DERECHOS Y BENEFICIOS DEL PERSONAL DE LA PNP CONTENIDO Y SUSTENTO NORMATIVO
del 21 de diciembre de 1999, Decreto Supremo No.0800-2000-IN del 4 de octubre del 2000 – Ley N° 28857 del 27JUL2006)
applications of the derivative, integration and application of the definite integral. Prereqs., two years high school algebra, one year geometry, and 1/2 year trigonometry or MATH 1150. Credit not granted for this course and MATH 1081, 1310, APPM 1345, 1350, and
ECON 1088. Similar to MATH 1080, 1090, and 1100. Approved for arts and sciences core curriculum: quantitative reasoning and mathematical skills.
MATH 1310-5. Calculus, Stochastics, and Modeling. Calculus, probability, statistics, and discrete and continuous modeling are central to understanding the behavior of complex systems, ranging from gene networks and cells to brains and ecosystems. This course is similar to MATH 1300, but a greater emphasis is placed on relevance and applications to complex systems. Especially recommended for biology majors. Prereq., 2 years high school algebra, 1 year geometry, and 1/2 year trigonometry, or MATH 1150. Credit not granted for this course and MATH 1080, 1081, 1090, 1100, 1300, APPM 1350, or ECON 1088. Approved for arts and sciences core
curriculum: quantitative reasoning and mathematical skills
MATH 1410-3. Mathematics for Secondary Educators. Assists students in meeting state mathematics certification requirements. Topics include problem solving, number systems, geometry and measurement, probability and statistics. Enrollment is restricted to students
already admitted to or intending to apply for admission to the secondary teacher education program. Prereqs., one year high school algebra, one year geometry. Approved for arts and sciences core curriculum: quantitative reasoning and mathematical skills.
MATH 2380-3. Mathematics for the Environment. An interdisciplinary course where analysis of real phenomena such as acid rain, population growth, and road-killed rabbits in Nevada leads to consideration of various fundamental concepts in mathematics. One- third of the course consists of individual projects chosen by students. Prereq.,
proficiency in high school mathematics. Credit not granted for this course and QRMS 2380. Approved for arts and sciences core
curriculum: quantitative reasoning and mathematical skills.
MATH 2510-3. Introduction to Statistics. Elementary statistical measures. Introduces statistical distributions, statistical inference, and hypothesis testing. Prereq., two years of high school algebra. Credit not granted for this course and MATH 4520/5520 or MATH 3510.
November 17, 2011 Carrie Muir
Department of Educational Administration 4905 Osage Dr #224 Boulder, CO 80303 Larry Dlugosh
Department of Educational Administration 141C TEAC, UNL, 68588-0360
IRB Number: 20111112103EP Project ID: 12103
Project Title: AN ANALYSIS OF FINAL COURSE GRADES IN TWO DIFFERENT ENTRY LEVEL MATHEMATICS COURSES BETWEEN AND AMONG FIRST YEAR COLLEGE STUDENTS WITH DIFFERENT LEVELS OF HIGH SCHOOL MATHEMATICS PREPARATION
Dear Carrie:
This letter is to officially notify you of the approval of your project by the Institutional Review Board (IRB) for the Protection of Human Subjects. It is the Board s opinion that you have provided adequate safeguards for the rights and welfare of the participants in this study based on the information provided. Your proposal is in compliance with this institution s Federal Wide Assurance 00002258 and the DHHS Regulations for the Protection of Human Subjects (45 CFR 46). Your project was approved as an Expedited protocol, category 5. Date of EP Review: 10/18/2011
You are authorized to implement this study as of the Date of Final Approval: 11/17/2011. This approval is Valid Until: 11/16/2012.
We wish to remind you that the principal investigator is responsible for reporting to this Board any of the following events within 48 hours of the event:
* Any serious event (including on-site and off-site adverse events, injuries, side effects, deaths, or other problems) which in the opinion of the local investigator was unanticipated, involved risk to subjects or others, and was possibly related to the research procedures;
* Any serious accidental or unintentional change to the IRB-approved protocol that involves risk or has the potential to recur;
* Any publication in the literature, safety monitoring report, interim result or other finding that indicates an unexpected change to the risk/benefit ratio of the research;
* Any breach in confidentiality or compromise in data privacy related to the subject or others; or
* Any complaint of a subject that indicates an unanticipated risk or that cannot be resolved by the research staff.
