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Job ID: 158400

Asst/Assoc/Professor
University of North Texas


Date Posted May 6, 2021
Title Asst/Assoc/Professor
University University of North Texas
Denton, TX, United States
Department UNT-Learning Technologies-133300
Application Deadline Open until filled
Position Start Date Available immediately
 
 
  • Assistant Professor
    Associate Professor
    Professor
  • Instructional Design/Technology
    Education - General
 
 

Department Summary
The Department of Learning Technologies at the University of North Texas in Denton is recruiting for an Assistant/Associate/Full Professor, full-time, tenure track faculty position.

As the textbook-driven, one-size-fits-all model fades, there is a growing recognition that there is an opportunity to provide truly a personalized learning experience to each and every learner in K-12, post-secondary, adult and career and technical areas. What is being learned is dependent on who the learner is, the goals and objectives involved in instruction, what the learner already knows, and how the learner learns; these factors imply specific instructional strategies that take into account both the learner and the learner’s situation. Personalized learning, learning that truly adapts to each and every learner using such technologies as learning analytics, requires that decisions about the what and the how are made by learners and instructors in concert with an instructional delivery system that may be face-to-face, online, or a blend of approaches involving different technologies. Providing personalized learning is, as a consequence of powerful new technologies including learning analytics, a growing enterprise at all educational and training levels.

The faculty in the Department of Learning Technologies have historically and consistently brought an interdisciplinary/multidisciplinary/transdisciplinary approach to their teaching and scholarship. Consistent with that tradition, we are seeking a faculty member who can work in the broad field of personalized instruction and learning analytics. where the design, development and evaluation of instructional systems that can deliver personalized learning will require an understanding of learning analytics/data science, psychology/sociology, curricula and digital media, and the effective design of learning activities and environments. Learning analytics (which involves the development of a dynamic and holistic model of a learner that includes personal interests and characteristics as well as learning styles, previous knowledge and experience, and current performance in a learning environment) when coupled with large sets of data about other learners can be used to customize specific feedback and activities to help an individual learner make continuous progress. The department believes, therefore, that the development of learning analytics is, therefore, tightly coupled with the development of adaptive instructional systems and learning environments.

The College of Information and Department of Learning Technologies are committed to creating a learning community that reflects and enacts the values of diversity, equity and inclusion that inform academic excellence. We encourage applicants who may enhance our representational diversity but especially whose research, teaching, and community engagement will contribute to diverse, equitable, and inclusive learning and working environments for our students, staff, and faculty.

Position Summary
This position will teach undergraduate, masters and doctoral level courses, core and elective, and will be responsible for creating and updating new course offerings, with primary focus on online courses.

There is a growing recognition that there is an opportunity to provide a truly personalized learning experience to each and every learner in all educational areas, and so we are looking for someone with a research focus on adaptive and personalized instruction, artificial intelligence in education, and learning analytics.

The new faculty is also expected to play a critical role in collaborating with current faculty in supporting the departments’ expanding doctoral programs, as we anticipate that there will be an increasing demand from incoming students for research and training in the emerging area of personalized learning systems. Expanding and sustaining a first-class doctoral program is essential to maintaining the goal of continuing to be a Carnegie Tier I research University.

Minimum Qualifications
Candidates must have an earned doctorate in Learning Technology or related fields; and demonstrate evidence of effective teaching, research, and scholarship with experience/expertise in broad areas of adaptive and personalized instruction, artificial intelligence in education, and learning analytics. Applicants seeking appointment with tenure at the associate professor rank or full professor rank must meet UNT’s criteria for tenure at the appropriate level.


 
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