Cited by 205Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in EducationOnline Learning and Analytics

The DOI matches its Crossref record; 64 of the 65 references it cites were found in a registry or an index.

Designing for Complementarity: Teacher and Student Needs for Orchestration Support in AI-Enhanced Classrooms

Holstein, Kenneth, McLaren, Bruce M., Aleven, Vincent·2019·Lecture Notes in Computer Science

DOI 10.1007/978-3-030-23204-7_14

Open this paper in CoChat — free account

Integrity signals

Registry

Crossref · 10.1007/978-3-030-23204-7_14

Cites

64 of 64 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Contextual Design: Defining Customer-Centered Systems
Beyer, H. R., & Holtzblatt, K. (1997) · Cited by 2,748
Guidelines for Human-AI Interaction
Amershi, S., Weld, D., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., Suh, J., Iqbal, S., Bennett, P. N., Inkpen, K., et al. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300233 · Cited by 2,439
Value-sensitive design
Friedman, B. (1996) · Interactions · doi:10.1145/242485.242493 · Cited by 966
Universal methods of design: 100 ways to research complex problems, develop innovative ideas, and design effective solutions
(2012) · Choice Reviews Online · doi:10.5860/choice.49-5403 · Cited by 943
Effectiveness of Intelligent Tutoring Systems: A Meta-Analytic Review
Kulik, J. A., & Fletcher, J. D. (2016) · Review of Educational Research · doi:10.3102/0034654315581420 · Cited by 930
Participatory design
Muller, M. J., & Kuhn, S. (1993) · Communications of the ACM · doi:10.1145/153571.255960 · Cited by 909
Intelligent tutoring systems and learning outcomes: A meta-analysis
Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014) · Journal of Educational Psychology · doi:10.1037/a0037123 · Cited by 840
Cognitive Tutor: Applied research in mathematics education
RITTER, S., Anderson, J. R., Koedinger, K. R., & Corbett, A. T. (2007) · Psychonomic Bulletin & Review · doi:10.3758/bf03194060 · Cited by 512
Co-Designing a Real-Time Classroom Orchestration Tool to Support Teacher–AI Complementarity
Holstein, K., McLaren, B. M., & Aleven, V. A. W. M. M. (2019) · Journal of Learning Analytics · doi:10.18608/jla.2019.62.3 · Cited by 429
Self-citation
Stupid tutoring systems, intelligent humans
Baker, R. S. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0105-0 · Cited by 425

Show all 65 references

Research works printed but not linked: 2

Mulligan, D.K., King, J.: Bridging the gap between privacy and design. U. Pa. J. Const. L. 14, 989 (2011)
Watters, A.: The Monsters of Education Technology. Smashwords Edition (2014)

