https://pedromoralesalmazan.com/feed/ A daily digest of news, research and policy on artificial intelligence in higher education, curated automatically and posted to Telegram, Mastodon and Bluesky. en publish_site.py https://www.rssboard.org/rss-specification 720 Thu, 10 Sep 2026 05:31:26 +0000 Wed, 09 Sep 2026 21:17:07 +0000 Pedro Morales-Almazán https://www.sciencedirect.com/science/article/pii/S2666920X26001153?dgcid=rss_sd_all dab504f2a4601c56 Wed, 09 Sep 2026 21:17:07 +0000 Computers and Education: Artificial Intelligence, Volume 11 Source: Computers and Education: Artificial Intelligence Ningxia Wang, Di Zou, Haoran Xie https://www.sciencedirect.com/science/article/pii/S2666920X26001165?dgcid=rss_sd_all 86f1d41bb9d8274a Wed, 09 Sep 2026 21:17:03 +0000 Computers and Education: Artificial Intelligence, Volume 11 Source: Computers and Education: Artificial Intelligence Mariana Neto, Rui Pinto, João Reis https://www.sciencedirect.com/science/article/pii/S2666920X26000901?dgcid=rss_sd_all 9bc7d3b320ff8801 Wed, 09 Sep 2026 21:16:58 +0000 Computers and Education: Artificial Intelligence, Volume 11 Source: Computers and Education: Artificial Intelligence Viola Deutscher, Herbert Thomann, Olga Zlatkin-Troitschanskaia https://www.sciencedirect.com/science/article/pii/S2666920X26001232?dgcid=rss_sd_all 300d2b5aa61c9cc2 Wed, 09 Sep 2026 21:16:54 +0000 Computers and Education: Artificial Intelligence Source: Computers and Education: Artificial Intelligence Li-Jen Wang, Tsung-Yen Chuang, Ying-Tien Wu https://www.sciencedirect.com/science/article/pii/S2666920X26001311?dgcid=rss_sd_all 1ea8affabb79bd24 Wed, 09 Sep 2026 20:23:16 +0000 Computers and Education: Artificial Intelligence Source: Computers and Education: Artificial Intelligence Wangda Zhu, Yin Yang, Yuqin Yang https://www.sciencedirect.com/science/article/pii/S2666920X2600130X?dgcid=rss_sd_all 9bbd674df124adab Wed, 09 Sep 2026 20:23:11 +0000 Computers and Education: Artificial Intelligence Source: Computers and Education: Artificial Intelligence Alona Strugatski, Giora Alexandron https://www.sciencedirect.com/science/article/pii/S0360131526001557?dgcid=rss_sd_all 1d1ca7232f4b8706 Wed, 09 Sep 2026 20:23:07 +0000 Computers & Education, Volume 254 Source: Computers & Education Pan Ye, Shulin Yu, Icy Lee https://www.sciencedirect.com/science/article/pii/S2666557326000856?dgcid=rss_sd_all 664dd3e45d680576 Wed, 09 Sep 2026 20:23:03 +0000 Computers and Education Open, Volume 11 Source: Computers and Education Open Nicola Brocca, Davide Garassino https://www.sciencedirect.com/science/article/pii/S2666557326000820?dgcid=rss_sd_all 435e60b82f118502 Wed, 09 Sep 2026 19:18:55 +0000 Computers and Education Open, Volume 11 Source: Computers and Education Open Leonardo Franco Cruz, Miguel Mira da Silva, Henrique S. Mamede https://www.sciencedirect.com/science/article/pii/S2666557326000790?dgcid=rss_sd_all c35664b65fa35b71 Wed, 09 Sep 2026 19:18:51 +0000 Computers and Education Open, Volume 11 Source: Computers and Education Open Emmanuel Duncan https://www.sciencedirect.com/science/article/pii/S2666557326000819?dgcid=rss_sd_all 8869a04900614758 Wed, 09 Sep 2026 19:18:47 +0000 Computers and Education Open, Volume 11 Source: Computers and Education Open Lindelani Mnguni, R. Ahmad Zaky El Islami, Prasart Nuangchalerm https://www.sciencedirect.com/science/article/pii/S2666557326000716?dgcid=rss_sd_all 1969a50a137f44d0 Wed, 09 Sep 2026 19:18:43 +0000 Computers and Education Open, Volume 11 Source: Computers and Education Open Daniel I. Adeniranye, Stephanie J. Lunn, Olatunde Mosobalaje https://www.sciencedirect.com/science/article/pii/S2666557326000583?dgcid=rss_sd_all 916fccb622752bfb Wed, 09 Sep 2026 18:33:11 +0000 Computers and Education Open, Volume 11 Source: Computers and Education Open Sung-Shun Weng, Hui-Chun Chiang https://www.sciencedirect.com/science/article/pii/S2666557326000686?dgcid=rss_sd_all 6064a6c1ba224797 Wed, 09 Sep 2026 18:33:07 +0000 Computers and Education Open Source: Computers and Education Open Ling Bai, Cristina Costa https://www.sciencedirect.com/science/article/pii/S1096751626000308?dgcid=rss_sd_all a5d674419e4c8168 Wed, 09 Sep 2026 18:33:02 +0000 The Internet and Higher Education, Volume 71 Source: The Internet and Higher Education Du Jingwen, Wang Jun https://www.sciencedirect.com/science/article/pii/S1096751626000217?dgcid=rss_sd_all 94c4b31dd48ac169 Wed, 09 Sep 2026 18:32:58 +0000 The Internet and Higher Education, Volume 71 Source: The Internet and Higher Education Li Zhang, Yunxue Deng https://www.sciencedirect.com/science/article/pii/S1096751626000333?dgcid=rss_sd_all f225558e435d0f19 Wed, 09 Sep 2026 17:34:39 +0000 The Internet and Higher Education Source: The Internet and Higher Education Jingjing Zhang, Yehong Yang, Xiaojie Niu https://www.sciencedirect.com/science/article/pii/S1560429226000168?dgcid=rss_sd_all f308b5540b7ecd32 Wed, 09 Sep 2026 17:34:34 +0000 International Journal of Artificial Intelligence in Education, Volume 36, Issues 1–2 Source: International Journal of Artificial Intelligence in Education Stephan Geschwind, Johann Graf Lambsdorff, Deborah Voss https://www.sciencedirect.com/science/article/pii/S1560429226000028?dgcid=rss_sd_all 7df8e52eb5b3d32d Wed, 09 Sep 2026 17:34:30 +0000 International Journal of Artificial Intelligence in Education, Volume 36, Issues 1–2 Source: International Journal of Artificial Intelligence in Education Paola Mejia-Domenzain, Seyed Parsa Neshaei, Eva Laini https://www.sciencedirect.com/science/article/pii/S1560429226000090?dgcid=rss_sd_all ccbce938532b1842 Wed, 09 Sep 2026 17:34:26 +0000 International Journal of Artificial Intelligence in Education, Volume 36, Issues 1–2 Source: International Journal of Artificial Intelligence in Education Zuheir N. Khlaif, Rasha Alshakhshir, Bilal Hamamra https://er.educause.edu/articles/2026/8/facilitative-teaching-for-transformational-learning-in-the-age-of-ai 9dd3b252f9990c43 Wed, 09 Sep 2026 16:34:45 +0000 Higher education institutions can better prepare students for an artificial intelligence–augmented workforce by shifting from teacher-centered models to facilitative instructional approaches that develop the enduring professional capacities that become more, not less, valuable as AI transforms work: critical thinking, collaboration, creativity, and adaptability. Source: EDUCAUSE Review — Teaching & Learning https://er.educause.edu/articles/2026/4/listening-to-skepticism-what-faculty-concerns-about-generative-ai-reveal 94a6093544e50d64 Wed, 09 Sep 2026 16:34:41 +0000 Listening to faculty concerns about generative AI can help institutions respond with more clarity, precision, and trust. Source: EDUCAUSE Review — Teaching & Learning https://er.educause.edu/articles/2026/4/building-ai-initiatives-with-bottom-up-champions d135df86b486e16f Wed, 09 Sep 2026 16:34:36 +0000 Driven by a bottom-up partnership between the Faculty Center for Teaching and Learning and the Division of Digital Learning, the University of Central Florida established an evolving campus infrastructure of policies, training, and a national conference to guide the ethical and effective integration of generative AI into teaching and learning. Source: EDUCAUSE Review — Teaching & Learning https://www.campusreview.com.au/2026/09/can-ai-truly-recognise-student-needs a01d542f19f777c5 Wed, 09 Sep 2026 16:23:48 +0000 Unis are using AI for a range of purposes. From a student’s perspective, most uses fall into four familiar functions: tutoring, lecturing, feedback provision, and marking. These are all core parts of teaching traditionally done by humans. Source: Campus Review (Australia) AI On Campus Technology AI and Technology AI ethics Thomas Corbin https://arxiv.org/abs/2609.05643 ae1d70e0e8308ce9 Wed, 09 Sep 2026 15:32:14 +0000 This Comment emerges from TPC26 (https://tpc26.org), a conference convening leaders from academia, national laboratories, and industry who are reshaping materials science discovery. The meeting explored how AI, autonomous agents, self-driving labs, higher performance and quantum computing converge to amplify their individual impact on materials science discovery. The perspectives here reflect the firsthand experiences of researchers at these frontiers and capture the essence of this