STEVE RITTER

2.0k total citations
139 papers, 1.1k citations indexed

About

STEVE RITTER is a scholar working on Artificial Intelligence, Computer Science Applications and Developmental and Educational Psychology. According to data from OpenAlex, STEVE RITTER has authored 139 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 21 papers in Computer Science Applications and 19 papers in Developmental and Educational Psychology. Recurrent topics in STEVE RITTER's work include Intelligent Tutoring Systems and Adaptive Learning (40 papers), Online Learning and Analytics (17 papers) and Innovative Teaching and Learning Methods (17 papers). STEVE RITTER is often cited by papers focused on Intelligent Tutoring Systems and Adaptive Learning (40 papers), Online Learning and Analytics (17 papers) and Innovative Teaching and Learning Methods (17 papers). STEVE RITTER collaborates with scholars based in United States, Germany and Canada. STEVE RITTER's co-authors include Kenneth R. Koedinger, John R. Anderson, Albert T. Corbett, Stephen E. Fancsali, Susan Berman, Michael Yudelson, Stephen B. Blessing, Mitchell J. Nathan, John Stamper and Candace Walkington and has published in prestigious journals such as Journal of Educational Psychology, Psychonomic Bulletin & Review and Cognitive Science.

In The Last Decade

STEVE RITTER

122 papers receiving 993 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
STEVE RITTER United States	16	575	401	342	140	126	139	1.1k
Ralph Gabbard United States	15	49 0.1×	79 0.2×	239 0.7×	9 0.1×	25 0.2×	33	1.2k
Stacey Lowery Bretz United States	35	65 0.1×	91 0.2×	870 2.5×	109 0.8×	6 0.0×	81	3.2k
Peter G. Mahaffy Canada	18	18 0.0×	33 0.1×	124 0.4×	466 3.3×	16 0.1×	51	1.1k
Pilar Martínez-Jiménez Spain	17	34 0.1×	61 0.2×	69 0.2×	9 0.1×	23 0.2×	54	1.0k
Mustafa Sözbi̇li̇r Türkiye	22	25 0.0×	59 0.1×	291 0.9×	24 0.2×	18 0.1×	87	1.7k
Yan Zhu China	21	21 0.0×	44 0.1×	257 0.8×	18 0.1×	28 0.2×	94	1.5k
Stanley G. Smith United States	19	23 0.0×	36 0.1×	71 0.2×	27 0.2×	39 0.3×	72	1.3k
Tak Wai Chan Canada	19	64 0.1×	82 0.2×	188 0.5×	1 0.0×	397 3.2×	76	1.2k
Gábor Kiss Hungary	17	111 0.2×	66 0.2×	54 0.2×	10 0.1×	2 0.0×	130	988

Countries citing papers authored by STEVE RITTER

Since Specialization

Citations

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

Fields of papers citing papers by STEVE RITTER

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of STEVE RITTER

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Norberg, K., et al.. (2024). Rewriting Content with GPT-4 to Support Emerging Readers in Adaptive Mathematics Software. International Journal of Artificial Intelligence in Education. 35(2). 587–626. 5 indexed citations

Fancsali, Stephen E., Michael Yudelson, Susan Berman, & STEVE RITTER. (2018). Intelligent Instructional Hand Offs.. Educational Data Mining. 6 indexed citations

Rus, Vasile, et al.. (2017). An Analysis of Human Tutors' Actions in Tutorial Dialogues.. The Florida AI Research Society. 122–127. 3 indexed citations

Fancsali, Stephen E., et al.. (2016). Implementation Factors and Outcomes for Intelligent Tutoring Systems: A Case Study of Time and Efficiency with Cognitive Tutor Algebra.. The Florida AI Research Society. 473–478. 3 indexed citations

RITTER, STEVE & Stephen E. Fancsali. (2016). MATHia X: The Next Generation Cognitive Tutor.. Educational Data Mining. 624–625. 5 indexed citations

RITTER, STEVE, Michael Yudelson, Stephen E. Fancsali, & Susan Berman. (2016). Towards Integrating Human and Automated Tutoring Systems.. Educational Data Mining. 626–627. 3 indexed citations

RITTER, STEVE. (2015). Plug-in Tutor Agents: Still Pluggin’. International Journal of Artificial Intelligence in Education. 26(1). 405–415. 1 indexed citations

Yudelson, Michael, et al.. (2015). Spectral Bayesian Knowledge Tracing.. Educational Data Mining. 360–363. 4 indexed citations

Fancsali, Stephen E., Matthew L. Bernacki, Timothy J. Nokes‐Malach, Michael Yudelson, & STEVE RITTER. (2014). Goal Orientation, Self-Efficacy, and “Online Measures” in Intelligent Tutoring Systems. Cognitive Science. 36(36). 3 indexed citations

10.

Yudelson, Michael, et al.. (2014). Better Data Beats Big Data.. Educational Data Mining. 205–208. 7 indexed citations

11.

Fancsali, Stephen E., et al.. (2014). Generalizing and Extending a Predictive Model for Standardized Test Scores Based On Cognitive Tutor Interactions. Educational Data Mining. 369–370. 5 indexed citations

12.

Fancsali, Stephen E., et al.. (2013). Optimal and Worst-Case Performance of Mastery Learning Assessment with Bayesian Knowledge Tracing. Educational Data Mining. 35–42. 17 indexed citations

13.

Fancsali, Stephen E., et al.. (2013). Simulated Students, Mastery Learning, and Improved Learning Curves for Real-World Cognitive Tutors.. 8 indexed citations

14.

Fancsali, Stephen E., et al.. (2013). The Complex Dynamics of Aggregate Learning Curves.. Educational Data Mining. 338–339. 6 indexed citations

15.

Lee, Hee Seung, et al.. (2013). Exploring Optimal Conditions of Instructional Guidance in an Algebra Tutor.. Society for Research on Educational Effectiveness. 1 indexed citations

16.

Stamper, John, et al.. (2012). The rise of the super experiment. Educational Data Mining. 2012(1). 196–200. 13 indexed citations

17.

Koedinger, Kenneth R., et al.. (2011). Avoiding Problem Selection Thrashing with Conjunctive Knowledge Tracing.. Educational Data Mining. 91–100. 29 indexed citations

18.

RITTER, STEVE, et al.. (2009). Reducing the Knowledge Tracing Space. Educational Data Mining. 151–160. 37 indexed citations

19.

Blessing, Stephen B., Stephen B. Gilbert, & STEVE RITTER. (2006). Developing an Authoring System for Cognitive Models within Commercial-Quality ITSs. The Florida AI Research Society. 497–502. 5 indexed citations

20.

RITTER, STEVE & Stephen B. Blessing. (1996). A programming-by-demonstration tool for retargeting instructional systems. International Conference of Learning Sciences. 292–299. 1 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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