Attempting to improve standardized test results using Study Islands' web-based mastery program

State standardized testing has always been a tool to measure a school’s performance and to help evaluate school curriculum. However, with the school of choice legislation in 1992, the MEAP test became a measuring stick to grade schools by and a major tool in attracting school of choice students. Now, declining enrollment and a state budget struggling to stay out of the red have made school of choice students more important than ever before. MEAP scores have become the deciding factor in some cases. For the past five years, the Hancock Middle School staff has been working hard to improve their students’ MEAP scores in accordance with President Bush's “No Child Left Behind” legislation. In 2005, the school was awarded a grant that enabled staff to work for two years on writing and working towards school goals that were based on the improvement of MEAP scores in writing and math. As part of this effort, the school purchased an internet-based program geared at giving students practice on state content standards. This study examined the results of efforts by Hancock Middle School to help improve student scores in mathematics on the MEAP test through the use of an online program called “Study Island.” In the past, the program was used to remediate students, and as a review with an incentive at the end of the year for students completing a certain number of objectives. It had also been used as a review before upcoming MEAP testing in the fall. All of these methods may have helped a few students perform at an increased level on their standardized test, but the question remained of whether a sustained use of the program in a classroom setting would increase an understanding of concepts and performance on the MEAP for the masses. This study addressed this question. Student MEAP scores and Study Island data from experimental and comparison groups of students were compared to understand how a sustained use of Study Island in the classroom would impact student test scores on the MEAP. In addition, these data were analyzed to determine whether Study Island results provide a good indicator of students’ MEAP performance. The results of the study suggest that there were limited benefits related to sustained use of Study Island and gave some indications about the effectiveness of the mathematics curriculum at Hancock Middle School. These results and implications for instruction are discussed.

SUPPORTING LEARNING FOR NAVAJO STUDENTS THROUGH ETHNOMATHEMATICS

The purpose of this research was to address how culturally informed ethnomathematical methods of teaching can be utilized to support the learning of Navajo students in mathematics. The study was conducted over the course of four years on the Navajo Reservations at Tohatchi Middle School in Tohatchi New Mexico. The students involved in the study were all in 8th grade and were enrolled either in Algebra 1 or a Response to Intervention, RTI, class. The data collected came in the form of a student survey, student observation and student assessment. The teacher written survey, a math textbook word problem, and two original math textbook problems along with their rewritten version were the sources of these three studies. The first year of the study consisted of a math attitude survey and how Navajo students perceived math as a subject of interest. The students answered four questions pertaining to their thoughts about mathematics. The students’ responses were positive according to their written answers. The second year of the study involved the observation of how students worked through a math word problem as a group. This method tested how the students culturally interacted in order to solve a math problem. Their questions and reasoning to solve the problem were shared with peers and the teacher. The teacher supported the students in understanding and solving the problem by asking questions that kept the students focused on the goal of solving the problem. The students worked collaboratively and openly in order to complete the activity. During the iv study, the teacher was more able to notice the students’ deficiencies individually or as a group, therefore was able to support them in a more specific manner. The last study was conducted over a period of two different years. This study was used to determine how textbook bias in the form of its sentence structure or word choice affects the performance of students who are not culturally familiar with one or both. It was found that the students performed better and took less time on the rewritten problem than on the original problem. The data suggests that focusing on the culture, language and education of Navajo students can affect how the students learn and understand math.

Open Tour of Poster Session

The campus community and your invited guests will have an hour and a half to tour your poster session. They will be able to hear you describe the problems you worked on this week and ask you questions about your work.

Panelist Presentations & Q&A

Immediately following lunch, our women panelists will speak about the mathematics courses they took and the role mathematics plays in their chosen career, followed by questions from the audience.

Warranty vs. Non-Warranty Road Construction

A project to show whether a Warranty or Non-Warranty option would end up cheaper in twenty years.

Healthcare Outlier Payment Costs

The purpose of this project is to determine the cost of healthcare per individual depending on the amount of care needed.

Warranty vs. Non-Warranty Road Options

Comparing the cost effectiveness of warranty vs. non-warranty road construction options for a 100 mile section of road over a 20 year period.

Social Networking Charts

This project resulted in a chart illustrating connections in Social Networks.