global endeavor. As AI-driven reasoning, autonomous agentic frameworks, self-driving laboratories, and… Source: arXiv — Computers & Society + AI cs.AI cond-mat.mtrl-sci Eliu Huerta, Xiaoyun Wang, Geetika Gupta https://arxiv.org/abs/2609.06573 3534118c4af53c0a Wed, 09 Sep 2026 15:16:12 +0000 Recent studies report that automated red-teaming finds more vulnerabilities, at lower cost, than human red-teaming on standard AI safety benchmarks, and some read this as evidence that human evaluators are becoming dispensable. The comparison measures one thing and the conclusion claims another. A benchmark measures how thoroughly an attacker searches a predefined set of harms, fixed in advance by the developers, and a harm left out of that set is invisible to any attacker working inside it, automated or not. The same blind spot appeared in academic cryptography and in clinical drug trials,… Source: arXiv — Computers & Society + AI cs.AI cs.CL cs.CR cs.CY Madhava Gaikwad https://arxiv.org/abs/2607.04572 5e647a04e1cbcf73 Wed, 09 Sep 2026 15:16:03 +0000 Large language model (LLM) tutors may have access to teacher notes, answer keys, rubrics, or retrieved solutions while producing student-facing explanations. We study whether truncated reasoning probes can distinguish direct access to such private context from answer information carried by the written explanation. Using Truncated Reasoning AUC Evaluation (TRACE), we evaluate 1000 GSM8K problems under question-only, correct answer-key, and wrong answer-key contexts. When forced-answer probes retain the private key, answer-key TRACE AUC rises from 0.375 to 0.900, and the gold answer is… Source: arXiv — Computers & Society + AI cs.AI cs.LG Bonan Shen, Dingyan Shang, Youting Wang https://arxiv.org/abs/2609.06769 c9dc9ace378a14b7 Wed, 09 Sep 2026 15:15:59 +0000 As people increasingly rely on artificial intelligence (AI) for guidance in their own lives, scholars, lawyers, and even judges have begun to consider the role of AI in legal decision-making. As "silicon sampling" -- the use of generative AI models in social science research -- is now impacting academia, "silicon jurors" could make an appearance in courtrooms. This study joins an emerging line of research on generative AI models' ability to simulate human legal judgments. In particular, we study how large language model (LLM)-powered chatbots respond to series of questions about legal… Source: arXiv — Computers & Society + AI cs.CY cs.AI Nirav Patel, Emily Wenger, Christopher Buccafusco https://arxiv.org/abs/2609.05452 5a75633301f647a5 Wed, 09 Sep 2026 14:21:30 +0000 Digital Twins for educational buildings can support sustainability-oriented learning, but their use in schools remains limited. This paper presents a GenAI-based chatbot built on top of an existing Digital Twin for two school buildings in Greece, using real IoT data from environmental sensors and energy meters. The chatbot enables educators to query live and historical building data, compare spaces, and generate ideas for classroom activities through natural language. The system was evaluated in an 80-minute workshop with 17 secondary-school educators, who compared it with an existing… Source: arXiv — Computers & Society + AI cs.HC cs.CY Themistoklis Sarantakos, Dimitrios Amaxilatis, Michail Giannakos https://arxiv.org/abs/2609.06095 004c121c324f4409 Wed, 09 Sep 2026 14:21:26 +0000 Motivation: Undergraduate computing students increasingly turn to generative AI (GenAI) tools to understand abstract concepts through analogies. Analogies compare an unfamiliar concept to something familiar, but judging whether the comparison holds requires knowledge of both. GenAI may also embed assumptions about who the learner is. GenAI education research centers on output correctness, leaving students' critical reception of analogies largely unexamined. Method: We investigate how students evaluate the accuracy, appropriateness, and assumptions in GenAI-generated analogies, and their… Source: arXiv — Computers & Society + AI cs.HC cs.AI Seth Bernstein, Naaz Sibia https://www.ecampusnews.com/ai-in-education/2026/09/09/building-an-everyday-equitable-practice-for-ai-in-schools 