The effectiveness of explicit strategy instruction on the top level structure of a text

Thesis (M.Ed.)-- Brock University, 1995.

The effects of teaching a mathematics problem solving strategy on the problem solving ability of grade nine students

Forty grade 9 students were selected from a small rural board in southern Ontario. The students were in two classes and were treated as two groups. The treatment group received instruction in the Logical Numerical Problem Solving Strategy every day for 37 minutes over a 6 week period. The control group received instruction in problem solving without this strategy over the same time period. Then the control group received the treat~ent and the treatment group received the instruction without the strategy. Quite a large variance was found in the problem solving ability of students in grade 9. It was also found that the growth of the problem solving ability achievement of students could be measured using growth strands based upon the results of the pilot study. The analysis of the results of the study using t-tests and a MANOVA demonstrated that the teaching of the strategy did not significaritly (at p s 0.05) increase the problem solving achievement of the students. However, there was an encouraging trend seen in the data.

The impact of integrated programming on student attitude and achievement in grade 9 academic mathematics and science

This research studioo the effect of integrated instruction in mathematics and~ science on student achievement in and attitude towards both mathematics and science. A group of grade 9 academic students received instruction in both science and mathematics in an integrated program specifically developed for the purposes of the research. This group was compared to a control group that had received science and mathematics instruction in a traditional, nonintegrated program. The findings showed that in all measures of attitude, there was no significant difference between the students who participated in the integrated science and mathematics program and those who participated in a traditional science and mathematics program. The findings also revealed that integration did improve achievement on some of the measures used. The performance on mathematics open-ended problem-solving tasks improved after participation in the integrated program, suggesting that the integrated students were better able to apply their understanding of mathematics in a real-life context. The performance on the final science exam was also improved for the integrated group. Improvement was not noted on the other measures, which included EQAO scores and laboratory practical tasks. These results raise the issue of the suitability of the instruments used to gauge both achievement and attitude. The accuracy and suitability of traditional measures of achievement are considered. It is argued that they should not necessarily be used as the measure of the value of integrated instruction in a science and mathematics classroom.

Winâ Foy : functional object-oriented programming language

This thesis will introduce a new strongly typed programming language utilizing Self types, named Win--*Foy, along with a suitable user interface designed specifically to highlight language features. The need for such a programming language is based on deficiencies found in programming languages that support both Self types and subtyping. Subtyping is a concept that is taken for granted by most software engineers programming in object-oriented languages. Subtyping supports subsumption but it does not support the inheritance of binary methods. Binary methods contain an argument of type Self, the same type as the object itself, in a contravariant position, i.e. as a parameter. There are several arguments in favour of introducing Self types into a programming language (11. This rationale led to the development of a relation that has become known as matching [4, 5). The matching relation does not support subsumption, however, it does support the inheritance of binary methods. Two forms of matching have been proposed (lJ. Specifically, these relations are known as higher-order matching and I-bound matching. Previous research on these relations indicates that the higher-order matching relation is both reflexive and transitive whereas the f-bound matching is reflexive but not transitive (7]. The higher-order matching relation provides significant flexibility regarding inheritance of methods that utilize or return values of the same type. This flexibility, in certain situations, can restrict the programmer from defining specific classes and methods which are based on constant values [21J. For this reason, the type This is used as a second reference to the type of the object that cannot, contrary to Self, be specialized in subclasses. F-bound matching allows a programmer to define a function that will work for all types of A', a subtype of an upper bound function of type A, with the result type being dependent on A'. The use of parametric polymorphism in f-bound matching provides a connection to subtyping in object-oriented languages. This thesis will contain two main sections. Firstly, significant details concerning deficiencies of the subtype relation and the need to introduce higher-order and f-bound matching relations into programming languages will be explored. Secondly, a new programming language named Win--*Foy Functional Object-Oriented Programming Language has been created, along with a suitable user interface, in order to facilitate experimentation by programmers regarding the matching relation. The construction of the programming language and the user interface will be explained in detail.

