching this subject to more than 80 students at the University of São Paulo (USP), fostering team work and simulating the industry's environment. We show it is possible to teach such advanced concepts for senior undergraduate students of Computer Science and related fields.

Teaching people how to use LLMs is not "upskilling", it's the opposite.

An elementary proof of Newman's eta-quotient theorem
David Savitt
https://arxiv.org/abs/2507.16225 https://arxiv.org/pdf/2507.162…

An elementary proof of Newman's eta-quotient theorem
Let eta(z) be the Dedekind eta function. Newman studied the modularity of eta-quotients, giving necessary and sufficient conditions for a function of the form \prod_{0 < m | N} eta(mz)^{r_m} to be a (weakly) holomorphic modular form of level N. We explain a proof of Newman's theorem, developed while teaching a class for talented high school students at Canada/USA Mathcamp. The key observation is that although Gamma_1(N) is not generated by its upper triangular and lower triangular subgroup…

Replaced article(s) found for physics.ed-ph. https://arxiv.org/list/physics.ed-ph/new
[1/1]:
- Coupled Oscillators, Frequency Transfer and the Higgs Mechanism's Teaching
M. O. Tahim, C. R. Muniz, M. S. Cunha, R. I. O. Junior

Another piece of sad US science news: Fulbright board is resigning to protest government interference. When I lived in Beijing as a student, I shared an apartment with a Fulbright scholar. She was so accomplished and amazing, and did really important work (in addition to volunteer teaching at a local middle school, impacting countless families - I wonder how much that achieved for US-China relations)
https://nfdi.social/@PetraSteiner/114712084471545669

Medicaid Cuts Set to Drain Revenue at Elite Teaching Hospitals (Bloomberg)
https://www.bloomberg.com/news/articles/2025-08-07/medicaid-cuts-set-to-drain-revenue-at-elite-teaching-hospitals
http://www.memeorandum.com/250807/p64#a250807p64

#Blakes7 Series C, Episode 10 - Ultraworld
AVON: When the planet was on the screen, did anyone notice Cally's reaction?
VILA: I didn't.
AVON: You were too busy teaching Orac nursery rhymes.
VILA: Riddles.
https://

Blakes7Bot | Search
Companion site to the Blakes7Bot Twitter, Mastodon, and Bluesky accounts. Automated lines of Blakes 7 dialog. Includes a script search facility.

What is happening? Have I gone through the looking glass?? C-suite types are saying things about AI that…actually make sense?!?
AWS CEO Matt Garman: “My view is you absolutely want to keep hiring kids out of college and teaching them the right ways to go build software and decompose problems and think about it, just as much as you ever have.” https://mastodon.social/@fromjason/115067646625547469

My slides on The Paradoxes of Open Data in Libraries, Archives and Museums #DH2025 panel on Openness in GLAM: Analysing, Reflecting, and D…

Reflection, co-founded by ex-Google researchers, unveils Asimov, an AI agent that reads a company's codebase, docs, and more to help software engineering teams (Will Knight/Wired)
https://www.wired.com/story/former-top-google-researchers-have-m…

Former Top Google Researchers Have Made a New Kind of AI Agent
The mission? Teaching models to better understand how to build code will lead to superintelligent AI.

Bridging MOOCs, Smart Teaching, and AI: A Decade of Evolution Toward a Unified Pedagogy
Bo Yuan, Jiazi Hu
https://arxiv.org/abs/2507.14266 https://

Bridging MOOCs, Smart Teaching, and AI: A Decade of Evolution Toward a Unified Pedagogy
Over the past decade, higher education has evolved through three distinct paradigms: the emergence of Massive Open Online Courses (MOOCs), the integration of Smart Teaching technologies into classrooms, and the rise of AI-enhanced learning. Each paradigm is intended to address specific challenges in traditional education: MOOCs enable ubiquitous access to learning resources; Smart Teaching supports real-time interaction with data-driven insights; and generative AI offers personalized feedback a…

My wife is smarter than me and better than me at almost everything, except a couple things. One of them is regrets. I've been working on teaching her how not to regret anything, ever. Over a series of years. I think it's working fairly well. Sometimes. 😂

T-TExTS (Teaching Text Expansion for Teacher Scaffolding): Enhancing Text Selection in High School Literature through Knowledge Graph-Based Recommendation
Nirmal Gelal, Chloe Snow, Ambyr Rios, Hande K\"u\c{c}\"uk McGinty
https://arxiv.org/abs/2506.12075

T-TExTS (Teaching Text Expansion for Teacher Scaffolding): Enhancing Text Selection in High School Literature through Knowledge Graph-Based Recommendation
The implementation of transformational pedagogy in secondary education classrooms requires a broad multiliteracy approach. Due to limited planning time and resources, high school English Literature teachers often struggle to curate diverse, thematically aligned literature text sets. This study addresses the critical need for a tool that provides scaffolds for novice educators in selecting literature texts that are diverse -- in terms of genre, theme, subtheme, and author -- yet similar in conte…

I agree!
#Anarchy #Anarchism

I overheard a woman ranting that it is bad that they are not teaching cursive in school. Her reasoning?
"If they can't write cursive, then they can't read cursive. If they can't read cursive, then they can't read The Constitution?"
This is 100% nonsense reasoning. I learned to write in cursive ~40 years ago. I've read the Constitution at least 4 times, but never by reading an image of the document - I only read it in print in a book or a website.