For projects which continue beyond one year from the starting date, the IRB will request continuing review and update of the research project. Your study will be due for continuing review as indicated above. The investigator must also advise the Board when this study is finished or discontinued by completing the enclosed Protocol Final Report form and returning it to the Institutional Review Board.
If you have any questions, please contact the IRB office at 472-6965. Sincerely,
Julia Torquati, Ph.D. Chair for the IRB
February 22, 2012 Carrie Muir
Department of Educational Administration 4905 Osage Dr #224 Boulder, CO 80303 Larry Dlugosh
Department of Educational Administration 141C TEAC, UNL, 68588-0360
IRB Number: 20111112103COLL Project ID: 12103
Project Title: AN ANALYSIS OF FINAL COURSE GRADES IN TWO DIFFERENT ENTRY LEVEL MATHEMATICS COURSES BETWEEN AND AMONG FIRST YEAR COLLEGE STUDENTS WITH DIFFERENT LEVELS OF HIGH SCHOOL MATHEMATICS PREPARATION
Dear Carrie:
The Institutional Review Board for the Protection of Human Subjects has completed its review of the Request for Change in Protocol submitted to the IRB.
**The change request has been approved to expand data collection to include first year students in the Fall 2011 semester, and for the investigator to collect the data on student grades in high school mathematics courses as well.**
We wish to remind you that the principal investigator is responsible for reporting to this Board any of the following events within 48 hours of the event:
* Any serious event (including on-site and off-site adverse events, injuries, side effects, deaths, or other problems) which in the opinion of the local investigator was unanticipated, involved risk to subjects or others, and was possibly related to the research procedures;
* Any serious accidental or unintentional change to the IRB-approved protocol that involves risk or has the potential to recur;
* Any publication in the literature, safety monitoring report, interim result or other finding that indicates an unexpected change to the risk/benefit ratio of the research;
* Any breach in confidentiality or compromise in data privacy related to the subject or others; or
* Any complaint of a subject that indicates an unanticipated risk or that cannot be resolved by the research staff.
This letter constitutes official notification of the approval of the protocol change. You are therefore authorized to implement this change accordingly.
If you have any questions, please contact the IRB office at 472-6965. Sincerely,
Julia Torquati, Ph.D. Chair for the IRB
References
Abraham, AA., Jr. (1992). College remedial studies: Institutional practices in the SREB states. Atlanta, GA: Southern Regional Education Board.
Ahmadi, M. & Raiszadeh, F. M. E. (1990). Predicting underachievement in business statistics. Educational and Psychological Measurement, 50, 923-929.
Aiken, L. R., Jr. (1961). The effects of attitudes on performance in mathematics. Journal of Educational Psychology, 52(1), 19-24.
Airasian, P. W. (1988). Symbolic validation: The case of state-mandated, high stakes testing. Educational Evaluation and Policy Analysis, 10(4), 301-313.
Akst, G., & Hirsch, L. (1991). Review of Research in Developmental Education 8(4): Selected studies on math placement. Boone, North Carolina: National Center for Developmental Education.
Aldridge, M., & DeLucia, R. C. (1989). Boredom: The academic plague of first year students. Journal of the Freshman Year Experience, 1(2), 43-56.
Anderson, J. (1989). Sex-related differences on objective tests among undergraduates. Educational Studies in Mathematics, 20, 165-177.
Anderson, R. E., & Darkenwald, G. G.(1979). Participation and persistence in American adult education: Implications for public policy and future research from a
multivariate analysis of a national data base. New York: College Entrance Examination Board.
Ang, C. H. & Noble, J. P. (1993). Incremental validity of ACT assessment scores and high school course information for freshman course placement. Report No. 93-5. Iowa City, IA: The American College Testing Program.
Anthony, G. (2000). Factors influencing first-year students' success in mathematics. International Journal of Mathematical Education in Science and Technology, 31 (1), 3-14.
Armstrong, A. G. (1999). An analysis of student placement into college algebra (Ed.D., Texas A&M University - Commerce, 1999).
Armstrong, W. B. (1994). Math placement validation study: A summary of the criterion- related validity evidence and multiple measures data for the San Diego Community College District. San Diego, California: San Diego Community College District. Armstrong, W. B. (2000). The association among student success in courses, placement
test scores, student background data, and instructor grading practices. Community College Journal of Research and Practice, 24, 681-695.
