Student Motivation in the High School Mathematics Classroom

This research project is being conducted to better understand how to motivate students in the high school mathematics classroom and to encourage student involvement in the subject area. This project was chosen because through observation and conversations with students and other mathematics teachers I have found that mathematics is not always a strength or interest for students. As such, they have no motivation to do the work required in mathematics. Therefore, their grades are dropping along with their involvement levels. I want to have students fill out a questionnaire in order to learn what students want from a mathematics course in order to make it more interesting and worth while for them. My hope for this project is that it will help inform myself and other mathematics teachers about student motivation and how to best create lessons to motivate students in mathematics

Communication in the classroom: Practice and reflection of a mathematics teacher

This paper discusses the conceptions, practices and reflections about practices of a mathematics teacher, Maria, with respect to classroom communication and their change during the activity of a collaborative project involving a researcher and two other mathematics teachers. The case study of this teacher, who teaches at grades 5-6, draws on interviews and participant observation of the collaborative project meetings. The results show the relevance of the project to develop the teacher’s understanding of communication issues in her classroom, putting her practices under scrutiny, and developing richer communication processes between her and her students

Escaping the Trap of too Precise Topic Queries

At the very center of digital mathematics libraries lie controlled vocabularies which qualify the {\it topic} of the documents. These topics are used when submitting a document to a digital mathematics library and to perform searches in a library. The latter are refined by the use of these topics as they allow a precise classification of the mathematics area this document addresses. However, there is a major risk that users employ too precise topics to specify their queries: they may be employing a topic that is only "close-by" but missing to match the right resource. We call this the {\it topic trap}. Indeed, since 2009, this issue has appeared frequently on the i2geo.net platform. Other mathematics portals experience the same phenomenon. An approach to solve this issue is to introduce tolerance in the way queries are understood by the user. In particular, the approach of including fuzzy matches but this introduces noise which may prevent the user of understanding the function of the search engine. In this paper, we propose a way to escape the topic trap by employing the navigation between related topics and the count of search results for each topic. This supports the user in that search for close-by topics is a click away from a previous search. This approach was realized with the i2geo search engine and is described in detail where the relation of being {\it related} is computed by employing textual analysis of the definitions of the concepts fetched from the Wikipedia encyclopedia.Comment: 12 pages, Conference on Intelligent Computer Mathematics 2013 Bath, U

Least Squares Ranking on Graphs

Given a set of alternatives to be ranked, and some pairwise comparison data, ranking is a least squares computation on a graph. The vertices are the alternatives, and the edge values comprise the comparison data. The basic idea is very simple and old: come up with values on vertices such that their differences match the given edge data. Since an exact match will usually be impossible, one settles for matching in a least squares sense. This formulation was first described by Leake in 1976 for rankingfootball teams and appears as an example in Professor Gilbert Strang's classic linear algebra textbook. If one is willing to look into the residual a little further, then the problem really comes alive, as shown effectively by the remarkable recent paper of Jiang et al. With or without this twist, the humble least squares problem on graphs has far-reaching connections with many current areas ofresearch. These connections are to theoretical computer science (spectral graph theory, and multilevel methods for graph Laplacian systems); numerical analysis (algebraic multigrid, and finite element exterior calculus); other mathematics (Hodge decomposition, and random clique complexes); and applications (arbitrage, and ranking of sports teams). Not all of these connections are explored in this paper, but many are. The underlying ideas are easy to explain, requiring only the four fundamental subspaces from elementary linear algebra. One of our aims is to explain these basic ideas and connections, to get researchers in many fields interested in this topic. Another aim is to use our numerical experiments for guidance on selecting methods and exposing the need for further development.Comment: Added missing references, comparison of linear solvers overhauled, conclusion section added, some new figures adde

Deep Learning in Sports Prediction

Sports prediction has always been an interesting problem in the entertainment industry. Many data scientists have come out different methods on this problem. We hope to see how well a neural network model can predict an individual game outcome and the final ranking on NBA data. We examined the possibility of different unbiased deep learning models can perform as well as other mathematics methods. We were also looking for what types of data are more influential for the models. Then, we can make some assumptions on our models and the other sports prediction methods

Understanding Teacher Leadership in Middle School Mathematics: A Collaborative Research Effort

We report findings from a collaborative research effort designed to examine how teachers act as leaders in their schools. We find that teachers educated by the Math in the Middle Institute act as key sources of advice for colleagues within their schools while drawing support from a network consisting of other teachers in the program and university-level advisors. In addition to reporting on our findings, we reflect on our research process, noting some of the practical challenges involved, as well as some of the benefits of collaboration

On examples of difference operators for {0,1}\{0,1\}-valued functions over finite sets

Recently V.I.Arnold have formulated a geometrical concept of monads and apply it to the study of difference operators on the sets of $\{0,1\}$-valued sequences of length $n$. In the present note we show particular examples of these monads and indicate one question arising here