It takes a village to write a book: Mapping anonymous contributions in Stephen Langton's Quaestiones Theologiae
Jan Maliszewski
https://arxiv.org/abs/2508.12830 https://

It takes a village to write a book: Mapping anonymous contributions in Stephen Langton's Quaestiones Theologiae
While the indirect evidence suggests that already in the early scholastic period the literary production based on records of oral teaching (so-called reportationes) was not uncommon, there are very few sources commenting on the practice. This paper details the design of a study applying stylometric techniques of authorship attribution to a collection developed from reportationes -- Stephen Langton's Quaestiones Theologiae -- aiming to uncover layers of editorial work and thus validate some hypo…

Interesting interview: Why a professor of fascism left the US: ‘The lesson of 1933 is – you get out’
https://www.theguardian.com/us-news/2025/jun/16/why-a-professor-of-fascism-left-the-us-the-lesson-of-1933-i…

A "simple generalization" of a #JavaScript "Stored Map" ended up taking 2 days of work (done in 4 days) but happy with the result: Able to drop-in replace the non-general version *and* satisfy a different use case. Plus, I learned a lot and gathered a ton of #teaching material. 😊
#softwareEngineering #webdev

This👇needs to be remembered. https://substack.com/@johncleese/note/c-125827219?r=e7vv

John Cleese on Substack
Steve Bannon illustrates the key point we made in ‘The Life of Brian’ - that people makes what they like of religious teaching Matthew 26,52 And then Jesus said unto him ‘Put your sword back into its place, for those who take the sword will perish by the sword” Steve Bannon has rewritten this as “Live by the sword, die by the sword” as though it was a command. I prefer Jesus’s warning of the consequences of violence Only a MAGA Christian could believe that Christ was inciti…

This👇needs to be remembered. https://substack.com/@johncleese/note/c-125827219?r=e7vv

John Cleese on Substack
Steve Bannon illustrates the key point we made in ‘The Life of Brian’ - that people makes what they like of religious teaching Matthew 26,52 And then Jesus said unto him ‘Put your sword back into its place, for those who take the sword will perish by the sword” Steve Bannon has rewritten this as “Live by the sword, die by the sword” as though it was a command. I prefer Jesus’s warning of the consequences of violence Only a MAGA Christian could believe that Christ was inciti…

Designing conflict-based communicative tasks in Teaching Chinese as a Foreign Language with ChatGPT
Xia Li (LIDILEM)
https://arxiv.org/abs/2506.09089 https…

Designing conflict-based communicative tasks in Teaching Chinese as a Foreign Language with ChatGPT
In developing the teaching program for a course in Oral Expression in Teaching Chinese as a Foreign Language at the university level, the teacher designs communicative tasks based on conflicts to encourage learners to engage in interactive dynamics and develop their oral interaction skills. During the design of these tasks, the teacher uses ChatGPT to assist in finalizing the program. This article aims to present the key characteristics of the interactions between the teacher and ChatGPT during…

Teaching LLMs to Speak Spectroscopy
Nesar Ramachandra, Yuan-Sen Ting, Zechang Sun, Azton Wells, Salman Habib
https://arxiv.org/abs/2508.10075 https://arxiv…

Teaching LLMs to Speak Spectroscopy
Pre-trained Large Language Models (LLMs) have revolutionized text processing, yet adapting Transformer-based neural networks to non-textual scientific modalities typically requires specialized architectures and extensive computational resources. We demonstrate that LLaMA-3.1-8B can be efficiently repurposed to predict galaxy redshifts from spectroscopic data through Low-Rank Adaptation (LoRA), achieving competitive performance while preserving its linguistic capabilities. Using only 16 GPU-hour…

'Not pushing the panic button,' Cowboys HC Schottenheimer not pulling plug on QB Milton https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2025/08/18/schottenheimer-cowboys-qb-milton-struggles-ravens…

Teaching Introductory Functional Programming Using Haskelite
Pedro Vasconcelos (University of Porto)
https://arxiv.org/abs/2508.03640 https://arxiv.org/pdf…

Teaching Introductory Functional Programming Using Haskelite
Learning functional programming requires learning a substitution-based computational model. While substitution should be a familiar concept from high-school algebra, students often have difficulty applying it to new settings, such as recursive definitions, algebraic data types and higher-order functions. Step-by-step interpreters have been shown to help beginners by clarifying misconceptions and improving understanding. This paper reports on the experience of using a step-by-step tracing inte…

from my link log —
Bril: an intermediate language for teaching compilers.
https://www.cs.cornell.edu/~asampson/blog/bril.html
saved 2024-07-27

Teaching Physical Awareness to LLMs through Sounds
Weiguo Wang, Andy Nie, Wenrui Zhou, Yi Kai, Chengchen Hu
https://arxiv.org/abs/2506.08524 https://

Teaching Physical Awareness to LLMs through Sounds
Large Language Models (LLMs) have shown remarkable capabilities in text and multimodal processing, yet they fundamentally lack physical awareness--understanding of real-world physical phenomena. In this work, we present ACORN, a framework that teaches LLMs physical awareness through sound, focusing on fundamental physical phenomena like the Doppler effect, multipath effect, and spatial relationships. To overcome data scarcity, ACORN introduce a physics-based simulator combining real-world sound…

You know what's the difference between a human programmer and an "#AI coding assistant"?
Sure, human programmers make mistakes. And rookies often make "worse" mistakes than an #LLM can come up with. However, the difference is that humans can actually learn. Teaching them comes with a payoff; not always and not necessarily for your project, but there's a good chance that they'll become better programmers and contribute back to the community.
Sure, human programmers sometimes plagiarize. And of course they need to look at some code while they learn. However, they actually can think on their own and come up with something original. And they can learn that plagiarism is wrong.
And most importantly, usually they don't lie if they don't have to, and there are limits to their smugness. You can build a healthy community with them.
You can't build a community with unethical bullshit-spitting machines.
#programming #FreeSoftware #OpenSource