Bahr, P.R. (2010). Making sense of disparities in mathematics remediation: What is the role of student retention? Journal of College Student Retention: Research, Theory and Practice, 12(1), 25-49.
Baldwin, C., Bensimon, E. M., Dowd, A. C. & Kleiman, L. (2011), Measuring student success. New Directions for Community Colleges, 2011(153), 75–88.
Barker, J. L. (1994). Selected factors related to academic achievement of developmental introductory algebra students at the two-year college level (Ph.D., University of Oklahoma, 1994).
Bassarear, T. J. (1991). An examination of the influence of attitudes and beliefs on achievement in a college developmental mathematics course. Research and Teaching in Developmental Education, 7(2), 43-56.
Belfield, C. R., & Crosta, P. M. (2012). Predicting success in college: The importance of placement tests and high school transcripts (Working Paper no. 42). Retrieved from Community College Research Center website: http://ccrc.tc.columbia.edu/ DefaultFiles/SendFileToPublic.asp?ft=pdf&FilePath=c:%5CWebsites
%5Cccrc_tc_columbia_edu_documents
%5C332_1030.pdf&fid=332_1030&aid=47&RID=1030&pf=ContentByType.asp? t=1.
Benbow, C. P., & Arjmand, O. (1990). Predictors of high academic achievement in mathematics and science by mathematically talented students: A longitudinal study. Journal of educational Psychology, 82(3), 430-441.
Berenson, S. B., Best, M. A., Stiff, L. V., & Wasik, J. L. (1990). Levels of thinking and success in college developmental algebra. Focus on Learning Problems in
Mathematics, 12(1), 3-13.
Berenson, S. B., Carter, G., & Norwood, K. S. (1992). The at-risk students in college developmental algebra. School science and Mathematics, 92(2), 55-58.
Bershinsky, D. M. (1993). Predicting student outcomes in remedial math: A study of demographic, attitudinal, and achievement variables (Ed.D., University of Wyoming, 1994).
Bessant, K. C. (1995). Factors associated with types of mathematics anxiety in college students. Journal for Research in Mathematics Education, 26(4), 327-345.
Betz, N. E. (1978). Prevalence, distribution, and correlates of math anxiety in college students. Journal of Counseling Psychology, 25(5), 441-448.
Boli, J., Allen, M. L., & Payne, A. (1985). High-ability women and men in undergraduate mathematics and chemistry courses. American Educational Research Journal, 22(4), 605-626.
Bone, M.A. (1981). A comparison of three methods of mathematics placement for college freshmen (Ph.D., Michigan State University, 1981).
Bragg, D.D. (2011). Two-year college mathematics and student progression in STEM programs of study. Paper presented at the meeting Community Colleges in the Evolving STEM Education Landscape: A Summit, December 2011, Washington, D.C.
Bressoud, D. M. (2004). The changing face of calculus: First-semester calculus as a high school course. FOCUS, 4(6) Retrieved from http://www.maa.org/features/
faceofcalculus.html.
Bridgeman, B., Hale, G. A., Lewis, C., Pollack, J., & Wang, M. (1992). Placement validity of a prototype SAT with and essay. ERIC Document Reproduction Service No. ED 390 893.
Bridgeman, B. & Wedler, C. (1989). Prediction of grades in college mathematics courses as a component of the placement validity of SAT-Mathematics scores. ERIC Document Reproduction Service No. ED 395 019.
Bridgeman, B., & Wendler, C. (1991). Gender differences in predictors of college mathematics performance and in college mathematics course grades. Journal of Educational Psychology, 82(2), 275-284.
Britton, S., Daners, D., & Stewart, M. (2007). A self-assessment test for incoming students. International Journal of Mathematical Education in Science and Technology, 38(7), 861-868.
Buchalter, B., & Stephens, L. (1989). Factors influencing calculus aptitude.
International Journal of Mathematics Education in Science and Technology, 20 (2), 225-227.
Buchanan, L. K. (1992). A comparative study of learning styles and math attitudes of remedial and college-level math students (Ed.D., Texas Tech University, 1992). Cage, M. C. (1991, 12 June). California community college system agrees to change role
of testing. Chronicle of Higher Education, p. A21.
Callahan, S. (1993). Mathematics placement at Cottey College. The Annual Conference of the American Mathematical Association of Two-Year Colleges, Boston,
Massachusetts.
Campbell, J. W., & Blakey, L. S. (1995). Using Astin’s I-E-O model to assess the impact of early remediation in the persistence of underprepared community college students. Paper presented at the conference of the Association for the Study of Higher Education, November 1995, Orlando, FL.
