Majority of North Carolina Counties Still Have More Unemployed Workers than Job Openings Hyde County Pamlico County Camden County Caswell County Warren County Bladen County Ashe County Chatham County Clay County Polk County Harnett County Alleghany County Johnston County Rutherford County Currituck County Scotland County Union County Sampson County Granville County Mitchell County Wayne County Davie County Haywood County Surry County Cherokee County Craven County Henderson County Pitt County Alamance County Iredell County Orange County New Hanover County Wake County Durham County 0 1 2 3 4 Unemployed Workers Per Job Openings 5 6 7
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Source: Senate Finance Committee Roanoke Times, November 21, 1998 STATEWIDE AVERAGE 38% Wythe County 35% Washington County 41% Smyth County 96% Salem 79% Rockbridge County Roanoke 99% Roanoke County 100% Radford 37% Pulaski County 22% Patrick County 85% Montgomery County 1% Martinsville 100% Lexington 79% Henry County Grayson County 87% Giles County 60% Gatax Franklin-County 95% Floyd County 0% Craig County 99% Covington 0% Carroll County 100% Buena Vista 80% Botetourt County 98% Btand County 40% Bedford County 100% Bath County Alleghany County Classrooms with Internet Computers Percentage of classrooms in Western Virginia that have computers connected to the internet 120% 96% 88% 79% 70% 50% 56% 36% 25% 20% 9% 0%
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June 2010 WV GIS Conference Key Statutory Requirements of Voter Precinct Delineation – – §3-1-5. Voting precincts and places established; number of voters in precincts; precinct map; municipal map. (a) The precinct shall be the basic territorial election unit. The county commission shall divide each magisterial district of the county into election precincts, shall number the precincts, shall determine and establish the boundaries thereof, and shall designate one voting place in each precinct, which place shall be established as nearly as possible at the point most convenient for the voters of the precinct. Each magisterial district shall contain at least one voting precinct and each precinct shall have but one voting place therein. – Each precinct within any urban center shall contain not less than three hundred nor more than one thousand five hundred registered voters. Each precinct in a rural or less thickly settled area shall contain not less than two hundred nor more than seven hundred registered voters, unless upon a written finding by the county commission that establishment of or retention of a precinct of less than two hundred voters would prevent undue hardship to the voters, the secretary of state determines that such precinct be exempt from the two hundred voter minimum limit. If, at any time the number of registered voters exceeds the maximum number specified, the county commission shall rearrange the precincts within the political division so that the new precincts each contain a number of registered voters within the designated limits. If a county commission fails to rearrange the precincts as required, any qualified voter of the county may apply for a writ of mandamus to compel the performance of this duty: Provided, That when in the discretion of the county commission, there is only one place convenient to vote within the precinct and when there are more than seven hundred registered voters within the existing precinct, the county commission may designate two or more precincts with the same geographic boundaries and which have voting places located within the same building. The county commission shall designate alphabetically the voters who will be eligible to vote in each precinct so created. Each such precinct shall be operated separately and independently with separate voting booths, ballot boxes, election commissioners and clerks, and whenever possible, in separate rooms. No two of such precincts may use the same counting board. – (b) In order to facilitate the conduct of local and special elections and the use of election registration records therein, precinct boundaries shall be established to coincide with the boundaries of any municipality of the county and with the wards or other geographical districts of the municipality except in instances where found by the county commission to be wholly impracticable so to do. Governing bodies of all municipalities shall provide accurate and current maps of their boundaries to the clerk of any county commission of a county in which any portion of the municipality is located. – (c) To facilitate the federal and state redistricting process, precinct boundaries must be comprised of intersecting geographic physical features or municipal boundaries recognized by the U.S. Census Bureau. For purposes of this subsection, geographic physical features include streets, roads, streams, creeks, rivers, railroad tracks and mountain ridge lines. The county commission of every county must modify precinct boundaries to follow geographic physical features or municipal boundaries and submit changes to the West Virginia office of legislative services by June 30, 2007 and by the thirtieth day of