The ML-PBL curriculum is among the best-researched school curricula in terms of design, implementation, and impacts on student learning and other outcomes. Research briefs, as well as the full article text, are available here, along with information on upcoming books, and the complete Technical Report on our efficacy study.


ML-PBL LogoML-PBL Curriculum Research Technical Report

A comprehensive research report on the ML-PBL curriculum, including details and results from a large-scale randomized control trial that examined the impacts of the ML-PBL approach on student learning compared with comparable schools on state-level test items.  

Designing for Play in Classrooms

A research study in the Journal of Leadership, Equity, and Research that describes integrating student play in project-based science units to enhance kindergarteners' understanding and ability to apply knowledge.

Literacy Development and Modeling Proficiency

An investigation into the relationship between teachers' support of literacy development during science and their students' proficiency in scientific modeling during project-based units.  Published in the international journal Education 3-13.

Motivating Teaching and Sustaining Change

Published in the Journal of Science Teacher Education, this article examines the design features and design principles that both curriculum authors and teachers use to build engaging project-based learning environments and build both students' science knowledge and their social and emotional learning.

Promoting Deep Learning

This piece in the journal Disciplinary and Interdisciplinary Science Education Research examines how the ML-PBL curriculum employed coherence, depth, and motivation to build students' knowledge-in-use through a project-based approach.

Supporting Equity in Virtual Instruction during COVID-19

Responding to the challenges of virtual instruction during COVID-19, this research examined how teachers' modified the ML-PBL projects for virtual environments to support all students, with assistance from the ML-PBL design and professional learning team.  Published in the ​​​​​​​Journal of Science Teacher Education.