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Elec Eng Comput Eng |
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EECE 564 - Convex Optimization
Credits: 3
Convex sets, functions, and problems; basics of convex analysis; least-squares, linear, quadratic, geometric, and semi-definite programs; duality theory; numerical linear algebra and algorithms; MATLAB-based tools for convex optimization; applications to in signal processing, networking, control, circuit design, etc.
Prerequisites: EECE 506 or working knowledge of linear algebra, exposure to probability, and some familiarity with MATLAB, or Instructor permission. Offered every third spring semester.
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EECE 566 - Detection Theory
Credits: 3
Course on statistical signal detection techniques and their applications in digital forensics. Lectures are interleaved with hands-on projects to show the students the usefulness of theoretical concepts introduced during lectures. Students will become familiar with an important forensic method for digital media that identifies digital cameras and manipulated images using the so-called sensor fingerprint. From the technical point of view, the course contains the following topics: Binary and multiple hypothesis testing, Neyman-Pearson theorem, Bayesian risk minimization, likelihood ratio test. Detection of deterministic signals and random signals, matched and generalized matched filter. Gaussian and non-Gaussian noise. Detection of signals with unknown parameters and unknown noise parameters, generalized likelihood ratio test, universally most powerful test. Basics of parameter estimation theory. The techniques will be demonstrated via hands-on projects drawn from the field of digital forensics (digital watermarking and sensor fingerprints). Prerequisite: Basic statistics. Offered every spring semester.
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EECE 567 - Cyber-Physical Sys Security
Credits: 3
Cyber-physical systems (CPS) represent a new class of systems that bring together sensing, computation, communication and control to enable continuous interactions with physical processes. Application areas are as diverse as aerospace, civil infrastructure, energy, manufacturing, transportation most of which are safety-critical. The availability of cheap communication technologies such as the Internet, makes such infrastructures to susceptible to cyber-threats. The goal of this class is to provide a unified overview of CPS security issues, from the perspective of control, communication and game theories, relating to various CPS including industrial control systems and those considered critical infrastructure systems. It will also introduce students to concepts in optimization, decentralized decision making in teams and games, and the interconnections between information and decision making, and networked control systems.
Prerequisites: EECE 212, ISE 261, or approval of instructor. Offered every other fall semester.
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EECE 568 - Fund of Reinforcement Learning
Credits: 3
This course will provide an introduction to the field of reinforcement learning (RL). The topics that will be covered (time permitting) include but not limited to Markov Chains; MDPs; Value Functions; Policy Iteration and Value Iteration; Monte Carlo Methods; Temporal Difference (TD) Learning; (Linear) Function Approximation; SARSA; Q-Learning; TD; Actor-Critic Methods; Neural Networks, Backpropagation and Applications to RL; Other topics (e.g., Multi-Agent RL, RL Theory; Deep Reinforcement Learning). This course will emphasize on hands-on experiences, students are expected to become well versed in key ideas and techniques for RL through a combination of lectures, written and coding assignments. Students will advance their understanding and the field of RL through a project.
Prerequisites: Calculus and Linear Algebra; Basic Probability and Statistics; Python. Offered in the Spring.
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EECE 570 - System On A Chip Design
Credits: 3
This course will provide an overview of the components of system on a chip (SOC) design from initial technology and architectural choices, to hardware/software design techniques (e.g., data/control flow modeling and implementation, embedded cores and coprocessors, hardware/software communication), as well as SOC implementation issues (e.g., performance, core selection, on-chip communication networks, power management, package constraints, and cost). Also covered are SOC design and implementation processes (e.g., functional integration, simulation, clocking strategies, timing, design for test, and debug strategies). Lecture portion meets with EECE 438. Extra assignments, and/or final project will be required at the graduate level. Prerequisites: EECE 315 and 287. Offered every spring semester.
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EECE 573 - Digital Systems Design II
Credits: 3
Advanced digital design principles, synthesis and test using hardware description language (HDL) at the register-transfer level (RTL). HDL programming and simulation basics, followed by advanced HDL programming for synthesis and test benching. Principles of RTL synthesis introduced. Design and synthesis of digital systems to meet constraints. Pre-synthesis and post-synthesis verification using simulation. Commercial synthesis tool discussed in detail. Lecture portion meets with EECE 451. Extra assignments, and/or the final project will be required at the graduate level.
