Biography

Joshua Enszer, Ph.D.

Assistant Professor of Instruction in Chemical & Biomolecular Engineering

University of Delaware

Experience

Associate Professor, University of Delaware, 2019-present

Assistant Professor of Instruction, University of Delaware, 2015-2019

Lecturer, University of Maryland Baltimore County, 2011-2015

Visiting Assistant Teaching Professor/Interim Director of First-Year Engineering, University of Notre Dame, 2011

Education

Ph.D., Chemical Engineering, University of Notre Dame, 2010

M.S., Chemical Engineering, University of Notre Dame, 2008

B.S., Chemical Engineering; Mathematics, Michigan Technological University, 2005

Professional Interests

The goal of my research is to develop mechanisms for increasing student engagement in science, technology, engineering, and mathematics (STEM) education. The major components of this work supplement current instructional strategies in undergraduate engineering courses: game-based learning, metacognitive exercises, and electronic portfolios.

Game-based learning (GBL) has been developing since the 1990s as a new way to engage students, teaching using games or game-like environments.The term “serious game” is used to describe a game whose goals are more than pure entertainment: its main purpose is to provide an environment for training or learning. In recent years, the New Media Consortium and the EDUCAUSE Learning Initiative’s annual Horizon Report has listed “Massively Multiplayer Educational Gaming” and "Game-Based Learning" as technologies to look for in the coming years. While the challenges of effectively implementing educational games are considerable, the technological resources are available, making this area ripe for research. On a smaller scale, "gamification," or the implementation of parts of games in the classroom, has been shown to increase student engagement and attitudes toward learning.

Metacognition, or thinking about thinking, is known to improve learning ability. By providing exercises for students to think about how they learn and what they are learning, it is expected that we can demonstrate gains in student learning. The "SPIT" (Summarize, Personalize, Integrate, Thoughtful Puzzle) approach common to the humanities can be slightly modified to STEM contexts to have students not simply solve problems, but connect concepts, skills, and strategies to their personal lives, integrate their coursework, and think of related applications and problems.

A portfolio has long been a staple of programs in architecture and education, but it is starting to gain traction in disciplines like engineering. In addition to being a convenient format for presenting a variety of related work, implementing portfolios in engineering courses provides opportunities for students to obtain a deeper and more serious ownership of their own abilities and knowledge. Portfolios address all three aspects of courses designed with significant learning in mind: learning goals including human interaction, application, and development of lifelong learning skills; learning activities related to experiences and reflection; and feedback in terms of self- and peer-assessment (an excellent discussion of this is given by L. Dee Fink in his book Creating Significant Learning Experiences). I am investigating the implementation of electronic portfolios inside and outside the classroom.

Courses

University of Notre Dame

Introduction to Engineering Systems I (EG 10111/11111), F09/F10

Introduction to Engineering Systems II (EG EG 10112/11112), Sp09/Sp11

Chemical and Biomolecular Engineering Analysis (CBE 20255/22255), F09/F10

Computational Methods for Chemical Engineers (CBE 20258), Sp08/Sp11

Chemical Process Control (CBE 30338), Sp11

Modeling the Earth's Systems: Dynamics in Ecology and the Environment (CBE 40472/60572), Sp08/Sp09

University of Maryland Baltimore County

Chemical Engineering Analysis (ENCH 215), F11/Su13/Su14/Su15

Chemical Engineering Laboratory (ENCH 437L), F11 (co-taught)

Chemical Engineering Problem Solving and Experimental Design (ENCH 225), Sp12/Sp13/F13/Sp14/F14/Sp15

Process Engineering Economics and Design II (ENCH 446), Sp12/Sp14/Sp15 (team-taught all terms)

Introduction to Engineering Science (ENES 101), F12

Chemical and Environmental Modeling (ENCH 470/654), F12/F13/F14/Su15

Chemical Engineering Systems Analysis (ENCH 442), Sp13

Transport I: Fluids (ENCH 425), F13

Chemical Process Control and Safety (new name/description for ENCH 442), Sp14/Sp15

Chemical Engineering Systems Analysis (ENCH 642), Sp15

University of Delaware

Chemical Engineering Thermodynamics I (CHEG 231), F15/16 (co-taught)

Chemical Processing Design I (CHEG 431), F15/16/17 (co-taught)

Introduction to Chemical Engineering (CHEG 112), Sp16/17/18 (co-taught)

Random Variability in Chemical Processes (CHEG 304), Sp16/17/18 (co-taught)

Chemical Engineering Laboratory I (CHEG 345), Sp16 (back-up) Sp17/18 (coordinator)

Chemical Engineering Laboratory II (CHEG 445), F16/17 (coordinator)

Introduction to Engineering (EGGG 101), F17 (co-taught)

Selected Publications

C. A. Bodnar, D. Anastasio, J. A. Enszer, and D. D. Burkey. “Engineers at Play: Games as Teaching Tools for Undergraduate Engineering Students.” J Eng Educ. 105: pp. 147-200 (2016).

J. A. Enszer, D. A. Măceş, and M.A. Stadtherr. “Probability Bounds Analysis for Nonlinear Population Ecology Models.” Math Biosci. 267: pp. 97-108 (2015).

J. A. Enszer, V. E. Goodrich, and R. B. Getman. "Improvements in Computational Methods Courses in Chemical Engineering." Proceedings from the 2012 ASEE Annual Conference and Exposition, San Antonio, TX (2012).

J. A. Enszer, J. A. Kuczenski, K. L. Meyers, J. B. Brockman, and M. J. McCready. "Electronic Portfolios in Academic Advising, Self-Guided Learning, and Self-Assessment." Proceedings from the 2011 ASEE Annual Conference and Exposition, Vancouver, Canada (2011).

J. A. Enszer, Y. Lin, S. Ferson, G. F. Corliss, and M. A. Stadtherr. “Probability Bounds Analysis for Nonlinear Dynamic Process Models.” AIChE J. 57: pp.404-422 (2011).

J. A. Enszer and M. A. Stadtherr, “Verified Solution and Propagation of Uncertainty in Physiological Models.” Reliab Comput. 15: pp. 168-178 (2011).

J. A. Enszer and M. A. Stadtherr, “Verified Solution Method for Population Epidemiology Models with Uncertainty.” Int. J. Appl. Math. Comput. Sci. 19: pp. 501-512 (2009).