— The use of information tools is a common activity for students of any educational stage when they encounter online learning activities. Finding the relevant information for particular learning tasks is the topic of this paper as it investigates the use of information tools for a group of student participants. The paper describes and discusses the results with particular implications for use in higher education, and the findings suggest that improvement in assessment design and subsequent student learning may be achieved by structuring the purposefulness of information tools usage and online reading behaviors of university students.
This paper discusses the conceptualization, implementation and initial findings of a professional learning program (PLP) which used LEGO® robotics as one of the tools for teaching general technology (GT)in China’s secondary schools. The program encouraged teachers to design learning environments that can be realistic, authentic, engaging and fun. 100 general technology teachers from high schools in 30 provinces of China participated. The program aimed to transform teacher classroom practice, change their beliefs and attitudes, allow teachers to reflect deeply on what they do and in turn to provide their students with meaningful learning. Preliminary findings indicate that these teachers had a huge capacity for change. They were open-minded and absorbed new ways of learning and teaching. They became designers who developed innovative models of learning which incorporated learning processes that effectively used LEGO® robotics as one of the more creative tools for teaching GT.
This paper demonstrates a blended teaching approach based on student's online feedback in an engineering unit at Curtin University, Western Australia and shows how it enhances the overall learning outcomes. The student's feedbacks are collected using a university-wide online survey system known as eVALUate-an evaluation instrument for measuring students' perceptions of their engagements and learning outcomes. Students are encouraged to put their feedback through eVALUate in each semester for their enrolled units. In this study, such eVALUate survey data was used for a Civil Engineering unit -Water Engineering 361 for two consecutive years 2008-2009. In 2008, the teaching was done mainly using traditional method and the overall student's satisfaction and the learning outcomes were found to be below the university or faculty agreement. All the suggestions and criticisms in eVALUate were taken into consideration for improvement of the unit in the following year. In 2009, a blended teaching approach composed of traditional and e-learning system based on the student's feedback was adopted. The eVALUate survey data in 2009 shows that the learning outcomes and the overall student's satisfaction exceed the target of university and faculty agreement showing blended teaching approach based on student's feedback could provide satisfactory learning outcomes in an engineering unit.
With the growth of the Web, E-commerce activities are also becoming popular. Product recommendation is an effective way of marketing a product to potential customers. Based on a user’s previous searches, most recommendation methods employ two dimensional models to find relevant items. Such items are then recommended to a user. Further too many irrelevant recommendations worsen the information overload problem for a user. This happens because such models based on vectors and matrices are unable to find the latent relationships that exist between users and searches. Identifying user behaviour is a complex process, and usually involves comparing searches made by him. In most of the cases traditional vector and matrix based methods are used to find prominent features as searched by a user. In this research we employ tensors to find relevant features as searched by users. Such relevant features are then used for making recommendations. Evaluation on real datasets show the effectiveness of such recommendations over vector and matrix based methods.