Prerequisite: EECE 351 or equivalent. Offered every fall semester.
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EECE 574 - CMOS VLSI Circuits & Arch.
Credits: 3
The topics include the principles of MOSFET transistors, characteristics of CMOS digital circuits, layout design and process, performance analysis of CMOS gates, circuit design styles using MOSFET, performance, area and power optimization of CMOS circuits. Commercial design and simulation tools will be used in the class. Laboratory assignments include design, layout, extraction and simulation.Lecture portion meets with EECE 455. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 351 or equivalent. Offered every fall semester.
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EECE 575 - VLSI System Design
Credits: 3
Gate level and physical level design of a complex system, such as RISC processor (including the ALU and memory) is discussed. Advanced topics in logic-level design, such as high performance design, dynamic logic, low power design, asynchronous logic, interconnect analysis, cross talk issues, bus architecture, layout floor planning, and placement and routing, will be covered. Students will be asked to use Cadence physical design, analysis, and simulation tools. Prerequisite: EECE 574. Offered every spring semester.
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EECE 578 - Intro to Microfabrication
Credits: Variable
Multidisciplinary Introduction to Microfabrication: Introduction to clean room tools, procedures, and theory through the fabrication and characterization of various devices from the fields of electrical engineering, mechanical engineering, physics and chemistry. Fabrication of the devices will cover most clean room tools and techniques, including lithography based patterning methodologies; chemical vapor deposition; sputtering; thermal and e-beam evaporation; thermal oxidation; reactive ion etching; ion implantation; and wet chemical processing. The accompanying lecture will cover the theory of the tools used. Lecture portion meets with EECE 431. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 332 or an equivalent course in basic semiconductor device physics. Offered every spring semester. Course fee applies. Refer to the Schedule of Classes.
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EECE 578X - Intro to Microfabrication
Credits: 4
Multidisciplinary Introduction to Microfabrication: Introduction to clean room tools, procedures, and theory through the fabrication and characterization of various devices from the fields of electrical engineering, mechanical engineering, physics and chemistry. Fabrication of the devices will cover most clean room tools and techniques, including lithography based patterning methodologies; chemical vapor deposition; sputtering; thermal and e-beam evaporation; thermal oxidation; reactive ion etching; ion implantation; and wet chemical processing. The accompanying lecture will cover the theory of the tools used. Lecture portion meets with EECE 431. Extra assignments, and/or final project will be required at the graduate level. Prerequisite: EECE 332 or an equivalent course in basic semiconductor device physics. Offered every spring semester.
Course Fees Course fee applies. Refer to the Schedule of Classes.
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EECE 580A - Special Topics
Credits: 3
Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. See semester schedule for current offering.
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EECE 580C - Special Topics
Credits: 3
Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. See semester schedule for current offering.
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EECE 580D - Special Topics
Credits: 3
Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. See semester schedule for current offering.
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EECE 580E - NeuralNetworks&DeepLearning
Credits: 3
In this course, we focus on the introduction of neural networks as well as their applications in deep learning. Fundamentals of neural networks and deep learning will be discussed, including multilayer perceptron, back-propagation algorithm, regularization theory, convolutional neural networks, recurrent neural networks, and reinforcement learning. After a brief overview of the python programming language and statistical signal processing, neural networks and their applications are followed. Application topics in speech recognition, image and language processing will be described. A final project will let students to work on the applications of deep learning or participate in online deep learning competitions. Prerequisites: EECE301 or equivalent signals and systems knowledge.
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EECE 580F - Special Topics
Credits: 3
Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. See semester schedule for current offering.
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EECE 580G - Special Topics
Credits: 3
Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. See semester schedule for current offering.
