This study investigated the relationships among perceived course value, student engagement, deep learning strategies, and surface learning strategies. The study relied on constructs from previous studies to measure course value, engagement, surface learning strategy, and deep learning strategy. Statistically significant findings were observed between perceived course value, student engagement, and deep learning strategy. Surface learning strategies occur when the student's perceived value of the course is low. These findings suggest that deep learning strategies occur when students are engaged in the learning process and their perceived value of the course content is high. While there is much research to support the finding that engagement is a way to help students learn, the findings of this study show that course value has a greater positive influence on deep learning and surface learning strategies than engagement. By understanding and enhancing perceived value and engagement, the ultimate goal of enhancing deep learning should result.

This study investigated the relationships among perceived course value, student engagement, deep learning strategies, and surface learning strategies. The study relied on constructs from previous studies to measure course value, engagement, surface learning strategy, and deep learning strategy. Statistically significant findings were observed between perceived course value, student engagement, and deep learning strategy. Surface learning strategies occur when the student's perceived value of the course is low. These findings suggest that deep learning strategies occur when students are engaged in the learning process and their perceived value of the course content is high. While there is much research to support the finding that engagement is a way to help students learn, the findings of this study show that course value has a greater positive influence on deep learning and surface learning strategies than engagement. By understanding and enhancing perceived value and engagement, the ultimate goal of enhancing deep learning should result.

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This paper presents the birth of an open source learning object repository (OSLOR) from design to implementation. Critical design issues such as user interface, type of LOR, standards, metadata, and the programming language were considered in the process. These issues revolve around the essential characteristics of LOR, i.e., interoperability, reusability, and accessibility. Conclusion and recommendations are made for future advancement of the OSLOR and its sustainability.

This panel will inform the audience about an undergraduate IT program's preparation and process for ABET accreditation. The School of Information Technology at Macon State College is seeking accreditation from the Accreditation Board of Engineering and Technology (ABET). ABET accredits academic programs that prepare graduates for entry into the following professional disciplines: 1) applied science, 2) computing, 3) engineering, and 4) technology. (http://www.abet.org). Specifically, the panel will discuss three themes essential in preparing the IT program for ABET accreditation. They are: 1) program educational objectives, 2) program outcome, and 3) program continuous improvement.