June, every ten calendar years thereafter. The county commission must also submit precinct boundary details to the U.S. Census Bureau upon request. – The West Virginia office of legislative services shall be available for consultation with the county commission regarding the precinct modification process: Provided, That nothing in this subsection removes or limits the ultimate responsibility of the county commission to modify precinct boundaries to follow geographic physical features. – (d) The provisions of this section are subject to the provisions of section twenty-eight, article four of this chapter relating to the number of voters in precincts in which voting machines are used. – (e) The county commission shall keep available at all times during business hours in the courthouse at a place convenient for public inspection a map or maps of the county and municipalities with the current boundaries of all precincts. Source: §3-1-5 WV Code
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5. Mean projections and mean student scores are calculated. Student Projection1 Student Score 1 Student Projection 2 Student Score 2 Student Projection 3 Student Score 3 Student Projection 4 Student Score 4 Student Projection 5 Your School Student Score 5 Student Projection 6 Student Score 6 Student Projection 7 Student Score 7 Student Projection 8 Student Score 8 Student Projection 9 Student Score 9 Student Projection 10 Student Score 10 Student Projection 11 Student Score 11 Student Projection 12 Student Score 12 Student Projection 13 Student Score 13 Student Projection 14 Student Score 14 Student Projection 15 Student Score 15 Student Projection 16 Student Score 16 Student Projection 17 Student Score 17 Student Projection 18 Student Score 18 Student Projection 19 Student Score 19 Student Projection 20 Student Score 20 Mean Projected Score Mean Student Score Copyright © 2003. Battelle for Kids
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Credit Student Origins High School Graduates GCC Does Regular Outreach to the Following High Schools: Hoover High School Glendale High School La Canada High School Franklin High School Eagle Rock High School Daily High School Crescenta Valley High School Clark Magnet Burroughs High School Burbank Adult School Burbank High School Belmont High School Bell-Jeff High School Los Angeles High School Marshall High School North Hollywood High School Verdugo Hills High School Downtown Magnet Miguel Contreras High School John Francis Poly Taft High School Temple City High School Garfield Campus
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June 2010 WV GIS Conference Key Statutory Requirements of Voter Precinct Delineation – – §3-1-6. Municipal voting precincts. The governing bodies of all municipalities shall, for the purpose of municipal elections, provide by ordinance for making the voting precincts in the respective municipalities coincide, as nearly as possible, to the boundaries of the voting precincts fixed by the county court for all state and county elections. – – §3-1-7. Precinct changes; procedure; precinct record. (a) Subject to the provisions and limitations of section five of this article, the county commission of any county may change the boundaries of any precinct within the county, or divide any precinct into two or more precincts, or consolidate two or more precincts into one, or change the location of any polling place whenever the public convenience may require it. – (b) No order effecting the change, division or consolidation shall be made by the county commission within ninety days prior to an election nor without giving notice at least one month before the change, division or consolidation by publication of the notice as a Class II-0 legal advertisement in compliance with the provisions of article three, chapter fifty-nine of this code. The publication area is the county in which the precinct or precincts are located. The county commission shall also, within fifteen days after the date of the order, publish the order in the manner required for publication of the notice. – (c) The county commission shall also, before the next succeeding election, cause the voters in the several precincts affected by the order to be duly registered in the proper precinct or precincts and shall mail written notification to all registered voters affected by the change. – (d) The county commission shall keep in a well-bound book, marked "election precinct record", a complete record of all their proceedings hereunder and of every order made creating a precinct or precincts or establishing a place of voting therein. The "election precinct record" shall be kept by the county commission clerk in his or her office and shall, at all reasonable hours, when not actually in use by the county commission, be open to inspection by any citizen of the county. – (e) When the county commission establishes a polling place at a location other than the location used for holding the preceding primary, general or special election in that precinct, the commission shall cause a notice to be posted on election day on the door of the previous polling place describing the location of the newly established polling place and shall mail written notification to all registered voters affected by the change. – (f) If for any reason the election cannot be held at the designated polling place in a precinct and no provision has been made by the county commission for holding the election at another place, the commissioners of election for that precinct may hold the election at the nearest place which they can secure for the purpose. They shall make known by proclamation to voters present at the time for opening the polls, and by posting a notice at or near the entrance of the first named polling place, the location at which the election will be held. The county commission shall establish another place of voting for that precinct as soon thereafter as practicable. – (g) Notwithstanding any provision herein to the contrary, in the case of an emergency, the county commission may make the precinct change no later than sixty days prior to an election in accordance with the requirements herein with the approval of the secretary of state. A change, if made however, shall not cause any voter to be moved to a different district. Source: §3-1-6 and §3-1-7 WV Code
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DEN 219/229 Reflection Journal Rubric GRADING Criteria Reflective Student Aware Student Reflective Novice BelowExpectations Clarity Language is clear and expressive. The reader can create a mental picture of the situation being described. Abstract concepts are explained accurately. Explanation makes sense to an uninformed reader. The learning experience being reflected upon is relevant and meaningful to student and course learning goals. Minor, infrequent lapses in clarity and accuracy. There are frequent lapses in clarity and accuracy. Language is unclear and confusing throughout. Concepts are either not discussed or are presented inaccurately. The learning experience being reflected upon is relevant and meaningful to student and course learning goals. Student makes attempts to demonstrate relevance, but the relevance is unclear to the reader. Most of the reflection is irrelevant to student and/ or course learning goals. The reflection demonstrates connections between the experience and material from other courses, but lacks relevance and depth. There is little to no attempt to demonstrate connections between the learning experience and previous other personal and/ or learning experiences. Student makes attempts at applying the learning experience to understanding of self, others, and/ or course concepts but fails to demonstrate depth of analysis. There is some attempt at self-criticism, but the selfreflection fails to demonstrate a new awareness of personal biases, etc. No attempt to demonstrate connections to previous learning or experience. Student’s language is clear and expressive Relevance The learning experience is relevant and meaningful to student. Interconnections The reflection demonstrates connections between the experience and material from The reflection demonstrates other courses; past connections between the experience and material from experience; and/ or personal goals. other courses. Analysis The reflection moves beyond simple description of the experience Self-criticism Ability of the student to question their own biases, stereotypes, preconceptions, and/ or assumptions. The reflection moves beyond simple description of the experience to an analysis of how the experience contributed to student understanding of self, others, and/ or course concepts. The reflection demonstrates student attempts to analyze the experience but analysis lacks depth. The reflection demonstrates ability of the student to question their own biases, stereotypes, preconceptions, and/ or assumptions and define new modes of thinking as a result. The reflection demonstrates ability of the student to question their own biases, stereotypes, preconceptions. Adapted from University of Iowa, Office of Service Learning Reflection does not move beyond description of the learning experience(s). No attempt at selfcriticism.
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County Per Capita Income New York County (Manhattan) Westchester County Nassau County Putnam County Rockland County Suffolk County Saratoga County Jefferson County Herkimer County Cattaraugus County Franklin County $42,922 $36,726 $32,151 $30,127 $28,082 $26,577 $23,945 $16,202 $16,141 $15,959 $15,888 St. Lawrence County Allegany County Lewis County $15,728 $14,975 $14,971 Bronx County (The Bronx) $13,959
