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School of Computer Science
5000 Forbes Ave
Pittsburgh, PA 15213
Educational Technology and Applied Learning Science (METALS)
The Masters in Educational Technology and Applied Learning Science (METALS) is a one-year interdisciplinary masters, jointly taught by the Human Computer Interaction Institute in the School of Computer Science and Psychology in Dietrich College of Humanities and Social Sciences, trains students to design, develop and evaluate evidenced-based programs for learning in settings that range from schools to homes, workplaces to museums, and online to offline learning environments. Graduates will be prepared to take key positions in corporations, universities and schools as designers, developers, and evaluators of educational technologies as well as learning engineers, curriculum developers, learning technology policy-makers, and even chief learning officers.
Students with backgrounds in psychology, education, computer science, design, information technology, or business are encouraged to apply.
The program integrates fundamental skills with project-based studio classes culminating in a final capstone project. It is distinct from the Learning Science track in the HCII PhD program, and, in particular, it is not designed as a feeder to that PhD program.
Upon completion of the Masters in Educational Technology and Applied Learning Science, graduates will:
* Be able to design, develop, and implement advanced educational solutions that make use of state-of-the-art technologies and methods such as artificial intelligence, machine learning, language technologies, intelligent tutoring systems, educational data mining, tangible interfaces.
* Understand how these technologies can be applied to engineer and implement innovative and effective educational solutions.
Understand cognitive and social psychology principles relevant to research-informed instructional design.
Have skills for instructional and interaction design needed to create solutions that not only enhance learning, but are also desirable.
* Understand the role of and have skills in using psychometric and educational data mining methods in evaluating and improving educational solutions
* Be able to develop continual improvement programs that employ “in vivo” experiments and educational data mining to reliably identify best practices and opportunities for change.
Carnegie Mellon University is known by the software and technical industries for it’s interdisciplinary nature, rigor and deep knowledge in Learning Science, Human-Computer Interaction, Psychology, Design, and Computer Science. This is a two-year masters degree set into a twelve month duration. During their first and second semesters, students learn core knowledge and skills in learning principles, technology design, and implementation as well as choose from a range of electives. During their second and third semesters the students participate in a substantial industry capstone project with an external client.
Financial Aid: No
International Financial Aid: No
In State Tuition (per year): 62000 USD
Out State Tuition (per year): 62000 USD
Classification: Doctoral/Research University—Extensive
Locale: Large City
Size & Settings: 10,000-19,999