Mini-Grants: Data Literacy Skills in Higher Education

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已更新 5/11/2016
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Intel is offering small grants ($5k-$20k) to support curriculum development for teaching entry-level data skills to students in disciplines that are not traditionally computationally intensive. Depending on the discipline, “entry level” could be focused on early undergraduate, late undergraduate, or graduate level courses. It might mean familiarizing students with some of the techniques for processing time series data as a first step into data science training, or it might mean that more advanced students who have advanced training in other research methods are taught how to work with time series data from sensors as a minor addition to the research toolkit. Intel is also interested in working with math departments and aligned disciplines that are interested in using sensor data—data which can be quite compelling in as much as it often reflects the day-to-day life of the person who collected it—as a way to attract students that are not normally interested in STEM topics.

While the call is not limited by discipline, we especially encourage participation from scholars in the following fields:

  • Sociology
  • Anthropology
  • Public Health
  • Geography
  • Environmental Studies
  • Kinesiology
  • Psychology
  • Marketing
  • Science and Technology Studies
  • Design
  • Atmospheric Sciences
  • Agricultural Sciences
  • Mathematics

There are two types of projects that we will support:

Feasibility Grants ($5000- $7000)

Smaller grants will be given to enable faculty to assess current ways their discipline or department supports entry-level data skills, focusing on sensor data. This would be an opportunity to identify potential areas or aspects of curriculum development that might be necessary in the future. How do you see sensor data fitting in to your curriculum? What kinds of software do you currently use (if any), and what future tools might better support student learning? The outcomes of these grants could be a brief report, or an equivalent.

Curriculum Grants ($7000 - $20,000)

Intel also seeks to collaborate with university partners to explore potential data processing tools for higher education environments. Intel wishes to support curriculum development by making available its Data Sense platform, a prototype designed to enable processing of sensor data without having to learn coding skills. We offer slightly larger amounts ($7000-$20,000) to projects that develop curricula in this area in combination with an exploration of the potentials and drawbacks of the Data Sense tool. For example, funds might be used to support a half- or full-time teaching assistant to help with student projects that experimented with sensor data collection, and used Data Sense for some of the processing and visualization. Another example of a possible project would be to produce video-based tutorials that would focus on data processing skills relevant to your particular discipline, using data as it would likely be used in your discipline. Finally, faculty might also consider developing smaller modules or student exercises using Data Sense, alongside the sort of report outlined above. As this is an experimental tool, Intel would appreciate feedback both on whether it was useful/appropriate in the classroom, and whether there were usability issues that need attention.

In addition to financial support, Intel will provide access to the software, and the research team that is developing it. This relationship could take a variety of forms, from a guest appearance by one of our researchers in class, to the team prioritizing feature requests or bug fixes on your behalf. It might even lead to a collaborative investigation into entirely new tools that might be necessary. For the purposes of intellectual property, all materials developed through the support of this grant will be dedicated to the public (i.e., open sourced and/or publishable without restriction from Intel). Where appropriate, curriculum materials will be made open access on a dedicated, shared website so that other faculty might also benefit. Proposals should specify which materials proposers intend to make open access.

Details about Data Sense to Consider Before Applying

Data Sense was built by a team co-led by an anthropologist and an engineer. It was originally built to help wearables users and other self-tracking enthusiasts to explore and reflect on patterns in their own data. It provides a fairly simple infrastructure for bringing datasets from different sources together, and visualizing them in various ways, focusing on temporal/spatial patterns, and linear correlation. It also has the ability to do more complex filtering tasks via a graphical interface (such as filtering one dataset by another), and the ability to create pools of data shared anonymously on an opt-in basis. Examples of its capabilities can be found at

The Application Process

Applications are due June 16, 2016. Recipients of awards will be notified June 30, 2016.

Submit your application.