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Expected Counts in Two-Way Tables Finding the expected counts is not that difficult, as the following example illustrates. The overall proportion of French wine bought during the study was 99/243 = 0.407. So the expected counts of French wine bought under each treatment are: 99 99 experiment is that there’s no 99 The null: hypothesis in theFrench wine and music No music ×84 =34.22 music : ×75 =30.56 Italian music : ×84 =34.22 243 243 243 difference in the distribution of wine purchases in the store when no music, French accordion music, or Italian string music is played. To find the proportion expected counts, wewine startbought by assuming thatstudy H0 is was true.31/243 We can=see The overall of Italian during the 0.128. So two-way the expected wine bought under each treatment from the table counts that 99ofofItalian the 243 bottles of wine bought during theare: study were 31 French wines. French music : 31 ×75 =9.57 Italian music : 31 ×84 =10.72 No music : ×84 =10.72 243 243 243 If the specific type of music that’s playing has no effect on wine purchases, the proportion of French The overall proportion of Other wine bought during the study was 113/243 = wine sold under each music 0.465. So the expected countscondition of Other wine bought under each treatment are: should be113 99/243 = 0.407. 113 113 No music : 243 ×84 =39.06 French music : 243 ×75 =34.88 Italian music : 243 ×84 =39.06 12
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Expected Counts in Two-Way Tables 9 Finding the expected counts is not that difficult, as the following example illustrates. The overall proportion of French wine bought during the study was 99/243 = 0.407. So the expected counts of French wine bought under each treatment are: 99 99 experiment is that there’s no 99 The null: hypothesis in theFrench wine and music No music ×84 =34.22 music : ×75 =30.56 Italian music : ×84 =34.22 243 243 243 difference in the distribution of wine purchases in the store when no music, French accordion music, or Italian string music is played. To find the proportion expected counts, wewine startbought by assuming thatstudy H0 is was true.31/243 We can=see The overall of Italian during the 0.128. So two-way the expected wine bought under each treatment from the table counts that 99ofofItalian the 243 bottles of wine bought during theare: study were 31 French wines. 31 31 No music : 243 ×84 =10.72 French music : ×75 =9.57 Italian music : ×75 =34.88 Italian music : 243 243 ×84 =10.72 If the specific type of music that’s playing has no effect on wine purchases, the proportion of French The overall proportion of Other wine bought during the study was 113/243 = wine sold under each music 0.465. So the expected countscondition of Other wine bought under each treatment are: should be113 99/243 = 0.407. 113 113 No music : 243 ×84 =39.06 French music : 243 243 ×84 =39.06
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Expected Counts in Two-Way Tables 12 Finding the expected counts is not that difficult, as the following example illustrates. The overall proportion of French wine bought during the study was 99/243 = 0.407. So the expected counts of French wine bought under each treatment are: 99 99 experiment is that there’s no 99 The null: hypothesis in theFrench wine and music No music ×84 =34.22 music : ×75 =30.56 Italian music : ×84 =34.22 243 243 243 difference in the distribution of wine purchases in the store when no music, French accordion music, or Italian string music is played. To find the proportion expected counts, wewine startbought by assuming thatstudy H0 is was true.31/243 We can=see The overall of Italian during the 0.128. So two-way the expected wine bought under each treatment from the table counts that 99ofofItalian the 243 bottles of wine bought during theare: study were 31 French wines. 31 31 No music : 243 ×84 =10.72 French music : ×75 =9.57 Italian music : ×75 =34.88 Italian music : 243 243 ×84 =10.72 If the specific type of music that’s playing has no effect on wine purchases, the proportion of French The overall proportion of Other wine bought during the study was 113/243 = wine sold under each music 0.465. So the expected countscondition of Other wine bought under each treatment are: should be113 99/243 = 0.407. 113 113 No music : 243 ×84 =39.06 French music : 243 243 ×84 =39.06
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Example of the Maximum Allowed in the US Missouri Max lodging by Month 2012 Primary Destination County Oct Nov 2013 Meals Dec Jan Feb Mar Apr May Jun Jul Aug Sep Standard Rate Applies for all locations without specified rates 77 77 77 77 77 77 77 77 77 77 77 77 46 Columbia Boone County 80 80 80 80 80 80 80 80 80 80 80 80 51 Kansas City Cass County, Platte County, Jackson County, Clay County 99 99 99 99 99 99 99 99 99 99 99 99 61 St. Louis St Louis County, Franklin County, Lincoln County, St Louis City, Warren County, Crawford County, 104 Washington County, Jefferson County, St Charles County 104 104 104 104 104 104 104 104 104 104 104 66 St. Robert Pulaski County 80 80 80 80 80 80 80 80 80 80 80 46 80 * Meals and Incidental Expenses, see Breakdown of M&IE Expenses for importan t information on first and last days of travel
