An ACT-R Model of Memory Applied to Finding the Optimal Schedule of Practice. - Philip I. Pavlik Jr.; John R. Anderson (ICCM, 2004)

Practice and Forgetting Effects on Vocabulary Memory: An Activation-Based Model of the Spacing Effect. - Philip I. Pavlik Jr.; John R. Anderson (Cogn. Sci., 2005)

Using Item-type Performance Covariance to Improve the Skill Model of an Existing Tutor. - Philip I. Pavlik; Hao Cen; Lili Wu; Kenneth R. Koedinger (EDM, 2008)

Using Optimally Selected Drill Practice to Train Basic Facts. - Philip I. Pavlik; Thomas Bolster; Sue-mei Wu; Kenneth R. Koedinger; Brian MacWhinney (Intelligent Tutoring Systems, 2008)

Performance Factors Analysis - A New Alternative to Knowledge Tracing. - Philip I. Pavlik; Hao Cen; Kenneth R. Koedinger (AIED, 2009)

Learning Factors Transfer Analysis: Using Learning Curve Analysis to Automatically Generate Domain Models. - Philip I. Pavlik Jr.; Hao Cen; Kenneth R. Koedinger (EDM, 2009)

Data Reduction Methods Applied to Understanding Complex Learning Hypotheses. - Philip I. Pavlik Jr. (EDM, 2010)

How to Build Bridges between Intelligent Tutoring System Subfields of Research. - Philip I. Pavlik; Joe Toth (Intelligent Tutoring Systems (2), 2010)

Using Contextual Factors Analysis to Explain Transfer of Least Common Multiple Skills. - Philip I. Pavlik; Michael Yudelson; Kenneth R. Koedinger (AIED, 2011)

Avoiding Problem Selection Thrashing with Conjunctive Knowledge Tracing. - Kenneth R. Koedinger; Philip I. Pavlik Jr.; John C. Stamper; Tristan Nixon; Steven Ritter 001 (EDM, 2011)

A Dynamical System Model of Microgenetic Changes in Performance, Efficacy, Strategy Use and Value during Vocabulary Learning. - Philip I. Pavlik Jr.; Sue-mei Wu (EDM, 2011)

Towards Better Understanding of Transfer in Cognitive Models of Practice. - Michael Yudelson; Philip I. Pavlik; Kenneth R. Koedinger (EDM, 2011)

User Modeling - A Notoriously Black Art. - Michael Yudelson; Philip I. Pavlik; Kenneth R. Koedinger (UMAP, 2011)

Learning Gains for Core Concepts in a Serious Game on Scientific Reasoning. - Carol Forsyth; Philip I. Pavlik Jr.; Arthur C. Graesser; Zhiqiang Cai 002; Mae-Lynn Germany; Keith K. Millis; Heather Butler; Diane F. Halpern; Robert P. Dolan (EDM, 2012)

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 (ITS, 2012)

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 (AIED, 2013)

Using Learner Modeling to Determine Effective Conditions of Learning for Optimal Transfer. - Jaclyn K. Maass; Philip I. Pavlik Jr. (AIED, 2013)

Utilizing Concept Mapping in Intelligent Tutoring Systems. - Jaclyn K. Maass; Philip I. Pavlik Jr. (AIED, 2013)

Modeling and Optimizing Forgetting and Spacing Effects during Musical Interval Training. - Philip I. Pavlik; Henry Hua; Jamal Williams; Gavin M. Bidelman (EDM, 2013)

iMinerva: A Mathematical Model of Distributional Statistical Learning. - Erik D. Thiessen; Philip I. Pavlik Jr. (Cogn. Sci., 2013)

Linguistic Features of Lectures: Offsetting Challenging Words. - Srdan Medimorec; Philip I. Pavlik Jr.; Andrew Olney; Arthur C. Graesser; Evan F. Risko (CogSci, 2014)

Discovering Theoretically Grounded Predictors of Shallow vs. Deep- level Learning. - Carol Forsyth; Arthur C. Graesser; Philip I. Pavlik Jr.; Keith K. Millis; Borhan Samei (EDM, 2014)

Predicting Performance Behaviors during Question Generation in a Game-Like Intelligent Tutoring System. - Carol Forsyth; Arthur C. Graesser; Borhan Samei; Breya Walker; Philip I. Pavlik (ICLS, 2014)

How Spacing and Variable Retrieval Practice Affect the Learning of Statistics Concepts. - Jaclyn K. Maass; Philip I. Pavlik Jr.; Henry Hua (AIED, 2015)

Evaluating the Effectiveness of Integrating Natural Language Tutoring into an Existing Adaptive Learning System. - Benjamin D. Nye; Alistair Windsor; Philip I. Pavlik; Andrew Olney; Mustafa H. Hajeer; Arthur C. Graesser; Xiangen Hu (AIED, 2015)

A Measurement Model of Microgenetic Transfer for Improving Instructional Outcomes. - Philip I. Pavlik; Michael Yudelson; Kenneth R. Koedinger (Int. J. Artif. Intell. Educ., 2015)

