Student Learning Benefits of a Mixed-Reality Teacher Awareness Tool in AI-Enhanced Classrooms
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
A current trend in AIEd is that systems typically notify teachers directly.
“a preference that runs counter to a current trend in AIEd where systems typically notify teachers directly (e.g., [31, 62]).”
From AI Sensing and Intervention in Higher Education: Student Perceptions of Learning Impacts, Affective Responses, and Ethical Priorities (2026) · cites this paper as [62]
Holstein et al. discovered that the least preferred feature of AI tutors among both teachers and students was providing automated emotional support to frustrated students.
“Holstein et al. [28, 30], which discovered the least preferred feature of AI tutors among both teachers and students was providing automated emotional support to frustrated students.”
From The Promise and Peril of ChatGPT in Higher Education: Opportunities, Challenges, and Design Implications (2024) · cites this paper as [30]
The citation lists haven’t been fetched yet
References 42 · Cited by 235
- Authors
- Holstein, K., McLaren, B. M., & Aleven, V.
- Affiliations
- Carnegie Mellon University (US)
- Corresponding author
- Holstein, Kenneth
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 154-168
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2808967136
- Cited by
- 235
- References
- 42
- Citations by year
- 2026: 36 · 2025: 43 · 2024: 43 · 2023: 25 · 2022: 25 · 2021: 28 · 2020: 17 · 2019: 15 · 2018: 3
- FWCI
- 6.40
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Augmented Reality Applications
- Keywords
- intelligent tutoring systems, teacher awareness, mixed reality, smart glasses, real-time analytics, human-AI collaboration, metacognition, K-12 education, junior high school students
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.
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