6e5d1de4053116e3 Wed, 09 Sep 2026 14:21:21 +0000 AI technology is advancing rapidly in schools, but research is increasingly showing that Large Language Models (LLMs) lack the common sense, morality, and knowledge of individual classroom dynamics needed to be truly equitable. The post Building an everyday equitable practice for AI in schools appeared first on eCampus News . Source: eCampus News AI in Education Featured on eCampus News Chelsie Thielen, Winona State University https://www.theverge.com/ai-artificial-intelligence/991956/student-ai-use-scores-oecd-pisa 859fd50c337d724e Wed, 09 Sep 2026 14:19:16 +0000 Students who use AI to help them study tend to perform worse at school than those who don't, according to data from a global OECD educational report. The situation is more complex than it sounds though, with certain types of AI use giving learners a slight boost, especially among students taught to critically assess how […] Source: The Verge — AI AI News Dominic Preston https://er.educause.edu/articles/2024/7/at-the-crossroads-of-innovation-embracing-ai-to-foster-deep-learning-in-the-college-classroom 50598e8a7e13b88a Tue, 08 Sep 2026 21:27:21 +0000 AI is here to stay. How can we, as educators, accept this change and use it to help our students learn? Source: EDUCAUSE Review — Teaching & Learning https://er.educause.edu/articles/2024/6/framing-generative-ai-in-education-with-the-genai-intent-and-orientation-model 39e714114ffeb492 Tue, 08 Sep 2026 21:27:16 +0000 The proposed model seeks to assist instructors and learners with a framing lens for how GenAI might be useful in educational settings. Source: EDUCAUSE Review — Teaching & Learning https://er.educause.edu/articles/2024/1/will-our-educational-system-keep-pace-with-ai-a-students-perspective-on-ai-and-learning d812a791e40db11c Tue, 08 Sep 2026 21:27:12 +0000 Reflecting on AI and learning, a student offers four insights gleaned from firsthand interactions with ChatGPT. Source: EDUCAUSE Review — Teaching & Learning https://www.reddit.com/r/Professors/comments/1w07jl2/generative_ai_can_harm_teaching 2f3e7c215640a0ff Tue, 08 Sep 2026 21:27:08 +0000 we have a lot of work showing the harms of AI on learning, from math skills to writing. This interesting working paper looking at how AI can harm learning when used in teaching. Seems that including AI as part of a course can really make students lose interest in learning https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7007339 Abstract Teachers are rapidly adopting generative AI, yet there is little causal evidence on whether AI-assisted teaching improves or harms student outcomes. We conducted a randomized field experiment across a chain of middle and high schools in Turkey, assigning… Source: r/Professors Professors /u/Urn https://www.reddit.com/r/Professors/comments/1w3odrh/recorded_notes_in_the_age_of_ai_deepfakes d1c57901b6dbbe3e Tue, 08 Sep 2026 20:27:09 +0000 Hello my fellow professors and happy semesters to all! So I don't allow class recordings, mainly for privacy reasons but also since no one was watching them anyway. This hasn't been an issue until now. I've gotten a student accommodation allowing them to record class, especially lectures. In the past, I wouldn't have blinked at this accommodation, but given the AI deepfakes and spiteful retaliatory nature students can have, as well as where I teach (red state), I am now worried about the recoding potentially being used to generate a deepfake of me, especially if a student doesn't like their… Source: r/Professors Professors /u/theelegantbookworm https://arxiv.org/abs/2609.00248 519974cfea57d437 Tue, 08 Sep 2026 20:27:05 +0000 Large Language Models (LLMs) are increasingly used as conversational search engines for academic literature, yet whether they judge papers on content or on authority signals has not been tested causally. We investigate authority bias: systematic preference for papers based on author prestige, venue, and citations rather than content. Holding title and abstract constant, we vary authority metadata across three counterfactual conditions (original, flipped, boosted) over eight LLMs (five open-weight and three frontier closed-weight) in an in-context, single-turn, top-1 recommendation setting.