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 Other Universities 1. SUNY Binghamton (NY) 2. Bradley University (IL) 3. Cameron University (OK) 4. The Citadel (SC) 5. College of the Muscogee Nation (OK) E E   Courses at OU 1. Chem Engr: Industrial & Environmental Transport Processes (D. Papavassiliou) 2. Engineering Numerical Methods (U. Nollert) 3. Math: Advanced Numerical Methods (R. Landes) 4. Electrical Engr: Computational Bioengineering (T. Ibrahim) Research Experience for Undergraduates at OU 1. Ind Engr: Metrology REU (T. Reed Rhoads) 2. Ind Engr: Human Technology Interaction Center REU (R. Shehab) 3. Meteorology REU (D. Zaras) External 1. American Society of Mechanical Engineers, OKC Chapter 2. Association for Computing Machinery (ACM) Special Interest Group on Computer Science Education (SIGCSE) 2010 3. Oklahoma State Chamber of Commerce 4. National Educational Computing Conference 2006 (virtual tour via videoconference) 5. Norman (OK) Lions Club 6. Society for Information Technology & Teacher Education conference 2008, 2009, 2010 7. Acxiom Conference on Applied Research in Information Technology 2008 8. Shawnee (OK) Lions Club 9. Oklahoma Louis Stokes Alliance for Minority Participation (@ OSU) 2010 (Keynote) 10. NEW! Norman (OK) Science Café 11. NEW! Tech Forum Texas 2010 12. NEW! Texas Computer Education Association 2011 13. NEW! Consortium for School Networking 2011  14. NEW! Consortium for Computing Sciences in Colleges 2011 (Keynote) E  E Teaching: Presentations & Tours 6. DeVry University (OK) 7. East Central University (OK) 8. El Bosque University (Bogota Colombia) 9. Southwestern University (TX) 10. Langston University (OK) 11. Louisiana State University 12. Midwestern State University (TX) 13. Northeastern Oklahoma State University 14. Northwestern Oklahoma State University 15. Oklahoma Baptist University 16. Oklahoma City University 17. Oklahoma State University x 2 18. Oklahoma State University – OKC 19. Oral Roberts University (OK) x 2 20. NEW! Philander Smith College (AR) 21. St. Gregory’s University (OK) x 2 22. Southeastern Oklahoma State University x 2 23. Southern Nazarene University (OK) 24. Southwestern Oklahoma State University x 2 25. Texas A&M-Commerce 26. University of Arkansas Fayetteville 27. University of Arkansas at Little Rock 28. NEW! University of Arkansas at Pine Bluff 29. University of Central Oklahoma 30. NEW! University of Oklahoma-Tulsa 31. University of Tulsa (OK) High Schools and High School Programs 1. Oklahoma School of Science & Mathematics x 2 2. Oklahoma Christian University’s Opportunity Bytes Summer Academy 3. Dept of Energy National Scholarship Finalists 4. Ardmore High School (OK) OSCER State of the Center Address Wednesday October 12 2011 42
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Universities that Employ Fellowship Alumni •Auburn Univesity •Arizona State University •Boston University •California Institute of Technology •Careton College •Carnegie Mellon University •Clark Atlanta University •City College of New York •Cornell University •Dartmouth College •Duke University •Florida A&M University •Georgetown University •Georgia Institute of Technology •Harvard University •Hiriam College •Hofstra University •Howard University •James Madison University •Loyola University •Massachusetts Institute of Technology •Morehouse College •Morgan State University •North Carolina A&T University •Northeastern University •New Jersey Institute of Technology •New Mexico State University •Oberlin College •Oregon State University •Pennslyvania State University •Polytechnic University •Pomonoa College •Princeton University •Rutgers University •Smith College •Spelman College •Stanford University •Texas A&M •University of California --Berkeley, Davis, Irvine, San Diego •University of Chicago •University of Dayton •University of Maryland--Balitmore County, College Park •University of Massachusetts--Lowell •University of Michigan •University of Nebraska •University of Pittsburgh •University of Puerto Rico •University of Texas--Austin •University of Washington •University of Wisconsin--Madison •Vassar •Wesleyan •Williams College •Yale University Copyright © 2002 AT&T All Rights Reserved
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International Linkages •Australia • Macquarie University •Chile • Pontificia Universidad Catolica de Chile •China • Beijing Normal University • China University of Mining and Technology • Hebei University • Nanjing Medical University • Southwest University of Political Science and Law • Tonji University • University of Hong Kong •Denmark • Copenhagen Business School •England • Kingston University • Lancaster University • Manchester Metropolitan University • University of Kent at Canterbury •France • Ecole National Superieure de Ceramique Industrielle • EDHEC Business School • University d’Artois • University of Jean Moulin Lyon III • University of Limoges •Germany • University of Heidelberg • Fachhochschule Aachen • Paedagogische Hochschule Ludwigsburg • Zeppelin University •Italy • University of Bari •Japan • Gakushuin University • Nagoya University of Foreign Studies • Oberlin University • Oita University • Sophia University • Tokyo University of Science & Technology •Korea • Hong-IK University •Mexico • Tecnologico de Monterrey www.oip.uncc.edu/links •Netherlands • Technical University of Delft • University of Amsterdam •Peru • Catholic University of Santa Maria •Poland • University of Wroclaw • Academy of Art & Design in Wroclaw •Scotland • University of Aberdeen •South Africa • Stellenbosch University •Spain • University of Cantabria • Universitat Jaume I •Sweden • Orebro University •Taiwan • National Kaohsiung Normal University •United Arab Emirates • United Arab Emirates University