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EECE 580H - Special Topics
Credits: 3
This course delves into the theoretical foundations and practical applications of Power System State Estimation. It aims to equip students with a deep understanding of how state estimation is integral to the operation and management of modern power systems. The curriculum is structured around the following key areas: Power Grid Data and Models- An introduction to the types of data and models used in power systems, emphasizing their role in state estimation processes. Weighted Least Squares Method- Detailed examination of the weighted least squares method for state estimation, including its mathematical foundations and implementation challenges. Observability Analysis- Techniques for analyzing system observability and identifying observable islands within the power grid. Bad Data Detection- Strategies for detecting and identifying erroneous data within the system to ensure the accuracy of state estimation. Parameter Estimation and Uncertainty Quantification- Methods for estimating parameters and quantifying uncertainties in state estimation, enhancing the reliability of power system operations. Topology Error Detection- Identification of topology errors within the power grid and approaches for their detection and resolution. Challenges and Opportunities in Renewable Integration- Exploration of the new challenges introduced by the integration of renewable energy sources into the power grid and the opportunities presented by smart grid data for improving state estimation. Throughout the course, students will engage in assignments that cover these topics, culminating in a comprehensive project. This project will require students to apply state estimation techniques and quantify the uncertainty of their results using statistical frameworks, thereby consolidating their learning and practical skills in power system state estimation.
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EECE 580I - Special Topics
Credits: 3
Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. See semester schedule for current offering.
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EECE 580J - Special Topics
Credits: 3
This course will cover topics related to renewable energy generation (solar photovoltaic cells), and storage (battery, supercapacitors and fuel cells) devices. The main topics include organic and inorganic photovoltaics, super-capacitors, and batteries. The course will also briefly discuss fuel cells and their application in power generation and hydrogen production. The course will emphasize the electronic and optical properties of the energy materials together with the theoretical and experimental aspects of device design. In addition, the course will also cover power system designs including PV cells and batteries for both grid connectivity and stand-alone systems. Students will also be asked to present a seminar on recent research reports published in these fields.
Prerequisites: ECE332 (Semiconductor Devices) or equivalent. Offered in Spring.
Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. See semester schedule for current offering.
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EECE 580K - Quantum Mech Comp of Mat
Credits: 3
The goal of this course is to teach basic theory and computational methods to understand and predict the material properties and functions. We feature hands-on in-class exercises that teaches students how to use the computational code and python programming to understand the electronic structures of materials, with a special focus on semiconductors. We will start with providing an overview of quantum mechanics and solid-state physics that are important to the understanding of basic concepts underlying the computational methods. We will then introduce foundations of density functional theory and discuss practical implementations: students will learn to run the actual first-principles computational code VASP (https://www.vasp.at/) on high performance computing (HPC) clusters, interpret and present the results. We will illustrate examples to calculate the band structures, surface properties, and defect properties of materials for real-world applications, including renewable energy, (opto)electronics, and quantum computing. We will also introduce python programming and the application of machine learning (mainly supervised learning) algorithms in computational materials science.
Prerequisites: EECE 332 or PHYS 323 or permission of instructor.
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EECE 580L - Implantable Bioelect Devices
Credits: 3
Implantable biomedical electronics is the application of engineering principles to biology, medicine, and health. These novel devices have become an important set of tools in medical technologies and are widely employed for the prevention, diagnosis, and treatment of disease in the human body, for patient rehabilitation, and for improving health. In this course, we cover the operational principles of diverse implantable bioelectronic devices in the context of human physiology and pathophysiology. Some of the topics include prosthetic devices, neural interfaces, brain implants, implantable biosensors, and more. This course also provides in depth discussion on human physiology and pathophysiology for understanding the potential impact of this emerging technology on patient care and clinical outcomes.
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EECE 590X - Instructional Mat. Development
Credits: 3
Students will learn undergraduate instruction aspects of a formal course under the direct supervision of a faculty member and perform substantial course development work. This may include design of new lecture materials, instructional techniques, assignments, and laboratory experiments combined with presentations and/or laboratory supervision. Written documentation of newly developed materials is submitted to the course instructor. May count for one M.S. elective and must be taken with normal (letter) grade option ONLY. It may also be used by Ph.D. students to satisfy the teaching proficiency requirement.
Prerequisites: Permission of course instructor. Offered in the Fall and Spring.
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EECE 592 - Tech. Dev. Curriculum I
Credits: 6
This course is a 32-week in-house course taught at BAE Systems for students enrolled in the BAE ELDP program only and devoted to a broad review of engineering fundamentals, with emphasis on interdisciplinary topics related to Electronic Systems products and processes, technologies, applications, and problem solving techniques. Coursework includes a team-project and presentation to engineering management. Offered every spring semester. 6 credits.