Carter, S. (1991). Current assessment practices utilized by two-year institutions of higher education to identify academic abilities of entering students (Ed.D., Oklahoma State University, 1991).
Case, J. D. (1983). Predicting student performance in entry level electrical engineering technology and mathematics courses using precollege data (PhD., University of Illinois at Champaign-Urbana, 1983).
Chand, S. (1984). The impact of developmental education at Triton College. Journal of Developmental Education, 9(1), 2-5.
Cohen, A. M. (1985). Mathematics in today’s community college. In D. J. Albers, S. B. Rodi, & A. E. Watkins (Eds.), New directions in two-year college mathematics. (pp. 3-19). New York: Springer-Verlag.
Cohen, A. M., & Brawer, F. B. (1989). The American community college (2nd ed.). San Francisco: Jossey-Bass.
Colorado Department of Higher Education. (2004). Statewide remedial education policy. Retrieved 23 November 2010 from http://highered.colorado.gov/Publications/ Policies/default.html.
Crocker, L., & Algina, J. (2006). Introduction to classical and modern test theory. Mason, OH : Wadsworth Group/Thomas Learning.
Culbertson, W. L. (1997). Improving predictive accuracy for placement in entry level college mathematics courses using available student information (PhD., The University of Toledo, 1997).
Cullinane, J., & Treisman, P. U. (2010). Improving developmental mathematics education in community colleges: A prospectus and early progress report on the Statway Initiative. Paper presented at the NCPR Developmental Education Conference: What Policies and Practices Work for Students?, September 2010, Columbia University.
Dorner, C. S., & Hutton, I. (2002). Mathematics placement tests and gender bias. College and University, 77(3), 27-31.
Durell, F. (1894). Application of the new education to the differential and integral calculus. The American Mathematical Monthly, 1(1), 15-19.
Dykes, I.J. (1980). Prediction of success in college algebra at Copiah-Lincoln Junior College (Ed.D., The University of Mississippi, 1980).
Economics and Statistics Administration of the United States Department of Commerce (1993). American almanac 1993-1994 (Statistical Abstract of the United States 1993). Austin, TX: Reference Press.
Edwards, R. R. (1972). The prediction of success in remedial mathematics courses in the public community junior college. Journal of Educational Research, 66(4), 157-160.
Eldersveld, P., & Baughman, D. (1986). Attitudes and student perceptions: Their measure and relationship to performance in elementary algebra, intermediate algebra, college algebra, and technical mathematics. Community & Jr. College Quarterly, 10, 203-217.
Elliott, J. C. (1990). Affect and mathematics achievement of nontraditional college students. Journal for Research in Mathematics Education, 21, 160-165. Eshenroder, A. (1987). Predictors of success in college developmental and technical
mathematics courses. Toledo: University of Toledo.
Felder, J. E., Finney, J. E., & Kirst, M. W. (2007). "Informed self-placement" at
American River College: A case study. National Center Report #07-2. San Jose, California, National Center for Public Policy and Higher Education.
Friedman, L. (1989). Mathematics and the gender gap: A meta-analysis of recent studies on sex difference in mathematical tasks. Review of Educational Research, 59(2), 185-213.
Geltz, R. L. (2009). Using data mining to model student success (MCIS, Youngstown State University, 2009).
Geradi, S. (1990). Academic self-concept as a predictor of academic success among minority and low-socioeconomic status students. Journal of College Student Development, 31, 402-407.
Goonatilake, R., & Chappa, E. (2010). Early intervention in college mathematics
courses: A component of the STEM RRG program funded by the US Department of Education. The Montana Mathematics Enthusiast, 7(1), 63-74.
Gougeon, D. (1985). CEEB SAT Mathematics scores and their correlation with college performance in math. Education Research Quarterly, 9(2), 8-11.
Green, L. T. (1990). Test anxiety, mathematics anxiety and teacher comments:
Relationships to achievements in remedial mathematics classes. The Journal of Negro Education, 59(3), 320-335.
Hackett, G., & Betz, N. E. (1989). An exploration of the mathematics self-efficacy/ mathematics performance correspondence. Journal for Research in Mathematics Education , 20(3), 261-273.
Hackett, G., Betz, N. E., Casas, J. M., & Rocha-Singh, I. A. (1992). Gender, ethnicity, and social cognitive factors predicting the academic achievement of students in engineering. Journal of Counseling Psychology, 29(4), 527-538.
