Mis investigaciones

in press

Deep learning for educational data science Pinto, J. D. & Paquette, L. Trust and Inclusion in AI-Mediated Education: Where Human Learning Meets Learning Machines . Springer International Publishing. [PDF] [arXiv] [book chapter]

Applications of explainable AI (XAI) in education Liu, Q., Pinto, J. D., & Paquette, L. Trust and Inclusion in AI-Mediated Education: Where Human Learning Meets Learning Machines . Springer International Publishing. [book chapter]

Intrinsically interpretable artificial neural networks for learner modeling Pinto, J. D., Paquette, L., & Bosch, N. Educational Data Mining [doctoral consortium]

2024

The imperative of explainability: Increasing transparency in educational AI Pinto, J. D. & Liu, Q. UIUC College of Education Graduate Student Conference [poster]

2023

Using problem similarity- and order-based weighting to model learner performance in introductory computer science problems Zhang, Y., Pinto, J. D., Fan, A., & Paquette, L. Journal of Educational Data Mining , 15(1), 63–99 [DOI] [PDF]

Utilizing programming traces to explore and model the dimensions of novices’ code writing skill Zhang, Y., Paquette, L., Pinto, J. D., & Fan, A. Computer Applications in Engineering Education [DOI] [PDF]

Trustworthy AI requires algorithmic interpretability: Some takeaways from recent uses of eXplainable AI (XAI) in education Pinto, J. D. & Liu, Q. Trustworthy AI Lab for Education Summit [poster] [best poster]

Investigating the relationship between programming experience and debugging behaviors in an introductory computer science course Pinto, J. D., Liu, Q., Paquette, L., Zhang, Y., & Fan, A. International Conference on Quantitative Ethnography 2023 [PDF] [nominated for best student paper]

Intelligent tutors, cultural blind spots: Implications of underrepresentation in adaptive learning research Pinto, J. D. International Society of the Learning Sciences Annual Meeting (ISLS 2023) [PDF] [poster]

Interpretable neural networks vs. expert-defined models for learner behavior detection Pinto, J. D., Paquette, L., & Bosch, N. The 13th International Learning Analytics and Knowledge Conference (LAK) [PDF] [poster]

Using problem similarity- and order-based weighting to model learner performance in introductory computer science problems Zhang, Y., Pinto, J. D., Fan, A., & Paquette, L. Educational Data Mining in Computer Science Education (CSEDM) Workshop [slides] [workshop paper]

2022

Combining latent profile analysis and programming traces to understand novices’ differences in debugging Zhang, Y., Paquette, L., Pinto, J. D., Liu, Q., & Fan, A. X. Education and Information Technologies [DOI] [PDF]

Artificial intelligence for equitable global education: A call for more representative adaptive learning research and design practices in low- and middle-income countries Pinto, J. D. 2022 Learning Sciences Graduate Student Conference (LSGSC) [poster]

Utilizing programming traces to explore the dimensions of novice programmers' code writing skill Zhang, Y., Paquette, L., Pinto, J. D., & Fan, A. Educational Data Mining in Computer Science Education (CSEDM) Workshop [DOI] [workshop paper]

2021

What We Learned When We Compared Discussion Posts from One MOOC Hosted on Two Platforms Quintana, R. M., Pinto, J. D., & Tan, Y. Online Learning Journal , 25(4), 101–118 [DOI] [PDF]

Investigating elements of student persistence in an introductory computer science course Pinto, J. D., Zhang, Y., Paquette, L., & Fan, A. X. 2021 Educational Data Mining in Computer Science Education (CSEDM) Workshop [PDF] [workshop paper]

Exploring how learners integrate personally meaningful issues in a project-based MOOC Pinto, J. D., Quintana, C., & Quintana, R. M. 2021 American Educational Research Association (AERA) Annual Meeting [PDF]

What we learned when we compared discussion posts from one mooc hosted on two platforms Quintana, R. M., Pinto, J. D., & Tan, Y. 2021 American Educational Research Association (AERA) Annual Meeting [PDF]

2020

Exemplifying Computational Thinking Scenarios in the Age of COVID-19: Examining the Pandemic’s Effects in a Project-Based MOOC Pinto, J. D., Quintana, C., & Quintana, R. M. Computing in Science & Engineering , 22(6), 97–102 [DOI] [PDF]

Personalizing digital learning environments Pinto, J. D. Research Evaluation and Action Plan (REAP) Symposium

Using data to inform learning experience design Pinto, J. D. Academic Innovation 2020 Student Showcase

The role students should play in the design, collection, and analysis of learning analytics Pinto, J. D. Academic Innovation Data Showcase [panel participant]

2018

Language learning for the 21st century: Interpersonal communication through digital communities Pinto, J. D. Texas Language Center: "Language Matters!" Lecture Series [video] [invited lecture]

Creating a conversational Hebrew vocabulary list: A reproducible use of technology to overcome scarcity of data Pinto, J. D. National Council of Less Commonly Taught Languages (NCOLCTL) 21st Annual Conference

Transitional semi-allophonic spirantization in Tiberian Hebrew Pinto, J. D. Jil Jadid Graduate Student Conference in Middle Eastern Languages and Literatures