Michelle Taub

1.9k total citations
44 papers, 934 citations indexed

About

Michelle Taub is a scholar working on Developmental and Educational Psychology, Computer Science Applications and Artificial Intelligence. According to data from OpenAlex, Michelle Taub has authored 44 papers receiving a total of 934 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Developmental and Educational Psychology, 20 papers in Computer Science Applications and 19 papers in Artificial Intelligence. Recurrent topics in Michelle Taub's work include Innovative Teaching and Learning Methods (30 papers), Intelligent Tutoring Systems and Adaptive Learning (18 papers) and Online Learning and Analytics (17 papers). Michelle Taub is often cited by papers focused on Innovative Teaching and Learning Methods (30 papers), Intelligent Tutoring Systems and Adaptive Learning (18 papers) and Online Learning and Analytics (17 papers). Michelle Taub collaborates with scholars based in United States, Canada and Spain. Michelle Taub's co-authors include Roger Azevedo, François Bouchet, Nicholas V. Mudrick, Robert G. Sawyer, Jonathan Rowe, James Lester, James C. Lester, Babak Khosravifar, Andy Smith and Elizabeth B. Cloude and has published in prestigious journals such as Journal of Educational Psychology, Computers in Human Behavior and Computers & Education.

In The Last Decade

Michelle Taub

41 papers receiving 897 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michelle Taub United States 16 590 389 301 265 143 44 934
Jaclyn Ocumpaugh United States 17 464 0.8× 521 1.3× 234 0.8× 481 1.8× 206 1.4× 56 1.1k
François Bouchet France 11 311 0.5× 223 0.6× 172 0.6× 182 0.7× 111 0.8× 34 612
Blair Lehman United States 11 388 0.7× 234 0.6× 226 0.8× 327 1.2× 207 1.4× 25 874
G. Tanner Jackson United States 14 584 1.0× 281 0.7× 135 0.4× 683 2.6× 92 0.6× 42 955
Arif Altun Türkiye 14 238 0.4× 346 0.9× 401 1.3× 104 0.4× 70 0.5× 74 849
Natalie K. Person United States 14 773 1.3× 206 0.5× 458 1.5× 791 3.0× 175 1.2× 22 1.4k
Agneta Gulz Sweden 15 331 0.6× 140 0.4× 173 0.6× 243 0.9× 112 0.8× 49 663
Victor Law United States 13 591 1.0× 239 0.6× 327 1.1× 121 0.5× 61 0.4× 32 869
Howard Hao-Jan Chen Taiwan 19 501 0.8× 172 0.4× 264 0.9× 415 1.6× 102 0.7× 41 1.2k
Stephen S. Killingsworth United States 7 668 1.1× 217 0.6× 258 0.9× 90 0.3× 85 0.6× 15 866

Countries citing papers authored by Michelle Taub

Since Specialization
Citations

This map shows the geographic impact of Michelle Taub'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 Michelle Taub with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michelle Taub more than expected).

Fields of papers citing papers by Michelle Taub

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michelle Taub. 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 Michelle Taub. The network helps show where Michelle Taub may publish in the future.