Sorted by citations

Items 101–200 of 205

Empowering Parents and Teachers to Support Children's Learning through AI-based and Robotic Learning Companions
Ho, H.-R. (2025) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3706599.3707605 · Cited by 6
Challenges and Opportunities for Multi-Device Management in Classrooms
Lachand, V., Michel, C., Serna, A., & Tabard, A. (2022) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3519025 · Cited by 5
Redefining and measuring student agency in AI-assisted learning: Development and validation of the agentic engagement with AI (AE-AI) scale
Dai, Y., Liu, S., Zhou, S., Lai, S., Liu, A., & Lim, C. P. (2026) · Computers & Education · doi:10.1016/j.compedu.2026.105687 · Cited by 4
The Ethics of AI in Education: Addressing Algorithmic Bias and Its Impact on Diverse Learners
Mohanty (2025) · Journal of Informatics Education and Research · doi:10.52783/jier.v5i4.4290 · Cited by 4
PELATIHAN UNTUK MEMAKSIMALKAN POTENSI ARTIFICIAL INTELLIGENCE DALAM MEMOTIVASI BELAJAR BAHASA JERMAN BAGI GURU BAHASA JERMAN DI MALANG
Kharis, M. (2024) · JMM (Jurnal Masyarakat Mandiri) · doi:10.31764/jmm.v8i1.20770 · Cited by 4
Predicting and Presenting Task Difficulty for Crowdsourcing Food Rescue Platforms
Shi, Z. R., Zhi, J., Zeng, S., Zhang, Z., Kapoor, A., Hudson, S., Shen, H., & Fang, F. (2024) · International World Wide Web Conference (WWW) · doi:10.1145/3589334.3648155 · Cited by 4
AI-Driven Curriculum Design and Course Management
Asrifan, A., Susanto, A. K., Elpisah, E., Syamsuardi, S., & Herlina, H. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3373-1017-6.ch007 · Cited by 4
PLA and The Future of Education
Almuraqab, N. A. S. (2024) · Studies in systems, decision and control · doi:10.1007/978-3-031-36895-0_70 · Cited by 4
Value-sensitive design in action: Designing student-centered intelligent tutoring systems with community college students and instructors
Ko, E. G., & Hughes, J. E. (2026) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2026.100560 · Cited by 3
AI Sensing and Intervention in Higher Education: Student Perceptions of Learning Impacts, Affective Responses, and Ethical Priorities
Han, B., Ma, Y., Coghlan, S., McKay, D., Buchanan, G., & Smith, W. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790360 · Cited by 3
“These systems aim to enhance teachers’ situational awareness [63, 91, 139] and deliver timely, individualised learning support to students.”
Caught between expansive world-building and the status quo: Using figured worlds to understand world-building in AI for educational co-design contexts
Chang, M. A., & Philip, T. M. (2025) · Journal of the Learning Sciences · doi:10.1080/10508406.2025.2490514 · Cited by 3
“Helping Me Versus Doing It for Me”: Designing for Agency in LLM-Infused Writing Tools for Science Journalism
Nishal, S., Lee, M., Diakopoulos, N. A., & Vaughan, J. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790372 · Cited by 3
From Answer Engines to Learning Partners: A Dual-ZPD Design Framework for AI-Supported Learning
Klein, R., Benden, D. K., Schier, A., Stotko, D., & Lauermann, F. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791476 · Cited by 5
Designing Multi Sensory Environments for Children’s Learning: An Analysis of Teachers’ and Researchers’ Perspectives
Cosentino, G., Lee‐Cultura, S., Papavlasopoulou, S., & Giannakos, M. N. (2023) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/3585088.3589368 · Cited by 3
Adverse effects of intelligent support of CSCL—the ethics of conversational agents
Thierfelder, B., Papadopoulos, P. M., Weinberger, A., Demetriadis, S., & Tegos, S. D. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-18851-0.00015-9 · Cited by 3
Setting an Agenda for Urban AI Adaptivity in Urban Planning and Architecture E-learning
Kayed, S. I., Ghoz, L., Elbehairy, F., Ghonim, A. S., & Hendawy, M. (2022) · Journal of Engineering Research - Egypt/Journal of Engineering Research · doi:10.21608/erjeng.2022.265385 · Cited by 3