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EECE 593 - Tech. Dev. Curriculum II
Credits: 3
This course is a 16-week in-house course taught at BAE Systems for students enrolled in the BAE ELDP program only and devoted to challenging students with problems very similar to those frequently facing Electronic Systems engineers. Coursework includes a technical project requiring the application of systems, software, and hardware engineering skills. Offered every fall semester.
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EECE 594 - Industrial Internship
Credits: Variable
Engineering work experience in industry. Daily logbook, memo progress reports, and formal final report required. Signature of faculty advisor and graduate director required prior to registration. Offered every semester.
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EECE 597 - Independent Study
Credits: Variable
Independent study or graduate laboratory exercises supervised by electrical/computer engineering faculty member. Signature of instructor required. Offered every semester.
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EECE 598 - Project/Pre-Thesis
Credits: Variable
Hardware and software design and development or other project as defined by a Learning Contract, approved by major professor and project advisor. Seminar presentation required. Formal report submitted to the Project advisor. Signature of advisor required prior to registration. Offered every semester.
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EECE 599 - Thesis
Credits: Variable
Mentoring in the methods of research. Theoretical analysis, computer modeling, software and hardware development and experimentation as determined by a Thesis Committee, faculty advisor, second reader or co-advisor and department chair. Oral defense. Preparation of journal article required. Thesis submitted to Graduate School electronically for the University Library. Signature of advisor required prior to registration. Offered every semester.
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EECE 613 - High Freq Pow Convers Emerg Ap
Credits: 3
This module deals extensively with the design of high frequency high efficiency power electronic converters for AC-DC, DC-DC, and DC-AC, using pulse width modulation (PWM) and resonant energy conversion techniques. This module will make the student aware of the fundamental considerations needed to design power electronic converters in an industrial environment and conforming to different industrial standards especially in terms of electromagnetic interference (EMI)/Efficiency/Line harmonics (AC-DC).
Prerequisites: EECE 419, and EECE 506 or EECE 507, or equivalent. Offered in the Fall.
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EECE 657 - Network Security
Credits: 3
This is a research oriented class that will focus on the state of the art in the network security area. The primary goal of the class is to expose students to cutting edge research works and prepare them for carrying out research independently. Topics include: Sources of Network Vulnerabilities; Overview of Network Security Problems; Standard Internet Security Solutions; Internet Infrastructure Protection; Security in Wireless Sensor Networks; Security Architecture of Grid Computing; Trust, Security and Privacy in P2P/Pervasive Computing Environments; Reconfigurable Hardware Implementation of Security Solutions. Prerequisite: EECE 553 or equivalent. Offered every spring semester.
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EECE 680C - Special Topics
Credits: Variable
Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. See semester schedule for current offering.
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EECE 680D - Special Topics
Credits: 3
Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. See semester schedule for current offering.
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EECE 680E - Special Topics
Credits: 3
Topics in electrical/computer engineering that vary from year to year. If applicable, may be run every fall or spring semester. See semester schedule for current offering.
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EECE 680F - Neural Network & Deep Learning
Credits: 3
In this course, we focus on the introduction of neural networks as well as their applications in deep learning. Fundamentals of neural networks and deep learning will be discussed, including multilayer perceptron, back-propagation algorithm, regularization theory, convolutional neural networks, recurrent neural networks, and reinforcement learning. After a brief overview of the python programming language and statistical signal processing, neural networks and their applications are followed. Application topics in speech recognition, image and language processing will be described. A final project will let students to work on the applications of deep learning or participate in online deep learning competitions.
Prerequisites: EECE301 and EECE506 or EECE507 or equivalent or permission of instructor. Offered in the Fall.
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EECE 697 - Independent Study
Credits: Variable
Independent study supervised by electrical/computer engineering faculty member. Student must obtain consent of instructor, who then determines description of program and number of credits. Offered every semester.
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EECE 698 - Pre Dissertation Research
Credits: Variable
Exploratory research oriented toward PhD dissertation. Offered every semester.
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EECE 699 - Dissertation Research
Credits: Variable
Research for and preparation of PhD dissertation. Offered every semester.
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EECE 700 - Continuous Registration
Credits: Variable
Required to maintain matriculation through any spring or fall semester when no other courses are taken. If the minimal one-credit registration is not maintained, student must reapply for admission. Offered every semester.
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EECE 701 - Pract/Research &Teaching Asst
Credits: Variable
May be used by all funded graduate assistants to obtain additional credits for full-time status. Research or teaching supervised by faculty advisor. Offered every semester.
