2025 ASEE Annual Conference & Exposition

WIP: The Design of a Professional Development Program for Petroleum Engineering Educators Towards Integrating Data Analytics and Machine Learning into Petroleum Engineering Curriculum

Presented at DSAI Technical Session 4: Workshops, Professional Development, and Training

The petroleum industry is increasingly embracing digital transformation, enabled by data analytics, machine learning and other data-driven innovations. The proliferation of oilfield data as well as the availability of open-source data mining softwares is opening up career frontiers in petroleum data analytics and machine learning. However, petroleum engineering curricula in academic programs are not keeping pace with these oilfield operational advances, leaving graduates with skill-gaps and unprepared for emerging career opportunities. There is a growing advocacy for curriculum upgrades towards producing graduates combining data analytics skills with petroleum engineering domain knowledge. Recently, a framework for the desired curriculum integration of data analytics and machine learning has been published, but a roadmap for its implementation is yet to be outlined. As the first component of the roadmap, we design a professional development program aiming to empower petroleum engineering educators with knowledge, skills and resources needed to effectively integrate data analytics and machine learning into teaching practices.
This project views the proposed professional development program as an intervention program, and therefore adopts the Theory of Change as a theoretical framework. Specifically, a series of steps is articulated as the causal pathway leading to the desired program impact: industry-ready graduates. Starting with the stated impact, we mapped backward through outcomes (improved teaching practices), outputs (educators’ knowledge and skills), activities (training workshops and mentorship) to inputs (need assessment and curriculum mapping). Key topics addressed include fundamentals and petroleum engineering applications of data analytics and machine learning; Python coding skills; field case-studies; curriculum design and integration strategies; teaching methods and assessment techniques. Recognizing the shortcomings of site-based one-shot or occasional programs, we adopt the online, on-going and intensive delivery approach. Also, the proposed professional development program is designed to be implemented in collaboration with industry professionals under the aegis of the Society of Petroleum Engineers, particularly, its Data Science and Engineering Analytics Technical Section. Additionally, the sustainability of this project is designed around the creation of a community of practice and a repository of shared resources.
It is anticipated that the deliverables of the proposed professional development program will bridge the gap between petroleum engineering academic programs and industry practice. We solicit feedback suggestions on the design presented in this paper.

Authors

Dr. Olatunde Olu Mosobalaje http://orcid.org/0000-0002-0989-3066 Covenant University [biography]

Dr. Olatunde Mosobalaje is a faculty member at the Petroleum Engineering Department of
Covenant University, where he is currently promoting digital innovations in engineering education.
He is a member of the American Society for Engineering Education (ASEE), and the Society of
Petroleum Engineers (SPE). His commitment to knowledge transfer is unmistakable as it manifest
in his ongoing projects aiming at enhancing petroleum engineering curriculum with digital and
data analytics contents. In 2023, he was part of a team that designed and published a module on
introducing Python coding to petroleum engineering undergraduates – an award-winning effort.
Most recently, he played a significant role in a team that developed an integrated framework for
the integration of data analytics and machine learning into the petroleum engineering curriculum.
He recently founded and is coordinating the Petroleum Data Analytics Special Interest Group
(PDA_SIG) of students and young professionals.
In teaching, Dr. Mosobalaje adopts a balanced blend of analogical reasoning, concept
visualization, field application and workflow coding as a pedagogy style. His research interest is in
engineering education, as well as in the deployment of data analytics and machine learning tools to
petroleum engineering applications. In a modest way, his research undertakings have produced
content-assessment-pedagogy alignment of innovative curriculum ideas, and extended the
functionality of some existing geostatistical routines. As a testimonial of his pursuit of excellence
in teaching, he received the Dean’s award as the best teacher in the department. He also received
the Best Paper award in an international conference featuring over 100 authors from 17 countries,
and a bronze medal in another. Notably, Dr. Mosobalaje is currently participating in the 2025 Spring Cohort of the prestigious ‘Empowering-the-Teachers’ (ETT) fellowship, at the Massachusetts
Institute of Technology (MIT).
Dr. Moses Olayemi http://orcid.org/https://0000-0003-1396-280X The University of Oklahoma [biography]

Moses Olayemi is an Assistant Professor of Engineering Pathways at the University of Oklahoma. He is the Founding President of the African Engineering Education Fellows in the Diaspora, a non-governmental organization that leverages the experiences of African scholars in engineering education to inform and support engineering education policy, practice, and pedagogies in Africa. His research revolves around the professional development of STEM educators and researchers in low-resource contexts for which he employs culturally relevant pedagogy and the contextualization and validation of measurement instruments with a keen interest in sub-Saharan Africa.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

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