Genetic programming for the RoboCup Rescue Simulation System

The Robocup Rescue Simulation System (RCRSS) is a dynamic system of multi-agent interaction, simulating a large-scale urban disaster scenario. Teams of rescue agents are charged with the tasks of minimizing civilian casualties and infrastructure damage while competing against limitations on time, communication, and awareness. This thesis provides the first known attempt of applying Genetic Programming (GP) to the development of behaviours necessary to perform well in the RCRSS. Specifically, this thesis studies the suitability of GP to evolve the operational behaviours required of each type of rescue agent in the RCRSS. The system developed is evaluated in terms of the consistency with which expected solutions are the target of convergence as well as by comparison to previous competition results. The results indicate that GP is capable of converging to some forms of expected behaviour, but that additional evolution in strategizing behaviours must be performed in order to become competitive. An enhancement to the standard GP algorithm is proposed which is shown to simplify the initial search space allowing evolution to occur much quicker. In addition, two forms of population are employed and compared in terms of their apparent effects on the evolution of control structures for intelligent rescue agents. The first is a single population in which each individual is comprised of three distinct trees for the respective control of three types of agents, the second is a set of three co-evolving subpopulations one for each type of agent. Multiple populations of cooperating individuals appear to achieve higher proficiencies in training, but testing on unseen instances raises the issue of overfitting.

Automatic Structure Generation using Genetic Programming and Fractal Geometry

Three dimensional model design is a well-known and studied field, with numerous real-world applications. However, the manual construction of these models can often be time-consuming to the average user, despite the advantages o ffered through computational advances. This thesis presents an approach to the design of 3D structures using evolutionary computation and L-systems, which involves the automated production of such designs using a strict set of fitness functions. These functions focus on the geometric properties of the models produced, as well as their quantifiable aesthetic value - a topic which has not been widely investigated with respect to 3D models. New extensions to existing aesthetic measures are discussed and implemented in the presented system in order to produce designs which are visually pleasing. The system itself facilitates the construction of models requiring minimal user initialization and no user-based feedback throughout the evolutionary cycle. The genetic programming evolved models are shown to satisfy multiple criteria, conveying a relationship between their assigned aesthetic value and their perceived aesthetic value. Exploration into the applicability and e ffectiveness of a multi-objective approach to the problem is also presented, with a focus on both performance and visual results. Although subjective, these results o er insight into future applications and study in the fi eld of computational aesthetics and automated structure design.

Enabling and Measuring Complexity in Evolving Designs using Generative Representations for Artificial Architecture

As the complexity of evolutionary design problems grow, so too must the quality of solutions scale to that complexity. In this research, we develop a genetic programming system with individuals encoded as tree-based generative representations to address scalability. This system is capable of multi-objective evaluation using a ranked sum scoring strategy. We examine Hornby's features and measures of modularity, reuse and hierarchy in evolutionary design problems. Experiments are carried out, using the system to generate three-dimensional forms, and analyses of feature characteristics such as modularity, reuse and hierarchy were performed. This work expands on that of Hornby's, by examining a new and more difficult problem domain. The results from these experiments show that individuals encoded with those three features performed best overall. It is also seen, that the measures of complexity conform to the results of Hornby. Moving forward with only this best performing encoding, the system was applied to the generation of three-dimensional external building architecture. One objective considered was passive solar performance, in which the system was challenged with generating forms that optimize exposure to the Sun. The results from these and other experiments satisfied the requirements. The system was shown to scale well to the architectural problems studied.

The Impact of a Text-Reader Support Program on Intermediate Students' Reading Comprehension

This study examined the efficacy of providing four Grade 7 and 8 students with reading difficulties with explicit instruction in the use of reading comprehension strategies while using text-reader software. Specifically, the study explored participants' combined use of a text-reader and question-answering comprehension strategy during a 6-week instructional program. Using a qualitative case study methodology approach, participants' experiences using text-reader software, with the presence of explicit instruction in evidence-based reading comprehension strategies, were examined. The study involved three phases: (a) the first phase consisted of individual interviews with the participants and their parents; (b) the second phase consisted of a nine session course; and (c) the third phase consisted of individual exit interviews and a focus group discussion. After the data collection phases were completed, data were analyzed and coded for emerging themes, with-quantitativ,e measures of participants' reading performance used as descriptive data. The data suggested that assistive technology can serve as an instructional "hook", motivating students to engage actively in the reading processes, especially when accompanied by explicit strategy instruction. Participants' experiences also reflected development of strategy use and use of text-reader software and the importance of social interactions in developing reading comprehension skills. The findings of this study support the view that the integration of instruction using evidence-based practices are important and vital components in the inclusion oftext-reader software as part of students' educational programming. Also, the findings from this study can be extended to develop in-class programming for students using text-reader software.