When topics of discourse prove difficult to approach, stories can help us on our way. This famed short story about a graceful city with an unexpected abberation helps me reflect on where I want to apply my capacity for writing, sketching and teaching.

https://axbom.com/omelas/

#DigitalEthics

In the end, “designing assignments that reward insight over polish, creating policies that prioritize learning over automation, and teaching students to question not just what AI produces but how and why they are using it” will have to mean: you can’t pass by using #GenAI.
But since GenAI can already do a pretty good impression of many things, we’ll have to make our courses extremely challe…

In the end, “designing assignments that reward insight over polish, creating policies that prioritize learning over automation, and teaching students to question not just what AI produces but how and why they are using it” will have to mean: you can’t pass by using #GenAI.
But since GenAI can already do a pretty good impression of many things, we’ll have to make our courses extremely challe…

A simple formalization of alpha-equivalence
Kalmer Apinis, Danel Ahman
https://arxiv.org/abs/2507.10181 https://arxiv.org/pdf/2507.10…

A simple formalization of alpha-equivalence
While teaching untyped $λ$-calculus to undergraduate students, we were wondering why $α$-equivalence is not directly inductively defined. In this paper, we demonstrate that this is indeed feasible. Specifically, we provide a grounded, inductive definition for $α$-equivalence and show that it conforms to the specification provided in the literature. The work presented in this paper is fully formalized in the Rocq Prover.

Offensive Lineman Speaks on Teaching and Competing Against Raiders' Young Talent https://www.si.com/nfl/raiders/las-vegas-alex-cappa-pete-carroll-chip-kelly-training-camp

Teaching with AI: Human Days and AI Days
In my previous post I outlined a plan for a no-tech pedagogy that would prevent students from using AI to do the assignments. However, my colleagues tell me that current policy at the university where I used to teach requires the use of AI in some classes. They have also eliminated the budget for photocopying handouts and texts. Everything must be delivered through the Learning Management System, which in this case is Canvas.

Has #DH2025 inspired you to get more involved in Digital Humanities communities? Sign up for the @… newsletter for updates from our 14 DH organisations and 10 special interest groups (SIGs)

So sad: #genAI

Teachers Are Not OK
AI, ChatGPT, and LLMs "have absolutely blown up what I try to accomplish with my teaching."

CFP: Edited Collection on Contingent Teaching from WAC Clearinghouse https://call-for-papers.sas.upenn.edu/cfp/2025/07/28/cfp-edited-collection-on-contingent-teaching-from-wac-clearinghouse

VeS: Teaching Pixels to Listen Without Supervision
Sajay Raj
https://arxiv.org/abs/2507.22008 https://arxiv.org/pdf/2507.22008

VeS: Teaching Pixels to Listen Without Supervision
Recent dense audio-visual (AV) models achieve impressive retrieval and emergent localization, but almost all evidence comes from English-centric, caption-rich web video. It is unclear whether these objectives survive in low-resource, code-switched, and noisy multilingual settings that typify developing regions. We show they do**-**and that the choice of aggregation function becomes even more critical. Using a multilingual subset of Project Vaani spanning dozens of Indian languages and dialectal…

Musician Ela Minus on having more power over your work
#creativity #artist

Musician Ela Minus on having more power over your work – The Creative Independent
Musician Ela Minus discusses demystifying your industry, questioning yourself and the systems around you, and the importance of teaching others

Classes start next week, and as usual, I am teaching Linux Systems Administration. Any pearls of wisdom or particular topics you think the next gen of admins needs to know? #linux #unix #sysadmin…

Developing a ChatGPT-Based Tool for Physics Experiment Teaching
Yifeng Liu, Min Li, Zhaojun Zhang, Youkang Fang, Meibao Qin
https://arxiv.org/abs/2508.13011 https://

Developing a ChatGPT-Based Tool for Physics Experiment Teaching
This paper examines how advanced AI assistants can help physics educators create practical teaching tools without specialized programming skills. Using the square-wave synthesis experiment as a case, we target common obstacles in laboratory instruction-complex setup, unstable signals, and limited class time-and show how AI-assisted development can shift attention from wiring and calibration to core physical ideas. To address this need, we guided an AI assistant through iterative prompts to ge…

MimicFunc: Imitating Tool Manipulation from a Single Human Video via Functional Correspondence
Chao Tang, Anxing Xiao, Yuhong Deng, Tianrun Hu, Wenlong Dong, Hanbo Zhang, David Hsu, Hong Zhang
https://arxiv.org/abs/2508.13534

MimicFunc: Imitating Tool Manipulation from a Single Human Video via Functional Correspondence
Imitating tool manipulation from human videos offers an intuitive approach to teaching robots, while also providing a promising and scalable alternative to labor-intensive teleoperation data collection for visuomotor policy learning. While humans can mimic tool manipulation behavior by observing others perform a task just once and effortlessly transfer the skill to diverse tools for functionally equivalent tasks, current robots struggle to achieve this level of generalization. A key challenge l…

Breakable Machine: A K-12 Classroom Game for Transformative AI Literacy Through Spoofing and eXplainable AI (XAI)
Olli Hilke, Nicolas Pope, Juho Kahila, Henriikka Vartiainen, Teemu Roos, Tuomo Parkki, Matti Tedre
https://arxiv.org/abs/2508.14201

