Courses

Theories of Development and Engineering Thinking

This course is a foundational course in engineering education research. It will delve into the learning theorists and classical research that has shaped the fields of mathematics, science, and engineering education. Students will read original work of the theorists and classical and contemporary research studies that have shaped current ideas about engineering learning and thinking. The focus of the course will be to develop theoretical frameworks related to engineering thinking and to answering the questions: (1) How does learning occur? (2) Which factors influence learning? (3) What is the role of memory? (4) How does transfer occur? (5) How should instruction occur to facilitate learning? It is helpful for students to have engaged in prior reading-and writing- intensive courses that required them to synthesize large amounts of information. For this reason, it is recommended that students are enrolled currently in a graduate program at Purdue University.

Content Assessment and Pedagogy: An Integrated Engineering Design Approach

Content, Assessment and Pedagogy is designed to help participants build a foundation of knowledge, skills, and habits of mind or modes of thinking that facilitate the alignment of content, assessment, and pedagogy for curriculum design. Rather than treat each of these areas separately, we strive to help the participants consider all three together in a systematic way. Our approach is essentially an engineering design approach, that is, we start with requirements or specifications, emphasize metrics, and then focus on the preparation of prototypes that meet the requirements. The course provides a community of practice culture in which students have opportunities to form their own intellectual neighborhood as well as participate within the broader community of engineering education via engagement in our practices, methods, and beliefs.

Educational Methods in Engineering

Each week, students must login for one hour via WebEx for LIVE participation in the class.

Mentored Teaching in Engineering

This course enables graduate students enrolled in any engineering program to deepen their understanding of college teaching and learning through a semester-long teaching experience with mentoring, feedback, and reflection. Most course topics complement topics in the prerequisite courses. The mentoring component could be structured to meet a requirement for the Certificate of Practice in College Teaching (CPCT) offered by the campus???s Center for Instructional Excellence. This course fulfills a requirement of the Teaching & Learning in Engineering graduate certificate program.

Seminar in Engineering Education

Through presentations on current topics in engineering education and related subjects, this seminar strives to build an intellectual community by forging connections within the School of Engineering Education (ENE), between ENE and the other schools in the College of Engineering, with colleagues who conduct STEM education research across the campus, and with other engineering education researchers across the U.S. Speakers may come from the campus, from other universities, or from business, industry, or government. The seminar is open to the entire Purdue community. This seminar is required for doctoral students in ENE. Each student must register for two semesters of the seminar, but students may register repeatedly in multiple semesters, without limit. This zero-credit course is graded pass/fail based on participation. Weekly seminar sessions are recorded and posted to the course Blackboard site. Students taking the course online are expected to watch a posted session, write a summary of and reflection on the presentation, and submit that document to the instructor via Blackboard. The summary and reflection should be at least 500-1000 words with an emphasis on content and quality of the writing rather than length. Guidelines for the document will be provided in the syllabus. Students must submit documents for seven of the seminar presentations to receive a grade of "pass".

Succeeding as an Engineering Professor

This course is one of four required for a graduate certificate in Teaching and Learning Engineering. The other three courses are devoted to educational methods and practice. This course is designed provide students with an opportunity to learn and practice the skills that complement and enhance teaching and learning in a tenure-track faculty position at either a research intensive university or at an institution that focuses on undergraduate engineering education. Teaching a course is only one aspect of helping students to learn. Obtaining funding for research, mentoring graduate and advanced undergraduate students, and building a network that continually provides new information related to doing the job well all contribute to a faculty member's ability to help students learn.

Program Management: A Comprehensive Overview of the Discipline

Through lectures, videos, interactive group discussion, and applied exercises, participants gain comprehensive breadth of understanding of program and project management--specifically, the multiple interrelated activities and attendant products that compose the program and project management process. Participants learn how to adequately define the requirements for a program; allocate and schedule the work; manage unanticipated risks; and monitor cost, schedule, and performance to the planned baseline. Qualitative aspects of the process focus on how to choose an organizational structure that best fits the organization, how to motivate program personnel, and how to increase the efficiency of the multiple generations at work within the program. Course materials are designed both for effective learning during the course and for future follow-up reference.

