In this paper we aim to describe the process by which our personalised web-based collaborative teaching/learning methodology (CECIP - Collaboration - Evaluation - Critical thinking - Individual assessment - learner Profile) evolved originating from Vygotsky's theory and based on the (C) collaborative construction of student's knowledge, (E) developing evaluation and assessment skills, (C) developing critical thinking skills, (I) integrating individual evaluation and (P) generating learner profile. Our CECIP methodology integrates individual learning style dimensions and their preferences into e-learning environment by filling out MBTI, Gardner, GEFT and Felder-Silverman questionnaires during our four-semester-research. The paper covers the theoretical foundations of Learning Styles giving analogies to preferred learning strategies. A three-part-research process is described through which the described CECIP model emerged: (1) analysing Learning Styles and Learning Management Systems that claim to support their work; (2) raising the background knowledge of students in cognitive psychology in order to improve design and evaluation methodologies of multimedia learning materials; (3) personalising tasks and assessment based on Bloom's Taxonomy.
We survey here the state-of-the-art in open courseware initiatives worldwide. First, the MIT OpenCourseWare project is overviewed, as it has been the real starting point of the OCW movement. Usually, open courseware refers to a free and open digital publication of high quality university level educational materials that are organized as courses, and include course planning materials, evaluation tools, and thematic content, under a Creative Commons license. OCW is free and open, accessible to anyone, anywhere, and anytime via the Internet. The OCW initiative started in 2002, and it has been followed by many more programs that offer open access to courseware: Carnegie Mellon Open Learning Initiative, Harvard Medical School's MyCourses, Webcast.Berkeley, Rice University's Connexions, OpenCourseWare Consortium, Open Education Resources Commons, and The Saylor Foundation's Free Education Initiative, along with other major open courseware projects worldwide. The prospects for futur development of open courseware are taken into consideration, while its potential to provide for both social construction of knowledge and for development of open educational models, and therefore for E-Learning 2.0 and Web 2.0 is emphasized.
Cloud computing is a significant alternative in today's educational perspective. The technology gives the students and teachers the opportunity to quickly access various application platforms and resources through the web pages on-demand. Unfortunately, not all educational institutions often have an ability to take full advantages of the newest information technology. The paper analyzes possibilities of the cloud computing technology that can help educational institutions to support the process of teaching and learning.
There is also presented a cloud computing technology based solution introducing the MS Live@Edu environment as a means of communication and collaboration between lecturers and students. The authors have a successful experience of using MS Live@Edu during 3 academic years for delivering about 10 unique courses for approximately 700 students in Kaunas University of Technology (KTU). The use of MS Live@Edu environment for educational purposes is summarized by explaining the advantages of cloud computing gained both by lecturers and students.
Student evaluations to measure the teaching effectiveness of instructor's are very frequently applied in higher education for many years. This study investigates the factors associated with the assessment of instructors teaching performance using two different data mining techniques; stepwise regression and decision trees. The data collected anonymously from students' evaluations of Management Information Systems department at Bogazici University. Additionally, variables related to other instructor and course characteristics are also included in the study. The results show that, a factor summarizing the instructor related questions in the evaluation form, the employment status of the instructor, the workload of the course, the attendance of the students, and the percentage of the students filling the form are significant dimensions of instructor's teaching performance.
The article presents the consideration of grading scales used for education outcomes in different countries, describes likeness and differences of applied grading scales. Application of the European Credit Transfer and Accumulation System (ECTS) grading scale is investigated according of the analysis of scientific literature as well as cases of its mistaken application. The article provides a model for grades transfer from one scale into another, specifies the results of experimental testing of the introduced model, and analyzes cases of mistaken grades transfer.
Artificial Neural Networks (ANN's) are nowadays a common subject in different curricula of graduate and postgraduate studies. Due to the complex algorithms involved and the dynamic nature of ANN's, simulation software has been commonly used to teach this subject. This software has usually been developed specifically for learning purposes, because the existing general packages often lack of a convenient user interface, and are too complex or inadequate for these goals. Since ANN's algorithms, types and applications grow regularly, this solution becomes more and more complex and inefficient. In this paper, we present Visual NNet, a learning-oriented ANN's simulation environment, which overcomes this problem by reusing Matlab Neural Networks Toolbox (MNNT), a well-known, comprehensive and robust ANN implementation. Visual NNet combines an on-purpose learning oriented design with the advantages of an ANN's implementation like MNNT. Furthermore, reusing MNNT has done Visual NNet development more cost-effective, fast and reliable.
In this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting different weight coefficient values for the criteria and solving single-criterion optimization problems (SOPs). However, the WS approach does not guarantee either finding evenly distributed solutions of a Pareto front, or finding Pareto optimal solutions in non-convex regions. In order to solve the problems, some methods have been proposed. In this paper, an adaptive weighted-sum (AWS) approach has been used. We suggest presenting the solutions, obtained not only by the weighted-sum method, but also by the adaptive weighted-sum approach, to a decision maker (DM). Thus the decision making will be facilitated.
Contests are usually applied in the academic environment to simulate real professional situations that require from the participants a more pro-active attitude than the one shown in conventional coursework. Although they are commonly applied in the scope of a unique course, the contest described here was an extracurricular experience applied in an Information System undergraduate program. The evaluation of the contest is also presented; the objective was to assess the role of the contest as a tool to bring together interdisciplinary subjects, complementary to the traditional disciplinary structure of the program curriculum. The results indicate that a significant portion of the participants noticed increase in their knowledge after the contest, which is verified by statistical tests. However, students from the first stages received more benefits, probably because such students were more motivated and had more available time to be involved in the contest activities.
Distance, e-education supported by technological development have enhanced educational processes by combining achievements from various scientific fields. This techno-educational enhancement has happened within the last decade. Virtual learning has grown in popularity as a new way of learning that gives preference to learn in convenient time and places, using specially prepared learning materials. The progression of technological developments implies the rise of user demands. It also aspires to look for flexible, but qualitative, training and learning ways. One of the outcomes is adaptive and intelligent learning environments that show to become a common tool used for virtual learning.
This paper focuses on the key feature elements of adaptive learning environments (ALE), also researching about intelligent agents and their behaviour in ALEs. The method to provide individual learning syllabus according student knowledge in rational way is proposed. It is based on latent semantic indexing algorithm and is featured with an ability to update syllabus according individual learning outcomes of the student. This is yet another tool in a teacher's tool box. The description of results obtained during the exploration of proposed method is presented as well.
This paper explores our experiences in deploying a video application tool in film studies, and its evaluation in terms of realistic contextual end-users who have real tasks to perform in a real environment. We demonstrate our experiences and core lesson learnt in deploying our novel movie browser application with undergraduate and graduate students completing a Film Studies course in Dublin City University over a semester. We developed a system called MOVIEBROWSER2 that has two types of browsing modes: Advanced and Basic. In general, students found that the features we provided were beneficial for their studies. Some issues or mismatches arose during the trial. A `wish-list' was drawn up that might be useful for the future system developer. The contribution and achievements reported in this article are on the demonstration and exploration of how advances in technology can be deployed, and media can be accessed in the context of a real user community. Exploring the usage indicates a positive acceptance among students, besides lessons learned that are important for further investigation.