Abstract

Data collection and analysis leading to the identification of variables that impact classroom performance, satisfaction, and early adoption of technology in distributed learning groups.

Issue

To identify both personality and group structural variables that contribute significantly to the success of distributed learning outcomes, early technology adoption, and satisfaction with the collaborative process.

Response

Students were given wireless computers to access access points installed on campus. Their research and communication activities were tracked and analyzed. Design teams from Cornell and Syracuse Universities were employed to study the impact of learning technologies through questionnaires, surveys, and internet tracking. The project was then extended to include wireless tool use in less formal learning contexts (campus tour using GPS and handheld technology and handheld applications for both children and adults for the Johnson Art Museum). Both contexts were designed to encourage collaboration and learning, social navigation, and to allow participation in the development of creative display.

Impact

The data analyzed has revealed that by varying contexts, populations, devices, and questions asked, many other questions can be answered -- what are the effects of mobile learning devices on classroom learning, what are users doing on the internet and why, how do users find information, how is learning transformed for children, and what are the social structures of effective teams? The answers have allowed the group to better understand the impact of technologies and how to design applications that improve further the potential impact for learning.

Funding Sources

• Private (e.g., commodity groups, foundations, companies)
• Other Federal non-USDA (e.g., NSF, NIH, DOA, DOD)

Collaborators

• Engineering College - Cornell
• Syracuse University
• Johnson Museum - Cornell
• Smithsonian Institute
• Langley Research
• Information Science - Cornell
• National Science Digital Library

Key Personnel

• Helene Hembrooke
• Kirsten Boehner
• Lori Lorigo
• Bing Pan
• Michael Stefanone
• Peggy Odom
• Connie Yuan
• Jeff Hancock
• Phoebe Sengers

All of the above are a part of the Human Computer Interaction Group, 301 College Avenue, Ithaca, NY 14850, 607-255-5530.