Robert (B.J.) Johnson

Clinical Associate Professor of Computer Science

  • Los Angeles CA UNITED STATES
  • Computer Science

Seaver College of Science and Engineering

Contact

Biography

Contact:
Phone: 310.338.1938
Email: rjohns19@lmu.edu; robert.johnson@lmu.edu
Office: Doolan 220

Robert (B.J.) Johnson earned his B.S. and M.S. in Computer Science from LMU in 2002 and 2005, respectively, and his PhD in Information Systems and Technology from Claremont Graduate University in 2018. He has been a part-time instructor at LMU since fall semester, 2005, and moved to full-time after retiring from Boeing Satellite Systems in 2017. Dr. Johnson worked in the aerospace industry for over 36 years as a programmer, analyst, and software engineer/architect, for Boeing Satellite Systems, Raytheon Company, GM/Delco, and Hughes Aircraft Company. In that career he has primarily focused on satellite control and telemetry systems, and on computer-automated spacecraft testing systems. He co-authored “Applying the Rapid Application Development Process to Satellite Payload Test Software” with Albert Lin of Boeing, and is currently working on a publication for the Journal of Computers and Education. B.J. is a member of the Tau Beta Pi and Sigma Alpha Nu honor societies, and served as former Chair and Vice-chair of the Los Angeles chapter of the ACM. His research interests include adult learning, contrasting virtual world learning with traditional PowerPoint methods, and tailoring learning to different preferred learning styles. B.J. is also very interested in software engineering, robotics, AI, machine learning, database applications, and engineering ethics.

Education

Claremont Graduate University

Ph.D.

Information Systems and Technology

2018

Loyola Marymount University

MSCS

Computer Science

2005

Loyola Marymount University

BSCS

Computer Science

2002

Areas of Expertise

Software Engineering
Computer Science
Agile Development
Computer Systems Organization
Operating Systems
Database Systems
Research

Industry Expertise

Electrical Engineering
Industrial Automation
Defense
Corporate Training
Writing and Editing
Computer/Network Security
Security
Education/Learning
Information Technology and Services
Computer Software
Safety

Style

Research Focus

TWELVE: Training With Experiential Learning using Virtual Environments

[PhD Dissertation]

Passive fact-based learning approaches are applied in most online training but suffer from tediousness, lack of experiential learning, and weak testing. A 3D Virtual World-based approach has the capability to overcome the first two problems because it uses a virtual environment in which the learner participates more actively in the learning. The goal of this research is to compare learning outcomes in a 3D Virtual World-based approach versus a passive fact-based approach in an experimental setting.

Courses

Senior Project Laboratory

Analysis, design, implementation, and presentation of a large-scale, individual project, demonstrating mastery of the computer science curriculum.

The idea of this course is for students to show they can successfully conceive of, design, implement, document, and present a medium-size software application.

A further goal is to expose students to the concepts of the software engineering discipline, by class lecture and by actually doing.

Another goal of this course is to expose the students to two different software development methodologies, the Agile Method and the Capability Maturity Model, Integration®. Since both of these disciplines are currently used in industry, it is important for the student to have the experience of both philosophies.

A final goal of this laboratory course is to learn more about software project management. This topic includes being able to estimate such things as the amount of time a project will require for the various phases of its development, and the related cost associated with this time requirement.

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Introduction to Computer Science

The goal of this course is to become familiar with some of the great ideas which have arisen from the science of computation, including (but not limited to):

* Algorithms and their analysis
* Data structures
* Programming languages and why they are used
* Algorithmic efficiency and complexity measures
* Number systems and representations
* Basic computer architectures and how they work
* The idea of abstraction and how it applies to problem solving
* Concepts behind cryptography and computer security
* Artificial and human intelligence

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Computer Programming

The goal of this course is to learn the basics of computer programming and software application construction. Students learn how to create working computer programs, how to think critically, and how to appreciate the difference between well-crafted programs and what is known (in the software industry) as "schlock". Students learn to view computer programming as an art form as well as a lucrative profession.

The topics covered include (but are not limited to):

* Famous computer scientists and early computing engines, and an introduction to computer programming
* JavaScript (and general) programming language fundamentals such as iteration and conditionals
* Number systems and their representations and some introductory data structures
* Statements and expressions, functions, and events and event-based programming
* Fundamentals of software engineering, generally and for web page construction/operation
* Algorithms and their analysis, including some well-known "demo" algorithm programming

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