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Design, development, and assessment of mobile applications: The case for problem-based learning Massey, A. P., Ramesh, V., & Khatri, V. IEEE Transactions.

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Presentation on theme: "Design, development, and assessment of mobile applications: The case for problem-based learning Massey, A. P., Ramesh, V., & Khatri, V. IEEE Transactions."— Presentation transcript:

1 Design, development, and assessment of mobile applications: The case for problem-based learning Massey, A. P., Ramesh, V., & Khatri, V. IEEE Transactions on Education, Vol.49, No.2, 2006

2 Abstract Via a collaborative effort involving industry sponsors, university technology services, and multiple academic units engaged in information technology education, a graduate- level course called Mobile Applications Development (MAD) was created. The core innovativeness of MAD lies in its delivery structure as a problem-based learning course centered on emerging technologies like mobile technology that brings together students with diverse backgrounds from different academic units across the campus. MAD culminates in an industry-sponsored competition, where student teams present their mobile solution to a panel of expert judges from industry and higher education. Via MAD and the associated competitions, students, faculty, and institutional partners can explore the opportunities and challenges associated with mobile technologies.

3 Background: context and pedagogical issues Prior research suggests that learning is facilitated when the following happens: 1.The learner is engaged in solving a real-world problem. 2.The learner is provided relevant experience that can be used as a foundation for acquiring new knowledge. 3.The learner is guided in problem solving by appropriate coaching that is gradually withdrawn. 4.The learner can create, invent, and explore new and personal ways to use his or her new skill knowledge.

4 Designing mobile applications development as a PBL course Lebow s PBL principles guided the design and implementation of MAD. 1.Design an authentic problem. 2.Design a task and the learning environment to reflect the complexity of a work environment in which they should be able to function. 3.Design the environment to support and challenge thinking. 4.Anchor all learning activities to the larger problem. 5.Encourage testing of ideas against alternative views and contexts.

5 Guiding questions

6 Comparison of three MAD offerings


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