… Source: arXiv — Computers & Society + AI cs.AI Uthman Jinadu, Parsa Ghazvinian, Anjila Budathoki https://er.educause.edu/articles/2026/8/seeing-learning-differently-what-generative-ai-reveals-about-human-capability-development 9320d1721c65808e Tue, 08 Sep 2026 20:27:01 +0000 As generative artificial intelligence reshapes conversations about teaching, learning, and assessment, colleges and universities have an opportunity to look beyond what learners produce and better understand how human capability develops over time, strengthening teaching, feedback, and assessment through richer evidence of learning. Source: EDUCAUSE Review — Emerging Technologies & Trends https://www.youtube.com/watch?is=oEm5b9PAQvG-bBvx&v=svl_1upFpQo&feature=youtu.be 640f87265ab9be76 Tue, 08 Sep 2026 19:56:21 +0000 Source: Curated https://er.educause.edu/articles/2026/3/from-prompt-to-practice-a-framework-for-transparent-genai-use-in-higher-education 98422241a1a455ce Tue, 08 Sep 2026 19:22:15 +0000 As generative artificial intelligence reshapes instructional workflows at colleges and universities, a four-level transparency framework can help education developers calibrate documentation and disclosure practices to support ethical responsibility and maintain student trust. Source: EDUCAUSE Review — Emerging Technologies & Trends https://er.educause.edu/articles/2025/10/a-more-human-university-the-role-of-ai-in-learning 139dee1a4f1c9849 Tue, 08 Sep 2026 19:22:11 +0000 Far from heralding the collapse of higher education, artificial intelligence offers a transformative opportunity to scale meaningful, individualized learning experiences across diverse classrooms. Source: EDUCAUSE Review — Emerging Technologies & Trends https://er.educause.edu/articles/2025/9/an-ai-plateau af2bd42b9fc52c06 Tue, 08 Sep 2026 19:22:07 +0000 Large language models may be nearing their limits, challenging assumptions about the transformative potential of artificial intelligence. Source: EDUCAUSE Review — Emerging Technologies & Trends https://www.sciencedirect.com/science/article/pii/S2666920X26001049?dgcid=rss_sd_all df156853cc15e61d Tue, 08 Sep 2026 19:22:02 +0000 Computers and Education: Artificial Intelligence, Volume 11 Source: Computers and Education: Artificial Intelligence Chenglu Li, Gökhan Gülfidan, Yinqi Zhang-Kopf https://arxiv.org/abs/2609.02611 d54a7f153d020ea0 Tue, 08 Sep 2026 18:18:06 +0000 Intelligent Tutoring Systems (ITSs) traditionally focus their adaptive support on cognitive aspects of learning. Although effective, little is known about how such systems can be enhanced by addressing students' emotional states. In particular, the role of mindful interventions for supporting student learning and experiences in adaptive math learning remains underexplored. We developed "Math with Matt", an ITS that leverages Large Language Models (LLMs) to provide both cognitive and emotional support in algebra learning. The system offers 1) an LLM-based mindful chat that delivers… Source: arXiv — Human-Computer Interaction cs.HC Vera Rief, Mirella Hladk\'y, Minju Yoo https://arxiv.org/abs/2609.04172 2dcd3d7f25d20f75 Tue, 08 Sep 2026 18:18:02 +0000 On-policy distillation (OPD) combines student-generated rollouts with dense token-level supervision from a teacher. Existing work has mainly studied its algorithmic behavior, leaving the role of training data unclear. We examine this role at the data-minimal limit by training on a single query. One-shot OPD keeps improving for hundreds of steps and recovers most of full-data OPD's gain across task domains and model families. We explain this result through the states visited during training and the rate at which the student aligns with the teacher. We measure \emph{state coverage}, the… Source: arXiv — Computers & Society + AI cs.AI cs.CL Zixuan Fu, Bingxiang He, Yuxin Zuo https://arxiv.org/abs/2609.02981 1e27083ce8808740 Tue, 08 Sep 2026 18:17:58 +0000 Artificial intelligence is changing the form of applied English