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(2023) Enhancing Engineering Education through LLM-Driven Adaptive Quiz Generation. <u>https:\/\/digitalcommons.kennesaw.edu\/cgi\/viewcontent.cgi?article=1399&context=cday<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-64302-6_30<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i21.30362<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1109\/tlt.2024.3384765<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.21203\/rs.3.rs-4399670\/v1<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1007\/s40593-024-00421-1<\/u>"},{"key":"ref","unstructured":"Stahl, M., Biermann, L., Nehring, A. and Wachsmuth, H. (2024) Exploring LLM Prompting Strategies for Joint Essay Scoring and Feedback Generation. arXiv: 2404.15845. <u>https:\/\/arxiv.org\/abs\/2404.15845<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-64315-6_3<\/u>"},{"key":"ref","unstructured":"Nie, A., Cheng, C.A., Kolobov, A. and Swaminathan, A. (2024) The Importance of Directional Feedback for LLM-Based Optimizers. arXiv: 2405.16434. <u>https:\/\/arxiv.org\/abs\/2405.16434<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1145\/3657604.3662040<\/u>"},{"key":"ref","unstructured":"Tanwar, H., Shrivastva, K., Singh, R. and Kumar, D. (2024) OpineBot: Class Feedback Reimagined Using a Conversational LLM. arXiv: 2401.15589. <u>https:\/\/arxiv.org\/abs\/2401.15589<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1007\/s40593-024-00406-0<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.21203\/rs.3.rs-3996137\/v1<\/u>"},{"key":"ref","unstructured":"Xu, F.Y., Lo, K.L., Soldaini, L.C., Kuehl, B., Choi, E. and Wadden, D. (2024) KIWI: A Dataset of Knowledge-Intensive Writing Instructions for Answering Research Questions. arXiv: 2403.03866."},{"key":"ref","unstructured":"Wang, S., Xu, T.L., Li, H., Zhang, C.L., Liang, J., Tang, J.L., Yu, P.S. and Wen, Q.S. (2024) Large Language Models for Education: A Survey and Outlook. arXiv: 2403.18105."},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.semeval-1.124<\/u>"},{"key":"ref","unstructured":"Li, Q., Yang, X.Y., <i>et al<\/i>. (2024) From Beginner to Expert: Modeling Medical Knowledge into General LLMs. arXiv: 2312.01040."},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.eacl-main.117<\/u>"},{"key":"ref","unstructured":"Talmor, A., Herzig, J., Lourie, N. and Berant, J. (2018) CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge. arXiv: 1811.00937."},{"key":"ref","unstructured":"Marini, T. and Brant-Ribeiro, T. (2024) Comparative Analysis of Intentional Gramatical Error Correction Techniques on Twitter\/X. <i>Proceedings of the <\/i>16<i>th International Conference on Computational Processing of Portuguese<\/i>, Santiago de Compostela, 14-15 March 2024, 527-531. <u>https:\/\/aclanthology.org\/2024.propor-1.55<\/u>"},{"key":"ref","unstructured":"Luhtaru, A., Korotkova, E. and Fishel, M. (2024) No Error Left Behind: Multilingual Grammatical Error Correction with Pretrained Translation Models. <i>Proceedings of the <\/i>18<i>th Conference of the European Chapter of the Association for Computational Linguistics<\/i> (<i>Volume<\/i> 1: <i>Long Papers<\/i>), St. Julian&#8217;s, 17-22 March 2024, 1209-1222. <u>https:\/\/aclanthology.org\/2024.eacl-long.73<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.sealp-1.3<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-acl.297<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.830"},{"key":"ref","unstructured":"Warstadt, A., Mueller, A., <i>et al<\/i>. (2023) Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning. Association for Computational Linguistics. <u>https:\/\/aclanthology.org\/2023.conll-babylm<\/u>"},{"key":"ref","unstructured":"Huang, P.W. 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(2024) LLM Augmented LLMs: Expanding Capabilities through Composition. arXiv: 2401.02412."},{"key":"ref","unstructured":"Cheng, Y.H., Zhang, C.Y., <i>et al<\/i>. (2024) Exploring Large Language Model Based Intelligent Agents: Definitions, Methods, and Prospects. arXiv: 2401.03428."