| 2025 | EDM | Evolutionary Features for Mitigating Cold Starts in Logistic Knowledge Tracing. | Philip I. Pavlik Jr., Luke Eglington |
| 2024 | EDM | Integrating Attentional Factors and Spacing in Logistic Knowledge Tracing Models to Explore the Impact of Train-ing Sequences on Category Learning. | Meng Cao, Philip I. Pavlik Jr., Wei Chu, Liang Zhang |
| 2024 | EDM | Logistic Knowledge Tracing Tutorial: Practical Educational Applications. | Philip I. Pavlik Jr., Luke G. Eglington, Meng Cao, Wei Chu |
| 2023 | EDM | The Predictiveness of PFA is Improved by Incorporating the Learner's Correct Response Time Fluctuation. | Wei Chu, Philip I. Pavlik Jr. |
| 2023 | EDM | Automated Search for Logistic Knowledge Tracing Models. | Philip I. Pavlik Jr., Luke G. Eglington |
| 2021 | AIED | The Mobile Fact and Concept Textbook System (MoFaCTS) Computational Model and Scheduling System. | Philip I. Pavlik Jr., Luke G. Eglington |
| 2021 | EDM | Automatic Domain Model Creation and Improvement. | Philip I. Pavlik Jr., Luke Eglington, Liang Zhang |
| 2021 | EDM | The Learner Data Institute - Conceptualization: A Progress Report. | Vasile Rus, Stephen E. Fancsali, Philip I. Pavlik Jr., Deepak Venugopal, Arthur C. Graesser, Steven Ritter, Dale Bowman, The LDI Team |
| 2020 | AIED | The Mobile Fact and Concept Textbook System (MoFaCTS). | Philip I. Pavlik Jr., Andrew McGregor Olney, Amanda Banker, Luke Eglington, Jeffrey Yarbro |
| 2019 | EDM | Incorporating Prior Practice Difficulty into Performance Factor Analysis to Model Mandarin Tone Learning. | Meng Cao, Philip I. Pavlik Jr., Gavin M. Bidelman |
| 2017 | AIED | Improving Reading Comprehension with Automatically Generated Cloze Item Practice. | Andrew McGregor Olney, Philip I. Pavlik Jr., Jaclyn K. Maass |
| 2017 | EDM | Online Learning Persistence and Academic Achievement. | Ying Fang, Benjamin Nye, Philip I. Pavlik Jr., Yonghong Xu, Arthur C. Graesser, Xiangen Hu |
| 2017 | EDM | Sharing and Reusing Data and Analytic Methods with LearnSphere. | Ran Liu, Kenneth R. Koedinger, John C. Stamper, Philip I. Pavlik Jr. |
| 2017 | EDM | Using an Additive Factor Model and Performance Factor Analysis to Assess Learning Gains in a Tutoring System to Help Adults with Reading Difficulties. | Genghu Shi, Philip I. Pavlik Jr., Arthur C. Graesser |
| 2016 | EDM | Modeling the Influence of Format and Depth during Effortful Retrieval Practice. | Jaclyn K. Maass, Philip I. Pavlik Jr. |
| 2016 | ITS | The Mobile Fact and Concept Training System (MoFaCTS). | Philip I. Pavlik Jr., Craig Kelly, Jaclyn K. Maass |
| 2015 | AIED | How Spacing and Variable Retrieval Practice Affect the Learning of Statistics Concepts. | Jaclyn K. Maass, Philip I. Pavlik Jr., Henry Hua |
| 2014 | CogSci | Linguistic Features of Lectures: Offsetting Challenging Words. | Srdan Medimorec, Philip I. Pavlik Jr., Andrew Olney, Arthur C. Graesser, Evan F. Risko |
| 2014 | EDM | Discovering Theoretically Grounded Predictors of Shallow vs. Deep- level Learning. | Carol Forsyth, Arthur C. Graesser, Philip I. Pavlik Jr., Keith K. Millis, Borhan Samei |
| 2013 | AIED | Didactic Galactic: Types of Knowledge Learned in a Serious Game. | Carol Forsyth, Arthur C. Graesser, Breya Walker, Keith K. Millis, Philip I. Pavlik Jr., Diane F. Halpern |
| 2013 | AIED | Using Learner Modeling to Determine Effective Conditions of Learning for Optimal Transfer. | Jaclyn K. Maass, Philip I. Pavlik Jr. |
| 2013 | AIED | Utilizing Concept Mapping in Intelligent Tutoring Systems. | Jaclyn K. Maass, Philip I. Pavlik Jr. |
| 2012 | EDM | Learning Gains for Core Concepts in a Serious Game on Scientific Reasoning. | Carol Forsyth, Philip I. Pavlik Jr., Arthur C. Graesser, Zhiqiang Cai, Mae-Lynn Germany, Keith K. Millis, Heather Butler, Diane F. Halpern, Robert P. Dolan |
| 2012 | ITS | Facilitating Co-adaptation of Technology and Education through the Creation of an Open-Source Repository of Interoperable Code. | Philip I. Pavlik Jr., Jaclyn K. Maass, Vasile Rus, Andrew Olney |
| 2011 | EDM | Avoiding Problem Selection Thrashing with Conjunctive Knowledge Tracing. | Kenneth R. Koedinger, Philip I. Pavlik Jr., John C. Stamper, Tristan Nixon, Steven Ritter |
| 2011 | EDM | A Dynamical System Model of Microgenetic Changes in Performance, Efficacy, Strategy Use and Value during Vocabulary Learning. | Philip I. Pavlik Jr., Sue-mei Wu |
| 2010 | EDM | Data Reduction Methods Applied to Understanding Complex Learning Hypotheses. | Philip I. Pavlik Jr. |
| 2009 | EDM | Learning Factors Transfer Analysis: Using Learning Curve Analysis to Automatically Generate Domain Models. | Philip I. Pavlik Jr., Hao Cen, Kenneth R. Koedinger |