Co-authorship network of co-authors of Michelle Taub

This figure shows the co-authorship network connecting the top 25 collaborators of Michelle Taub. A scholar is included among the top collaborators of Michelle Taub 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 Michelle Taub. Michelle Taub is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Taub, Michelle, et al.. (2024). Leveraging student planning in game-based learning environments for self-regulated learning analytics.. Journal of Educational Psychology. 117(1). 88–105. 4 indexed citations
2.
Marino, Matthew T., et al.. (2024). Navigating AI-Powered Personalized Learning in Special Education: A Guide for Preservice Teacher Faculty. Teaching History A Journal of Methods. 4(2). 90–95. 4 indexed citations
3.
Taub, Michelle & Roger Azevedo. (2023). Teachers as self‐regulated learners: The role of multimodal data analytics for instructional decision making. New Directions for Teaching and Learning. 2023(174). 25–32. 3 indexed citations
4.
Hunt, Jessica H., et al.. (2023). Elementary Teachers’ Perceptions and Enactment of Supplemental, Game-Enhanced Fraction Intervention. Education Sciences. 13(11). 1071–1071. 2 indexed citations
5.
Taub, Michelle, et al.. (2023). Towards scaffolding self-regulated writing: implications for developing writing interventions in first-year writing. Metacognition and Learning. 18(3). 749–782. 3 indexed citations
6.
Hunt, Jessica H., et al.. (2023). Effects of Game-Enhanced Supplemental Fraction Curriculum on Student Engagement, Fraction Knowledge, and STEM Interest. Education Sciences. 13(7). 646–646. 2 indexed citations
7.
Taub, Michelle, et al.. (2022). Tracking Changes in Students’ Online Self-Regulated Learning Behaviors and Achievement Goals Using Trace Clustering and Process Mining. Frontiers in Psychology. 13. 813514–813514. 16 indexed citations
8.
Azevedo, Roger, François Bouchet, Melissa Duffy, et al.. (2022). Lessons Learned and Future Directions of MetaTutor: Leveraging Multichannel Data to Scaffold Self-Regulated Learning With an Intelligent Tutoring System. Frontiers in Psychology. 13. 813632–813632. 86 indexed citations
9.
Yang, Xi, et al.. (2020). Student Subtyping via EM-Inverse Reinforcement Learning.. Educational Data Mining. 2 indexed citations
10.
Cerezo, Rebeca, et al.. (2020). Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties. Journal of Visualized Experiments. 3 indexed citations
11.
Taub, Michelle, Robert G. Sawyer, James C. Lester, & Roger Azevedo. (2019). The Impact of Contextualized Emotions on Self-Regulated Learning and Scientific Reasoning during Learning with a Game-Based Learning Environment. International Journal of Artificial Intelligence in Education. 30(1). 97–120. 39 indexed citations
12.
Wortha, Franz, Roger Azevedo, Michelle Taub, & Susanne Narciss. (2019). Multiple Negative Emotions During Learning With Digital Learning Environments – Evidence on Their Detrimental Effect on Learning From Two Methodological Approaches. Frontiers in Psychology. 10. 2678–2678. 32 indexed citations
13.
Taub, Michelle, et al.. (2019). How are students’ emotions related to the accuracy of cognitive and metacognitive processes during learning with an intelligent tutoring system?. Learning and Instruction. 72. 101200–101200. 70 indexed citations
14.
Taub, Michelle & Roger Azevedo. (2018). How Does Prior Knowledge Influence Eye Fixations and Sequences of Cognitive and Metacognitive SRL Processes during Learning with an Intelligent Tutoring System?. International Journal of Artificial Intelligence in Education. 29(1). 1–28. 56 indexed citations
15.
Lallé, Sébastien, Cristina Conati, Roger Azevedo, Michelle Taub, & Nicholas V. Mudrick. (2017). On the Influence on Learning of Student Compliance with Prompts Fostering Self-Regulated Learning.. Educational Data Mining. 4 indexed citations
16.
Taub, Michelle, et al.. (2017). The Effects of Autonomy on Emotions and Learning in Game-Based Learning Environments.. Cognitive Science. 7 indexed citations
17.
Zhong, Boxuan, Shuo Yang, Junyu Chen, et al.. (2017). Emotion recognition with facial expressions and physiological signals. 1–8. 22 indexed citations
18.
Wise, Alyssa Friend, Roger Azevedo, Karsten Stegmann, et al.. (2015). CSCL and Learning Analytics: Opportunities to Support Social Interaction, Self-Regulation and Socially Shared Regulation.. Computer Supported Collaborative Learning. 607–614. 7 indexed citations
19.
Khosravifar, Babak, Roger Azevedo, Reza Feyzi-Behnagh, et al.. (2013). Adaptive Multi-Agent Architecture to Track Students' Self-Regulated Learning..
20.
Azevedo, Roger, Ronald S. Landis, Reza Feyzi-Behnagh, et al.. (2012). The Effectiveness of Pedagogical Agents’ Prompting and Feedback in Facilitating Co-adapted Learning with MetaTutor. Lecture notes in computer science. 212–221. 8 indexed citations

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.

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