Academic literature on the topic 'Conceptual change model based instruction'

The purpose of the study was to investigate the effect of conceptual change oriented instruction accompanied by computer-based interactive conceptual change text (CBICCT) on 11th grade students understanding of electrochemistry and attitude toward chemistry. The study was conducted in an anatolian high school in Ankara with two science classes with 66 students in May 2009. A quasi experimental design was used. The classes was assigned to groups<br>one as control group and the other as experimental group. While control group was given traditional instruction, experimental group was given conceptual change oriented instruction accompanied by CBICCT. Electrochemistry Concept Test (ECT) was administered before and after treatment and Attitude Toward Chemistry Scale (ATCS) was administered after treatment to collect data about students&rsquo<br>concepts about electrochemistry and attitude toward chemistry, respectively. To investigate possible covariates, Science Process Skills Test (SPST) was administered after treatment. The collected data were analyzed with two way analysis of covariance (ANCOVA) and two way analysis of variance (ANOVA). Gain scores of ECT was analyzed with two way ANCOVA when SPST scores controlled as covariate and the results showed that the experimental group developed significantly better understanding of concepts than control group. The results also showed that no mean difference between males and females, and no interaction effect between instruction method and gender were found. The analysis of ATCS showed that experimental group developed significantly more positive attitude toward chemistry than control group. However, no significant difference between males and females, and no significant interaction between method and gender in terms of attitude toward chemistry were found.

The overall goal of this study was to better understand how the academic system affects change in instructional practices, referred to as instructional change, in engineering education. To accomplish this goal, and acknowledging the complex nature of academia, I used a technique designed to understand complex systems called System Dynamics Modeling. With such technique, I created a conceptual System Dynamics Model (SDM) that illustrates how the factors in the academic system interact dynamically to drive or hinder faculty motivation to adopt Research-based Instructional Strategies (RBIS) in their courses. The creation of this model followed a process that combined research literature with data gathered from 17 professors at an Engineering Department in another country. The model was constructed through an iterative process of systematically reviewing the literature, gather empirical data and creating Causal Loop Diagrams (CLD). The CLD are representations of the different causal relationships between elements in a system which ultimately create what we called virtuous or vicious (reinforcing) cycles and balancing cycles. The whole idea was not to find the causes for professors' motivation to change but how the factors in the academic system reinforce or limit such motivation. With this model I offered a different answer to the calls for change in engineering education toward increasing the pedagogical quality of our learning environments. My biggest argument is that previous instructional change initiatives have yielded low to moderate success, because effective instructional change would require a perspective that accounts for the complex nature of academia. With this study I am providing a different understanding of instructional change by using a system perspective that shows the interactions of elements within a complex system that ultimately influences faculty to adopt RBIS in their courses.<br>Doctor of Philosophy<br>The overall goal of this study was to better understand how the academic system affects change in instructional practices, referred to as instructional change, in engineering education. To accomplish this goal, and acknowledging the complex nature of academia, I used a technique designed to understand complex systems called System Dynamics Modeling. With such technique, I created a conceptual System Dynamics Model (SDM) that illustrates how the factors in the academic system interact dynamically to drive or hinder faculty motivation to adopt Research-based Instructional Strategies (RBIS) in their courses. The creation of this model followed a process that combined research literature with data gathered from 17 professors at an Engineering Department in another country. The model was constructed through an iterative process of systematically reviewing the literature, gather empirical data and creating Causal Loop Diagrams (CLD). The CLD are representations of the different causal relationships between elements in a system which ultimately create what we called virtuous or vicious (reinforcing) cycles and balancing cycles. The whole idea was not to find the causes for professors’ motivation to change but how the factors in the academic system reinforce or limit such motivation. With this model I offered a different answer to the calls for change in engineering education toward increasing the pedagogical quality of our learning environments. My biggest argument is that previous instructional change initiatives have yielded low to moderate success, because effective instructional change would require a perspective that accounts for the complex nature of academia. With this study I am providing a different understanding of instructional change by using a system perspective that shows the interactions of elements within a complex system that ultimately influences faculty to adopt RBIS in their courses.

The purpose of this study was to investigate the effects of conceptual change based instruction accompanied by demonstrations (CCBIAD) and gender on 11th grade students&rsquo<br>understanding and achievement in rate of reaction concepts, and their attitudes toward chemistry as a school subject compared to traditionally designed chemistry instruction (TDCI). Sixty nine 11th grade students from two classes in a public high school in Ankara participated in this study in the Fall Semester of 2008-2009. These classes were randomly assigned as control and experimental groups. In the control group TDCI was used, while in the experimental group CCBIAD was used as instructional methods. Rate of Reaction Concept Test, Rate of Reaction Achievement Test, and Attitude Scale toward Chemistry were administered to both groups as pre-tests and post-tests to assess students&rsquo<br>understanding of rate of reaction concepts, achievement in these concepts, and attitudes toward chemistry, respectively. Science Process Skills Test was given at the beginning of the study to control students&rsquo<br>science process skills. After treatment six students from each group were interviewed to determine their misconceptions about rate of reaction. The hypotheses were tested by using Analysis of Covariance (ANCOVA) and Two-Way Analysis of Variance (ANOVA). The results show that CCBIAD used a significantly better acquisition of scientific conceptions related to rate of reaction than TDCI. In addition, there was a significant effect of CCBIAD on students&rsquo<br>attitudes toward chemistry. There was no significant effect of gender on both students&rsquo<br>understanding of rate of reaction concepts and their attitudes toward chemistry.

