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

Friday 13 Mar 20

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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.

Project Description
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 21st 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. 

Responsibilities and tasks
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: 

  • Revie the existing literature on nursing education quality and establish the scope of contribution through adaptive learning technologies, short-term and long-term evaluation mechanisms.
  • Qualify baseline tests for core science subjects and tests for employer satisfaction with student skills to be integrated into Rhapsode NURSING™
  • Produce knowledge on the effect and moderators of interventions with ALTs through extensive quantitative data analysis gathered in Rhapsode™ and supplementary data on students. Continuously create and use short-term feedback from all parts of the project.
  • Co-develop features of Rhapsode NURSING™
  • Test alternative ALTs tailored to meet educational needs other than those covered by Rhapsode NURSING™
  • Disseminate the scientific outcomes in international academic educational technology community through publication of papers in journals, books, and conferences.
  • You have the motivation and ability to define, execute and achieve quality of the research and development activities in collaboration with your colleagues.

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 DTU PhD Guide.

The assessment of the applicants will be made by Professor Helle Rootzén and Associate Professor Md Saifuddin Khalid.

We offer
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.

Salary and appointment terms
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 Rootzén, and Md Saifuddin Khalid,

Further information concerning the application is available at the DTU Compute PhD homepage

Please submit your online application no later than 15 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. The file must include: 

  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma
  • Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)
Candidates may apply prior to obtaining their master's degree, but cannot begin before having received it.

Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Compute is an internationally unique academic environment spanning the science disciplines mathematics, statistics and computer science. At the same time we are an engineering department covering informatics and communication technologies (ICT) in their broadest sense. Finally, we play a major role in addressing the societal challenges of the digital society where ICT is a part of every industry, service, and human endeavour.

DTU Compute has a total staff of 400 including 100 faculty members and 130 Ph.D. students. We offer introductory courses to all engineering programmes at DTU and specialised courses to the mathematics, computer science, and other programmes. We offer continuing education courses and scientific advice within our research disciplines, and provide a portfolio of innovation activities for students and employees.

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 11,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup and in Sisimiut in Greenland.