More information about this job:
The Learning Analytics Specialist will support the development and coordination of NYU learning analytics priorities, processes and practices. Through the design, development and implementation of an innovative and sustainable learning analytics service strategy the specialist will engage with academic staff to encourage the use of analytic design plans and tools to support teaching and learning.
M.A. Educational Data Mining or Learning Analytics.
Ph.D. Educational Data Mining or Learning Analytics.
5 years of related experience developing learning analytics design plans or equivalent combination of education and experience. Must include experience using various forms of Learning Analytics tools and processes to inform learning analytics design plans and design strategy, such as Social Networking Analytics (SNA), Natural Language Processing (NLP), Educational Data Mining (EDM), Predictive Analytics, Adaptive Analytics, and Multimodal Learning Analytics. Experience providing formal instruction, preferably at the college level. Experience developing surveys and conducting focus groups. Experience designing Educational Databases and Reporting Tools. Experience using data visualization software. Experience navigating Learning Management Systems (especially Sakai). Experience applying Psychometrics and Assessment.
Required Skills, Knowledge and Abilities:
Knowledge of data warehousing technologies and data mining computational methods. Excellent analytical and problem solving skills. Excellent written and verbal communication skills, including excellent presentation skills. Excellent interpersonal skills, including the ability to work with others effectively at all levels of the organization in support of the University’s academic mission. Demonstrated knowledge of SPSS, R, Shiny, RStudio, EventFlow, Text Analysis Software, or other statistical packages required for specific analysis. Demonstrated ability to work with sensitive, personal or protected data. Knowledge of Higher Education Student Information Systems. Knowledge of data warehousing technologies and data mining computational methods.
EOE/AA/Minorities/Females/Vet/Disabled/Sexual Orientation/Gender Identity