A cooperative small group facilitated case-based learning method has been used in the medical college at the researchers educational institution since the 2003-2004 academic year. They were designed to be a supplement to a primarily lecture-based curriculum where it was believed that these cooperative cases helped students to develop a better understanding of the material taught in the lectures, although no rigorous investigations had been completed. The purpose of this study was to investigate the impact of these cooperative facilitated small group cases on five specific outcomes which included: 1) achievement, 2) knowledge confidence, 3) student satisfaction, 4) students perceived time on task, and 5) the students perceptions of the degree to which they believed a facilitator helped them to learn the material. These outcomes for cooperative learning (CL) were compared with individual learning (IL) outcomes. Quantitative data on student achievement and knowledge confidence were collected using a pre-test post-test 10 multiple choice question quiz. A brief questionnaire was also distributed to students to collect data regarding student satisfaction, time on task and perceived helpfulness of the facilitator.<p>Fifty-nine medical students were randomly assigned to either the CL or IL cohort (cooperative cohort, n = 32; individual cohort, n = 27). All students were blinded to the purpose of the study until all data were collected at the end of the investigation. Students completed the 10 multiple choice question pre-test. After each question they rated their level of confidence (on a scale from 1 to 10) that they had chosen the correct answer. Immediately after completion of the pre-test, they worked on the case, either cooperatively or individually. One week after the pre-test and case, the students completed the post-test quiz with the same questions, as well as the questionnaire.<p>A repeated-measures MANOVA was used to compare achievement and confidence in the CL (n =19) and IL (n =13) cohorts. An alpha level of .05 was used for all statistical tests. Effect sizes (d) were calculated for within-group and between-groups comparisons for achievement and confidence. Descriptive data on student satisfaction, time on task and facilitator helpfulness were gathered from the questionnaire and compared between groups.<p> Within-group results from the study showed that CL had a greater impact on student achievement and confidence than IL (achievement, d = 0.57 vs. 0.16; confidence, d = 0.52 vs. 0.14). The results for the statistical analysis did not reach significance for achievement or confidence. Between-groups effect sizes were calculated for average pre- to post-test change for achievement and confidence (achievement, d = 0.35; confidence, 0.40). Students in the CL cohort reported spending more time on task before and during the case session and less after the session. They also reported greater levels of satisfaction with the learning experience than IL group. The majority of students (90.5%) in the CL cohort felt that the facilitator helped them to learn.<p>The findings from this study showed that this CL method had a greater impact on the five outcomes outlined above compared to the IL method. Students made greater gains in achievement and confidence. They also spent more time on task, and had higher levels of satisfaction with the learning experience. Students in the CL cohort also believed that the facilitator helped them to learn. Implications of the study include possible expanded use of the cases within the curriculum of this medical college although the demands of resources and curriculum content would have to be carefully considered.

It has been widely discussed that current practices of preservice teacher education are still far away from utilizing contemporary methods and strategies in its curriculum practices in Turkey. Preservice teachers are not provided enough classroom experiences connecting theory to teaching practice. As a result of this, many senior teachers need further guidance and supervision to transfer their knowledge into school environments. In order to address this failure in bridging what is learned and practiced in preservice teacher education to that of real class happenings, an experimental study was conducted with the application of an alternative method namely video-case based instruction. This research study aimed to examine the differences between traditional lecture based instruction and video-case based instruction in terms of their effectiveness of presenting the content at &ldquo / Introduction to Teaching Profession Course&rdquo / delivered to the preservice teachers. Additionally, the study also aimed to evaluate the attitudes of students toward video-case based instruction to which they were exposed. In this study, video-case based instruction and lecture based instruction were applied in three sessions of application and they were compared in terms of delivering the course content. Data were collected from two sections of EDS 119 Course during 2005-2006 fall semester by administrating pretests, posttests, questionnaires and interviews. Data analysis was carried out through both quantitative and qualitative analysis techniques. Results demonstrated that video-case based instruction demonstrated achievement of course content and support significant difference overall between video-case based instruction and lecture based instruction in content achievement. The participants of the study reported positive attitudes towards video-case based instruction both for its current application and future uses. The results revealed that using video-case based methods in preservice teacher education programs may be a viable alternative for allowing students connect real teaching practices with what they learn in their pedagogy courses.

The main purpose of this study is to compare the effectiveness of case- based learning method instruction over traditional method instruction on eleventh grade high school students&rsquo / understanding of solubility equilibrium concepts. In addition, students&rsquo / attitudes toward chemistry as a school subject and students&rsquo / epistemological beliefs were investigated. Sixty-two eleventh grade students from two classes of a chemistry course taught by the same teacher in Atakent High School in 2007-2008 spring semesters were enrolled in the study. The classes were randomly assigned as experimental and control group. Experimental group students instructed by case-based learning method in which specific situations, generally real-life examples were discussed. On the other hand, control group students were instructed by traditional method. Solubility Concept Test was administered as a pre-test to both groups. Moreover, Attitude Scale toward chemistry and Epistemological Belief Scale about chemistry were administered as a pre- and post-tests to all groups. Solubility Equilibrium Concept Test and Open-Ended Solubility Equilibrium Concept Test were administered as a post-test to all groups. The results showed that case based learning instruction produced significantly greater achievement in understanding of solubility equilibrium than the traditional instruction. Also, there was a significant difference between the experimental and the control group with respect to their epistemological beliefs and attitudes toward chemistry as a school subject in the favor of experimental group. Results obtained revealed that students have several misconceptions related to solubility equilibrium. Case based learning was effective for remediation of misconceptions and enhancing students&rsquo / understanding in comparison to traditional method.