Modeling the Influence of Format and Depth during Effortful Retrieval Practice. - Jaclyn K. Maass; Philip I. Pavlik Jr. (EDM, 2016)

The Mobile Fact and Concept Training System (MoFaCTS). - Philip I. Pavlik Jr.; Craig Kelly; Jaclyn K. Maass (ITS, 2016)

Testing Theories of Transfer Using Error Rate Learning Curves. - Kenneth R. Koedinger; Michael Yudelson; Philip I. Pavlik Jr. (Top. Cogn. Sci., 2016)

Improving Reading Comprehension with Automatically Generated Cloze Item Practice. - Andrew McGregor Olney; Philip I. Pavlik Jr.; Jaclyn K. Maass (AIED, 2017)

Online Learning Persistence and Academic Achievement. - Ying Fang; Benjamin Nye; Philip I. Pavlik Jr.; Yonghong Xu; Arthur C. Graesser; Xiangen Hu (EDM, 2017)

Sharing and Reusing Data and Analytic Methods with LearnSphere. - Ran Liu 008; Kenneth R. Koedinger; John C. Stamper; Philip I. Pavlik Jr. (EDM, 2017)

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 (EDM, 2017)

Community based educational data repositories and analysis tools. - Ken Koedinger; Ran Liu 008; John C. Stamper; Candace Thille; Phil Pavlik (LAK, 2017)

Mitigating Knowledge Decay from Instruction with Voluntary Use of an Adaptive Learning System. - Andrew J. Hampton; Benjamin D. Nye; Philip I. Pavlik; William R. Swartout; Arthur C. Graesser; Joseph Gunderson (AIED (2), 2018)

Clustering the Learning Patterns of Adults with Low Literacy Skills Interacting with an Intelligent Tutoring System. - Ying Fang; Keith T. Shubeck; Anne Lippert; Qinyu Cheng; Genghu Shi; Shi Feng; Jessica Gatewood; Su Chen; Zhiqiang Cai 002; Philip I. Pavlik; Jan C. Frijters; Daphne Greenberg; et al. (EDM, 2018)

Incorporating Prior Practice Difficulty into Performance Factor Analysis to Model Mandarin Tone Learning. - Meng Cao; Philip I. Pavlik Jr.; Gavin M. Bidelman (EDM, 2019)

The Mobile Fact and Concept Textbook System (MoFaCTS). - Philip I. Pavlik Jr.; Andrew McGregor Olney; Amanda Banker; Luke Eglington; Jeffrey Yarbro (iTextbooks@AIED, 2020)

The Mobile Fact and Concept Textbook System (MoFaCTS) Computational Model and Scheduling System. - Philip I. Pavlik Jr.; Luke G. Eglington (iTextbooks@AIED, 2021)

Automatic Domain Model Creation and Improvement. - Philip I. Pavlik Jr.; Luke Eglington; Liang Zhang (EDM, 2021)

The Learner Data Institute - Conceptualization: A Progress Report. - Vasile Rus; Stephen E. Fancsali; Philip I. Pavlik Jr.; Deepak Venugopal; Arthur C. Graesser; Steven Ritter 001; Dale Bowman; The LDI Team (EDM (Workshops), 2021)

Modeling the EdNet Dataset with Logistic Regression. - Philip I. Pavlik Jr.; Luke G. Eglington (CoRR, 2021)

Logistic Knowledge Tracing: A Constrained Framework for Learner Modeling. - Philip I. Pavlik; Luke G. Eglington; Leigh M. Harrell-Williams (IEEE Trans. Learn. Technol., 2021)

A Variant of Performance Factors Analysis Model for Categorization. - Meng Cao; Philip I. Pavlik (EDM, 2022)

The Predictiveness of PFA is Improved by Incorporating the Learner's Correct Response Time Fluctuation. - Wei Chu; Philip I. Pavlik Jr. (EDM, 2023)

Automated Search for Logistic Knowledge Tracing Models. - Philip I. Pavlik Jr.; Luke G. Eglington (EDM, 2023)

Exploring the Individual Differences in Multidimensional Evolution of Knowledge States of Learners. - Liang Zhang; Philip I. Pavlik; Xiangen Hu; Jody L. Cockroft; Lijia Wang; Genghu Shi (HCI (34), 2023)

How to Optimize Student Learning Using Student Models That Adapt Rapidly to Individual Differences. - Luke G. Eglington; Philip I. Pavlik (Int. J. Artif. Intell. Educ., 2023)

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 (EDM, 2024)

Logistic Knowledge Tracing Tutorial: Practical Educational Applications. - Philip I. Pavlik Jr.; Luke G. Eglington; Meng Cao; Wei Chu (EDM, 2024)

Integrating Attentional Factors and Spacing in Logistic Knowledge Tracing Models to Explore the Impact of Training Sequences on Category Learning. - Meng Cao; Philip I. Pavlik Jr.; Wei Chu; Liang Zhang (CoRR, 2024)

Evolutionary Features for Mitigating Cold Starts in Logistic Knowledge Tracing. - Philip I. Pavlik Jr.; Luke Eglington (EDM, 2025)