Dr. Mohammad Fayez Al Bataineh
← Back to HomeMy teaching philosophy centers on creating an engaging, interactive learning environment where students are not passive recipients of information but active participants in their educational journey. I believe in bridging theoretical concepts with practical applications, making complex engineering principles accessible and relevant to real-world challenges.
Through innovative use of technology—including iPad-integrated lectures, recorded sessions for flexible learning, and comprehensive digital course management—I strive to accommodate diverse learning styles and create opportunities for students to learn at their own pace. My goal is not just to teach formulas and theories, but to inspire critical thinking, problem-solving skills, and a passion for lifelong learning in electrical engineering and communications.
I am committed to maintaining the highest standards of teaching excellence, as evidenced by my consistent student evaluations (4.52/5.0) that exceed departmental averages, and my continuous pursuit of professional development through programs like the Faculty Teaching Academy Program (FTAP) and Quality Matters certification.
Analysis of continuous-time and discrete-time signals and systems using time-domain and frequency-domain techniques.
UndergraduateFundamental concepts of probability theory, random variables, and stochastic processes essential for communication systems analysis.
UndergraduateMathematical tools and analytical techniques essential for solving electrical engineering problems.
UndergraduateFundamentals of information theory, source coding, channel coding, and error control coding techniques.
UndergraduateDiscrete-time signals and systems, z-transform, DFT, FFT algorithms, and FIR/IIR digital filter design.
UndergraduateImage enhancement, restoration, compression, and analysis techniques using digital signal processing methods.
UndergraduateHands-on laboratory course exploring AI applications in engineering, including machine learning, neural networks, and intelligent systems.
UndergraduateCapstone design projects integrating knowledge from multiple courses to solve real-world engineering problems.
Senior ProjectAdvanced study of neural network architectures, training algorithms, and applications in engineering systems.
GraduateInteractive lectures using iPad technology for real-time problem-solving, annotations, and dynamic visualizations that enhance student engagement.
All lectures recorded and made available for students, enabling flexible learning, review, and accommodating different learning paces.
Comprehensive online platforms using MS Teams for seamless communication, assignment submission, and resource sharing.
Integration of NotebookLM and AI tools to provide additional learning support and personalized study materials.
Implementation of constructivist learning theory from Faculty Teaching Academy Program (FTAP) for active student participation.
Applying Quality Matters standards for course design, ensuring accessibility, alignment, and evidence-based practices.
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