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266 resources
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Rose E. Wang, Ana T. Ribeiro, Carly D. R...|Oct 3rd, 2024|preprintRose E. Wang, Ana T. Ribeiro, Carly D. R...Oct 3rd, 2024
Generative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited. For example, in education, training novice educators with expert guidance is important for effectiveness but expensive, creating significant barriers to improving education quality at scale. This challenge disproportionately harms students from under-served communities, who stand to gain the most from high-quality...
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Rose E. Wang, Ana T. Ribeiro, Carly D. R...|Oct 3rd, 2024|preprintRose E. Wang, Ana T. Ribeiro, Carly D. R...Oct 3rd, 2024
Generative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited. For example, in education, training novice educators with expert guidance is important for effectiveness but expensive, creating significant barriers to improving education quality at scale. This challenge disproportionately harms students from under-served communities, who stand to gain the most from high-quality...
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Chung Kwan Lo, Khe Foon Hew, Morris Siu-...|Oct 2nd, 2024|journalArticleChung Kwan Lo, Khe Foon Hew, Morris Siu-...Oct 2nd, 2024
ChatGPT, a state-of-the-art artificial intelligence (AI) chatbot, has gained considerable attention as a transformative yet controversial tool for enhancing teaching and learning experiences. Several reviews and numerous articles have been written about harnessing ChatGPT in education since its release on November 30, 2022. Besides summarising its strengths, weaknesses, opportunities, and threats (SWOT) as identified in previous systematic reviews of ChatGPT research, this systematic review...
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav...|Aug 15th, 2024|preprintAbhimanyu Dubey, Abhinav Jauhri, Abhinav...Aug 15th, 2024
Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language...
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Jul 30th, 2024|blogPostJul 30th, 2024
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S Christie, Baptiste Moreau-Pernet, Yu T...|Jul 24th, 2024|conferencePaperS Christie, Baptiste Moreau-Pernet, Yu T...Jul 24th, 2024
Large language models (LLMs) are increasingly being deployed in user-facing applications in educational settings. Deployed applications often augment LLMs with fine-tuning, custom system prompts, and moderation layers to achieve particular goals. However, the behaviors of LLM-powered systems are difficult to guarantee, and most existing evaluations focus instead on the performance of unmodified 'foun-dation' models. Tools for evaluating such deployed systems are currently sparse, inflexible,...
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Steve Lohr|Jul 23rd, 2024|newspaperArticleSteve LohrJul 23rd, 2024
A.I.’s math problem reflects how much the new technology is a break with computing’s past.
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Pepper Miller, Kristen DiCerbo|Jul 3rd, 2024|preprintPepper Miller, Kristen DiCerboJul 3rd, 2024
Large Language Models (LLMs) face documented challenges in solving mathematical problems. While substantial work has been done to quantify and improve LLMs’ abilities to solve static math problems, evaluating their performance in real-time math tutoring scenarios presents distinct challenges that remain underexplored. This paper specifically addresses the accuracy of LLMs in performing math correctly while tutoring students. It highlights the unique difficulties of this context, classifies...
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The Rise of Artificial Intelligence in Educational Measurement: Opportunities and Ethical ChallengesOkan Bulut, Maggie Beiting-Parrish, Jodi...|Jun 27th, 2024|preprintOkan Bulut, Maggie Beiting-Parrish, Jodi...Jun 27th, 2024
The integration of artificial intelligence (AI) in educational measurement has revolutionized assessment methods, enabling automated scoring, rapid content analysis, and personalized feedback through machine learning and natural language processing. These advancements provide timely, consistent feedback and valuable insights into student performance, thereby enhancing the assessment experience. However, the deployment of AI in education also raises significant ethical concerns regarding...
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Oluwanife Segun Falebita|Jun 16th, 2024|journalArticleOluwanife Segun FalebitaJun 16th, 2024
Many revelations have been made about the revolution that artificial intelligence (AI) has brought to the education sector, including the opening of opportunities for personalised instruction, boosting the quality of content developed by teachers while preparing for lessons, and improving the quality of classroom evaluations. Despite the many benefits of AI adoption, there have been concerns and apprehensions about its use in the educational sector. A survey was conducted to investigate the...