},{"key":"ref","unstructured":"Li, Q.Y., Fu, L.Y., <i>et al<\/i>. (2024) Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges. arXiv: 2401.08664."},{"key":"ref","unstructured":"Sun, Z.H., Lyu, C., Li, B.L., Wan, Y., Zhang, H.Y., Li, G. and Jin, Z. (2024) Enhancing Code Generation Performance of Smaller Models by Distilling the Reasoning Ability of LLMs. arXiv: 2403.13271."},{"key":"ref","unstructured":"Zheng, C., Sun, K., Wu, H., Xi, C.G. and Zhou, X. (2024) Balancing Enhancement, Harmlessness, and General Capabilities: Enhancing Conversational LLMs with Direct RLHF. arXiv: 2403.02513."},{"key":"ref","unstructured":"Hu, S.J., Zhou, L., <i>et al<\/i>. (2024) WavLLM: Towards Robust and Adaptive Speech Large Language Model. arXiv: 2404.00656."},{"key":"ref","unstructured":"Lee, C., Xia, C.S., Huang, J., Zhu, Z., Zhang, L. and Lyu, M.R. (2024) A Unified Debugging Approach via LLM-Based Multi-Agent Synergy. arXiv: 2404.17153."},{"key":"ref","unstructured":"Guo, S.Y., Deng, C., Wen, Y., Chen, H.C., Chang, Y. and Wang, J. (2024) DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning. arXiv: 2402.17453."},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.89<\/u>"},{"key":"ref","unstructured":"Huang, L., <i>et al<\/i>. 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(2022) CSECU-DSG@SMM4H&#8217;22: Transformer Based Unified Approach for Classification of Changes in Medication Treatments in Tweets and WebMD Reviews. <i>Proceedings of the Seventh Workshop <\/i><i>on Social Media Mining for Health Applications<\/i>,<i> Workshop & Shared Task<\/i>, Gyeongju, 12-17 October 2022, 118-122. <u>https:\/\/aclanthology.org\/2022.smm4h-1.33<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-emnlp.552<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-emnlp.758<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-emnlp.634<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.804<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2024\/381<\/u>"},{"key":"ref","unstructured":"Kong, X.H., Chen, J.Y., Wang, W.G., Su, H., Hu, X.L., Yang, Y. and Liu, S. (2024) Controllable Navigation Instruction Generation with Chain of Thought Prompting. arXiv: 2407.07433.<u>https:\/\/arxiv.org\/abs\/2407.07433<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i21.30364<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1007\/s40593-024-00414-0<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1016\/j.caeai.2024.100289<\/u>"},{"key":"ref","unstructured":"Dimbisoa, W.G., Mahatody, T. and Razafimandimby, J.P. (2018) Creating a Metamodel of UI Components in Form of Model Independent of the Platform. <i>International Journal of Conceptions on Computing and Information Technology<\/i>, 6, 48-52. <u>http:\/\/wairco.org\/IJCCIT\/November2018Paper12.pdf<\/u>"},{"key":"ref","unstructured":"Logaprakash, M., Manjunath, N., Rubanraaj, K. and Srinivas, V. (2024) Personalised Learning System Using LLM. <i>International Journal of Creative Research Thoughts <\/i>(<i>IJCRT<\/i>), 12, c24-c26. <u>https:\/\/www.ijcrt.org\/papers\/IJCRT2405220.pdf<\/u>"},{"key":"ref","unstructured":"Abu-Rasheed, H., Weber, C. and Fathi, M. (2024) Knowledge Graphs as Context Sources for LLM-Based Explanations of Learning Recommendations. arXiv: 2403.03008."},{"key":"ref","unstructured":"Fahl, W. (2024) GraphWiseLearn: Personalized Learning through Semantified TEL, Leveraging QA-Enhanced LLM-Generated Content. <u>https:\/\/2024.eswc-conferences.org\/wp-content\/uploads\/2024\/05\/77770405.pdf<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1145\/3613905.3651122<\/u>"},{"key":"ref","unstructured":"Shoeibi, N. (2023) Cross-Lingual Transfer in Generative AI-Based Educational Platforms for Equitable and Personalized Learning. <i>Learning Analytics Summer Institute<\/i> (<i>LASI<\/i>), Madrid, June 29-30 2023, 524-540. <u>https:\/\/ceur-ws.org\/Vol-3542\/paper8.pdf<\/u>"},{"key":"ref","unstructured":"Shi, Y.X., Zi, X., Shi, Z.J., Zhang, H.M., Wu, Q. and Xu, M. (2024) ERAGent: Enhancing Retrieval-Augmented Language Models with Improved Accuracy, Efficiency, and Personalization. arXiv: 2405.06683."},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1109\/access.2024.3420709<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1109\/rasse60029.2023.10363506<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2022.839982<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-50574-4_18<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.23919\/ifipnetworking57963.2023.10186404<\/u>"},{"key":"ref","unstructured":"Gorban, A.N., Mirkes, E.M. and Zinovyev, A.Y. (2023) Exploring the Impact of Adaptive Video on Personalized Learning Experiences. <i>Proceedings of the Workshop on the Influence of Adaptive Video Learning<\/i>, Plovdiv, 13-14 October 2022, 9-16. <u>https:\/\/ceur-ws.org\/Vol-3372\/paper01.pdf<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548047<\/u>"},{"key":"ref","unstructured":"Liu, X.D. and Xue, X.W. (2023) Research on Learning Video Recommendation System Based on DBSCAN Clustering Algorithm. <i>International Conference on Algorithms<\/i>,<i> High Performance Computing<\/i>,<i> and Artificial Intelligence<\/i> (<i>AHPCAI<\/i> 2023), Yinchuan, 18-19 August 2023, 129-137."},{"key":"ref","unstructured":"Bontchev, B., Antonova, A. and Dankov, Y. (2020) Educational Video Game Design Using Personalized Learning Scenarios. In: Gervasi, O., <i>et al<\/i>., Eds., <i>Computational Science and Its Applications<\/i>&#8212;<i>ICCSA<\/i> 2020, Springer, 829-845."},{"key":"ref","unstructured":"Yi, R., Ye, Z.P., Zhang, J.Y., Bao, H.J. and Liu, Y.J. (2020) Audio-Driven Talking Face Video Generation with Learning-Based Personalized Head Pose. arXiv: 2002.10137. <u>https:\/\/arxiv.org\/abs\/2002.10137<\/u>"},{"key":"ref","unstructured":"Qu, Z.Y., Yin, L., Yu, Z.T., Wang, W.B. and Zhang, X. (2024) CourseGPT-ZH: An Educational Large Language Model Based on Knowledge Distillation Incorporating Prompt Optimization. arXiv: 2405.04781."},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1109\/fie58773.2023.10343467<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1016\/j.caeai.2024.100326<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.3390\/ime2030019<\/u>"},{"key":"ref","unstructured":"Wang, T.Y., Zhou, N.J. and Chen, Z.X. (2024) Enhancing Computer Programming Education with LLMs: A Study on Effective Prompt Engineering for Python Code Generation. arXiv: 2407.05437. <u>https:\/\/arxiv.org\/abs\/2407.05437<\/u>"},{"key":"ref","unstructured":"Taylor Gonzalez, D.J., Djulbegovic, M.B. and Bair, H. (2024) We Need to Add Prompt Engineering Education to Optimize Generative Artificial Intelligence in Medicine. <i>Academic Medicine<\/i>, 99, 1050-1051."},{"key":"ref","unstructured":"Devlin, J., Chang, M.W., Lee, K. and Toutanova, K. (2018) Bert: Pretraining of Deep Bidirectional Transformers for Language Understanding. arXiv: 1810.04805."},{"key":"ref","unstructured":"Zhang, H.J., Xu, Y.M. andPerez-Beltrachini, L. (2024) Fine-Grained Natural Language Inference Based Faithfulness Evaluation for Diverse Summarisation Tasks. <i>Proceedings of the <\/i>18<i>th Conference of the European Chapter of the Association for Computational Linguistics<\/i> (<i>Volume<\/i> 1: <i>Long Papers<\/i>), St. Julian&#8217;s, 17-22 March 2024, 1701-1722. <u>https:\/\/aclanthology.org\/2024.eacl-long.102.<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.nlrse-1.12<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-industry.13<\/u>"},{"key":"ref","unstructured":"Austin, E., Za&#239;ane, O.R. and Largeron, C. (2022) Community Topic: Topic Model Inference by Consecutive Word Community Discovery. <i>Proceedings of the<\/i> 29<i>th International Conference on Computational Linguistics<\/i>, Gyeongju, 12-17 October 2022, 971-983. <u>https:\/\/aclanthology.org\/2022.coling-1.81<\/u>"},{"key":"ref","unstructured":"Pletenev, S., Chekalina, V., Moskovskiy, D., Seleznev, M., Zagoruyko, S. and Panchenko, A. (2023) A Computational Study of Matrix Decomposition Methods for Compression of Pre-Trained Transformers. <i>Proceedings of the<\/i> 37<i>th Pacific Asia Conference on Language<\/i>,<i> Information and Computation<\/i>, Hong Kong, 2-5 December 2023, 723-742. <u>https:\/\/aclanthology.org\/2023.paclic-1.73<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.semeval-1.30<\/u>"},{"key":"ref","unstructured":"Kotitsas, S., Kounoudis, P., Koutli, E. and Papageorgiou, H. (2024) Leveraging Fine-tuned Large Language Models with LoRA for Effective Claim, Claimer, and Claim Object Detection. <i>Proceedings of the<\/i> 18<i>th Conference of the European Chapter of the Association for Computational Linguistics<\/i> (<i>Volume<\/i> 1: <i>Long Papers<\/i>), St. Julian&#8217;s, 17-22 March 2024, 2540-2554. <u>https:\/\/aclanthology.org\/2024.eacl-long.156<\/u>"},{"key":"ref","unstructured":"Power, R. and Scott, D. (1998) WYSIWYM: Knowledge Editing with Natural Language Feedback. Association for Computational Linguistics. <u>https:\/\/aclanthology.org\/W98-1437<\/u>"},{"key":"ref","unstructured":"Yehudai, A., Carmeli, B., Mass, Y., Arviv, O., Mills, N., Toledo, A., Shnarch, E. and Choshen, L. (2024) Genie: Achieving Human Parity in Content-Grounded Datasets Generation. arXiv: 2401.14367."},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.748<\/u>"},{"key":"ref","unstructured":"Xu, X.H., Li, M., Tao, C.Y., Shen, T., Cheng, R., Li, J.Y., Xu, C., Tao, D.C. and Zhou, T.Y. (2024) A Survey on Knowledge Distillation of Large Language Models. arXiv: 2402.13116."},{"key":"ref","unstructured":"Li, Q.Y., Fu, L.Y., Zhang, W.M., Chen, X.Y., Yu, J.W., Xia, W., Zhang, W.N., Tang, R.M. and Yu, Y. (2023) Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges. arXiv: 2401.08664."},{"key":"ref","unstructured":"Rai, D. and Yao, Z.Y. (2024) An Investigation of Neuron Activation as a Unified Lens to Explain Chain-of-Thought Eliciting Arithmetic Reasoning of LLMs. arXiv: 2406.12288. <u>https:\/\/arxiv.org\/abs\/2406.12288<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.228<\/u>"},{"key":"ref","unstructured":"Tutunov, R., Grosnit, A., Ziomek, J., Wang, J. and Bou-Ammar, H. (2024) Why Can Large Language Models Generate Correct Chain-of-Thoughts? arXiv: 2310.13571.<u>https:\/\/arxiv.org\/abs\/2310.13571<\/u>"},{"key":"ref","unstructured":"Zou, A., Zhang, Z.S. and Zhao, H. (2024) AuRoRA: A One-for-All Platform for Augmented Reasoning and Refining with Task-Adaptive Chain-of-Thought Prompting. <i>Proceedings of the <\/i>2024<i> Joint International Conference on Computational Linguistics<\/i>,<i> Language Resources and Evaluation<\/i> (<i>LREC<\/i>-<i>COLING<\/i> 2024), Torino, 20-25 May 2024, 1801-1807. https:\/\/aclanthology.org\/2024.lrec-main.160"},{"key":"ref","unstructured":"Sultan, A., Ganhotra, J. and Astudillo, R.F. (2024) Structured Chain-of-Thought Prompting for Few-Shot Generation of Content-Grounded QA Conversations. arXiv: 2402.11770. <u>https:\/\/arxiv.org\/abs\/2402.11770<\/u>"},{"key":"ref","unstructured":"Chu, Z., Chen, J.C., <i>et al<\/i>. (2024) Navigate through Enigmatic Labyrinth a Survey of Chain of Thought Reasoning: Advances, Frontiers and Future.  arXiv: 2309.15402. <u>https:\/\/arxiv.org\/abs\/2309.15402<\/u>"},{"key":"ref","doi-asserted-by":"publisher","DOI":"10.1007\/s10639-023-12249-8<\/u>"}],"container-title":["Journal of Intelligent Learning Systems and Applications"],"original-title":[],"link":[{"URL":"https:\/\/www.scirp.org\/journal\/doi.aspx?doi=10.4236\/jilsa.2024.164023","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.scirp.org\/xml\/137833.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.scirp.org\/journal\/doi.aspx?doi=10.4236\/jilsa.2024.164023","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T05:45:01Z","timestamp":1732859101000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.scirp.org\/journal\/doi.aspx?doi=10.4236\/jilsa.2024.164023"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":160,"journal-issue":{"issue":"04","published-print":{"date-parts":[[2024]]}},"URL":"https:\/\/doi.org\/10.4236\/jilsa.2024.164023","relation":{},"ISSN":["2150-8402","2150-8410"],"issn-type":[{"value":"2150-8402","type":"print"},{"value":"2150-8410","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}