Mia Stern
Impact in
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- Online Learning and Analytics
- Teaching and Learning Programming
- Health Informatics top 10%
Papers in
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- Intelligent Tutoring Systems and Adaptive Learning 3
- AI-based Problem Solving and Planning 1
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- Online Learning and Analytics 2
- Teaching and Learning Programming 1
- Co-authors
- Joseph E. Beck (2 shared papers)Beverly Park Woolf (2 shared papers)Paul Moody (1 shared paper)Bernard J Kerr (1 shared paper)Martin Wattenberg (1 shared paper)Steven L. Rohall (1 shared paper)Kushal Dave (1 shared paper)Eric Wilcox (1 shared paper)
- Journals
- ScholarWorks@UMassAmherst (University of Massachusetts Amherst) (1 paper)MIT Press eBooks (1 paper)XRDS Crossroads The ACM Magazine for Students (1 paper)
- Partner nations
- United States
In The Last Decade
Mia Stern
5 papers receiving 186 citations
Peers
Comparison fields: 5 of 45
- Computer Science Applications 78
- Health Informatics 12
- Information Systems and Management 40
- Human-Computer Interaction 25
- Developmental and Educational Psychology 48
Countries citing papers authored by Mia Stern
This map shows the geographic impact of Mia Stern's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mia Stern with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mia Stern more than expected).
Fields of papers citing papers by Mia Stern
This network shows the impact of papers produced by Mia Stern. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mia Stern. The network helps show where Mia Stern may publish in the future.
Co-authors
The 8 scholars most cited alongside Mia Stern, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1996 | 153 | |
| 2 | 2004 | 38 | |
| 3 | Growth and maturity of intelligent tutoring systems: a status report | 2001 | 22 |
| 4 | Using adaptive hypermedia and machine learning to create intelligent web-based courses | 2001 | 9 |
| 5 | 2004 | 7 |
About Mia Stern
Mia Stern is a scholar working on Artificial Intelligence, Computer Science Applications, Information Systems, Information Systems and Management and Computer Vision and Pattern Recognition, having authored 5 papers that have together received 229 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (3 papers), Personal Information Management and User Behavior (2 papers), Online Learning and Analytics (2 papers), Web Data Mining and Analysis (1 paper), AI-based Problem Solving and Planning (1 paper), Innovative Teaching and Learning Methods (1 paper), Teaching and Learning Programming (1 paper) and Usability and User Interface Design (1 paper). The work is most often cited by research in Computer Science Applications (78 citations), Health Informatics (12 citations), Information Systems and Management (40 citations), Human-Computer Interaction (25 citations) and Developmental and Educational Psychology (48 citations). Mia Stern has collaborated with scholars based in United States. Frequent co-authors include Joseph E. Beck, Beverly Park Woolf, Paul Moody, Bernard J Kerr, Martin Wattenberg, Steven L. Rohall, Kushal Dave and Eric Wilcox. Their work appears in journals such as ScholarWorks@UMassAmherst (University of Massachusetts Amherst), MIT Press eBooks and XRDS Crossroads The ACM Magazine for Students.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.