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VI. Cooperating Teacher Evaluation Forms The University of Tennessee at Martin Final Student Teaching Performance Assessment Evaluation b y Cooperating Teacher STUDENT TEACHER (Last, First, Middle) MAJOR/LICENSURE AREA DATE PREPARED HOST SCHOOL CITY, STATE PRINCIPAL GRADE LEVEL(S)/SUBJECT TAUGHT COOPERATING TEACHER UNIVERSITY SUPERVISOR The cooperating teacher should complete this evaluation and ALL COPIES RETURNE D to the DIRECTOR OF FIELD EXPE RIENCES by Monday of the last week of the student teaching experience. Unsatisfactory Performance Level A Developing Performance Level B Proficient Performance Level C Advanced ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ DOMAI N I: Planning Indicators A. Establishes appropriate instructional goals and objectives B. Plans instruction and student evaluation based on an in-depth understanding of the content, student needs, curriculum standards, and the community C. Adapts instructional opportunities for diverse learners Unsatisfactory Performance Level A Developing ___ ___ ___ ___ ___ ___ ___ ___ DOMAI N II: Teaching Strategies Indicators A. B. Demonstrates a deep understanding of the central concepts, assum ptions, structures, and pedagogy of the content area. Uses research-based classroom strategies that are grounded in higher order thinking, problem-solving, and real world connections for all students. ________ Required Area to Strengthen Performance Performance Level B Level C Proficient Advanced Unsatisfactory Performance Level A Developing ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ DOMAI N III: Assessment and Evalua tion Indicators Uses appropriate evaluation and assessments to determine student mastery of content and make instructional decisions. B. Communicates student achievement and progress to students, their parents, and appropriate others C. Reflects on teaching practice through careful examination of classroom evaluation and assessments ________ Required Area to Strengthen Performance Performance Level B Level C Proficient Advanced A. Unsatisfactory Performance Level A Developing ___ ___ ___ ___ ___ ___ ___ ___ DOMAIN IV: Learning Environment Indicators A. Creates a classroom culture that develops student intellectual capacity in the content area. B. Manages classroom resources effectively ________ Required Area to Strengthen Performance Performance Level B Level C Proficient Advanced Unsatisfactory Performance Level A Developing ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ ___ DOMAI N V: Professional Growth Indicators A. Collaborates with colleagues and appropriate others B. Engages in high-quality, on-going professional development as defined by the Tennessee State Board of Education Professional Development Policy to strengthen knowledge and skill in the content of the teaching assignment. C. Performs professional responsibilities efficiently and effectively ________ Required Area to Strengthen Performance Performance Level B Level C Proficient Advanced ________ Required Area to Strengthen
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Transfer Acceptances Butler University Whittier College Stanford University Purdue University University of Pennsylvania University of Indianapolis DePauw University Earlham College Illinois Institute of Technology University of Pennsylvania University of Michigan University of Illinois Urbana Goshen College Georgia State University University of Central Florida Flagler College Manchester University University of Southern California Miami University Middlebury University Smith College Ohio State University Wabash College Hanover College University of Nevada Las Vegas Wellesley College University of Massachusetts Harvard Extension School Columbia College of Chicago Rose-Hulman Concordia University Chicago Eastern Illinois University Purdue University School of the Art Institute of Chicago American University Valparaiso University Trine University University of Colorado University of Arizona SUNY - Buffalo Bridgewater University Indiana University Ball State University IUPUI Western Michigan University Holy Cross College Marian University Columbia College Indiana Wesleyan University Olivet Nazarene University University of Evansville
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Level II Placements 1st Rotation 2nd Rotation FW Site 1 1 Student 1- 1st Choice 1 Student 2- 1st Choice FW Site 1 1 Student 1- 1st 0 Student 2- 1st FW Site 2 1 Student 2- 1st Choice Student 3- 2nd Choice Student 4- 3rd Choice 1 Student A- 1st Student B- 2nd choice Student C- 3rd Choice FW Site 3 1 Student 4- 1st Choice Student 5- 1st Choice Student 6- 1st Choice Student 7-2nd Choice Student 8- 2nd Choice Student 9- 3rd Choice 1 Student 2- 1st Student 3- 1st Student 4- 1st Student 5- 1st Student 6- 1st Student 7- 1st FW Site 4 0 Student 10- 1st 0 Student 11- 1st Choice FW Site 5 1 No Student 1 No Student FW Site 6 1 No Student 1 Student 11- 1st Student 12- 1st Lake Charles MC with free housing
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