Zachary A. Pardos
About
In The Last Decade
Zachary A. Pardos
87 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 89
- Computer Science Applications 1.0k
- Artificial Intelligence 940
- Developmental and Educational Psychology 332
- Information Systems 308
- Education 230
Countries citing papers authored by Zachary A. Pardos
This map shows the geographic impact of Zachary A. Pardos'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 Zachary A. Pardos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zachary A. Pardos more than expected).
Fields of papers citing papers by Zachary A. Pardos
This network shows the impact of papers produced by Zachary A. Pardos. 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 Zachary A. Pardos. The network helps show where Zachary A. Pardos may publish in the future.
Co-authorship network of co-authors of Zachary A. Pardos
This figure shows the co-authorship network connecting the top 25 collaborators of Zachary A. Pardos. A scholar is included among the top collaborators of Zachary A. Pardos 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 Zachary A. Pardos. Zachary A. Pardos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 3 | |
| 4 | 9 | |
| 5 | Improving Student Outcomes Through Informed Use of Learning Analytics | 1 |
| 6 | Distributed Representation of Misconceptions. | 1 |
| 7 | Is this Model for Real? Simulating Data to Reveal the Proximity of a Model to Reality. | 0 |
| 8 | Proceedings of the Seventh International Conference on Educational Data Mining (EDM) (7th, London, United Kingdom, July 4-7, 2014). | 1 |
| 9 | Refining Learning Maps with Data Fitting Techniques: Searching for Better Fitting Learning Maps. | 5 |
| 10 | A Spectral Learning Approach to Knowledge Tracing | 18 |
| 11 | Developing Data Standards and Systems for MOOC Data Science. | 1 |
| 12 | Adapting Bayesian Knowledge Tracing to a Massive Open Online Course in edX | 51 |
| 13 | Interleaved Practice with Multiple Representations: Analyses with Knowledge Tracing Based Techniques. | 3 |
| 14 | 84 | |
| 15 | 27 | |
| 16 | Does Time Matter? Modeling the Effect of Time with Bayesian Knowledge Tracing. | 37 |
| 17 | Less is More: Improving the Speed and Prediction Power of Knowledge Tracing by Using Less Data. | 11 |
| 18 | Comparing of Traditional Assessment with Dynamic Testing in a Tutoring System | 1 |
| 19 | Navigating the parameter space of Bayesian Knowledge Tracing models: Visualizations of the convergence of the Expectation Maximization algorithm. | 46 |
| 20 | Determining the Significance of Item Order In Randomized Problem Sets | 20 |
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.