John S. Kinnebrew
About
In The Last Decade
John S. Kinnebrew
47 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Computer Science Applications 864
- Developmental and Educational Psychology 717
- Artificial Intelligence 410
- Education 263
- Information Systems 187
Countries citing papers authored by John S. Kinnebrew
This map shows the geographic impact of John S. Kinnebrew'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 John S. Kinnebrew with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John S. Kinnebrew more than expected).
Fields of papers citing papers by John S. Kinnebrew
This network shows the impact of papers produced by John S. Kinnebrew. 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 John S. Kinnebrew. The network helps show where John S. Kinnebrew may publish in the future.
Co-authorship network of co-authors of John S. Kinnebrew
This figure shows the co-authorship network connecting the top 25 collaborators of John S. Kinnebrew. A scholar is included among the top collaborators of John S. Kinnebrew based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John S. Kinnebrew. John S. Kinnebrew is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Comparison of Selection Criteria for Multi-Feature Hierarchical Activity Mining in Open Ended Learning Environments. | 1 |
| 3 | Learning Behavior Characterization with Multi-Feature, Hierarchical Activity Sequences. | 2 |
| 4 | Mining and Identifying Relationships Among Sequential Patterns in Multi-Feature, Hierarchical Learning Activity Data. | 1 |
| 5 | Investigating Student Generated Computational Models of Science. | 8 |
| 6 | 1 | |
| 7 | Adaptive Multi-Agent Architecture to Track Students' Self-Regulated Learning. | 0 |
| 8 | Digital Games and Science Learning: Design Principles and Processes to Augment Commercial Game Design Conventions. | 1 |
| 9 | Analyzing Students' Metacognitive Strategies in Open-Ended Learning Environments | 2 |
| 10 | Mining Temporally-Interesting Learning Behavior Patterns | 8 |
| 11 | Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework breakdown → | 359 |
| 12 | Identifying Students' Characteristic Learning Behaviors in an Intelligent Tutoring System Fostering Self-Regulated Learning | 29 |
| 13 | Supporting Student Learning using Conversational Agents in a Teachable Agent Environment. | 11 |
| 14 | Identifying Learning Behaviors by Contextualizing Differential Sequence Mining with Action Features and Performance Evolution. | 40 |
| 15 | 10 | |
| 16 | Modeling Learner’s Cognitive and Metacognitive Strategies in an Open-Ended Learning Environment | 6 |
| 17 | Global sensor web coordination and control using multi-agent systems | 0 |
| 18 | Modeling and Measuring Self-Regulated Learning in Teachable Agent Environments | 4 |
| 19 | A Decision-Theoretic Planner with Dynamic Compound Reconfiguration for Distributed Real-Time Applications. | 5 |
| 20 | Onboard Processing using the Adaptive Network Architecture | 6 |
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.