Funding Search Tools

A number of web-based tools exist which will help you to find funding for your project. In conducting a search for funds, there are a couple of key points which should be considered.

  1. Most agencies have well established areas of interest, and they fund proposals which help them achieve their goals. Study potential funding agencies closely to become familiar with their interests.
  2. A very valuable source of information with regard to charitable foundations is their IRS Tax Form 990. This tax document is publicly available and will contain information on their actual charitable giving. This information typically includes recipient names, locations, amount of award, project name, etc. This type of information, examined closely, reveals whether or not the foundation typically gives to institutions similar to ACU, the types of projects funded, geographic giving boundaries, and the typical monetary range of awards. Form 990’s can be accessed via GuideStar and Foundation Directory Online (see below).
  3. Some of the sites listed below have the capability to provide RSS feeds and/or set up user profiles which will then automatically send customized information regarding new opportunities. SPIN has some particularly powerful capabilities in this regard.

Following are a number of web-based search tools and other sites which should be useful in a search for funds.

ACU Subscription Services:

SPIN Info-Ed: Government and Non-Government Funding. Faculty and staff may access this website on a designated computer in the ORSP. Contact the Office of Research and Sponsored Programs at or 325-674-2885 for additional information. 

Foundation Center Directory Online: 

This is a very powerful search tool. ACU has subscribed to this service, but with license restrictions. Faculty and Staff may also access this website on a designated computer in the ORSP.

Government Funding Sources:

Non-Government Funding Sources: (Foundations/Corporations)

New in Reasearch

Dr. Ryan Jessup, Assistant Professor of Marketing

Dr. Jessup is interested in decisions.  What causes people to choose poorly?  How do learning and contextual factors influence choice?  In seeking to answer these questions, his research uses psychological models of motivation to distill the computational properties of decision making.  Computational modeling enhances research by requiring precision in theory formulation and constraining predictions.

One of Dr. Jessup’s primary streams of research concerns the behavioral differences between decisions when options are completely described vs. decisions when options must be learned about via experience.  Prior research found that individuals choose quite differently between the two paradigms but the reasons underlying the difference are poorly understood.  One of Dr. Jessup’s studies demonstrated that the reception of feedback overwhelms descriptive information, driving the behavioral differences between paradigms.  This work has led him and his colleagues (including Dr. John Homer and undergraduate researcher Allison Phillips) to build a new model that merges sophisticated decision making mechanisms with reinforcement learning in order to successfully predict behavior in both paradigms better than existing models. Dr. Jessup has previously received Cullen awards for this work and is currently seeking external funding to continue this fascinating line of research.

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