Breakable Machine: A K-12 Classroom Game for Transformative AI Literacy Through Spoofing and eXplainable AI (XAI)
This paper, submitted to the special track on resources for teaching AI in K-12, presents an eXplainable AI (XAI)-based classroom game "Breakable Machine" for teaching critical, transformative AI literacy through adversarial play and interrogation of AI systems. Designed for learners aged 10-15, the game invites students to spoof an image classifier by manipulating their appearance or environment in order to trigger high-confidence misclassifications. Rather than focusing on building AI models,…

Careful Queries, Credible Results: Teaching RAG Models Advanced Web Search Tools with Reinforcement Learning
Yuqin Dai, Shuo Yang, Guoqing Wang, Yong Deng, Zhanwei Zhang, Jun Yin, Pengyu Zeng, Zhenzhe Ying, Changhua Meng, Can Yi, Yuchen Zhou, Weiqiang Wang, Shuai Lu
https://arxiv.org/abs/2508.07956…

Careful Queries, Credible Results: Teaching RAG Models Advanced Web Search Tools with Reinforcement Learning
Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by integrating up-to-date external knowledge, yet real-world web environments present unique challenges. These limitations manifest as two key challenges: pervasive misinformation in the web environment, which introduces unreliable or misleading content that can degrade retrieval accuracy, and the underutilization of web tools, which, if effectively employed, could enhance query precision and help mitigate this noise, ul…

Feedback Indicators: The Alignment between Llama and a Teacher in Language Learning
Sylvio R\"udian, Yassin Elsir, Marvin Kretschmer, Sabine Cayrou, Niels Pinkwart
https://arxiv.org/abs/2508.11364

Feedback Indicators: The Alignment between Llama and a Teacher in Language Learning
Automated feedback generation has the potential to enhance students' learning progress by providing timely and targeted feedback. Moreover, it can assist teachers in optimizing their time, allowing them to focus on more strategic and personalized aspects of teaching. To generate high-quality, information-rich formative feedback, it is essential first to extract relevant indicators, as these serve as the foundation upon which the feedback is constructed. Teachers often employ feedback criteria g…

Some excellent talks in #DH2025 LP-07 on 'What Happens When "Hacking" Becomes Easy? Teaching Python in 2025'
Filipa (?): 'A claim about abundance in the future is often a disguised claim about scarcity in the present'
Patrick: 'what do we do when our students can reach for a 'not learning' button? Things that could have been done at home may need …

ALEA IACTA EST: A Declarative Domain-Specific Language for Manually Performable Random Experiments
Baltasar Tranc\'on y Widemann, Markus Lepper
https://arxiv.org/abs/2506.11794

ALEA IACTA EST: A Declarative Domain-Specific Language for Manually Performable Random Experiments
Random experiments that are simple and clear enough to be performed by human agents feature prominently in the teaching of elementary stochastics as well as in games. We present Alea, a domain-specific language for the specification of random experiments. Alea code can either be analyzed statically to obtain and inspect probability distributions of outcomes, or be executed with a source pseudo-randomness for simulation or as a game assistant. The language is intended for ease of use by non-expe…