The effectiveness of lightweight automated support for learning about dynamic systems with qualitative representations
Kragten, M., & Bert Bredeweg, A. (2024) · ACM Symposium on Applied Computing · doi:10.1145/3605098.3635950 · Cited by 3
WeAudit: Scaffolding User Auditors and AI Practitioners in Auditing Generative AIPreprint
Deng, W. H., Wang, C., Han, H. Z., Hong, J., Holstein, K., & Eslami, M. (2025) · Qeios · doi:10.32388/b1lxnv · Cited by 3
Self-citation
What is Ethical: AIHED Driving Humans or Human-Driven AIHED? A Conceptual Framework Enabling the 'Ethos' of AI-Driven Higher EducationPreprint
Mahajan, P. T. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5339873 · Cited by 3
Comparing Dynamic Versus Pre‐Planned Combinations of Individual and Collaborative Learning in a Classroom Experiment
Yang, K. B., Pan, Y., Liu, M., Rummel, N., & Aleven, V. A. W. M. M. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70158 · Cited by 2
Self-citation
Open-Source Large Language Models in Education: A Narrative Review of Evidence, Pedagogical Roles, and Learning Outcomes
Lin, M. P.-C., Huang, J.-Y., Chang, D., Tembrevilla, G., Bowen, G. M., Poitras, E., Janarthanan, V., & Ryoo, J. (2026) · AI in Education · doi:10.3390/aieduc2010004 · Cited by 4
ClassAid: A Real-time Instructor-AI-Student Orchestration System for Classroom Programming Activities
Zhang, G., Sun, G., Xia, M., & Liang, R. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790824 · Cited by 4
Mapping the triadic interaction network in AI-enhanced L2 classrooms: A social network analysis of learning outcomes and the moderating role of AI literacy
Zhang, X., Xun, H., & 王小梦 (2026) · System · doi:10.1016/j.system.2026.104050 · Cited by 3
Machine teachers and human-AI collaboration: student differences in perceptions of AI-based education
Kim, J., Spence, P. R., & Kelly, S. E. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2667455 · Cited by 2
Preparing Students for an AI-Enhanced Future
Gobara, R. E. G. E., & Ahmed, Z. E. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-2728-9.ch013 · Cited by 2
The Reality of Employing Artificial Intelligence in the Educational Process from the Perspective of Public-School Principals in Bani Ubaid District
Al-Ma'ani, D. (2024) · Jordan Journal of Applied Science-Humanities Series · doi:10.35192/jjoas-h.v38i2.680 · Cited by 2
Potential Pitfalls of False Positives
Dey, I., Gnesdilow, D., Passonneau, R. J., & Puntambekar, S. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-64315-6_45 · Cited by 2
The effect of artificial intelligence applications GymBuddy & Elomia on the mental health and physical activities of teachers and learners exposed to e-learning platforms
Zhang, Y. (2025) · Current Psychology · doi:10.1007/s12144-025-08015-3 · Cited by 2
Educational and Psychological Measurement
Finch, W. H., French, B. F., Immekus, J. C., & Dai, S. (2025) · Routledge eBooks · doi:10.4324/9781003439769 · Cited by 2
AI-Enhanced Speech-Language Intervention Documentation: Opportunities and Design Goals
Zheng, Q., Choudhry, A., Liu, Z., Rabbani, P., Hu, Y., Olszewski, A., Huang, Y., & Xiong, J. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-98465-5_17 · Cited by 1
Enhancing SEE With LLMs: A Human-In-The-Loop Platform for Student-Tutor Collaboration
Levchuk, O., Sanchez, C., Lopez, I., & Favela, J. (2025) · International Conference in Software Engineering Research and Innovation (CONISOFT) · doi:10.1109/conisoft66928.2025.00035 · Cited by 1
Transformations in Learning and Social Relations in the Age of Artificial Intelligence
Alesanco, E. B., & Cuartas, R. S. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-4480-5.ch013 · Cited by 1
Responding to AI-generated emotional alerts: teachers’ intervention and students’ engagement in the mathematics classroom
Swidan, O. (2026) · ZDM · doi:10.1007/s11858-026-01810-7 · Cited by 1
Innovations in Language Teaching Methods Based on Multiple Intelligences Theory
(2025) · International Journal of Educational Curriculum Management and Research · doi:10.38007/ijecmr.2025.060106 · Cited by 1