Reflection Reframed: The Process of Photography as Strategy for Teachers' Reflective Practice

Teacher reflective practice is described as an effective method for engaging teachers in improving their own professional learning. Yet, some teachers do not understand how to effectively engage in the reflective processes, or prefer not to formalize the process through writing a reflective journal as taught in most teacher education programs. Developing reflective skills through the process of photography was investigated in this study as a strategy to allow enhanced teacher reflection for professional and personal growth. The process of photography is understood as the mindful act of photographing rather than focusing on the final product-the image. For this study, 3 practicing educators engaged in photographic exercises as a reflective process. Data sources included transcribed interviews, participant journal reflections, and sketchbook artifacts, as well as the researcher's personal journal notes. Findings indicated that, through the photographic process, (a) teacher participants developed new and individual strategies for professional leaming; and (b) teacher participants experienced shifts in the way they conceptualized their personal worldviews.

Genetic Programming for Non-Photorealistic Rendering

This thesis focuses on developing an evolutionary art system using genetic programming. The main goal is to produce new forms of evolutionary art that filter existing images into new non-photorealistic (NPR) styles, by obtaining images that look like traditional media such as watercolor or pencil, as well as brand new effects. The approach permits GP to generate creative forms of NPR results. The GP language is extended with different techniques and methods inspired from NPR research such as colour mixing expressions, image processing filters and painting algorithm. Colour mixing is a major new contribution, as it enables many familiar and innovative NPR effects to arise. Another major innovation is that many GP functions process the canvas (rendered image), while is dynamically changing. Automatic fitness scoring uses aesthetic evaluation models and statistical analysis, and multi-objective fitness evaluation is used. Results showed a variety of NPR effects, as well as new, creative possibilities.

Peer-Led Team Learning as an Instructional Strategy for Secondary School Science

This study investigated the impact of an instructional learning strategy, peer-led team learning (PLTL), on secondary school students' conceptual understanding of biology concepts related to the topic of evolution. Using a mixed methods approach, data were gathered quantitatively through pre/posttesting using a repeated measures design and qualitatively through observations, questionnaires, and interviews. A repeated measures design was implemented to explore the impact of PLTL on students' understanding of concepts related to evolution and students' attitudes towards PLTL implementation. Results from quantitative data comparing pre/posttesting were not able to be compared through inferential statistics as a result of inconsistencies in the data due to a small sample size and design limitations; however, qualitative data identified positive attitudes towards the implementation of PLTL, with students reporting gains in conceptual understanding, academic achievement, and interdependent work ethic. Implications of these findings for learning, teaching, and the educational literature include understanding of student attitudes towards PLTL and insight into the role PLTL plays in improving conceptual understanding of biology concepts. Strategies are suggested to continue further research in the area of PLTL.

The Synthesis and Coordination Chemistry of Two Families of Polydentate Ligands - Exploring Their Potential for the Preparation of Molecule-Based Magnets