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Elementary Education |
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ELED 502 - Child Growth & Development
Credits: 3
In this course we will work together to learn more about the role that theories of child development play in the education of children. Through readings, discussions, classroom observations, and projects, we will examine the relationship between child development, education, and socio-cultural contexts. Using Bronfenbrenner’s bioecological theory as a framework, we will explore an approach to development that situates children in their natural contexts. Teacher candidates will engage in extensive fieldwork activities in order to consolidate the links between developmental theory, educational practice, and the lived experiences of children.
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ELED 503 - Curriculm/Teaching Elem Grades
Credits: 3
This course uses the metaphor of windows and mirrors to allow teacher candidates to foster student-centered learning environments that both affirm children’s identities (mirrors) and provide them opportunities to view and relate to the experiences of others (windows). Using culturally responsive and progressive theory and pedagogy, teacher candidates will develop rich lessons based on student interests and community assets that will allow children to explore real world situations, extend their knowledge of and beyond their own experiences, and take action to create positive social change. A main purpose of this course is to sow the seeds of active citizenship by helping young learners begin to understand that their actions within and beyond their immediate classroom context contribute to the kind of world we live in and can either foster or prevent democratic, peaceful and inclusive societies. Using a variety of methods such as art integration, hands-on experiences and play-based learning, teacher candidates will develop lessons to engage all students and allow for deep learning about both the promise and inequities in our world. The focus of this course is three-fold: 1) to develop curriculum about important, real-world issues 2) to make learning relevant, meaningful and engaging and 3) to respect and foster the power and purpose of young learners.
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ELED 507 - Elem Sci Methods
Credits: 3
This course is designed to help prospective elementary school teachers develop a foundation level understanding of ‘3-Dimensional’ science & engineering practices, crosscutting concepts (or common themes) & disciplinary core ideas, as well as the science pedagogical content knowledge to creatively use research-informed, best practice Curriculum resources, Instructional strategies and Assessment techniques. The ‘lessons learned’ will enable you to safely & effectively explore the wonders of science with children ages 5-12 (grades K-6) as aligned with the NYSED Elementary (K-4) & Intermediate (5-8) Science Core Curriculum and, the Next Generation Science Standards (with explicit links to the CCSS-ELA + Mathematics). Emphasis will be placed on constructivist teaching cycles (5E: Engage, Explore, Explain, Elaborate & Evaluate) built around safe, hands-on/minds-on science activities the use inexpensive, household type materials (e.g., toys, grocery store materials & ‘garbage’) and children’s literature/tradebooks to lead to an understanding of how key science concepts work in our everyday lives. As such, students will be expected to develop as creative, reflective practitioners by alternating between the roles of student and teacher by doing, thinking, and writing/talking about science and science education
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ELED 510 - Elem Soc St Methods
Credits: 3
The focus of ELED 510 is teaching and learning social studies in the elementary school. We explore a variety of topics and issues related to social studies content, instruction, and assessment. Much of our conversation and work highlights questions relevant to the social studies field at large, e.g., what is/are the goal(s) of social studies what is a viable relationship among teaching, learning, and assessment? How do we construct classrooms that reflect democratic ideals’ These questions are important and play a role in every teacher’s practice. But given the nature of ELED 510, our focus always returns to the classroom and to the practical issues of teaching and learning social studies. Offered: winter.
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ELED 540 - Elem Schl Math:Content/Methods
Credits: 3
The focus of this course is on early childhood and elementary school mathematics content and instructional pedagogy. We will explore how to establish appropriate mathematical goals, how to select and implement educative tasks, and to examine the characteristics of instruction that promotes learning. We will use our discussion of elementary students’ meanings and strategies as a context for exploring teaching strategies that help teachers (1) understand what students are thinking and (2) design instruction that supports procedural fluency, conceptual understanding, and mathematical reasoning. In addition, part of this course is about doing mathematics, generating mathematical conversations with each other, and reflecting on your own mathematical knowledge.Weekly fieldwork is a required component of this course
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ELED 590 - Internship in Childhood Educ
Credits: 3
ELED 590 and 591 are companion courses. ELED 590 is the Internship for Childhood Education. The purpose of ELED 590 is that you put into practice in a classroom setting the skills and dispositions you have been learning about throughout your prior fieldwork experiences and coursework. The Internship for Childhood Education is a full-time, full-semester student teaching experience, which provides you the exciting opportunity to put what you have been learning into practice. You are expected to arrive at school half an hour before the students so that you can touch base with your team and ready yourself for the day. Once the students arrive, you will be busy so make the most of this morning time. Although you are expected to plan and teach from the beginning, as the semester goes on, you will assume more and more responsibilities in the classroom. This will culminate in your solo week, where you will take the lead on planning, teaching, and classroom management. Your solo week will take place sometime after Thanksgiving, at the beginning of December. During your solo week, your teacher and aides will be present in the classroom and continue their work supporting students but you will take on the lead role.