The Use of AI in Teaching and Learning
Kaiser, G., & Kaiser, S. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-2397-8.ch010 · Cited by 1
GenAI Chatbots as Agents in a Community of Inquiry: Exploring Their Role in Online Distance Learning
Olivier, C., & Weilbach, L. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-031-99965-9_2 · Cited by 1
Educator Professional Development Through LA and AIED Participatory Design: A Missing Link
Nazaretsky, T. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-03873-9_4 · Cited by 1
Integrating Generative AI with VR and AR: Enhancing Immersive Educational Experiences Via Authentic Learning and Assessment
Aydemir, M., & Başman, M. (2026) · Springer eBooks · doi:10.1007/978-981-95-4871-2_10 · Cited by 2
The Impact of AI-Assisted Personalized Learning on Student Achievement Gaps
Paul, J., & Jeyanthi, R. (2025) · International Journal of Education and Pedagogy (IJEP) · doi:10.63090/ijep/3108.1800.0012 · Cited by 1
A Thorough Review of AI Developments in Education: Historical Progress, Current Applications, and Future Directions
Adablanu, S., Ghansah, B., Benuwa, B., & Oppong, S. O. (2025) · Journal of Artificial Intelligence in Education · doi:10.29303/jaie.v1i2.706 · Cited by 1
Artificial Intelligence and Moodle: Advancing Intelligent Learning and Digital Marketing in Education
Sofianos, K. C., Kaponis, A., Stefanidakis, M., Μaragoudakis, M., Pappas, T., & Bukauskas, L. (2026) · Engineering Technology & Applied Science Research · doi:10.48084/etasr.13756 · Cited by 1
Examining the Role of AI-Based Learning Tools in Higher Education: A Critical Synthesis of Effects on Student Performance and Engagement
Atianashie Miracle, A., Kuffour, M. K., Kyiewu, B., & Amponsah, C. (2025) · SAP Social AI · doi:10.62486/sai202529 · Cited by 1
Towards Evaluating Student Agency in AI‑Mediated Learning
Pauzi, Z., Vizgirda, V., Duran, L. D. D., & Mavrikis, M. (2026) · Designing Interactive Systems Conference · doi:10.1145/3802974.3809419 · Cited by 1
Self-Reported Preparedness and Factors Influencing AI Tools Integration in Teaching Among Master's Degree Students in a Selected Teachers Education College
-, M. M., -, R. A. M., -, D. M. M., & -, M. B. (2024) · International Journal For Multidisciplinary Research · doi:10.36948/ijfmr.2024.v06i01.12894 · Cited by 1
Cultivating Computational Thinking Through STEM and AI in Early Education
Bataineh, R. F., & Bataineh, R. F. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-6210-5.ch001 · Cited by 1
The Development of Individualized Assignment Generator
Zaripova, R. R., Danilov, A., Salekhova, L., & Fazliakhmetov, T. R. (2024) · International Conference on Developments in eSystems Engineering (DeSE) · doi:10.1109/dese63988.2024.10911947 · Cited by 1
Work in Progress: Investigating the Effectiveness of an Orchestration Tool on the Nature of Students’ Collaborative Interactions During Group Work
Tucker, T., Lawrence, L., & Mercier, E. (2024) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--38174 · Cited by 1
A Evolução da Área de Busca como um Processo de Aprendizagem com base em um Mapeamento Sistemático
Machado, M. D. O. C., Pinelli, C., & Siqueira, S. W. M. (2019) · Anais ... Workshops do Congresso Brasileiro de Informática na Educação · doi:10.5753/cbie.wcbie.2019.833 · Cited by 1
Work-in-Progress–Computer Vision Methods to Examine Neurodiverse Gaze Patterns in 360-Video
Glaser, N. J., Schmidt, M., Palmer, H., Xing, W., & Schmidt, C. T. (2022) · International Conference of the Immersive Learning Research Network (iLRN) · doi:10.23919/ilrn55037.2022.9815974
Research on Solving Text-Diagram Function Problems and Its Application in Tutoring System
Sun, H., & Yu, X. (2022) · International Conference on Intelligent Education and Intelligent Research (IEIR) · doi:10.1109/ieir56323.2022.10050062
AI Transformation for Learning in Organizations
Bidarra, J., & Neves, C. (2024) · Advances in human resources management and organizational development book series · doi:10.4018/979-8-3693-0556-0.ch004
الذكاء الاصطناعي في التعليم