The synthesis and studies of two classes of poly dentate ligands are presented as two projects. In project 1, four new carboxamide ligands have been synthesised via the condensation of 2,2',6,6'-tetrachloroformyl-4,4'-bipyridine or 2,6-dichloroformyl pyridine together with heterocyclic amines containing pyridine or pyrazole substituents. The coordination chemistry of these ligands has been investigated and studies have shown that with a Cu(II) salt, two carboxamide ligands LJ and L2 afford large clusters with stoichiometries [Cu8(L1)4Cl16].CHCl3.5H2O.7CH3OH (I) and [Cu9(L2)6Cl6].CH3OH.5H2O.(C2H5)3N (II) respectively. [molecular diagram availabel in pdf]. X-ray diffraction studies of cluster (I) reveal that it has approximate S4 symmetry and is comprised of four ligands and eight copper (II) centers. Here, coordination takes place via amide 0 atoms, and pyrazole nitrogens. This complex is the first reported example of an octanuclear copper cluster with a saddle-shaped structure. The second cluster comprises nine copper ions that are arranged in a cyclic array. Each ligand coordinates three copper centers and each copper ion shares two ligands to connect six ligands with nine copper ions. The amide nitrogens are completely deprotonated and both amide Nand 0 atoms coordinate the metal centres. The cluster has three-fold symmetry. There are six chloride ions, three of which are bridging two neighbouring Cu(II) centres. Magnetic studies of (I) and (II) reveal that both clusters display weak antiferromagnetic interactions between neighbouring Cu(II) centers at low temperature. In the second project, three complexes with stoichiometries [Fe[N302](SCN)2]2 (III), R,R-[Fe[N3O2](SCN)2 (IV) and R,R-]Fe[N3O2](CN)2] (V) were prepared and characterized, where [N302] is a pentadentate macrocycle. Complex (III) was prepared via the metal templated Schiff-base condensation of 2,2',6,6'-tetraacetyl-4,4'-bipyridine together with 3,6-dioxaoctane-I,8-diamine and comprises of a dimeric macro cycle where the two Fe(II) centres are in a pentagonal-bipyramidal environment with the [N302] ligands occupying the equatorial plane and two axial NCS ligands. Complexes (IV) and (V) were prepared via the condensation of 2,6-diacetylpyridine together with a chiral diamine in the presence of FeCh. The synthetic strategy for the preparation of the chiral diamine (4R,5R)-4,5-diphenyl-3,6-dioxa-I,8-octane-diamine was elucidated. The chirality of both macrocycles (IV) and (V) was probed by circular dichroism spectroscopy. The crystal structure of (IV) at 200 K contains two independent molecules in the unit cell, both of which contain a hepta-coordinated Fe(II) and axial NCS ligands. Variable temperature magnetic susceptibility and structural studies are consistent with a high spin Fe(II) complex and show no evidence of any spin crossover behaviour. In contrast, the bis cyanide derivative (V) crystallizes with two independent molecules in the unit cell, both of which have different coordination geometries consistent with different spin states for the two Fe(II) centres. At 250 K, the molecular structure of (V) shows the presence of both 7- and a 6-coordinate Fe(II) complexes in the crystal lattice. As the temperature is lowered, the molecules undergo a structural change and at 100 K the structural data is consistent with a 6- and 5-coordinate Fe(II) complex in the unit cell. Magnetic studies confirm that this complex undergoes a gradual, thermal, spin crossover transition in the solid state. Photomagnetic measurements indicate this is the first chiral Fe (II) sea complex to exhibit a LIESST.

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.

Passive Solar Building Design Using Genetic Programming

Passive solar building design is the process of designing a building while considering sunlight exposure for receiving heat in winter and rejecting heat in summer. The main goal of a passive solar building design is to remove or reduce the need of mechanical and electrical systems for cooling and heating, and therefore saving energy costs and reducing environmental impact. This research will use evolutionary computation to design passive solar buildings. Evolutionary design is used in many research projects to build 3D models for structures automatically. In this research, we use a mixture of split grammar and string-rewriting for generating new 3D structures. To evaluate energy costs, the EnergyPlus system is used. This is a comprehensive building energy simulation system, which will be used alongside the genetic programming system. In addition, genetic programming will also consider other design and geometry characteristics of the building as search objectives, for example, window placement, building shape, size, and complexity. In passive solar designs, reducing energy that is needed for cooling and heating are two objectives of interest. Experiments show that smaller buildings with no windows and skylights are the most energy efficient models. Window heat gain is another objective used to encourage models to have windows. In addition, window and volume based objectives are tried. To examine the impact of environment on designs, experiments are run on five different geographic locations. Also, both single floor models and multi-floor models are examined in this research. According to the experiments, solutions from the experiments were consistent with respect to materials, sizes, and appearance, and satisfied problem constraints in all instances.