(Learning Sciences & Assessment Academic Group)
Overview
The National Institute of Education (NIE) is among the world’s top education institutes, recognised for its excellence in teacher education and educational research. NIE has played a key and pivotal role in shaping and developing Singapore’s teaching profession and landscape through evidence-informed, practice-focused and values-based programmes and initiatives.
An autonomous institute situated within the research-intensive Nanyang Technological University, NIE is consistently ranked within the top 15 in the world for research impact in the field of Education.
The Learning Sciences & Assessment Academic Group (LSA) invites applications with an earned doctorate and research portfolio in Instructional Design / Learning analytics & Data Visualization, for a tenure-track Assistant/Associate Professor position. This is an excellent opportunity for outstanding scholars to engage in a dynamic department to advance our education and research goals.
LSA is an interdisciplinary academic group that focuses on understanding learning and assessment from multiple perspectives with the ultimate goal of enhancing and ensuring educative outcomes for all learners. Our mission is to enable educational practitioners to become designers of learning experiences and environments and active contributors in a reflective community of practice. The academic group is concerned with the relationship between theory and practice, and adopts a variety of methodologies, including but not limited to experimental studies, reflection-in-action, action research, design experiments and ethnography for the advancement of its research and teaching. We grapple with the tensions and the nexus between learning, assessment and instructional design, by mediating the design process as both a science and an art. Currently, we offer courses for initial teacher education, as well as graduate programmes such as the Master of Arts (Instructional Design and Technologies), Master of Education (Learning Sciences and Technologies), Master of Arts in Professional Education (Training and Development), Master of Teaching, Master of Science in Science of Learning and Design, Doctor of Education (Technologies and Technology-Mediated Learning Environments) and Doctor of Philosophy (Education).
The candidate would play an active role in some or all of these programmes. Applicants who are prepared to support and work with colleagues on learning and assessment issues in common or new expertise areas are valued. Working across disciplinary interests is encouraged.
Requirements
Successful candidates must have:
For assistant professor
- A PhD or equivalent qualifications or will be acquiring the qualifications at the time of application in the area of Instructional Design / Learning Analytics and Data Visualization
- A keen and updated awareness of technological/social/global effects on Instructional Design / learning analytics and data visualization
- Indicators of ability to secure and manage competitive grants
- An emerging record of associated scientific research, presentations and publications in the area of Instructional designs / learning analytics and data visualization
- Evidence of excellence in teaching, and understanding of school practice
- A developing international network of scholarly collaborators
- Excellent communication (verbal and written English)
- Willingness to understand and support the work of colleagues beyond one’s niche expertise
For Associate Professor
- A doctorate in a field relevant to Instructional Design / Learning Analytics and Data Visualization
- Excellent track record of work as an Assistant/Associate Professor in reputable universities.
- Excellent knowledge and skills in Instructional Design / Learning Analytics and Data Visualization
- An excellent record in securing and managing competitive grants
- A proven track record of publications in reputable peer-reviewed, international journals in the area of Instructional designs / learning analytics and data visualization
- Evidence of excellence in teaching, and understanding of school practice
- Good international network of scholarly collaborators
- Excellent communication (verbal and written English)
- Willingness to understand and support the work of colleagues beyond one’s niche expertise
- Workplace experience in educational settings inclusive of schools is preferred
Responsibilities
Successful candidates will be expected:
- To initiate and/or participate in research examining a wide range of issues related to Instructional Design / Learning Analytics and Data Visualization, both within and beyond the Singapore educational system
- To teach existing and new courses in initial teacher education, executive, undergraduate and graduate programmes
- To work with a team of faculty to develop and teach courses, and pioneer changes in practices in schools
- To supervise initial teacher education and/or graduate students
- To publish research in reputable journals or other outlets as is customary in his/her field
- To establish professional connections with local and international researchers and practitioners in the specific expertise area
- To share expertise with NIE colleagues through various platforms
- To contribute to services at the departmental, institutional, university, national and international levels
Application
Please submit your application together with the following documents to us through : https://ntu.wd3.myworkdayjobs.com/Careers/job/NTU-Main-Campus-Singapore/Associate-Professor-Assistant-Professor-in-Instructional-Design-Learning-analytics---Data-Visualization--LSA---NIE-_R00008118
- A cover letter addressing how you meet the requirements of this position
- A research statement
- A teaching statement
- Course outline or teaching plan of courses you may be interested in teaching
- A resume including a publication list, names of three referees and your desired starting date of employment
- Your best publications
- Any other documents beyond those listed here or requested on the application form that demonstrate your qualifications and credentials
Closing Date
This position will remain open until filled.
Other Information
More information on LSA can be found at https://www.nie.edu.sg/our-people/academic- groups/learning-sciences-assessment
For enquiries, interested applicants may write to A/P Chen Wenli, Head/LSA at email: [email protected] or [email protected]
Note to applicants
Please note that only shortlisted candidates will be notified (via email).
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