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Zhoumingju Jiang, Mengjun Jiang|Jun 16th, 2024|preprintZhoumingju Jiang, Mengjun JiangJun 16th, 2024
The integration of artificial intelligence (AI) in education has shown significant promise, yet the effective personalization of learning, particularly in physics education, remains a challenge. This paper proposes Physics-STAR, a framework for large language model (LLM)- powered tutoring system designed to address this gap by providing personalized and adaptive learning experiences for high school students. Our study evaluates Physics-STAR against traditional teacher-led lectures and...
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José Campino|Jun 13th, 2024|journalArticleJosé CampinoJun 13th, 2024
Artificial Intelligence (AI) has witnessed widespread application across diverse domains, with education being a prominent focus for enhancing learning outcomes and tailoring educational approaches. Transformer models, exemplified by BERT, have demonstrated remarkable efficacy in Natural Language Processing (NLP) tasks. This research scrutinizes the current landscape of AI in education, emphasizing the utilization of transformer models. Specifically, the research delves into the influence of...
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Michael Townsen Hicks, James Humphries, ...|Jun 8th, 2024|journalArticleMichael Townsen Hicks, James Humphries, ...Jun 8th, 2024
Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way...
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Xian Li, Guangxin Han, Bei Fang|Jun 7th, 2024|journalArticleXian Li, Guangxin Han, Bei FangJun 7th, 2024
The development of artificial intelligence (AI) significantly improves the effectiveness of classroom dialogue systems, but their integration into the learning environment remains challenging. To address this gap, this research presents a framework for automatic intelligent dialogue analysis, intending to promote high-quality classroom dialogue and facilitate teaching and learning. The proposed framework includes two main components: a dialogue-oriented interactive classroom and an...
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Bhashithe Abeysinghe, Ruhan Circi|Jun 5th, 2024|preprintBhashithe Abeysinghe, Ruhan CirciJun 5th, 2024
Chatbots have been an interesting application of natural language generation since its inception. With novel transformer based Generative AI methods, building chatbots have become trivial. Chatbots which are targeted at specific domains such as medicine, psychology, and general information retrieval are implemented rapidly. This, however, should not distract from the need to evaluate the chatbot responses. Especially because the natural language generation community does not entirely agree...
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David Ifeoluwa Adelani, Jessica Ojo, Isr...|Jun 5th, 2024|preprintDavid Ifeoluwa Adelani, Jessica Ojo, Isr...Jun 5th, 2024
Despite the widespread adoption of Large language models (LLMs), their remarkable capabilities remain limited to a few high-resource languages. Additionally, many low-resource languages (e.g. African languages) are often evaluated only on basic text classification tasks due to the lack of appropriate or comprehensive benchmarks outside of high-resource languages. In this paper, we introduce IrokoBench -- a human-translated benchmark dataset for 16 typologically-diverse low-resource African...
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Johanna Fleckenstein, Jennifer Meyer, Th...|Jun 1st, 2024|journalArticleJohanna Fleckenstein, Jennifer Meyer, Th...Jun 1st, 2024
The potential application of generative artificial intelligence (AI) in schools and universities poses great challenges, especially for the assessment…
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Jun 2nd, 2024|journalArticleJun 2nd, 2024
The potential application of generative artificial intelligence (AI) in schools and universities poses great challenges, especially for the assessment…
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Riordan Alfredo, Vanessa Echeverria, Yue...|Jun 2nd, 2024|journalArticleRiordan Alfredo, Vanessa Echeverria, Yue...Jun 2nd, 2024
The rapid expansion of Learning Analytics (LA) and Artificial Intelligence in Education (AIED) offers new scalable, data-intensive systems but raises concerns about data privacy and agency. Excluding stakeholders—like students and teachers—from the design process can potentially lead to mistrust and inadequately aligned tools. Despite a shift towards human-centred design in recent LA and AIED research, there remain gaps in our understanding of the importance of human control, safety,...
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Jennifer Meyer, Thorben Jansen, Ronja Sc...|Jun 2nd, 2024|journalArticleJennifer Meyer, Thorben Jansen, Ronja Sc...Jun 2nd, 2024
Writing proficiency is an essential skill for upper secondary students that can be enhanced through effective feedback. Creating feedback on writing tasks, however, is time-intensive and presents a challenge for educators, often resulting in students receiving insufficient or no feedback. The advent of text-generating large language models (LLMs) offers a promising solution, namely, automated evidence-based feedback generation. Yet, empirical evidence from randomized controlled studies about...