HarvardX Research Fellow (Computational Focus)
|Date Posted||May 12, 2014|
Auto req ID 32585BR
School/Unit University Administration
Sub-Unit Office of the President and Provost
Location USA - MA - Cambridge
Job Function Research
Schedule Mon. - Fri. (35hrs/wk)
Department University Initiative HarvardX
Salary Grade 057
Union 00 - Non Union, Exempt or Temporary
Duties & Responsibilities
The HarvardX Research Team is seeking a Postdoctoral Research Fellow (Computational Focus) to conduct research about online learning in HarvardX courses. The fellow will report directly to a faculty member of the HarvardX Research Committee selected according to the incumbent's academic training, at the discretion of the co-chairs of the research committee. This position is intended for a dedicated scholar with exceptional research skills who has a relevant background in computer science or quantitative social science. The position requires experience with “big data” research and analytics and an interest in advancing higher education through evidence-based, innovative methods of online learning. The competitive salary and unique opportunities for independent, high-impact research are intended to attract unusually talented candidates, particularly those interested in tenure-track faculty positions.
The responsibilities of the incumbent will relate to three main domains: (1) original research into foundational issues of online learning, (2) development and validation of metrics for the participation, persistence, and learning of students, and (3) the design, implementation, and analysis of assessments in HarvardX courses. An ideal candidate may have particular strengths and prior experience in one domain but should possess the skills to excel in all three.
The HarvardX Research Fellow (Computational Focus) will design and conduct research into online learning to address general questions of scholarly and practical interest. This research must be methodologically rigorous, conducted in active collaboration with other researchers and faculty, and focused primarily on informing methods of online teaching and learning in higher education. The Fellow will have the opportunity to mine large datasets collected through the edX platform and HarvardX learning experiences, test research hypotheses through the design of experiments and interventions, and shape the edX research infrastructure.
The HarvardX Research Fellow (Computational Focus) will support the HarvardX research enterprise through the development of new techniques for measuring student participation, persistence, and learning. The Fellow will become deeply familiar with event logs from the edX platform and other platforms and plug-ins used by HarvardX courses. The Fellow will partner with other research team members to develop new ways to classify and analyze learners and learner behaviors, with particular attention towards developing new metrics for evaluating learning.
Assessment design, implementation, and analysis. The HarvardX Research Fellow (Computational Focus) will help faculty, administrators and HarvardX course team members construct and implement valid assessments of intended educational outcomes for HarvardX courses, including measures of learning, retention, transfer, skill, interest, and attitude. Furthermore, the Fellow will analyze these assessment data, use them to make practical recommendations for improving online pedagogy, and clearly present these results and recommendations to members of the Harvard community.
As appropriate, insights gained through the above activities will be disseminated through a mix of publishable academic manuscripts, internal reports, in-person presentations, posters, and conference proceedings.
Candidates should have a Ph.D. or Ed.D. at the time of application or by the proposed start date. The degree should be in a relevant field, including but not limited to computer science, human-computer interaction, computational social science, digital humanities, statistics, learning analytics, or educational data mining. Candidates should have demonstrated expertise in research methodologies appropriate for “big data” and a record demonstrating the ability to publish in scholarly journals. Applicant must possess strong writing, presentation, interpersonal, and technical skills and be willing to work as part of a collaborative, diverse research team.
The ideal applicant will have experience with MongoDB, Python, Pandas, and R; other applicants will demonstrate an ability to learn these tools quickly.
Additional Information Launched in parallel with edX, the Harvard- and MIT-founded not-for-profit, online learning enterprise, HarvardX integrates the development of instructional approaches and digital tools across Harvard's campus by providing faculty with pedagogical and research support. HarvardX is one critical endeavor, among many, designed to empower faculty to improve teaching and learning on-campus, online, and beyond. A faculty-driven and university-wide endeavor, HarvardX aims to be collaborative and representational of Harvard's academic diversity, showcasing the highest quality offerings of the University to serious learners everywhere. The HarvardX team supports MOOCs and online learning more generally, in line with HarvardX's overarching strategic goals to improve teaching and learning on campus, online and beyond; advance the understanding of how students learn, and expand access to high-quality education worldwide.
Appointment is yearly, renewable annually for up to three years contingent on satisfactory job performance, university priorities and funding. Salary is $75,000 per year. The position is available for immediate appointment, but summer or fall 2014 start dates are possible. If possible, please include a letter of reference in addition to a cover letter and resume in your application.
- Please note: Harvard University requires pre-employment reference and background screening.
- HarvardX is unable to provide work authorization and/or visa sponsorship.
How To Apply
You can apply for this position online at http://www.Click2Apply.net/478c9pd