الهادي, م. (2024) · Compunet ( The Egyptian Information Journal ) · doi:10.21608/jstc.2024.338390
Integration of a Teacher Dashboard in a Hybrid Support Approach for Constructing Qualitative Representations
Kragten, M., Hoogma, T., & Bert Bredeweg, A. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72315-5_15
Smart Education Using Explainable Artificial Intelligence
Sharma, N. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-8151-9.ch004
Tell Me Why I Should “Not” Follow Your Recommendation: On the Role of Explainable AI in Collaborative Human-AI Decision MakingPreprint
Abu-Rasheed, H., Weber, C., & Fathi, M. (2025) · doi:10.31219/osf.io/x867z
The Development and Alleviation of Humanistic Artificial Intelligence in the Digital Age Education: A Content Analysis research
Chen, X., Hu, Z., Jing, Y., & Wang, C. (2024) · International Conference on Advances in Artificial Intelligence (ICAAI) · doi:10.1145/3704137.3704189
Assessing Emotional Intelligence in the Era of Artificial Intelligence by Elementary School Educators
Sarwat, Q., Mahmood, A., Behlol, G., & Rubab, U. E. (2025) · Research Journal for Social Affairs · doi:10.71317/rjsa.003.01.0260
Generative Artificial Intelligence Practices for Doctoral Student Engagement
Orr, L., Burton, K., Blakely, J., & Harrison, S. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5092-9.ch003 · Cited by 1
Understanding Students’ Nuanced Views on AI-Supported Classroom Learning Through Perspective Taking
Nagashima, T., Vincoli, M., Scholz, N., & Su, M. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-98414-3_2
Percepção de estudantes de Psicologia sobre inteligência artificial
Nakano, T. D. C., Brandine, J. V. S., Vilvert, P. D. N., Garcia, A. L. P., & de Andrade, M. E. V. (2025) · LATAM Revista Latinoamericana de Ciencias Sociales y Humanidades · doi:10.56712/latam.v6i4.4390
AI-Driven Assessment: Redefining Student Preparation for Standardised Graduation
Villarreal, K. L., Bustillo, E. B., Swain-Oropeza, R., & Hernández-Aguirre, Á. I. (2025) · World Engineering Education Forum - Global Engineering Deans Council (WEEF-GEDC) · doi:10.1109/weef-gedc66748.2025.11256367
Technology-Driven Assessment Methods in Teacher Education
Asanre, A. A., Adeleke, H. O., & Adeyemi, A. H. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-3872-9.ch010
Educators as Creators: Enabling CS Faculty to Build Educational Interventions with Sustainable AI Models
Vincent, V., Indra, R., Pathan, R., & Parthasarathy, P. D. (2025) · Communications in computer and information science · doi:10.1007/978-3-032-14583-3_4
Mesterséges Intelligencia alkalmazása az oktatásban: lehetőségek és félelmek
Antal, P. (2025) · Kortárs Kihívások a Köznevelésben és a Felsőoktatásban Nemzetközi Konferencia · doi:10.70832/kkkf.2025.07
Learning Progression Certification: A Framework for Using Blockchain-Based Microcredentials to Reflect Acquired Knowledge in Physics and Mathematics Education
Bednorz, D., & Neumann, K. (2026) · Educational communications and technology: issues and innovations · doi:10.1007/978-3-032-06823-1_10
CAD: AI-Agent Framework for Learning Word Game
Vu, D.-H., Minh, D. V., The, V. T., & Anh, M. H. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-21625-0_14
Aider les enseignants pendant la phase d'élaboration du scénario pédagogique par une approche ontologique de la modélisation des connaissances tâches-techniques du domaine considéré
Vu, T. M. H. (2020) · theses.fr (ABES) · doi:10.70675/c40ad236zd1baz4ee2z915az6ae801a76289
OpenCD: Empowering Diagnosis of Children's Mathematical Cognition through Open-ended Multimodal Tasks
Zheng, Z., Yu, C., Chen, W., Song, M., Liu, B., Liu, J., Wang, S., Wang, X. Q., Cai, J., & Shi, Y. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790318 · Cited by 1
Agentic Audio Moderator vs Human Moderator in Think-Aloud Usability Testing: Results from a Randomized Controlled Trial
Zhu, W., Chen, G., Wang, Y., An, P., Du, J., & Li, C. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791653
C.A.T.E.: A Multimodal AI Agent for Context-Aware and Bilingual Learning in Technical Education
