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Course Criteria
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3.00 Credits
Considers topics including abstract data types and objects, strings, vectors, linked lists, stacks, queues, deques, sets, maps, tress, hash tables and applications of data structures. Includes weekly laboratories. Tix, Veilleux.
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3.00 Credits
Addresses the need for authentication, confidentiality, and integrity of data in a networked environment. Examines the services and mechanisms currently available to prevent successful attacks. Includes security models, encryption, digital signatures and certificates, authentication techniques, e-mail confidentiality, firewalls, Web servers, malware, and security management strategies. Tis.
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4.00 Credits
Teaches the strategies used in designing a complex computer-based application system: identifying stakeholders, gathering information, writing requirements, analyzing for technical and financial feasibility, setting priorities, planning and managing projects, and designing for usability. Includes extensive use of cases and UML for indepth examples. Involves team projects. Menzin.
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4.00 Credits
In this class we will review the presuppositions of behaviorism and critically analyze those presuppositions. This will be accomplished by reviewing the work of Watson and Skinner.
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4.00 Credits
In this course students will study the philosophy of verbal behavior and the application of Skinner?s principles. Particular emphasis will be placed on the application of the science of behavior analysis to teaching verbal behavior. The primary verbal operants, which are most often initially discussed in relation to teaching language, are echoics, mands, tacts, and intraverbals. Within this course we will explain the functions of these operants and how they may be taught. Within this course we will also teach establishing operation and how they relate to teaching language. All readings will be complimented by a study of Skinner?s seminal book Verbal behavior.
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4.00 Credits
This course examines the conceptual and methodological issues of the application of applied behavior analysis into educational settings. This class is designed to provide the doctoral student with a broad overview of the educational applications of the science of behavior analysis, including general and special education, reading instruction, early intervention, higher education, professional training and development in education, and educational assessment.
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