The aim of this study was to investigate the changes on what the prospective elementary mathematics teachers noticed as they watched video cases and discussed online. More specially, I wanted to answer the question &ldquo / To what extent the elementary prospective mathematics teachers&rsquo / noticing with respect to reform-minded teaching changes during their video case-based teacher education, in terms of teacher and student roles?&rdquo / With this question in mind, I asked senior prospective mathematics teachers at METU to watch six video cases depicting real elementary mathematics classrooms, and then discuss these cases in an online forum. The research was conducted during the 2008-2009 fall semester. Participants were asked to write reflection papers after watching a video each week. The online discussions took place in Metu Online-Net ClassR online forum, and each discussion was about a long week. The research study was qualitative in nature. Specifically, it was a case study research. Prospective teachers&rsquo / reflection papers on the videos, the online discussions, and interviews with the selected 15 focus participants at the beginning, in the middle and at the end of the study were the data sources. The data were analyzed through the qualitative data analysis techniques. The findings suggested that prospective teachers&rsquo / noticing skills with respect to the teacher and student roles in reform-minded teaching and learning were developed throughout the online video-case based discussions.

The rapid growth of the Internet has shaped up the global economy. The stock market information is thus more and more transparent. Although the investors can get more helpful information to judge future trend of the stock market, they may get wrong judgments because the stock market data are too huge to be completely analyzed. Therefore, the purpose of this study is to develop an artificial stock market analyst by employing the information technology with high speed and performance, as well as integrating the artificial intelligence techniques. We exploit case-based reasoning to simulate the analysts in using history stock market data, employ the artificial neural network to imitate the analysts in analyzing the macrofactors of stock market, and apply the fuzzy logic to humanize the artificial stock market analyst in making judgments close to the real stock market analysts. The artificial stock market analyst would use the modified case-based reasoning system combined with the artificial neural network, and incorporate the designed membership functions for macrofactors of stock market. We expect the system to improve the accuracy of Taiwan electric stock price prediction by applying macrofactors from the technical analysis indicators and financial crisis factors, and make better stock trading strategies.

Quality of service is commonly used to shape network traffic to meet specified criteria. The various scenarios include limiting and reserving bandwidth for a particular application, host or user, prioritizing latency sensitive traffic or equal distribution of unreserved bandwidth. The DynShaper software distributes and controls a traffic quota by more sophisticated means than fixed per user limits and simple disconnection after the user reaches the limit. It distributes the quota on a daily basis, where each day receives the same share. The users are sorted into predefined groups with different bandwidths depending on their recent consumption. This classification is periodically updated to ensure the sorting order is maintained. The bandwidths of these groups is dynamically adjusted depending on the actual consumption to provide an efficient utilization. This thesis presents another distribution model using a case-based reasoning approach, a method for machine learning which is classified as conventional artificial intelligence. Case-based reasoning tries to solve new problems based on the solutions of similar problems from the past. Controlling the network traffic to remain within a fixed quota can be modeled as such a problem if the traffic patterns are recurring. Possible solutions can be derived from statistical data and altered to suit the new problems. When an untested solution is applied, the software supervises the execution and revises the solution accordingly, if the actual results deviate from the precalculated schedule.

Up to 1998, the Institutes of Nursing in the United Arab Emirates have been using the traditional lecture-based teaching/learning process in their graduate-nursing program. In 1998, however, these Institutes adopted a new approach; namely, the case-based learning (CBL) for the education of their nursing students. This approach emphasizes the use of self-directed and cooperative learning that is supposed to help students increase their critical thinking (CT) level. As the students were experiencing changes in the teaching practices, it was important to determine the effect of the teaching and learning approaches on students' CT abilities, and to describe suggestions needed for improvement. Empirically, very little is known regarding the influence of CBL on a student's CT. The question then remains, as to whether students who have undergone case-based learning, differ significantly in their CT abilities from those who studied in the traditional method. This study investigates the critical thinking skills in relation to two types of nursing educational programs: (a) the traditional teaching and (b) the case-based learning. The professed purpose of the study in hand is to measure and compare the level of critical thinking in participants from each of the two programs. The instrument of measurement guiding this study is the model developed by Facione and Facione (1998). The design has been a comparative descriptive survey. The critical thinking abilities were measured by the CCTST, which was administered to 38 participants from the traditional curriculum and 65 from the case-based learning curriculum who agreed to participate in the study. When the scores were analyzed by using the independent sample 1- test, this study found that, in general, participants from both programs performed badly on the CCTST. Nevertheless, the CBL program participants performed significantly better when compared to the traditional program participants in all aspects of the CCTST. / Thesis (M.Cur.)-University of Natal, Durban, 2001.