Should we teach vibe coding? Here's why not.
Should AI coding be taught in undergrad CS education?
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I teach undergraduate computer science labs, including for intro and more-advanced core courses. I don't publish (non-negligible) scholarly work in the area, but I've got years of craft expertise in course design, and I do follow the academic literature to some degree. In other words, In not the world's leading expert, but I have spent a lot of time thinking about course design, and consider myself competent at it, with plenty of direct experience in what knowledge & skills I can expect from students as they move through the curriculum.
I'm also strongly against most uses of what's called "AI" these days (specifically, generative deep neutral networks as supplied by our current cadre of techbro). There are a surprising number of completely orthogonal reasons to oppose the use of these systems, and a very limited number of reasonable exceptions (overcoming accessibility barriers is an example). On the grounds of environmental and digital-commons-pollution costs alone, using specifically the largest/newest models is unethical in most cases.
But as any good teacher should, I constantly question these evaluations, because I worry about the impact on my students should I eschew teaching relevant tech for bad reasons (and even for his reasons). I also want to make my reasoning clear to students, who should absolutely question me on this. That inspired me to ask a simple question: ignoring for one moment the ethical objections (which we shouldn't, of course; they're very stark), at what level in the CS major could I expect to teach a course about programming with AI assistance, and expect students to succeed at a more technically demanding final project than a course at the same level where students were banned from using AI? In other words, at what level would I expect students to actually benefit from AI coding "assistance?"
To be clear, I'm assuming that students aren't using AI in other aspects of coursework: the topic of using AI to "help you study" is a separate one (TL;DR it's gross value is not negative, but it's mostly not worth the harm to your metacognitive abilities, which AI-induced changes to the digital commons are making more important than ever).
So what's my answer to this question?
If I'm being incredibly optimistic, senior year. Slightly less optimistic, second year of a masters program. Realistic? Maybe never.
The interesting bit for you-the-reader is: why is this my answer? (Especially given that students would probably self-report significant gains at lower levels.) To start with, [this paper where experienced developers thought that AI assistance sped up their work on real tasks when in fact it slowed it down] (https://arxiv.org/abs/2507.09089) is informative. There are a lot of differences in task between experienced devs solving real bugs and students working on a class project, but it's important to understand that we shouldn't have a baseline expectation that AI coding "assistants" will speed things up in the best of circumstances, and we shouldn't trust self-reports of productivity (or the AI hype machine in general).
Now we might imagine that coding assistants will be better at helping with a student project than at helping with fixing bugs in open-source software, since it's a much easier task. For many programming assignments that have a fixed answer, we know that many AI assistants can just spit out a solution based on prompting them with the problem description (there's another elephant in the room here to do with learning outcomes regardless of project success, but we'll ignore this over too, my focus here is on project complexity reach, not learning outcomes). My question is about more open-ended projects, not assignments with an expected answer. Here's a second study (by one of my colleagues) about novices using AI assistance for programming tasks. It showcases how difficult it is to use AI tools well, and some of these stumbling blocks that novices in particular face.
But what about intermediate students? Might there be some level where the AI is helpful because the task is still relatively simple and the students are good enough to handle it? The problem with this is that as task complexity increases, so does the likelihood of the AI generating (or copying) code that uses more complex constructs which a student doesn't understand. Let's say I have second year students writing interactive websites with JavaScript. Without a lot of care that those students don't know how to deploy, the AI is likely to suggest code that depends on several different frameworks, from React to JQuery, without actually setting up or including those frameworks, and of course three students would be way out of their depth trying to do that. This is a general problem: each programming class carefully limits the specific code frameworks and constructs it expects students to know based on the material it covers. There is no feasible way to limit an AI assistant to a fixed set of constructs or frameworks, using current designs. There are alternate designs where this would be possible (like AI search through adaptation from a controlled library of snippets) but those would be entirely different tools.
So what happens on a sizeable class project where the AI has dropped in buggy code, especially if it uses code constructs the students don't understand? Best case, they understand that they don't understand and re-prompt, or ask for help from an instructor or TA quickly who helps them get rid of the stuff they don't understand and re-prompt or manually add stuff they do. Average case: they waste several hours and/or sweep the bugs partly under the rug, resulting in a project with significant defects. Students in their second and even third years of a CS major still have a lot to learn about debugging, and usually have significant gaps in their knowledge of even their most comfortable programming language. I do think regardless of AI we as teachers need to get better at teaching debugging skills, but the knowledge gaps are inevitable because there's just too much to know. In Python, for example, the LLM is going to spit out yields, async functions, try/finally, maybe even something like a while/else, or with recent training data, the walrus operator. I can't expect even a fraction of 3rd year students who have worked with Python since their first year to know about all these things, and based on how students approach projects where they have studied all the relevant constructs but have forgotten some, I'm not optimistic seeing these things will magically become learning opportunities. Student projects are better off working with a limited subset of full programming languages that the students have actually learned, and using AI coding assistants as currently designed makes this impossible. Beyond that, even when the "assistant" just introduces bugs using syntax the students understand, even through their 4th year many students struggle to understand the operation of moderately complex code they've written themselves, let alone written by someone else. Having access to an AI that will confidently offer incorrect explanations for bugs will make this worse.
To be sure a small minority of students will be able to overcome these problems, but that minority is the group that has a good grasp of the fundamentals and has broadened their knowledge through self-study, which earlier AI-reliant classes would make less likely to happen. In any case, I care about the average student, since we already have plenty of stuff about our institutions that makes life easier for a favored few while being worse for the average student (note that our construction of that favored few as the "good" students is a large part of this problem).
To summarize: because AI assistants introduce excess code complexity and difficult-to-debug bugs, they'll slow down rather than speed up project progress for the average student on moderately complex projects. On a fixed deadline, they'll result in worse projects, or necessitate less ambitious project scoping to ensure adequate completion, and I expect this remains broadly true through 4-6 years of study in most programs (don't take this as an endorsement of AI "assistants" for masters students; we've ignored a lot of other problems along the way).
There's a related problem: solving open-ended project assignments well ultimately depends on deeply understanding the problem, and AI "assistants" allow students to put a lot of code in their file without spending much time thinking about the problem or building an understanding of it. This is awful for learning outcomes, but also bad for project success. Getting students to see the value of thinking deeply about a problem is a thorny pedagogical puzzle at the best of times, and allowing the use of AI "assistants" makes the problem much much worse. This is another area I hope to see (or even drive) pedagogical improvement in, for what it's worth.
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From Data to Insight: Using Contextual Scenarios to Teach Critical Thinking in Data Visualisation
Jonathan C. Roberts, Peter Butcher, Panagiotis D. Ritsos
https://arxiv.org/abs/2508.08737

From Data to Insight: Using Contextual Scenarios to Teach Critical Thinking in Data Visualisation
This paper explores the use of scenario-based visualisation examples as a pedagogical strategy for teaching students the complexities of data insight, representation, and interpretation. Teaching data visualisation often involves explaining intricate issues related to data management and the challenges of presenting data meaningfully. In this work, we present a series of data-driven scenarios. These concise stories depict specific situations, and are created to help the educators highlight key …

Enhancing Physics Hand-on Lab through Online Educational Tools
Marina Babayeva
https://arxiv.org/abs/2506.16193 https://arxiv.org/pdf…

Enhancing Physics Hand-on Lab through Online Educational Tools
The increasing availability of digital tools for education offers significant opportunities to enhance teaching practices and student engagement. This study presents a structured categorization of online educational tools based on their core functionalities, including content creation, assessment, classroom management, and collaboration. A pilot implementation of selected tools was conducted in secondary-level science education, followed by a refinement phase to address usability and integratio…

Few-shot transfer of tool-use skills using human demonstrations with proximity and tactile sensing
Marina Y. Aoyama, Sethu Vijayakumar, Tetsuya Narita
https://arxiv.org/abs/2507.13200