materials from fixed paper sequences to adaptive learning systems that can diagnose learners, recommend tasks, and provide formative feedback. This paper studies the structure and application of a new practical English textbook driven by artificial intelligence. A five-layer architecture is proposed: knowledge mapping, learner profiling, task generation, feedback orchestration, and teacher-side governance. A prototype was tested on 186 non-English-major undergraduates for eight weeks of teaching. Compared with a static digital… Source: arXiv — Computers & Society + AI cs.AI Ya Wang, Lei Zhang, Xueguang Yang https://www.sciencedirect.com/science/article/pii/S2666920X26001372?dgcid=rss_sd_all a0bf0ecd299d6a50 Tue, 08 Sep 2026 18:17:54 +0000 Computers and Education: Artificial Intelligence Source: Computers and Education: Artificial Intelligence Yanjie Sun, Hongzhou Li, Xiaohui Tao https://osf.io/8e2zk 174f001f0fbce32d Tue, 08 Sep 2026 17:16:46 +0000 This systematic review evaluates the reported predictive performance of machine learning (ML) models that use low birth weight (LBW) or high birth weight (HBW, including macrosomia and large-for-gestational-age) as the directly predicted outcome. A systematic search was conducted across five databases (PubMed, Web of Science, Scopus, CINAHL Plus with Full Text, and IEEE Xplore) through June 2026, supplemented by an August 2026 search of the Consensus academic database, yielding 35 eligible studies after full-text verification. Deep-learning-specific architectures (e.g., CNN, LSTM) were… Source: EdArXiv (education preprints) bepress|Medicine and Health Sciences|Medical Specialties|Pediatrics bepress|Life Sciences|Bioinformatics bepress|Medicine and Health Sciences|Medical Specialties|Obstetrics and Gynecology bepress|Medicine and Health Sciences bepress|Life Sciences Umer Ilyas et al. https://osf.io/p4y8c 9a84a839e5b9f844 Tue, 08 Sep 2026 17:16:41 +0000 This project contains supplement material for the paper "Changes in Help-Seeking Strategies Predict unaided Performance during AI-based Mathematical Learning". It contains: - Fully-anonymized and curated chat data - Data for the questionnaires administered during the study - Full configuration and explanation of the automated coding procedure for the conversational data. For usage, please cite: @article{abdelghani2026prompting, title={From Prompting to Epistemic Proactivity: Temporal Trajectories of Student-AI Interaction in Mathematics Learning}, author={Abdelghani, Rania and Kaiser, Peter… Source: EdArXiv (education preprints) bepress|Education bepress|Social and Behavioral Sciences Rania Abdelghani https://osf.io/bp43w e395c17f26764857 Tue, 08 Sep 2026 16:18:16 +0000 No description provided. Source: EdArXiv (education preprints) Anjana Yatawara https://osf.io/hg69n affd8a5bbb20090f Tue, 08 Sep 2026 16:18:12 +0000 Scoping review of survey studies which report how many university students are using GenAI in their assessments Source: EdArXiv (education preprints) Philip Mark Newton https://news.google.com/rss/articles/CBMiwAFBVV95cUxPcWZnMkNaTHVmTy14Nm0zbFdvY0NhUXhnbHFNZFRlZmw0OGFzck1ZUkRNczJLRmRvY1M3VmJfdkp3bXFIMUx0ZE92dUxtaS1oN24tR3Q5TTJXeFd4c1NlLURZb3FmZGl3Umgzd1pIVWpMZnRmX01kUENKa21QcVJMR0poRG5vMnBrVHg1dGNVdjdUUE00S1ZXOW9wVHFMamdpT1l3ZFNkVkxtLWpTSmxFbHJ6VGdRbURLRU55Y1lnZDA?oc=5&hl=en-US&gl=US&ceid=US%3Aen fecd47662cf361d3 Tue, 08 Sep 2026 16:18:07 +0000 Source: Google News — Times Higher Education (replaces dead native feed) https://news.google.com/rss/articles/CBMiyAFBVV95cUxObk1yaFVnNjlJTjdGOFNjT044MWtOUGoyM0w5d1MzaHNOZEVXb3ozVzhiZWJGM2diLXVaVVQ4U19hdFZmTWZBemswVnFLajV4QkptdFI3amI0bjFURFNpMU95UXBIcEdzNTV3bXpIbG90R0hOMy16TjdyU2plODNORHE4d2lXZzNSREdUZkNfdlFSOVcwNms5NVBXYXJjRWpJR2RMUUFJeE1hb1cxYjFydWRYaTg2SHo0WVFxVko1UEdnNEFnNk5oYg?oc=5&hl=en-US&gl=US&ceid=US%3Aen 13d1687c0571506b Tue, 08 Sep 2026 16:18:03 +0000 Source: Google News (ES) — inteligencia artificial + universidad https://arxiv.org/abs/2608.26107 083f7c2f285b1121 Tue, 08 Sep 2026 15:33:17 +0000 Predicting students' academic risk in online education is crucial for enabling timely interventions that can improve