Inma Borrella, PhD
Research Scientist / Engineer | Academic Lead MIT Center for Transportation & Logistics
MIT Center for Transportation & Logistics
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Biography
Her research focuses on learning analytics and online education, with an emphasis on how digital platforms and emerging technologies can improve learner engagement, feedback, and outcomes at scale. Her work has been published in academic journals and conference proceedings, and she contributes to the MIT Digital Supply Chain Transformation Lab and the MIT Omnichannel in Education Lab.
In addition to her academic work, Inma collaborates with industry partners to translate research into practice and address real-world supply chain challenges through data-driven analysis and education. She earned her PhD in Industrial Engineering from the Technical University of Madrid, where her dissertation examined inclusive business models to advance social sustainability in agri-food supply chains.
Prior to joining MIT in 2017, she was an Assistant Professor at the Technical University of Madrid and completed a predoctoral research stay at Utrecht University.
Research Focus
Human-Centered Systems & Quality of Life
Designing systems, services, and policies that enhance human well-being across work, home, and society.
Intelligent & Autonomous Supply Chains
AI-driven, data-centric, and increasingly autonomous decision systems for supply chain planning and execution.
Areas of Expertise
Education
Universidad Politécnica de Madrid
PhD
Sustainable Supply Chains
2016
Utrecht University
PhD
Sustainable Supply Chains
2014
Universidad Politécnica de Madrid
MEng
Industrial Engineering
2012
Languages
- English
- French
- Spanish
Speaking Engagements/Featured Conversations
Enterprise Analytics: Achieving Supply Chain Visibility at Scale
Watch Dr. Inma Borrella, Academic Lead - MITx MM in SCM, and Mr. Paulo Sousa Jr, Course Lead - SC0x, as they host Arturo Torres Arpi, CEO and Founder of Ventagium Data Consulting. On this live event, you will learn how effective data management and engineering frameworks can unlock large-scale analytics capabilities, enhancing visibility and efficiency in supply chain operations. Watch the full event: https://www.youtube.com/watch?v=trTwMq8YcIQ
Research Papers
Design Principles and Impact of a Learning Analytics Dashboard: Evidence from a Randomized MOOC Experiment
Applied SciencesInma Borrella, Eva Ponce-Cueto
2025-10-28
This study demonstrates that Learning Analytics Dashboards are most effective when designed with actionable, motivationally framed feedback. In practice, MOOC providers and instructional designers can apply these design principles to creating dashboards that foster learner commitment and reduce cognitive burden. Specifically, dashboards should combine clear, low-inference visualizations with concise ARCS-framed feedback and visible pacing cues (e.g., weekly study indicators) to strengthen motivation and support self-regulated learning in online course environments.
Taking action to reduce dropout in MOOCs: Tested interventions
Computers & EducationInma Borrella, Sergio Caballero-Caballero, Eva Ponce-Cueto
2022-04-01
Massive Open Online Courses (MOOCs) have democratized access to higher education, but low entry and exit barriers make dropout rates in these courses much higher than in traditional in-person courses. Previous research has explored the main factors driving student dropout and proposed predictive models to identify students at risk.
Digital supply chain transformation: aligning operations and strategy
Supply Chain Management ReviewMJ Saenz, I Borrella, E Revilla
2022-03-14
Digital transformation is a supply chain imperative. But too many companies take too long to accomplish their goals only to be disappointed by the results. Here, we present a supply chain-based framework that helps companies avoid these common pitfalls.
Awards
Young Researcher Award at the International Conference on Industrial Engineering and Industrial Management
Issued by ADINGOR · Jul 2012
Irwin Sizer Award for the Most Significant Improvement to MIT Education
Issued by Massachusetts Institute of Technology · May 2018
Courses
MIT Kaufman Teaching Certificate Program (KTCP)
(details to be added)
Quantitative Research Methodologies and Statistical Techniques
(details to be added)