The purpose of this study was three-fold: to measure the ability of the Medical Explorers case-based curriculum to improve higher order thinking skills; to evaluate the impact of the Medical Explorers case-based curriculum to help students be self directed learners; and to investigate the impact of the Medical Explorers case-based curriculum to improve student attitudes of the life sciences. The target population for this study was secondary students enrolled in advanced life science programs. The resulting sample (n = 71) consisted of 36 students in the case-based experimental group and 35 students in the control group. Furthermore, this study employed an experimental, pretest-posttest control group research design. The treatment consisted of two instructional strategies: case-based learning and teacher-guided learning. Analysis of covariance indicated no treatment effect on critical thinking ability or Motivation and Self-regulation of Learning. However, the Medical Explorers case-based curriculum did show a treatment effect on student attitudes toward the life sciences. These results seem to indicate that case-based curriculum has a positive impact on students’ perspectives and attitudes about the study of life science as well as their interest in life science based careers. Such outcomes are also a good indicator that students enjoy and perceive the value to use of case studies in science, and because they see value in the work that they do they open up their minds to true learning and integration. Of additional interest was the observation that on average eleventh graders showed consistently stronger gains in critical thinking, motivation and self-regulation of learning strategies, and attitudes toward the life sciences as compared to twelfth grade students. In fact, twelfth grade students showed a pre to post loss on the Watson-Glaser and the MSLQ scores while eleventh grade students showed positive gains on each of these instruments. This decline in twelfth grade performance is an endemic indicator of underlying problems that exists in this transitional year of education and supports the need to strengthen the transitional connections between high schools and institutions of higher learning. / Department of Biology

Development of an automated method for classifying digital images using a combination of image quality modification and Bayesian classification is the subject of this thesis. The specific example is classification of images obtained by monitoring molten plastic in an extruder. These images were to be classified into two groups: the “with particle” (WP) group which showed contaminant particles and the “without particle” (WO) group which did not. Previous work effected the classification using only an adaptive Bayesian model. This work combines adaptive image quality modification with the adaptive Bayesian model. The first objective was to develop an off-line automated method for determining how to modify each individual raw image to obtain the quality required for improved classification results. This was done in a very novel way by defining image quality in terms of probability using a Bayesian classification model. The Nelder Mead Simplex method was then used to optimize the quality. The result was a “Reference Image Database” which was used as a basis for accomplishing the second objective. The second objective was to develop an in-line method for modifying the quality of new images to improve classification over that which could be obtained previously. Case Based Reasoning used the Reference Image Database to locate reference images similar to each new image. The database supplied instructions on how to modify the new image to obtain a better quality image. Experimental verification of the method used a variety of images from the extruder monitor including images purposefully produced to be of wide diversity. Image quality modification was made adaptive by adding new images to the Reference Image Database. When combined with adaptive classification previously employed, error rates decreased from about 10% to less than 1% for most images. For one unusually difficult set of images that exhibited very low local contrast of particles in the image against their background it was necessary to split the Reference Image Database into two parts on the basis of a critical value for local contrast. The end result of this work is a very powerful, flexible and general method for improving classification of digital images that utilizes both image quality modification and classification modeling.

A look at today's US military will see them operating much beyond the scope of protecting and defending the United States. These operations now consist of, but are not limited to humanitarian aid, disaster relief, and conflict resolution. This broad spectrum of operational environments has necessitated a transformation of the individual military services into a hybrid force that can leverage the inherent and emerging capabilities from the strengths of those under the umbrella of the Department of Defense (DOD), this concept has been coined Joint Operations. Supporting Joint Operations requires a new approach to determining a viable military logistics support system. The logistics architecture for these operations has to accommodate scale, time, varied mission objectives, and imperfect information. Compounding the problem is the human in the loop (HITL) decision maker (DM) who is a necessary component for quickly assessing and planning logistics support activities. Past outcomes are not necessarily good indicators of future results, but they can provide a reasonable starting point for planning and prediction of specific needs for future requirements. Adequately forecasting the necessary logistical support structure and commodities needed for any resource intensive environment has progressed well beyond stable demand assumptions to one in which dynamic and nonlinear environments can be captured with some degree of fidelity and accuracy. While these advances are important, a holistic approach that allows exploration of the operational environment or design space does not exist to guide the military logistician in a methodical way to support military forecasting activities. To bridge this capability gap, a method called A Technique for Logistics Architecture Selection (ATLAS) has been developed. This thesis describes and applies the ATLAS method to a notional military scenario that involves the Navy concept of Seabasing and the Marine Corps concept of Distributed Operations applied to a platoon sized element. This work uses modeling and simulation to incorporate expert opinion and knowledge of military operations, dynamic reasoning methods, and certainty analysis to create a decisions support system (DSS) that can be used to provide the DM an enhanced view of the logistics environment and variables that impact specific measures of effectiveness.