Jantan, S. R., Shahrul, U. H., & Murad, R. (2026) · Advances in engineering research/Advances in Engineering Research · doi:10.2991/978-94-6239-636-4_6
Human-AI collaboration in classroom video analysis: evaluating the feasibility and usability of multimodal large language models for nonverbal behavior recognition
Zhou, Y., Kang, J., & Nguyen, H. (2026) · Behaviour and Information Technology · doi:10.1080/0144929x.2026.2662406
Integrating Generative AI in Engineering Education: Interaction Dynamics and Pedagogical Implications
Filippi, S. (2026) · Intelligent Information Management · doi:10.4236/iim.2026.183005
Science Teaching and Learning with Artificial Intelligence
Neumann, K., Zhaı, X., & Kubsch, M. (2026) · Springer eBooks · doi:10.1007/978-3-032-16871-9_6
Quality Science Education: Role of Digital Technologies in the Developing World
Misra, R., Rahul, Nishu, & Mathur, V. (2026) · Springer eBooks · doi:10.1007/978-981-95-7785-9_9
Artificial intelligence and machine learning approaches for predicting student achievement in science and STEM education: a bibliometric analysis
Şentürk, C., & Yağcı, A. (2026) · Journal of Computers in Education · doi:10.1007/s40692-026-00392-3
Balancing Teacher and Student Agency: Co-Orchestration Tool Design Supporting Real-Time Dynamic Pairing
Yang, K. B., Liu, M., Xu, L., Rummel, N., & Aleven, V. (2026) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3816902
Self-citation
AI-Empowered Teaching Quality Evaluation in Higher Education: A Three-Path Practical Framework
Jiang, J. (2026) · US-China Education Review A · doi:10.17265/2161-623x/2026.05.001
Modeling Completion Time in Mathematics Formative Assessments: Content-Based Prediction of Time Variation
Botelho, A. F., Huang, Z., Martin, N. S., & Shin, J. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29755-6_21
Using an MR-Based Teacher Orchestration Tool in AI-Supported K-12 Classrooms
Jin, Q., Zhan, Y., Morgus, W., Price, K., Sandbothe, M., Sewall, J., Popescu, O., Berman, S., Fancsali, S. E., RITTER, S., et al. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29770-9_36
Self-citation
AI Is Available, Partnership Is Optional: Student Agency in Human–AI Interaction
Retes, R. M., Escalona, S. G., Webster, M., Giotto, F. M., & Wayllace, C. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29770-9_7 · Cited by 1
Narrative Approaches to Teacher Agency: How Educators’ Stories Shape Educational Change
Erwin, E., Maseko, T., Amir, S., & Fallah, S. (2025) · International Journal of Educational Narratives · doi:10.70177/ijen.v3i6.2893
Passive Governance for AI Learning Assistants: Enabling Teacher Control Through Knowledge Base Curation in Vocational Education
Thierfelder, B., Spilski, J., Löber, J., Lachmann, T., & Bleistein, T. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29596-5_36
Sruthi: What Becomes Sayable Through Peer-Mode Reflective Scaffolding in Fieldwork Communication
Sheshadri, S., Pillai, M. B., Kumar, R., Nair, P. P. M., Gupta, A., Megha, T. M., Nair, S. S., Menon, B. M., Radhakrishnan, U., & Bhavani Rao, R. (2026) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3816046.3816219
A rural student sports belief transformation system based on multimodal biosensing and AI dynamic tuning
Fu, X., Meng, Z., & Shi, H. (2026) · Discover Applied Sciences · doi:10.1007/s42452-026-09069-z
Transparent AI Feedback via Process-Aware Modeling: An Educational Middleware Approach
Ardimento, P., Scalera, M., & Scalera, M. (2026) · International Conference on Emerging and Intelligent Technologies and Systems (EITS) · doi:10.1109/eits70066.2026.11609624
Beyond the Gradebook
Rantz, R. (2026) · IGI Global eBooks · doi:10.4018/979-8-2600-2508-6.ch008
How Artificial Intelligence Revolutionizes Education
Du, Z. (2026) · Advances in Education Humanities and Social Science Research · doi:10.56028/aehssr.17.1.341.2026
Analysis of the effectiveness of innovation and entrepreneurship education reform in universities driven by artificial intelligence
