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001469971 001__ 1469971
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001469971 020__ $$a9783031362729$$q(electronic bk.)
001469971 020__ $$a3031362721$$q(electronic bk.)
001469971 020__ $$z9783031362712
001469971 0247_ $$a10.1007/978-3-031-36272-9$$2doi
001469971 035__ $$aSP(OCoLC)1385981748
001469971 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dOCLCF
001469971 049__ $$aISEA
001469971 050_4 $$aLB1028.43$$b.I64 2023eb
001469971 08204 $$a371.33/463$$223/eng/20230626
001469971 1112_ $$aInternational Conference on Artificial Intelligence in Education$$n(24th :$$d2023 :$$cTokyo, Japan)
001469971 24510 $$aArtificial intelligence in education :$$b24th International Conference, AIED 2023, Tokyo, Japan, July 3-7, 2023, Proceedings /$$cNing Wang, Genaro Rebolledo-Mendez, Noboru Matsuda, Olga C. Santos, Vania Dimitrova, editors.
001469971 2463_ $$aAIED 2023
001469971 264_1 $$aCham :$$bSpringer,$$c2023.
001469971 300__ $$a1 online resource (xxvi, 840 pages) :$$billustrations (some color).
001469971 336__ $$atext$$btxt$$2rdacontent
001469971 337__ $$acomputer$$bc$$2rdamedia
001469971 338__ $$aonline resource$$bcr$$2rdacarrier
001469971 4901_ $$aLecture notes in computer science ;$$v13916
001469971 4901_ $$aLecture notes in artificial intelligence
001469971 4901_ $$aLNCS Sublibrary, SL 7, Artificial intelligence
001469971 500__ $$aIncludes author index.
001469971 5050_ $$aIntro -- Preface -- Organization -- International Artificial Intelligence in Education Society -- Contents -- Full Papers -- Machine-Generated Questions Attract Instructors When Acquainted with Learning Objectives -- 1 Introduction -- 2 Related Work -- 3 Overview of Quadl -- 4 Evaluation Study -- 4.1 Model Implementation -- 4.2 Survey Study -- 5 Results -- 5.1 Instructor Survey -- 5.2 Accuracy of the Answer Prediction Model -- 5.3 Qualitative Analysis of Questions Generated by Quadl -- 6 Discussion -- 7 Conclusion -- References
001469971 5058_ $$aSmartPhone: Exploring Keyword Mnemonic with Auto-generated Verbal and Visual Cues -- 1 Introduction -- 2 Methodology -- 2.1 Pipeline for Auto-generating Verbal and Visual Cues -- 3 Experimental Evaluation -- 3.1 Experimental Design -- 3.2 Experimental Conditions -- 3.3 Evaluation Metrics -- 3.4 Results and Discussion -- 4 Conclusions and Future Work -- References -- Implementing and Evaluating ASSISTments Online Math Homework Support At large Scale over Two Years: Findings and Lessons Learned -- 1 Introduction -- 2 Background -- 2.1 The ASSISTments Program -- 2.2 Theoretical Framework
001469971 5058_ $$a2.3 Research Design -- 3 Implementation of ASSISTments at Scale -- 3.1 Recruitment -- 3.2 Understanding School Context -- 3.3 Training and Continuous Support -- 3.4 Specifying a Use Model and Expectation -- 3.5 Monitoring Dosage and Evaluating Quality of Implementation -- 4 Data Collection -- 5 Analysis and Results -- 6 Conclusion -- References -- The Development of Multivariable Causality Strategy: Instruction or Simulation First? -- 1 Introduction -- 2 Literature Review -- 2.1 Learning Multivariable Causality Strategy with Interactive Simulation
001469971 5058_ $$a2.2 Problem Solving Prior to Instruction Approach to Learning -- 3 Method -- 3.1 Participants -- 3.2 Design and Procedure -- 3.3 Materials -- 3.4 Data Sources and Analysis -- 4 Results -- 5 Discussion -- 6 Conclusions, Limitations, and Future Work -- References -- Content Matters: A Computational Investigation into the Effectiveness of Retrieval Practice and Worked Examples -- 1 Introduction -- 2 A Computational Model of Human Learning -- 3 Simulation Studies -- 3.1 Data -- 3.2 Method -- 4 Results -- 4.1 Pretest -- 4.2 Learning Gain -- 4.3 Error Type -- 5 General Discussion -- 6 Future Work
001469971 5058_ $$a7 Conclusions -- References -- Investigating the Utility of Self-explanation Through Translation Activities with a Code-Tracing Tutor -- 1 Introduction -- 1.1 Code Tracing: Related Work -- 2 Current Study -- 2.1 Translation Tutor vs. Standard Tutor -- 2.2 Participants -- 2.3 Materials -- 2.4 Experimental Design and Procedure -- 3 Results -- 4 Discussion and Future Work -- References -- Reducing the Cost: Cross-Prompt Pre-finetuning for Short Answer Scoring -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Task Definition -- 3.2 Scoring Model -- 4 Method -- 5 Experiment -- 5.1 Dataset
001469971 506__ $$aAccess limited to authorized users.
001469971 520__ $$aThis book constitutes the refereed proceedings of the 24th International Conference on Artificial Intelligence in Education, AIED 2023, held in Tokyo, Japan, during July 3-7, 2023. This event took place in hybrid mode. The 53 full papers and 26 short papers presented in this book were carefully reviewed and selected from 311 submissions. The papers present result in high-quality research on intelligent systems and the cognitive sciences for the improvement and advancement of education. The conference was hosted by the prestigious International Artificial Intelligence in Education Society, a global association of researchers and academics specializing in the many fields that comprise AIED, including, but not limited to, computer science, learning sciences, and education.
001469971 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed June 26, 2023).
001469971 650_0 $$aArtificial intelligence$$xEducational applications$$vCongresses.
001469971 650_0 $$aComputer-assisted instruction$$vCongresses.
001469971 650_0 $$aIntelligent tutoring systems$$vCongresses.
001469971 655_0 $$aElectronic books.
001469971 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001469971 7001_ $$aWang, Ning,$$eeditor.$$0(orcid)0000-0001-5229-4192$$1https://orcid.org/0000-0001-5229-4192
001469971 7001_ $$aRebolledo-Mendez, Genaro,$$eeditor.$$1https://orcid.org/0000-0002-3214-0935
001469971 7001_ $$aMatsuda, Noboru,$$eeditor.$$0(orcid)0000-0003-2344-1485$$1https://orcid.org/0000-0003-2344-1485
001469971 7001_ $$aSantos, Olga C.,$$d1978-$$eeditor.$$1https://orcid.org/0000-0002-9281-4209
001469971 7001_ $$aDimitrova, Vania,$$d1965-$$eeditor.$$1https://orcid.org/0000-0002-7001-0891
001469971 830_0 $$aLecture notes in computer science ;$$v13916.
001469971 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001469971 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
001469971 852__ $$bebk
001469971 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-36272-9$$zOnline Access$$91397441.1
001469971 909CO $$ooai:library.usi.edu:1469971$$pGLOBAL_SET
001469971 980__ $$aBIB
001469971 980__ $$aEBOOK
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