This CPATH award supports a curriculum initiative to inject computational thinking capability into computer science and gerontology disciplines at the local and state levels with a plan to conduct, assess, and to analyze the outcomes to guide future nationwide efforts. The proposal consists of three major components: Developing a new interdisciplinary curriculum track in Gerotechnology culminating in an undergraduate certificate; Transforming the existing SmartHome Laboratory at Iowa State University into an open project platform, so that experiments and projects on the Smart Home can be run from remote locations; and Establishing an open source community on software based on service-oriented architecture to support collaborative projects. The new track is strongly supported by the latter two components to ensure that the proposed curriculum is supported by meaningful materials, examples, and projects and that enable community building between disciplines, stakeholders, and institutions.
Intellectual Merit: The proposed work introduces a new pedagogy that is interdisciplinary, incorporates the recent developments in multiple disciplines, and focuses on hands-on and practical experience. The SmartHome Laboratory allows students to make lasting contributions to real and meaningful applications and to collaborate with students from other colleges and backgrounds. Computer science students will be able to demonstrate their computational thinking competences through human-centered learning opportunities. Students from outside computer science should have opportunities to work in teams in order to fully utilize modern technologies that have begun to transform their professions. A competent team of experts in the fields and experienced practitioners has been assembled to ensure success of the project. The main national impact should be the creation a model of a program for a tightly focused application, gerontechnology, a new collaborative program model for the nation.
Broader Impact: In addition to the main goal of injecting computational thinking capabilities into the curriculum, the investigators plan proactive recruiting and support of a diverse group of students, including those with disabilities, females, and underrepresented minorities. The proposed curriculum provides stronger incentives and better accommodations to these groups while disseminating exciting, immediately applicable, cutting edge technologies. The results from learning and project activities can be disseminated immediately to the aging population and people with disabilities through service learning courses and family outreach extension.
We had set out to create a gerontechnology curriculum at Iowa State University as well as to promote awareness and interdisciplinary collaboration on gerontechnology. Our approach was designed to achieve these overall objectives through three components: design and implementation of a gerontechnology curriculum, creation of an open source community, and establishing an open project platform. We were able to accomplish the following six outcomes: 1) Six course modules developed for Gerotechnology: This included aging, assistive technology, system modeling and service computing, software engineering, design principles, and human computer interface, as shown in Figure 1. Seven faculty members from three departments and programs started a five-phase course design process in the fall of 2009. One of the core requirements in this design process was to embed Computational Thinking skills in learning activities, and to emphasize basic system modeling techniques and software engineering practices. Students learnt how to systematically analyze problem domains and use methodologies for requirements elicitation, software design, and software testing. In addition to Computational Thinking, the collaborating faculty members also identified two other crosscutting themes - Interdisciplinary teamwork and Universal design - to be integrated with every module in the course materials. 2) New pedagogy developed and adopted for interdisciplinary teamwork: Adapted best practices from computer science, human sciences, and design under one roof, as shown in Figure 1. The learning modules were primarily designed to be taught in a sequence within one semester of an independent, interdisciplinary course on gerontechnology. However, they were also designed to be flexible and were incorporated as a new module in multiple existing courses, such as "Aging and the Family", "Fundamentals of Computer Network", "Graphic Design and Human Interaction" and "CHI Competition Workshop". Some of the topics identified has also been incorporated in an ongoing Smart Home Seminar. The experience of interdisciplinary curriculum and course design has been presented in Frontier in Education conference and disseminated through the round table discussion at International Society of Gerontechnology 2010 in Vancouver, as well as submitted to conference Design Research Society and ACM SIGCSE. 3) Successfully disseminated computational thinking (CT) to non-CS students: Enrolled a total of 27 students from 4 different colleges in the new gerontechnology course, 48% of them female and 40% minority, and one student with special needs. We were able to evaluate the effectiveness of the newly created materials as well as the pedagogical approach through both quantitative and qualitative methods. The evaluation was conducted using an IRB-approved 37-question survey for paired pre-test and post-test for quantitative evaluation, as well as by gathering data from separate focus groups of students and from faculty members. Overall, a total of more than 350 students has been evaluated and the results shows significant improvements in students’ Computational Thinking and interdisciplinary teamwork skills, as illustrated by Figure 2 and Figure 3 which show the results from one of the courses. 4) Open Project Platform established: Developed an open-source smart home lab API and reusable software artifacts to formulate this platform. The number and diversity of sensors, self-care medical equipment, and mobile devices has seen considerable improvement, so the OPP is capable of supporting large groups of students working on a wide variety of semester-long projects on gerontechnology and assistive technology. The creation of virtual machine based instruction significantly improves the capacity of our Smart Home Laboratory to support concurrent projects from students (including those at remote locations) and collaborating researchers alike. The platform includes a coherent programming API, a software library for smart environments, and a programmer’s manual designed to guide students with minimal programming experience. 5) Community building: Established and strengthened links to older adult community by establishing a senior mentor program with local retirement and assisted living facilities so that older adults can interact and collaborate with students. Some of the older adult residents mentored undergraduate students on the usefulness and usability of students’ ideas. Through the senior mentor program, the learning module/pedagogy development process, and the participations and exchanges in the related engineering/design/gerontology conferences, we have successfully built a tight knit community consisting of educators and researchers in the field of computer science, gerontology, design and human-computer interface, as well as the practitioners, caregivers, and the older adult community in Iowa. We have also established a network of like-minded professionals from organizations such as GSA, IEEE Education society, IEEE CS society, and the Iowa Undergraduate CS Consortium, who are interested in educating the next generation of gerontechnologists. 6) Innovative gerontechnology prototypes created: Representative projects include Retriever, an item locator using security cameras and image recognition software to help elderly locates lost wallet, key and glasses; OnHealth, a fall detection and emergency responding system using Kinect; and Health Navigator, a recommendation system that records, displays, and analyzes users’ weight, blood pressure and other data to make meaningful suggestions to the user.