retention and learning outcomes. However, existing models often suffer from limited early detection capability and insufficient interpretability, leading to a "black-box" trust crisis that hinders their adoption in real-world pedagogical settings. To address these challenges, we propose EduRiskX, a neuro-symbolic framework that integrates a temporal Transformer-based predictor with F-Logic symbolic reasoning. The neural component models longitudinal student activity sequences… Source: arXiv — Computers & Society + AI cs.AI Yu Fu, Yongqi Kang, Yong Zhao https://arxiv.org/abs/2608.26937 b495951c5c1169dc Tue, 08 Sep 2026 15:33:13 +0000 Generative artificial intelligence (GenAI) has been primarily framed as an impartial educational tool. However, this framing overlooks an even larger shift: the reassignment of epistemological authority from teachers to students to machines. This paper presents a conceptual evaluation of the extent to which GenAI redistributes students' and teachers' ability to act in classrooms to produce knowledge, validate each other's claims, and create evidence of student learning while collaborating with and competing against humans. This evaluation draws on various theoretical paradigms, including… Source: arXiv — Computers & Society + AI cs.CY Biranchi Poudyal https://arxiv.org/abs/2411.15129 ad8e6e64d71b45f3 Tue, 08 Sep 2026 15:33:08 +0000 What can we learn about language from studying how it is used by ChatGPT and other large language model (LLM)-based chatbots? In this paper, we analyse the distinctive character of language generated by ChatGPT, in relation to questions raised by natural language processing pioneer, and student of Wittgenstein, Margaret Masterman. Following frequent complaints that LLM-based chatbots produce "bullshit," in the sense of Frankfurt's popular monograph On Bullshit, we conduct an empirical study to contrast the language of 1,000 scientific publications with typical text generated by ChatGPT. We… Source: arXiv — Computers & Society + AI cs.CL cs.AI cs.HC Alessandro Trevisan, Harry Giddens, Sarah Dillon https://arxiv.org/abs/2608.06831 841843f06ff85ef1 Tue, 08 Sep 2026 15:33:04 +0000 The harms in which AI is implicated range in nature and scope from unsafe user interactions through to the societal-wide consequences of AI adoption. Classification of the diverse risks of AI is foundational to AI governance: regulators, technology firms, and policymakers need structured accounts of risk upon which to act. Researchers and practitioners have accordingly developed many Sociotechnical Outcome Taxonomies (SOT). This paper presents an empirical study of SOT development and use, drawing on 25 interviews with researchers and practitioners across industry, academia, civil society,… Source: arXiv — Computers & Society + AI cs.CY Glen Berman, Ned Cooper, Angel Hsing-Chi Hwang https://arxiv.org/abs/2608.26710 f763f1815b9df7de Tue, 08 Sep 2026 14:25:58 +0000 AI text detectors are increasingly employed in academic settings, but it remains unclear whether their outputs reflect AI authorship itself or broader linguistic features associated with polished academic English. Previous studies have reported high false-positive rates (FPRs) for non-native English writing, but population-level comparisons confound authorship with differences in topic, domain, and writing style. Professional editing provides a useful setting for examining this issue because it changes the linguistic form of manuscripts while preserving authorship and content. We examined… Source: arXiv — Computers & Society + AI cs.AI Hyeonchu Park, Gahye Jeong, Bugeun Kim https://news.google.com/rss/articles/CBMi6AFBVV95cUxOMHBld1JZbVlNQ0U0NFpqbDBTTnJROTlaeHhWdG9ZMklseUNiLVlpZkRuQVJZbUhMZ004cjM3NHI4TmR0dlRlcnFsOFJPaExoNi1XbTE1aUk0RHBVM1RSN0lRN3VBMDNlbEJZdzZwbkJSX284MVBfOVF3ZDN4YVBncC1QaThJU2VPRXdyQ3prVWx4eWZ2cWZTem5YeFhNb3ozMy1XTkw0ZTVMUHZSTC1HVmdMb192djdxa1ZvcllUaHJQZGc5LVN6WXNHeFRMSERZaTBaMlRKUVJjVXNxU0plWnljNGJLc2p0?oc=5&hl=en-US&gl=US&ceid=US%3Aen 6709ad0b5559ea6f Tue, 08 Sep 2026 14:25:53 +0000 Source: Google News — Times Higher Education (replaces dead native feed)