Open to matriculated students only. Graded S/U only
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ELED 591 - Childhood Internship Seminar
Credits: 3
ELED 591 is the Childhood Internship Seminar. The purpose of ELED 591 is to improve and support your teaching practice by addressing shared issues that frequently arise when new teachers make the move from coursework to instruction. ELED 591 will help you develop the necessary techniques and dispositions required to establish effective and positive learning environments so you work successfully with elementary school children, their families, and school personnel.The Childhood Internship Seminar is designed to support your success in your Internship for Childhood Education by helping you develop necessary techniques and dispositions required to establish effective and positive learning environments and work successfully with elementary school children, their families, and school personnel. There are five themes for the Internship Seminar: 1) Professionalism and professional development; 2) Teaching effectively. This includes planning, instructing and assessing student learning. It also includes analysis of your own teaching practice; 3) The edTPA including planning, instruction, assessment and analysis of teaching using student data as evidence. This is closely linked to the second theme, but is more specific in its requirements; 4) Classroom management; 5) arts integration. The Childhood Internship Seminar is a 3-credit course, which means that students are expected to do at least 9.5 hours of course-related work or activity each week during the Fall semester. This includes time spent completing assigned readings, preparing written assignments, and other course-related tasks. It does not include your student teaching hours or planning for your teaching. That said, many of the assignments overlap with your preparation for teaching and the teaching itself. (Your time spent planning for teaching primarily is linked to the Internship for Childhood Education rather than the seminar.)
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English |
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ENG 180A - Topics in English
Credits: 4
Broad introductory courses in English.
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ENG 180B - Topics in English
Credits: 4
Broad introductory courses in English.
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ENG 180C - Topics in English
Credits: 4
Broad introductory courses in English.
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ENG 180I - Topics in English
Credits: 4
Broad introductory courses in English.
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ENG 180J - Topics in English
Credits: 4
Broad introductory courses in English.
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ENG 180M - Topics in English
Credits: 4
Broad introductory courses in English.
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ENG 180N - Topics in English
Credits: 4
Broad introductory courses in English.
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ENG 180O - Topics in English
Credits: 4
Broad introductory courses in English.
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ENG 200A - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200B - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200C - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200D - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200E - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200F - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200G - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200H - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200J - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200L - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200M - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200N - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200R - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 200W - Special Topics In Literature
Credits: 4
Broad, introductory-level courses outside the scope of the department’s British and American survey courses, such as national literatures in translation or classical mythology. May be repeated for credit if topic varies.
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ENG 205 - Introduction To Folklore
Credits: 4
Introduction to folklore and folk culture.
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ENG 227 - British Literature I
Credits: 4
British Literature from the Middle Ages to the Seventeenth Century Offered every semester
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ENG 228 - British Literature II
Credits: 4
British Literature of the 18th and 19th centuries. Offered every semester
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ENG 230 - Medieval Literature
Credits: 4
British Literature of the Middle Ages.
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ENG 245 - Shakespeare
Credits: 4
Study of several representative plays. Offered every semester
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ENG 270 - American Literature to 1920
Credits: 4
American Literature from the colonial era to the early 19th century. Offered spring or fall
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ENG 280A - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280B - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280C - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280D - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280E - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280F - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280G - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280H - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280I - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280J - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280K - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280L - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280M - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280N - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280O - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280P - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280Q - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280R - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280S - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280T - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280U - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280V - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280W - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280X - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 280Y - Topics in Literature
Credits: 4
Topics in Literature. Topics vary by semester.
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ENG 281E - Special Topics In Literature
Credits: 2
Special Topics in Literature. Topics vary by semester.
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