Few-shot transfer of tool-use skills using human demonstrations with proximity and tactile sensing
Tools extend the manipulation abilities of robots, much like they do for humans. Despite human expertise in tool manipulation, teaching robots these skills faces challenges. The complexity arises from the interplay of two simultaneous points of contact: one between the robot and the tool, and another between the tool and the environment. Tactile and proximity sensors play a crucial role in identifying these complex contacts. However, learning tool manipulation using these sensors remains challe…

ParaStudent: Generating and Evaluating Realistic Student Code by Teaching LLMs to Struggle
Mihran Miroyan, Rose Niousha, Joseph E. Gonzalez, Gireeja Ranade, Narges Norouzi
https://arxiv.org/abs/2507.12674

ParaStudent: Generating and Evaluating Realistic Student Code by Teaching LLMs to Struggle
Large Language Models (LLMs) have shown strong performance on programming tasks, but can they generate student-like code like real students - imperfect, iterative, and stylistically diverse? We present ParaStudent, a systematic study of LLM-based "student-like" code generation in an introductory programming course setting. Using a dataset of timestamped student submissions across multiple semesters, we design low- and high-resolution experiments to model student progress and evaluate code outpu…

A Humanoid Social Robot as a Teaching Assistant in the Classroom
Thomas Sievers
https://arxiv.org/abs/2508.05646 https://arxiv.org/pdf/2508.05646

A Humanoid Social Robot as a Teaching Assistant in the Classroom
Although innovation and the support of new technologies are much needed to ease the burden on the education system, social robots in schools to help teachers with educational tasks are rare. Child-Robot Interaction (CRI) could support teachers and add an embodied social component to modern multi-modal and multi-sensory learning environments already in use. The social robot Pepper, connected to the Large Language Model (LLM) ChatGPT, was used in a high school classroom to teach new learning cont…

Hey, folks who understand alt text and limited vision accessibility:
I have need to write alt text for the diagram below. The alt text needs to be comprehensible to somebody who is encountering this kind of diagram for the ••very first time••. I could describe the images using the relevant jargon, but that would only serve people who already know the thing this activity is teaching them!
Any suggestions for how I could write good alt text for something like this? Is it possible? (The horizontal black bars are minus signs, i.e. subtraction. This is clear from context in the text, but probably not clear in the image.)
PLEASE NOTE: I am looking for people with ••relevant accessibility expertise••, not just random best shots from people who (like me) don’t really know much about this kind of problem.

Notes from the Physics Teaching Lab: NMR Experiments at 21 Gauss
Kenneth G. Libbrecht
https://arxiv.org/abs/2508.10738 https://arxiv.org/pdf/2508.10738

Notes from the Physics Teaching Lab: NMR Experiments at 21 Gauss
We describe a series of laboratory experiments that can be performed with the Quantum Control apparatus sold by TeachSpin, which uses pulsed NMR techniques to observe the precession of protons in a liquid water sample. With a uniform background magnetic field of 21 Gauss, the protons precess at about 90 kHz, yielding numerous relatively simple observations and measurements that are well suited to undergraduate physics teaching labs. Our goal in this paper is to document some of these experiment…

Teaching Introduction to Programming in the times of AI: A case study of a course re-design
Nikolaos Avouris, Kyriakos Sgarbas, George Caridakis, Christos Sintoris
https://arxiv.org/abs/2508.06572

Teaching Introduction to Programming in the times of AI: A case study of a course re-design
The integration of AI tools into programming education has become increasingly prevalent in recent years, transforming the way programming is taught and learned. This paper provides a review of the state-of-the-art AI tools available for teaching and learning programming, particularly in the context of introductory courses. It highlights the challenges on course design, learning objectives, course delivery and formative and summative assessment, as well as the misuse of such tools by the studen…

Ashes or Breath: Exploring Moral Dilemmas of Life and Cultural Legacy through Mixed Reality Gaming
Black Sun, Ge Kacy Fu, Shichao Guo
https://arxiv.org/abs/2508.13074 https://…

Ashes or Breath: Exploring Moral Dilemmas of Life and Cultural Legacy through Mixed Reality Gaming
Traditional approaches to teaching moral dilemmas often rely on abstract, disembodied scenarios that limit emotional engagement and reflective depth. To address this gap, we developed \textit{Ashes or Breath}, a Mixed Reality game delivered via head-mounted displays(MR-HMDs). This places players in an ethical crisis: they must save a living cat or a priceless cultural artifact during a museum fire. Designed through an iterative, values-centered process, the experience leverages embodied interac…

Coupled Oscillators, Frequency Transfer and the Higgs Mechanism's Teaching
M. K. Tahim, C. R. Muniz, M. S. Cunha, R. I. Oliveira Junior
https://arxiv.org/abs/2508.08640 http…

Coupled Oscillators, Frequency Transfer and the Higgs Mechanism's Teaching
In this work, we propose a simple model for teaching the Higgs mechanism of spontaneous symmetry breaking in Particle Physics. The basic idea is associated with analyzing the motion of two particles subjected to specific potentials in certain situations, which will reproduce the movements of harmonic oscillators with the effect of frequency transfer."

Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AI
Ryota Okumura, Tadahiro Taniguchi, Akira Taniguchi, Yoshinobu Hagiwara
https://arxiv.org/abs/2506.15468

Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AI
We propose co-creative learning as a novel paradigm where humans and AI, i.e., biological and artificial agents, mutually integrate their partial perceptual information and knowledge to construct shared external representations, a process we interpret as symbol emergence. Unlike traditional AI teaching based on unilateral knowledge transfer, this addresses the challenge of integrating information from inherently different modalities. We empirically test this framework using a human-AI interacti…

Sociotechnical Imaginaries of ChatGPT in Higher Education: The Evolving Media Discourse
Yinan Sun, Ali Unlu, Aditya Johri
https://arxiv.org/abs/2508.14692 https://

Sociotechnical Imaginaries of ChatGPT in Higher Education: The Evolving Media Discourse
This study investigates how U.S. news media framed the use of ChatGPT in higher education from November 2022 to October 2024. Employing Framing Theory and combining temporal and sentiment analysis of 198 news articles, we trace the evolving narratives surrounding generative AI. We found that the media discourse largely centered on institutional responses; policy changes and teaching practices showed the most consistent presence and positive sentiment over time. Conversely, coverage of topics su…

Teaching Problem Solving in Undergraduate Physics Courses: An Endorsement for Deliberate Practice
Kelly Miller, Olivia Miller, Georgia Lawrence
https://arxiv.org/abs/2508.08133 …

Teaching Problem Solving in Undergraduate Physics Courses: An Endorsement for Deliberate Practice
Developing expert-like problem-solving skills is a central goal of undergraduate physics education. In this study, we investigate the impact of teaching explicit problem-solving frameworks, combined with deliberate practice, on students' problem-solving approaches. Using multidimensional scaling to analyze students' decision-making patterns, we compare the similarity of students taught with these methods to physics experts and to students taught with traditional repeated practice. Our results s…

Teaching at Scale: Leveraging AI to Evaluate and Elevate Engineering Education
Jean-Francois Chamberland, Martin C. Carlisle, Arul Jayaraman, Krishna R. Narayanan, Sunay Palsole, Karan Watson
https://arxiv.org/abs/2508.02731

Teaching at Scale: Leveraging AI to Evaluate and Elevate Engineering Education
Evaluating teaching effectiveness at scale remains a persistent challenge for large universities, particularly within engineering programs that enroll tens of thousands of students. Traditional methods, such as manual review of student evaluations, are often impractical, leading to overlooked insights and inconsistent data use. This article presents a scalable, AI-supported framework for synthesizing qualitative student feedback using large language models. The system employs hierarchical summa…

Can you see how I learn? Human observers' inferences about Reinforcement Learning agents' learning processes
Bernhard Hilpert, Muhan Hou, Kim Baraka, Joost Broekens
https://arxiv.org/abs/2506.13583

Can you see how I learn? Human observers' inferences about Reinforcement Learning agents' learning processes
Reinforcement Learning (RL) agents often exhibit learning behaviors that are not intuitively interpretable by human observers, which can result in suboptimal feedback in collaborative teaching settings. Yet, how humans perceive and interpret RL agent's learning behavior is largely unknown. In a bottom-up approach with two experiments, this work provides a data-driven understanding of the factors of human observers' understanding of the agent's learning process. A novel, observation-based paradi…

From Misunderstandings to Learning Opportunities: Leveraging Generative AI in Discussion Forums to Support Student Learning
Stanislav Pozdniakov, Jonathan Brazil, Oleksandra Poquet, Stephan Krusche, Santiago Berrezueta-Guzman, Shazia Sadiq, Hassan Khosravi
https://arxiv.org/abs/2508.11150

From Misunderstandings to Learning Opportunities: Leveraging Generative AI in Discussion Forums to Support Student Learning
In the contemporary educational landscape, particularly in large classroom settings, discussion forums have become a crucial tool for promoting interaction and addressing student queries. These forums foster a collaborative learning environment where students engage with both the teaching team and their peers. However, the sheer volume of content generated in these forums poses two significant interconnected challenges: How can we effectively identify common misunderstandings that arise in stud…

Learning by Teaching: Engaging Students as Instructors of Large Language Models in Computer Science Education
Xinming Yang, Haasil Pujara, Jun Li
https://arxiv.org/abs/2508.05979

Learning by Teaching: Engaging Students as Instructors of Large Language Models in Computer Science Education
While Large Language Models (LLMs) are often used as virtual tutors in computer science (CS) education, this approach can foster passive learning and over-reliance. This paper presents a novel pedagogical paradigm that inverts this model: students act as instructors who must teach an LLM to solve problems. To facilitate this, we developed strategies for designing questions with engineered knowledge gaps that only a student can bridge, and we introduce Socrates, a system for deploying this metho…

Networked Observatory for Virtual Astronomy (NOVA): Teaching astronomy with AI
Jorge Pinochet
https://arxiv.org/abs/2507.08195 https://arxiv.org/pdf/2507.0…

Networked Observatory for Virtual Astronomy (NOVA): Teaching astronomy with AI
The term artificial intelligence (AI) first appeared in the mid-20th century. It wasn't until well into the 21st century that AI began to flourish. Today, AI has found very diverse applications. One area that is just beginning to be explored is physics education. The aim of this work is to contribute to this burgeoning educational field through a ChatGPT application named Networked Observatory for Virtual Astronomy (NOVA). This application provides students with simulated astronomical data in a…

Research on Comprehensive Classroom Evaluation System Based on Multiple AI Models
Cong Xie, Li Yang, Daben Wang, Jing Xiao
https://arxiv.org/abs/2506.23079