Bai, H. (2026) · Progress in Artificial Intelligence · doi:10.1007/s13748-026-00470-8
From Moral Gatekeeping to Social Autopilot: Revealing the Normative Substitution Paradox in AI Delegation
Alhelaly, Y., & Ashofteh, A. (2026) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac69091.2026.00162
An AI–Driven Real–Time Feedback Framework for Personalized Learning and Improved Educational Outcomes
Ramamoorthy, S. K., Hope, E., & Thanappan, S. (2026) · CompSci & AI Advances · doi:10.69626/cai.2026.0211
Rethinking Learning with AI-Powered Personalized Virtual Agents and Human-AI Collaboration
Dai, C. (2026) · Springer international handbooks of education · doi:10.1007/978-3-032-04596-6_14-1
Scalable Orchestration of Immersive Learning Environments using a Teacher-Centered Control Framework for VR Classrooms
Terschüren, J.-N., Fey, M. P., Raskar, M., Varney, V., & Muller, L. (2026) · International Conference on Virtual Reality · doi:10.1109/icvr70658.2026.11672401
Mapping AI’s Potential for Social-Emotional Support in Second Language Acquisition: A Scoping Review
Gao, K.-W., Huang, D., Feng, S., He, W., & Zhang, J. (2026) · SAGE Open · doi:10.1177/21582440261488375
Rethinking teachers’ diagnostic skills in AI-supported formative assessment: from diagnosis to meta-diagnosis
Hoppe, T., Loibl, K., & Leuders, T. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1857661
Integrating AI-Assisted Programming Tools into Project-Based Web Development Education: A Dynamic Decay Strategy with Tripartite Collaborative Model
Dao, J. (2026) · International Conference on Educational Digitalization and Computer Science in the Guangdong-Hong Kong-Macao Greater Bay Area · doi:10.1145/3828183.3828429
The impact of artificial intelligence based learning tools on students performance and engagement in higher education
Atianashie Miracle, A., Kuffour, M. K., Kyiewu, B., & Amponsah, C. (2025) · SAP Social AI · doi:10.62486/sai202544 · Cited by 1
Human-Centred Artificial Intelligence for Inclusive Education and Social Development: An Integrative Review
Wali, A. W. (2026) · International Journal of Pedagogical Humanities and Social Studies · doi:10.66324/ijphss.v1i3.214
The Pocket Tutor Has a Price: Scaffolding Self-Paced Learning with AI
Jamil, H. M. (2026) · Big Data and Cognitive Computing · doi:10.3390/bdcc10100322
SMOKEChem: developing and piloting a digital learning environment integrating AI-based and peer feedback for socio-scientific argumentation
Leppla, L. C., Spanier, M., & Seibert, J. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1952302
Exploring AI-Based Math Learning Applications in Higher Education: Evaluation and Recommendations
Wang, Y., & Ge, Z.-G. (2025) · International Conference on Digital Technology in Education (ICDTE) · doi:10.1145/3796159.3796169

Authors: Holstein, K., McLaren, B. M., & Aleven, V.
Affiliations: Carnegie Mellon University (US)
Corresponding author: Holstein, Kenneth
ORCID: Holstein, Kenneth
McLaren, Bruce M.
Aleven, Vincent
Venue: Lecture Notes in Computer Science
Publisher: Springer International Publishing
Published: 2019
Pages: 157-171
ISSN: 0302-9743 (ISSN-L)
1611-3349
DOI: 10.1007/978-3-030-23204-7_14
OpenAlex: W2952696298
Cited by: 189
References: 65
Citations by year: 2026: 46 · 2025: 45 · 2024: 29 · 2023: 21 · 2022: 21 · 2021: 14 · 2020: 12 · 2019: 1
FWCI: 4.59
Type: conference paper
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Lecture notes in computer science (publishedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Social Sciences › Education › Artificial Intelligence in Education
Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
Keywords: human-AI collaboration, artificial intelligence in education, K-12 education, teacher needs, student needs, AI tutors, human tutoring, student motivation, emotional support, human-centered design

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Designing for Complementarity: Teacher and Student Needs for Orchestration Support in AI-Enhanced Classrooms

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks