PhD Project on Statistical Evaluation of The Integration of Adaptive Learning Technologies in Nursing Education

Technical University of Denmark is pleased to invite applicants to apply for a new opening PhD position in sustainable development. The funding allows successful candidate to work for 5 years. Applications are invited up to April 15, 2020.

DTU Compute the Department of Applied Mathematics and Computer Science's Section for Statistics and Data Analysis, would like to invite applications for a 3-year PhD position starting 1st May 2020 or as soon as possible thereafter. The PhD project is part a funded project and affiliated with LearnT - Center for Digital Learning Technology. The project is financed by Innovation Fund Denmark (IFD), under the project titled "NURSEED – Designing 21st century nursing education by integrating adaptative learning technologies".

learnT was initiated 3.5 years ago and is dedicated to both using statistics for making learning better and for developing new digital learning technology. The center is placed in the section for Statistics and Data Analysis which is dedicated to methodological development and applied research within the field of statistics and data analysis. The section is dedicated to support other departments at DTU and external partners with skills, knowledge and consultancy within the field of statistics and data analysis including biological and educational data. The section has special emphasis on statistics, quantitative genomics, bioinformatics, pattern recognition and software development. DTU Compute has a long history of conducting statistical consultancy and participating in research and publication collaboration with other departments at DTU, other universities and external partners. The basic purpose of the unit is to formalize this collaboration and contribute to even better research and public service sector consultancy at DTU. The Danish nursing education have experienced problems and finds opportunities in digitalized learning activities. The problems include higher dropouts than the average rate in the tertiary education while there is increasing number of patients in hospitals, old-age dependency ratio in Europe, and scope to achieve increasing satisfaction of employers or clinical managers towards the hired graduates. Funded by the Danish innovation fund, "Designing 21 st century nursing education by integrating adaptive learning technologies NURSEED" project which will tailor and integrate the adaptive learning platform Rhapsode, developed by Danish edtech frontrunner Area9, into core science subjects of the University College Absalon's nursing education curriculum. This PhD project will contribute by baseline (survey) of employer satisfaction with student skills and investigate the evidence of improving nursing education by adaptive learning starting with redefining quality criteria for nursing education by establishing the baseline measurements, and evaluation criteria. Are you interested in developing new quality criteria and applying statistical methods in nursing education and adaptive learning technologies? Would you like to contribute in the broad scope of digital learning technology and outcome evaluation? Then you might be our new PhD student. You will be involved in the project and collaborating with both industry and academia. Some of your key tasks will be to be part of the following objectives of the NURSEED project: You will be responsible for publishing academic outcomes in collaboration with the NURSEED project partners, especially with Area9 and Unviersity College Absalon.

Candidates should have a two-year master’s degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master’s degree. The master degree should be in statistics, computational science, computer engineering, data science, applied mathematics, or equivalent academic qualifications. Preference will be given to candidates who can document experience in statistics, data science, statistical machine learning and to those who have combined this with experience in working with nursing education, health professionals, or tertiary educational development. Furthermore, good command of the Danish language is essential for field work and good command of English language is required for academic dissemination. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the DTU Compute PhD School Programme. For information about the general requirements for enrolment and the general planning of the PhD study programme, please see the . The assessment of the applicants will be made by Professor Helle Rootzn and Associate Professor Md Saifuddin Khalid. DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility. The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The position is a full-time position. The period of employment is 3 years starting June 1, 2020 (or as soon as possible thereafter). You will be based at DTU Lyngby Campus but you can expect to work multiple days to weeks per year at the NURSEED partners' work contexts. You can read more about career paths at DTU here . Further Information Further information concerning the project can be obtained from the supervisor and co-supervisor of the project Helle Rootzn, and Md Saifuddin Khalid, Further information concerning the application is available at the DTU Compute PhD homepage . Application Please submit your online application no later than15 April 2020 (23:59 local time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link “Apply online”, fill out the online application form, and attach all your materials in English in one PDF file Excel sheet with translation of grades to the Danish grading system (see guidelines and Candidates may apply prior to obtaining their master’s degree, but cannot begin before having received it.


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