Browsing by Subject "Computer aided instruction"

Now showing 1 - 9 of 9

Open Access
Advantage of using Web 2.0 applications in class
(ACM, 2010) Aydinol, Ayşe Begüm; Gültekin, Özgür
In this study the advantage of using Web 2.0 applications in terms of increasing student attention and enthusiasm will be emphasized by presenting the example of community service activities which were supported by the blog usage. Copyright 2010 ACM.
Open Access
Alternate strategies for tutorial modules in intelligent tutoring systems
(ASME, 1992) Cankat, E.; Güvenir, Altay H.
Intelligent Tutoring Systems (ITS) have now reached a structure in which the major components of an instructional system are separated in a way that provides both the system and the student with a flexibility within the learning environment. This atmosphere is an interactive, realistic scene similar to actual face-to-face teacher and student instructional environment. A major problem in determining the tutorial strategy of an ITS is how to balance the executive control of the system. In other words to what extend will the teacher be allowed to control the session and where is the point the computer will not allow any external interference. The dividing line is hard to draw and very sensitive to changes in the instructional strategy. Another aspect is that even the student would like to take over the control of execution mostly by asking questions. Now we have three main elements of the system: computer, teacher and student. Who should possess what level of executive control? This is the question we would like to discuss from different points of view in the domain of teaching science courses at secondary school level.
Open Access
Collaborative digital environments to enhance the creativity of designers
(Elsevier, 2015-01) Karakaya, A. F.; Demirkan H.
This study explores the interaction of the essential components of creativity and collaboration in a digital environment in the design process. The framework is based on Amabile’s componential theory of creativity, which is composed of three intra-individual components of creativity and the social environment. The digital environment as the social component of creativity provides the technical infrastructure for the analysis of data related to creativity and collaboration. Protocol coding method is used for the analysis of the qualitative and quantitative data stored in The Modular Object Oriented Developmental Learning Environment (MOODLE) forum posts that were formed by the comments or critiques given during the collaboration process by the team members, instructors or jury members. Findings indicate that the social environment component named as the reactivity to proposals is closely related to idea generation as the creative relevant process component and group interaction as the task motivation component. Furthermore, it is found that the number of sketches and design ideas produced through critiques are the main design issues that enhance creativity in collaborative digital environments.
Open Access
The effect of competition on learning in games
(Pergamon Press, 2015) Cagiltay, N. E.; Ozcelik, E.; Ozcelik, N. S.
Today serious games are having an important impact on areas other than entertainment. Studies show that serious games have a potential of creating learning environments to better reach the educational and training goals. The game design characteristics and game elements are need to be explored in detail for increasing the expected benefits of the gaming environments. In this study, the effect of competition, one of the design elements of game environments, on learning is analyzed experimentally. The study is conducted with 142 students. The results of this study show that when a competition environment is created in a serious game, motivation and post-test scores of learners improve significantly. The results of this study are expected to guide the serious game designers for improving the potential benefits of serious games. © 2015 Elsevier Ltd.
Open Access
The effect of uncertainty on learning in game-like environments
(Pergamon Press, 2013) Ozcelik, E.; Cagiltay, N. E.; Ozcelik, N. S.
Considering the role of games for educational purposes, there has an increase in interest among educators in applying strategies used in popular games to create more engaging learning environments. Learning is more fun and appealing in digital educational games and, as a result, it may become more effective. However, few research studies have been conducted to establish principles based on empirical research for designing engaging and entertaining games so as to improve learning. One of the essential characteristics of games that has been unexplored in the literature is the concept of uncertainty. This study examines the effect of uncertainty on learning outcomes. In order to better understand this effect on learning, a game-like learning tool was developed to teach a database concept in higher education programs of software engineering. The tool is designed in two versions: one including uncertainty and the other including no uncertainty. The experimental results of this study reveal that uncertainty enhances learning. Uncertainty is found to be positively associated with motivation. As motivation increases, participants tend to spend more time on answering the questions and to have higher accuracy in these questions. © 2013 Elsevier Ltd. All rights reserved.
Open Access
The effect of video tutorials on learning spreadsheets
(ACM, 2010) Aydınol, Ayşe Begüm; Gültekin, Özgür
In this study a video tutorial for spreadsheet use (Excel) will be prepared by two undergraduate students by using a recorder and applied on a group of students to understand how effective this kind of a tutorial is to increase student achievement. Copyright 2010 ACM.
Open Access
How k-12 students search for learning?: analysis of an educational search engine log
(ACM, 2014-07) Usta, Arif; Altıngövde, İsmail Şengör; Vidinli, İ. B.; Özcan, R.; Ulusoy, Özgür
In this study, we analyze an educational search engine log for shedding light on K-12 students' search behavior in a learning environment. We specially focus on query, session, user and click characteristics and compare the trends to the findings in the literature for general web search engines. Our analysis helps understanding how students search with the purpose of learning in an educational vertical, and reveals new directions to improve the search performance in the education domain. Copyright 2014 ACM.
Open Access
An inquiry into the learning-style and knowledge-building preferences of interior architecture students
(Elsevier, 2016-05) Demirkan, H.
This study explores the learning-style and knowledge-building preferences of interior architecture students using Felder-Soloman's Index of Learning Styles. Considering the learning and knowledge-building skills of students in design education, this study concludes that the instructor should not only be a conveyor of knowledge but also a facilitator. The findings indicate that design students' preferred learning styles are as follows, in descending order: Sensing/Intuitive, Visual/Verbal, Active/Reflective and Sequential/Global. In the two-way analysis, where the student's design studio grade was the dependent variable, significant effects were obtained for each scale. Furthermore, double interactions were highly significant between the Active/Reflective and Sensing/Intuitive scales and between the Active/Reflective and Sequential/Global scales. © 2016 Elsevier Ltd. All rights reserved.
Open Access
Recognizing daily and sports activities in two open source machine learning environments using body-worn sensor units
(Oxford University Press, 2014-11) Barshan, B.; Yüksek, M. C.
This study provides a comparative assessment on the different techniques of classifying human activities performed while wearing inertial and magnetic sensor units on the chest, arms and legs. The gyroscope, accelerometer and the magnetometer in each unit are tri-axial. Naive Bayesian classifier, artificial neural networks (ANNs), dissimilarity-based classifier, three types of decision trees, Gaussian mixture models (GMMs) and support vector machines (SVMs) are considered. A feature set extracted from the raw sensor data using principal component analysis is used for classification. Three different cross-validation techniques are employed to validate the classifiers. A performance comparison of the classifiers is provided in terms of their correct differentiation rates, confusion matrices and computational cost. The highest correct differentiation rates are achieved with ANNs (99.2%), SVMs (99.2%) and a GMM (99.1%). GMMs may be preferable because of their lower computational requirements. Regarding the position of sensor units on the body, those worn on the legs are the most informative. Comparing the different sensor modalities indicates that if only a single sensor type is used, the highest classification rates are achieved with magnetometers, followed by accelerometers and gyroscopes. The study also provides a comparison between two commonly used open source machine learning environments (WEKA and PRTools) in terms of their functionality, manageability, classifier performance and execution times. © 2013 © The British Computer Society 2013. All rights reserved.