Assistant Professor/Associate Professor

Location
Denton, TX
Posted
Nov 26, 2018
Position Type
Tenured & Tenure-Track
Institution Type
Four-Year Institution

System Identification Number:
6002001

Posting Origination:
UNT

Department:
Learning Technologies (133300)

College/School:
College of Information http://ci.unt.edu

Rank/Title:
Assistant Professor/Associate Professor

Job Summary/Basic Function:
The Department of Learning Technologies at the University of North Texas in Denton is recruiting for an Assistant/Associate Professor, full-time, tenure track faculty position. This faculty will teach core and elective courses in LT's programs.
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. The new faculty will 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.
Normal responsibilities associated with this position includes teaching two graduate courses or equivalent service or research each long semester, serving on department and college committees, and engaging actively in scholarly efforts including publishing, research and seeking external funding. Each faculty member is expected to supervised graduate students and maintain an up-to-date summary in the university's faculty information system.
The University of North Texas System is firmly committed to equal opportunity and does not permit - and takes actions to prevent - discrimination, harassment (including sexual violence), and retaliation on the basis of race, color, religion, national origin, sexual orientation, gender identity or expression, age, disability, family status, genetic information, citizenship or veteran status in its application and admission processes, educational programs and activities, facilities, and employment practices. The University of North Texas System immediately investigates and takes remedial action when appropriate.
The University of North Texas System also takes actions to prevent retaliation against individuals who oppose a discriminatory practice, file a charge, or testify, assist or participate in an investigative proceeding or hearing.

Minimum Qualifications:
PhD in Instructional Psychology and Technology or closely related field

Preferred Qualifications:
Master's in Information Science and strong publication record. Grant experience highly desired along with supervision of doctoral students, and evidence of collaborative leadership in the broad area of learning technologies as shown by active membership and leadership service in professional associations.

Position Type:
Faculty

Tenure Status:
Tenure Track

Appointment Basis:
9 Months

Pay Frequency:
Monthly

Non-Tenured Appointment Term:
No Response

Closing Date:
Open Until Search Closed

Required Applicant Documents:
Curriculum Vita

PI105815312

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