Supporting the Algebra I Curriculum with an Introduction to Computational Thinking Course

The Louisiana Workforce Commission predicts a 33.6% increase in computer science and mathematical occupations by 2022 and the Bureau of Labor Statistics foresees a 16% increase in computer scientists from 2018-2028. Despite these opportunities for job and financial security, the number of Louisiana students enrolled in a nationally accredited computing course is less than 1%, compared to national leaders California and Texas which have 3% and 3.8% of students respectively. Furthermore, the international assessments of mathematical literacy, PISA and TIMMS, both report American students continue to fall further behind their international peers in mathematics achievement. This thesis rejects these statistics as definitive and attempts to contribute to an expansion of the mathematical libraries of a computational thinking course that a teacher could use to support a standards-based Algebra I course. The framework presented in this thesis supports the Louisiana State University (LSU) STEM Pathway course entitled Introduction to Computational Thinking (ICT). The course introduces students to a systematic problem-solving approach in which they learn to solve problems computationally, that is, through abstraction, decomposition, and pattern recognition. ICT utilizes the functional programming language Haskell in the educational programming environment “CodeWorld” in order to create pictures and animations. Jean Piaget, the great child cognitive development psychologist, proclaimed “The goal of intellectual education is not to know how to repeat or retain ready-made truths”; rather, one becomes educated by “learning to master the truth by oneself” (Piaget, 1973). Because of the graphical outputs that one can easily code in CodeWorld, students have the ability to explore an algebraic concept with a computer programmed model, alongside the textbook’s given table, equation and graph. This thesis provides additional projects for supporting the Algebra I curriculum through LSU’s ICT course and an overview of the history of computing with an emphasis on highlighting some of the attempts that were undertaken within the past 80 years to use computational thinking and programming to support problem solving across disciplines, including the humanities, math and sciences

Evolving Spatio-temporal Data Machines Based on the NeuCube Neuromorphic Framework: Design Methodology and Selected Applications

The paper describes a new type of evolving connectionist systems (ECOS) called evolving spatio-temporal data machines based on neuromorphic, brain-like information processing principles (eSTDM). These are multi-modular computer systems designed to deal with large and fast spatio/spectro temporal data using spiking neural networks (SNN) as major processing modules. ECOS and eSTDM in particular can learn incrementally from data streams, can include ‘on the fly’ new input variables, new output class labels or regression outputs, can continuously adapt their structure and functionality, can be visualised and interpreted for new knowledge discovery and for a better understanding of the data and the processes that generated it. eSTDM can be used for early event prediction due to the ability of the SNN to spike early, before whole input vectors (they were trained on) are presented. A framework for building eSTDM called NeuCube along with a design methodology for building eSTDM using this are presented. The implementation of this framework in MATLAB, Java, and PyNN (Python) is presented. The latter facilitates the use of neuromorphic hardware platforms to run the eSTDM. Selected examples are given of eSTDM for pattern recognition and early event prediction on EEG data, fMRI data, multisensory seismic data, ecological data, climate data, audio-visual data. Future directions are discussed, including extension of the NeuCube framework for building neurogenetic eSTDM and also new applications of eSTDM

Atwood’s Machine and Electromagnetic Induction: A Real Quantitative Experiment to Analyze Students’ Ways of Reasoning

We report a research-based proposal on electromagnetic induction within the theoretical framework of the Model of Educational Reconstruction. The proposal is based on a sequence of inquiry-based experimental activities centered on hands-on materials and Real-Time quantitative experiments, through which students explore the phenomenology of electromagnetic induction. The sequence was planned to address Faraday-Neumann-Lenz law analyzing the involved physics quantities and constructing quantitative relationships between them. Our hypothesis was based on the idea that phenomenological explorations performed through online sensors promote a functional understanding of electromagnetic induction and help students to face the conceptual knots highlighted by international literature about these phenomena.The educational sequence was proposed to a sample of 87 high school students with the aim of analyzing the evolution of the educational processes employing a set of inquiry-based tutorials. The qualitative analysis of students’ answers demonstrates that students increased their knowledges in the analysis of electromagnetic induction phenomena recognizing the fundamental role of time-variation of the magnetic field flux in the Faraday-Neumann-Lenz la

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft