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In its efforts to continue the modernization of its curriculum, the Faculty of Dentistry at the University of Toronto has developed a series of web-based interactive learning applications. This article presents the production cycle of these new interactive learning objects and the preliminary study conducted to measure the students’ perception of the objects’ effectiveness for learning. Three applications are described in detail in this article, namely: Panoramic Radiography: Principles and Interpretation, Gross Human Anatomy 3D Atlas and Restorative Dentistry: Virtual and Interactive Cavity Preparation. Each of these applications introduces unique elements of interactivity with the learning content, specifically designed to address hard-to-grasp concepts in their respective dental disciplines. The results of a student survey conducted post-deployment suggest that the visual and interactive features embedded in the three applications have the potential to induce positive outcomes in mediating the students’ conceptualization of difficult theoretical notions.
Building computerized mechanisms that will accurately, immediately and continually recognize a learner’s affective state and activate an appropriate response based on integrated pedagogical models is becoming one of the main aims of artificial intelligence in education. The goal of this paper is to demonstrate how the various kinds of evidence could be combined so as to optimize inferences about affective states during an online self-assessment test. A formula-based method has been developed for the prediction of students’ mood, and it was tested using data emanated from experiments made with 153 high school students from three different regions of a European country. The same set of data is analyzed developing a neural network method. Furthermore, the formula-based method is used as an input parameter selection module for the neural network method. The results vindicate to a great degree the formula-based method’s assumptions about student’s mood and indicate that neural networks and conventional algorithmic methods should not be in competition but complement each other for the development of affect recognition systems. Moreover, it becomes apparent that neural networks can provide an alternative for and improvements over tutoring systems’ affect recognition methods.
High-ranking officers require advanced military education in war tactics for future combat. However, line officers rarely have time to take such courses on campus. The conventional solution to this problem used to take the inefficient correspondence courses. Whereas Internet technologies progress, online course is the current trend for military training. However, the question is what distance learning methodology best suits such a proprietary learning purpose. This study presents a sequential process of developing distance learning courses in advanced military education. Further, the Petri-Net analytical approach is adopted to discover the essential interaction requirements of advanced military education delivered via Internet. This study developed a systematic method for designing e-learning systems according to specific requirements of target courses. The proposed approach starts by comparing on-campus programs with the existing e-learning systems to identify the steps required to transform the program into an e-learning system. After first outlining the pedagogy of the on-campus program, its proposed teaching flow through the Internet is then sketched. Finally, the Petri-Net model was used for in-depth analysis of the stages affecting the learning curve of the line office taking e-learning courses. The example of a “Joint Operations” AME course elaborated the presented approach. An e-learning system prototype was also designed accordingly. Lastly, an experiment was conducted to verify the efficiency of the presented approach.
While there has been extensive experimental research on haptics, less has been conducted on cross-modal interactions between visual and haptic perception and even less still on cross-modal applications in instructional settings. This study looks at a simulation on the principles of levers using both visual and haptic feedback: one group received visual and haptic feedback while the other just visual feedback. Using the triangulation of learning scores, eye tracking data, and video analysis of interaction with the levers, the efficacy of haptic feedback to improve learning was explored. The results indicate that while the total fixation time on the levers and numeric readout was greater for the visual and haptic group, very similar patterns of visual attention were seen between groups. Perhaps surprisingly, the visual only group scored higher on an embedded assessment. Explanations for these results are synthesized from theories of cross-modal perception and cognitive architecture.
Brazil is a developing country that has undergone important changes at the social, economic, scientific and educational levels. A main policy challenge at present is related to the unequal distribution of vital resources, including technology. In the educational context, many changes have been observed, such as a decrease in analphabetism and an increase in the number of physicians, lawyers, and scientists. In this paper we will describe the educational experience involving the use of information technology, especially computers, at Brazilian primary and secondary schools. We live in a technological era in which it is important to educate our children to be aware of the impact of technology on society and the environment in general, as well as how to personally deal with them. From home to workplace, digital technological tools have become a part of day-to-day life. Digital technology has become essential in everyday life, and demands have been placed on schools to educate students so as to make them “technologically literate”. Millions of Reals (R$) have been invested by the Brazilian government to equip schools with computers and communication tools, but low technological literacy remains a serious challenge. To address this problem, it is crucial to elucidate the real advantages and disadvantages of the use of computers in the educational system.
Learning Management Systems (LMS) are web-based systems that allow instructors and/or students to share materials, submit and return assignments, and communicate online. In this study, we explored the uses and perceived benefits of using a LMS to support traditional classroom teaching as reported by instructors and students at a large American Midwestern university. We examined two years of survey data focusing on specific uses of the LMS that emphasized either efficient communication or interactive teaching and learning practices. We matched aggregate user log data with corresponding survey items to see if system use was consistent with patterns seen in the survey results. Findings suggest that instructors and students value tools and activities for efficient communication more than interactive tools for innovating existing practices. However, survey item analysis reveals that instructors and students also highly value the teaching and learning tools within the LMS.
In this work, we analyze the results obtained by a group of freshmen students in a test of prior knowledge on technical drawing carried out before and after attending an introductory course on this subject. The aim of this course was to help students to gain knowledge necessary to take full advantage of the CAD software that is regularly used to teach engineering graphics education in the classroom. Two aspects of the results will be analyzed. First, if this kind of course is good enough to show an improvement in students’ ability. As will be shown, the score obtained by the students improved after attending the course. Second, we have analyzed the results in order to know if the students’ prior knowledge is good enough to allow them coping with their first year. Although the answer to this question depends on many factors, it will be shown that an introductory course is a useful tool to reduce the possible gap between the students’ prior knowledge and the basic knowledge on geometry that should be requested to a first-year engineering student. The kind of test we propose here could also be implemented to test the cognitive abilities of the students.
Though blogs and wikis have been used to support knowledge management and e-learning, existing blogs and wikis cannot support different types of knowledge and adaptive learning. A case in point, types of knowledge vary greatly in category and viewpoints. Additionally, adaptive learning is crucial to improving one’s learning performance. This study aims to design a semantic bliki system to tackle such issues. To support various types of knowledge, this study has developed a new social software called “bliki” that combines the advantages of blogs and wikis. This bliki system also applies Semantic Web technology to organize an ontology and a variety of knowledge types. To aid adaptive learning, a function called “Book” is provided to enable learners to arrange personalized learning goals and paths. The learning contents and their sequences and difficulty levels can be specified according to learners’ metacognitive knowledge and collaborative activities. An experiment is conducted to evaluate this system and the experimental results show that this system is able to comprehend various types of knowledge and to improve learners’ learning performance.
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