Technology integration in project oriented design based learning for distance education

Technology plays critical role in delivering modern education to the next generation. Proper and effective use of technology is extremely important especially for distance education. Students who enroll in distance mode have a number of limitations as most of them work full time along with the commitments to the family. This paper discusses technology integration for the distance students based on the Project Oriented Design Based Learning.

Integration of cloud based learning in project oriented design based learning

The School of Engineering at Deakin University has been practicing design based learning as one of its engineering learning principles for further development in the learning and teaching process. It has been exploring the student and industry perspectives in this regards and has embarked in the development of a new framework for a project oriented design based learning approach for the development of the engineering curriculum. Along with this change in the engineering curriculum Deakin University also has been going through a major change in the delivery of education. The policy shift has been initiated through Live the Future: Agenda 2020 which focusses on Cloud and Located Learning. This change in policy has had an impact on delivery framework for the project oriented design based learning model which has been incorporated through the use of lecture videos, a learning management system called Cloud Deakin and online tutorials through the eLive system.

Infusing instructional design principles into an active student-centred social learning framework

Social and participatory media offer a plethora of ways for students to communicate, collaborate, and learn in schools. Using a social learning approach, Casey (2013a) investigated ways that social media could be integrated into Australian public high school classrooms to enhance student learning. In the process, she developed a social learning framework as discussed in Casey (2013b). Similarly, Davidson-Shivers and Hulon (2013; Hulon & Daidson-Shivers, 2013) suggest ways to employ ID principles to prepare college instructors and pre-service teachers to integrate technology into classrooms. Prior to that, Davidson-Shivers with Rasmussen (2006) developed an instructional design (ID) model for creating effective Web-based learning environments. Through collaboration, Casey and Davidson-Shivers consider a wide range of social learning and instructional design principles and approaches to help develop frameworks for new media integration that can work within varying levels of education.

Greater cognitive effort for better learning : tailoring an instructional design for learners with different levels of knowledge and motivation

The capacity limitation of working memory is a widely recognised determinant of human learning. A cognitive load exceeding the capacity hampers learning. Cognitive load can be controlled by tailoring an instructional design to levels of learner prior knowledge. However, such as design does not necessarily motivate to use the available capacity for better learning. The present review examines literatures on the effects of instructional design, motivation, emotional state, and expertise level on cognitive load and cognitive effort, which ultimately affect working memory performance and learning. This examination suggests further studies on the effects of motivation and negative emotional states on the use of working memory. Prospective findings would help better explain and predict individual differences in the use of working memory for cognitive learning and task performance.