hero image
Marsha Lovett - Carnegie Mellon University. Pittsburgh, PA, US

Marsha Lovett

Teaching Professor and Vice Provost | Carnegie Mellon University


Marsha Lovett's research considers how learning works (mostly in college-level courses) and ways to improve it.


Marsha Lovett's research considers how learning works (mostly in college-level courses) and ways to improve it. She has used various methodologies in her work, including A/B testing, computational modeling, protocol analysis, laboratory experiments and classroom studies. She has developed several innovative, educational technologies to promote student learning and metacognition, including StatTutor (an intelligent tutoring system for statistics) and the Learning Dashboard (a learning analytics system that promotes adaptive teaching and learning in online instruction). At the Eberly Center, Lovett leads a team of teaching consultants, learning engineers, designers, data scientists and technologists to help instructors create meaningful and demonstrably effective educational experiences – both in-person and online. A signature of this work is research-based design combined with data-informed refinement.

Areas of Expertise (8)

Higher Education

Classroom Studies

Computational Modeling

Machine Learning

Protocol Analysis

Educational Technologies


Learning Dashboard



Marsha Lovett Publication




#96: Marsha Lovett — Author of “How Learning Works: 8 Research Based Principles of Smart Teaching” What is Learning Science from an Educator's Perspective? Learning Engineering in Action



Industry Expertise (1)


Education (3)

Carnegie Mellon University: Ph.D., Cognitive Psychology

Carnegie Mellon University: M.S., Cognitive Psychology

Princeton University: B.A., Cognitive Science

Articles (5)

Nightly sleep duration predicts grade point average in the first year of college

Proceedings of the National Academy of Sciences

2023 Academic achievement in the first year of college is critical for setting students on a pathway toward long-term academic and life success, yet little is known about the factors that shape early college academic achievement. Given the important role sleep plays in learning and memory, here we extend this work to evaluate whether nightly sleep duration predicts change in end-of-semester grade point average (GPA). First-year college students from three independent universities provided sleep actigraphy for a month early in their winter/spring academic term across five studies. Findings showed that greater early-term total nightly sleep duration predicted higher end-of-term GPA, an effect that persisted even after controlling for previous-term GPA and daytime sleep. Specifically, every additional hour of average nightly sleep duration early in the semester was associated with an 0.07 increase in end-of-term GPA. Sensitivity analyses using sleep thresholds also indicated that sleeping less than 6 h each night was a period where sleep shifted from helpful to harmful for end-of-term GPA, relative to previous-term GPA.

view more

Distinguishing Two Types of Prior Knowledge That Support Novice Learners


2019 Prior knowledge has long been recognized as an important predictor of learning, yet the term prior knowledge is often applied to related but distinct constructs. We define a specific form of prior knowledge, ancillary knowledge, as knowledge of concepts and skills that enable learners to gain the most from a target lesson. Ancillary knowledge is not prior knowledge of the lesson's target concepts and skills, and may even fall outside the domain of the lesson. Nevertheless, ancillary knowledge affects learning of the lesson, e.g., lower ancillary knowledge can hinder performance on lesson-related tasks. We measured ancillary knowledge, prior knowledge of the domain, and controlled for general ability, and found that (a) stronger ancillary knowledge and general ability predicted better performance on transfer tasks, but (b) prior knowledge of the domain did not. This research suggests that enhancing instruction by remediating gaps in ancillary knowledge may improve learning in introductory-level courses.

view more

Improving Student-Driven Feedback and Engagement in the Classroom: Evaluating the Effectiveness of the Speed Dating Model

ACM SIGMIS Conference

2018 Information Systems (IS) pedagogy research supports the use of collaborative learning strategies that are based on the belief that learning increases when students work together to solve problems and develop cooperative learning skills. The use of innovative active learning approaches instead of lecture-based approaches have helped to engage student learning and build a broader range of skills and experiences (e.g., [1, 2]). In this project, we present an empirical comparison of two active learning classroom approaches - the speed dating method and a traditional presentation format. The speed dating method supports low-cost rapid comparison of project ideas, design, application and progress in a structured and bounded series of serial engagements. In contrast, traditional student presentations allow individuals to provide content but offer somewhat limited interactions. We analyzed data from 174 student surveys and in-class researcher observations of student engagement in an undergraduate senior capstone course entitled, Innovation in Information Systems.

view more

Multimedia learning principles at scale predict quiz performance

Conference: the Fifth Annual ACM Conference

2018 Empirically supported multimedia learning (MML) principles [1] suggest effective ways to design instruction, generally for elements on the order of a graphic or an activity. We examined whether the positive impact of MML could be detected in larger instructional units from a MOOC. We coded instructional design (ID) features corresponding to MML principles, mapped quiz items to these features and their use by MOOC participants, and attempted to predict quiz performance. We found that instructional features related to MML, namely practice problems with high-quality examples and text that is concisely written, were positively predictive. We argue it is possible to predict quiz item performance from features of the instructional materials and suggest ways to extend this method to additional aspects of the ID.

view more

Supporting Technical Professionals’ Metacognitive Development in Technical Communication through Contrasting Rhetorical Problem Solving

Technical Communication Quarterly

2016 This article presents an experimental pedagogical framework for providing technical professionals with practice on writing skills focusing on the development of their metacognitive rhetorical awareness. The paper outlines the theoretical foundation that led to the development of the framework, followed by a report of a pilot study involving IT professionals in a global setting using an online learning environment that was designed based on the framework.

view more