The main purpose of this study was to compare the effectiveness of the cooperative learning based on conceptual change conditions and traditionally designed science instruction on 7th grade students&rsquo<br>understanding of chemical and physical changes and classification of matter concepts and attitudes toward science as a school subject. In this study 102 seventh grade students from four classes of a Science Course instructed by the two teachers from ODT&Uuml<br>G.V. &Ouml<br>zel ilk&ouml<br>gretim Okulu took part. One of the classes of each teacher was randomly assigned as experimental group, which were instructed with cooperative learning based on conceptual change conditions and the other classes were assigned as control group, which were instructed traditionally. This study was conducted during the 2004-2005 fall semester over a period of four weeks. In this study, to examine the effect of the treatment on dependent variables<br>science achievement related to chemical and physical changes and classification of matter concepts measured with Classification and Changes of Matter Concepts Test, and science attitude scores measured with Attitude Scale Toward Science as a school subject. Science Process Skills Test was used at the beginning of the study to determine students&rsquo<br>science process skills. ANCOVA and ANOVA were used testing the hypotheses of the study. The results showed that the cooperative learning based on conceptual change conditions group had a significantly higher scores with respect to achievement related to chemical and physical changes and classification of matter concepts than the traditionally designed science instruction group. However, there is no significant difference between the mean scores of cooperative learning based on conceptual change conditions group and traditionally designed science instruction group with respect to attitudes toward science as a school subject. Science process skills were a strong predictor for the achievement related to chemical and physical changes and classification of matter concepts. It may be useful to use the results of this study and instruments and strategies developed for this study for classroom teachers in order to help students to reduce or eliminate their misconceptions.

<p>Today’s information systems engineering involves large number of stakeholders, wide geographical distribution and wide range of tools. Success in system engi-neering depends on effective human communication. Early understanding and modelling of the problem domain is a key to manage large scale systems and pro-jects. This requires stakeholders to reach a certain level of shared interpretation of the domain referred throughout the development</p><p>We propose a method for semantics driven change impact assessment. In our method, first a collaborative problem analysis is conducted. The problem analysis results in an agreed and committed common understanding of the prob-lem domain, expressed in a conceptual domain model. The constructed concep-tual domain-specific model is then actively used as a communication medium, e.g., to abstract development objects from representation format in order to expli-cate their semantics. Stakeholders browse the domain model and interactively as-sociate to product fragments by selecting concept clusters that best describe the contents (intended meaning) of the product fragments.</p><p>Associations of the development objects with concepts from domain model, as well as the domain model itself constitute the basis for change impact assess-ment throughout the development. Every revision of a development object in-vokes change impact notifications that are either confirmed or rejected. Accumu-lated statistics are used to refine associations via the domain model to the direct dependency links among development objects.</p><p>The method has been implemented in a prototype system CO2SY and has been evaluated in an experiment, where a set of test users has been provided with a problem domain description including a domain model and a set of develop-ment objects. The experiment was based on two real world cases. Users were asked to perform tasks using the prototype and two comparative tools. The method and prototype have been evaluated with respect to actual performance and users perceptions. The result shows actual effectiveness, perceived ease of use and usefulness comparing to other tools used in the experiment, as well as intention of the subjects to use the method in future.</p><p>A discussion of future research directions and possible revisions of the method concludes the thesis.</p>

[Truncated abstract] During the last fifty years mathematical models of catchment hydrology have been widely developed and used for hydrologic forecasting, design and water resources management. Most of these models need large numbers of parameters to represent the flow generation process. The model parameters are estimated through calibration techniques and often lead to ‘unrealistic’ values due to structural error in the model formulations. This thesis presents a new strategy for developing catchment hydrology models for representing streamflow and salinity generation processes. The strategy seeks to ‘learn from data’ in order to specify a conceptual framework that is appropriate for the particular space and time scale under consideration. Initially, the conceptual framework is developed by considering large space and time scales. The space and time scales are then progressively reduced and conceptual model complexity systematically increased until ultimately, an adequate simulation of daily streamflow and salinity is achieved. This strategy leads to identification of a few key physically meaningful parameters, most of which can be estimated a priori and with minimal or no calibration. Initially, the annual streamflow data from ten experimental catchments (control and cleared for agriculture) were analysed. The streamflow increased in two phases: (i) immediately after clearing due to reduced evapotranspiration, and (ii) through an increase in stream zone saturated area. The annual evapotranspiration losses from native vegetation and pasture, the ‘excess’ water (resulting from reduced transpiration after land use change), runoff and deep storage were estimated by a simple water balance model. The model parameters are obtained a priori without calibration. The annual model was then elaborated by analysing the monthly rainfall-runoff, groundwater and soil moisture data from four experimental catchments. Ernies (control, fully forested) and Lemon (53% cleared) catchments are located in zone with a mean annual rainfall of 725 mm. Salmon (control, fully forested) and Wights (100% cleared) are located in zone with mean annual rainfall of 1125 mm. Groundwater levels rose and the stream zone saturated area increased significantly after clearing. From analysis of this data it was evident that at a monthly time step the conceptual model framework needed to include a systematic gain/loss to storage component in order to adequately describe the observed lags between peak monthly rainfall and runoff.