Healthcare Costs: How Much Could a Hospital Make on Outlier Patients in Montana?

This poster illustrates hospital cost for outlier patients in Montana.

Social Networking: How to Build Social Networks

This poster illustrates variables and connections in social networking.

What Makes Science Hard for Newcomers?

Part I What makes science hard for newcomers? 1) The background (briefly) of my research - (why the math anxiety model doesn’t fit) 2) The Tier analysis (a visual) – message: there are many types of science learners in your class than simply younger versions of yourself 3) Three approaches (bio, chem, physics) but only one Nature 4) The (different) vocabularies of the three Sciences 5) How mathematics is variously used in Science Part II Rules and rules-driven assignments- lQ vs OQ1) How to incorporate creativity into assignments and tests? 2) Tests- borrowing “thought questions" from other fields (If Columbus hadn't discovered the new World, when and under whose law would it have been discovered?) 3) Grading practices (partial credit, post-exam credit for finding and explaining nontrivial errors 4) Icing on the cake – applications, examples of science/engineering from Tuesdays NY Times Part III Making Change at the Departmental Level 1) Taking control of at least some portion of the curriculum 2) Varying style of presentation 3) Taking control of at least some portion of the exams 4) GRADING pros and cons of grading on a curve 5) Updating labs and lab reporting.

Mathe-Üben in Studium und Abitur

Fehlende Grundkenntnisse in der Mathematik zählen zu den größten Hindernissen für einen erfolgreichen Start in ein Hochschulstudium. Studienanfänger in einem MINT-Studium bringen inzwischen deutlich unterschiedliche Vorrausetzungen mit: „Mathe-Angst“ gilt als typisches Phänomen und der Übergang in ein selbstbestimmtes Lernverhalten stellt eine große Herausforderung dar. Diese Fall-Studie beschreibt, wie mit Hilfe einer Mathe-App bereits zu Beginn des Studiums aktives Lernen unterstützt und selbstbestimmtes Lernen eingeübt werden kann. Das neue Kurskonzept mit App-Unterstützung stößt an der Hochschule Offenburg auf breite Akzeptanz. Der mobile BYOD-Ansatz ermöglicht Lern-Szenarien, die über PC- bzw.- Laptop-gebundene eLearning-Lösungen nicht realisierbar sind. Der Inhalt des MassMatics-Vorbereitungskurs orientiert sich am Mindestanforderungskatalog des cosh-Arbeitskreises für den Übergang Schule-Hochschule. In der Zwischenzeit wurde der App-gestützte Kurs mit seinen über 500 Aufgaben von mehr als 1000 Studierenden besucht.

The block numerical range of analytic operator functions

We introduce the block numerical range Wn(L) of an operator function L with respect to a decomposition H = H1⊕. . .⊕Hn of the underlying Hilbert space. Our main results include the spectral inclusion property and estimates of the norm of the resolvent for analytic L . They generalise, and improve, the corresponding results for the numerical range (which is the case n = 1) since the block numerical range is contained in, and may be much smaller than, the usual numerical range. We show that refinements of the decomposition entail inclusions between the corresponding block numerical ranges and that the block numerical range of the operator matrix function L contains those of its principal subminors. For the special case of operator polynomials, we investigate the boundedness of Wn(L) and we prove a Perron-Frobenius type result for the block numerical radius of monic operator polynomials with coefficients that are positive in Hilbert lattice sense.

On restricted families of projections in ℝ3

We study projections onto non-degenerate one-dimensional families of lines and planes in R 3 . Using the classical potential theoretic approach of R. Kaufman, one can show that the Hausdorff dimension of at most 12 -dimensional sets [Math Processing Error] is typically preserved under one-dimensional families of projections onto lines. We improve the result by an ε , proving that if [Math Processing Error], then the packing dimension of the projections is almost surely at least [Math Processing Error]. For projections onto planes, we obtain a similar bound, with the threshold 12 replaced by 1 . In the special case of self-similar sets [Math Processing Error] without rotations, we obtain a full Marstrand-type projection theorem for 1-parameter families of projections onto lines. The [Math Processing Error] case of the result follows from recent work of M. Hochman, but the [Math Processing Error] part is new: with this assumption, we prove that the projections have positive length almost surely.