Hassett, M., Downs, F., & Jenkins, J. (1992). A cased for in-context placement testing. AMATYC Review, 14(1), 68-76.
Helmick, F.I. (1983). Evaluation of the placement test for first-year mathematics at the University of Akron (Ph.D., The University of Akron, 1983).
Hembree, R. (1990). The nature, effects, and relief of mathematics anxiety. Journal for Research in Mathematics Education, 21, 33-46.
Hern, K. (2010). Exponential attrition and the promise of acceleration in developmental English and math. Retrieved from http://www.ftp.rpgroup.org/sites/default/files/ Hern%20Exponential%20Attrition.pdf.
Hills, J. R., Hirsch, T. M., & Subhiyah, R. G. (1990). Issues in college placement. Washington, DC: The ERIC Clearinghouse on Tests, Measurement, and Evaluation.
Hood, D. W. (1992). Academic and noncognitive factors affecting the retention of Black men at a predominantly White university. Journal of Negro Education, 61(1), 12-23.
Hyde, J. S., Fennema, E., & Lamon, S. J. (1990). Gender differences in mathematics performance: A meta-analysis. Psychological Bulletin, 107(2), 139-155.
Ingalls, V.A. (2008). A mixed methods comparison study of placement strategies for college mathematics courses (Ed.D., Ashland University, 2008).
Jaggars, S.S., & Hodara, M. (2011). The opposing forces that shape developmental education: Assessment, placement, and progression at CUNY community colleges (Working Paper no. 36). Retrieved from Community College Research Center website: http://ccrc.tc.columbia.edu/DefaultFiles/SendFileToPublic.asp? ft=pdf&FilePath=c:%5CWebsites%5Cccrc_tc_columbia_edu_documents %5C332_974.pdf&fid=332_974&aid=47&RID=974&pf=Publication.asp? UID=974.
Jenkins, D., & Cho, S. (2012). Get with the program: Accelerating community college students’ entry into and completion of programs of study (Working Paper no. 32). Retrieved from Community College Research Center website: http://
ccrc.tc.columbia.edu/DefaultFiles/SendFileToPublic.asp?ft=pdf&FilePath=c: \Websites\ccrc_tc_columbia_edu_documents
\332_885.pdf&fid=332_885&aid=47&RID=885&pf=ContentByType.asp?t=1. Jenkins, J. H. (1990). Placement practices for calculus in two-year colleges.
Community/Junior College Quarterly of Research and Practice, 14, 123-127. Johnson, L. F. (1993). Relationship of performance in developmental mathematics to
academic success in intermediate algebra (Ph.D., The University of Texas at Austin, 1993).
Kennedy, P. A. (1990). Mastery teaching in college mathematics: Reteaching/retesting. Mathematics and Computer Education, 24(1), 44-51.
Krawczyk, D., & Toubassi, E. (1999). A mathematics placement and advising program. MAA Notes #49: Assessment Practices in Undergraduate Mathematics. Retrieved 9 August 2004 from the World Wide Web: http://www.maa.org/saum/
maanotes49/181.html.
Krol, E. J. (1993). Determining the predictors for student success in achievement in higher education: A focus on the ASSET (Assessment for Successful Entry and Transfer) and HS GPA (high school grade point average) at Henry Ford
Lepley, C. G. (1993). The administrative implications of mandatory and voluntary student placement in developmental education programs for student retention (Ed.D., West Virginia University, 1993).
Llabre, M. M., & Suarez, E. (1985). Predicting math anxiety and course performance in college women and men. Journal of Counseling Psychology, 325, 283-287.
Lovering, S. A. (1989). A study of the relationships between student background factors and grade earned in an introductory college mathematics course and in final cumulative grade point average (Ed.D., Peabody College for Teachers of Vanderbilt University, 1989).
Mathematical Association of America (1990). Official MAA statement on college placement testing. Focus, 10(2), 6.
McCausland, D. F., D. F., & Stewart, N. E. (1974). Academic aptitude, study skills, and attitudes and college GPA. Journal of Educational Research, 67(8), 354-357. McTarnaghan, R. E. (1987). The impact of assessment on minority access. In D. Bray
& M. J. Betcher (Eds.), Issues in student assessment: New directions for community colleges: No. 59 (pp. 75-81). San Francisco: Jossey-Bass.