Quality Control

** This is the same course as STAT51300 Statistical Quality Control ** The course will comprise a balanced blend of the statistical quality control concepts and hands-on training in the methods, standards and guidelines currently being used for industrial quality control. The course will not assume any prior knowledge other than previous exposure to elementary probability theory; the discussion will be self-contained and all of the topics will be developed from the fundamentals. The course will enable a practising engineer to gain a firm grasp of statistical quality control methods and enable him/her to not only analyze and improve existing quality control processes, but also design and implement new quality control processes in industrial settings.

Industrial Applications of Statistics

Design of experiments and analysis of experimental results are covered in depth. These include Single-factor, Factorial, Nested, Latin-square, 2 to the f, Incomplete block, Fractional factorial, response surface, and Taguchi designs. Depending on the context, an appropriate design can be chosen in order to minimize the costs for the experiment while gathering sufficient data to achieve undiscovered knowledge. This course will be application-oriented.

Linear Programming

Linear programming (LP) problems arise pervasively in science and engineering. The students will obtain a broad exposure to the theoretical underpinnings of linear optimization, as well as to the algorithms for solving LP problems. Prior exposure to optimization is not necessary; however, good knowledge of linear and matrix algebra is strongly desired.

Stochastic Models In Operations Research I

An introduction to techniques for modeling random processes used in operations research - Markov chains, continuous time Markov processes, Markovian queues, Martingales, Optimal Stopping/Optional Stopping Theorem, Brownian Motion, Option Pricing.

Engineering Economic Analysis

Students who have already taken an intermediate microeconomics course may find parts of this course repetitive. The course will cover the following topics: mathematics of optimization, consumer choice and demand theory, demand estimation, production and the theory of the firm, an introduction to cost accounting, and market structures.

Economic Decisions in Engineering

Classical decision theory, deterministic decision rules, decision trees, influence diagrams, single/multiple stage analysis, sensitivity analysis; subjective probability, heuristics and biases, Bayesian methods, conjugate belief forms, inference, belief assessment methods, value of information, risk analysis; utility theory, risk aversion, conflicting objectives, multi-attribute decision theory, analytic hierarchy process.

Safety Engineering

Application of human factors (ergonomics) and engineering practice in accident prevention and the reduction of health hazards in the occupational environment are presented. Special attention is devoted to the detection and correction of hazards and to contemporary laws and enforcement on occupational safety and health.

Production Management Control

Manufacturing Process Engineering

Theories and applications of materials forming and removal processes in manufacturing, including product properties, process capabilities, processing equipment design, and economics. A systems approach to all aspects of manufacturing process engineering.

Industrial Robotics & Flexible Assembly

We will learn about the use of automation and robotics in industry with an emphasis on current applications. We will learn some fundamentals of robotic configuration and kinematic chains, trajectory planning, sensors and safety in the context of robot operation in the industrial setting. All classes will be complemented with simulation software acting as lab supplements. In the simulation environment, the students will program the robots and sensors using scripting language. A highlight of this year's class is the introduction of Artificial Intelligence as part of robotics learning models.

Human Factors in Engineering

The course provides a survey of Human Factors and Ergonomics with particular reference human-systems integration and human functions in human-machine systems. We consider basic human capabilities and the ways that these capabilities are taken into account in the design of human-machine systems and work environments.

Applied Ergonomics

Upon completion of this course, students will be able to perform specific types of ergonomic analyses as well as design jobs and systems consistent with human factors engineering principles. Based on a survey at the beginning of the course, some topics may be changed if there is specific demand.

Design and Control of Production and Manufacturing Systems

To achieve cost-effective, sustainable production/mfg/service systems, a thorough understanding of production system operations and flow is essential. This course focuses on the fundamental understanding of the factors affecting operational performance of production systems. We develop this understanding by discussing the basic models and techniques of inventory control, queuing analysis, job scheduling, and supply networks, and their role in the context of analytics and informatics (A&I).