Research on Comprehensive Classroom Evaluation System Based on Multiple AI Models
The promotion of the national education digitalization strategy has facilitated the development of teaching quality evaluation towards all-round, process-oriented, precise, and intelligent directions, inspiring explorations into new methods and technologies for educational quality assurance. Classroom teaching evaluation methods dominated by teaching supervision and student teaching evaluation suffer from issues such as low efficiency, strong subjectivity, and limited evaluation dimensions. How…

Teaching Critical Visualization: A Field Report
Andrew McNutt, Shiyi He, Sujit Kumar Kamaraj, Purbid Bambroo, Nastaran Jadidi, John Bovard, Chang Han
https://arxiv.org/abs/2508.02592

Teaching Critical Visualization: A Field Report
Critical Visualization is gaining popularity and academic focus, yet relatively few academic courses have been offered to support students in this complex area. This experience report describes a recent experimental course on the topic, exploring both what the topic could be as well as an experimental content structure (namely as scavenger hunt). Generally the course was successful, achieving the learning objectives of developing critical thinking skills, improving communication about complex i…

Singing Syllabi with Virtual Avatars: Enhancing Student Engagement Through AI-Generated Music and Digital Embodiment
Xinxing Wu
https://arxiv.org/abs/2508.11872 https://

Singing Syllabi with Virtual Avatars: Enhancing Student Engagement Through AI-Generated Music and Digital Embodiment
In practical teaching, we observe that few students thoroughly read or fully comprehend the information provided in traditional, text-based course syllabi. As a result, essential details, such as course policies and learning outcomes, are frequently overlooked. To address this challenge, in this paper, we propose a novel approach leveraging AI-generated singing and virtual avatars to present syllabi in a format that is more visually appealing, engaging, and memorable. Especially, we leveraged t…

Using Video Games to Teach Kepler's Laws and Orbital Dynamics
Brian DiGiorgio Zanger
https://arxiv.org/abs/2508.13259 https://arxiv.org/pdf/2508.13259

Using Video Games to Teach Kepler's Laws and Orbital Dynamics
Physics instructors often rely on demonstrations when teaching, using real-time examples to appeal to student intuition or tinkering with a physical system to develop a deeper and more natural understanding of a topic. However, some subjects, like Kepler's laws of planetary motion, are impractical to demonstrate at a human scale, and when reality proves difficult, it is often easier to move to simulations and video games. In particular, using video games in the classroom benefits student learni…

Listening with Language Models: Using LLMs to Collect and Interpret Classroom Feedback
Sai Siddartha Maram, Ulia Zaman, Magy Seif El-Nasr
https://arxiv.org/abs/2508.11707 https:…

Listening with Language Models: Using LLMs to Collect and Interpret Classroom Feedback
Traditional end-of-quarter surveys often fail to provide instructors with timely, detailed, and actionable feedback about their teaching. In this paper, we explore how Large Language Model (LLM)-powered chatbots can reimagine the classroom feedback process by engaging students in reflective, conversational dialogues. Through the design and deployment of a three-part system-PromptDesigner, FeedbackCollector, and FeedbackAnalyzer-we conducted a pilot study across two graduate courses at UC Santa …

Inverted Classroom in der Einf\"uhrungsveranstaltung Programmierung
Ulrich von Zadow, Natalie Kiesler
https://arxiv.org/abs/2506.10057 https://…

Inverted Classroom in der Einführungsveranstaltung Programmierung
Traditionally, the introductory programming course for computer science students at Nuremberg Tech had been implemented as a combination of lectures and exercise sessions. Due to high failure rates in the winter semester 2023/24, an experimental teaching concept based on the inverted classroom was implemented for one cohort in the winter semester 2024/25. Students had to prepare themselves through literature work and activating teaching and learning methods. The course was accompanied by a seri…

Teaching Sustainable Creative Technologies
Chelsea Thompto
https://arxiv.org/abs/2507.05320 https://arxiv.org/pdf/2507.05320

Teaching Sustainable Creative Technologies
Artists and especially new media artists contribute to public perceptions and adoption of new technologies through their own use of emerging media technologies such as augmented and virtual reality, generative image systems, and high-resolution displays in the production of their work. In this way, art and media production can be understood as part of the larger issue of unsustainable computational consumption. As such, it is critical for artists to develop, share, and promote new and more sust…

Rookie Mistakes: Measuring Software Quality in Student Projects to Guide Educational Enhancement
Marco De Luca, Sergio Di Martino, Sergio Di Meglio, Anna Rita Fasolino, Luigi Libero Lucio Starace, Porfirio Tramontana
https://arxiv.org/abs/2507.12488

Rookie Mistakes: Measuring Software Quality in Student Projects to Guide Educational Enhancement
When teaching Programming and Software Engineering in Bachelor's Degree programs, the emphasis on creating functional software projects often overshadows the focus on software quality, a trend that aligns with ACM curricula recommendations. Software Engineering courses are typically introduced later in the curriculum, and can generally allocate only limited time to quality-related topics, leaving educators with the challenge of deciding which quality aspects to prioritize. In this decision, the…

The Transition Matrix -- A classification of navigational patterns between LMS course sections
Tobias Hildebrandt, Lars Mehnen
https://arxiv.org/abs/2506.13275

The Transition Matrix -- A classification of navigational patterns between LMS course sections
Learning management systems (LMS) like Moodle are increasingly used to support university teaching. As Moodle courses become more complex, incorporating diverse interactive elements, it is important to understand how students navigate through course sections and whether course designs are meeting student needs. While substantial research exists on student usage of individual LMS elements, there is a lack of research on broader navigational patterns between course sections and how these patterns…