References

Birnbaum, R. (1988). How colleges work: The cybernetics of academic organization and leadership. San Francisco: Jossey-Bass.

-  college structures (collegial, bureaucratic, political, anarchical)

-  power structures (collegial, decision by consensus; bureaucratic, little involvement from below; political, deal making/quid pro quo; anarchical, power at department level, president simply goes with the flow)

-  are collegial institutions the only place where all constituents are consulted for effects of decisions??

Brown, R. P. (2004). The transition of a historically Black university into a predominately white institution. Unpublished doctoral dissertation, University of Maryland, College Park.

-  supports the point that Morrill II perpetuated the growth of HBCUs in the United States

Bryson, J. M. (1995). Strategic planning for public and nonprofit organizations. San Francisco: Jossey-Bass.

-  planning strategies (short term, strategic, long-term)

-  planning differs between corporate model and academic model

-  REMEMBER, motivations between corporate and academic not that different…it’s how they get to the outcomes that differs

-  good planning involves obtaining input and by-in from as many constituents as possible (diametrically opposite of what occurs in higher education except at the collegial level; other types of higher ed [bureaucratic/political/anarchical] only want feedback and by-in from constituents at the department/division level and only when those constituents can affect their operations/outcomes)

Campbell, J. (1995). Understanding John Dewey. Chicago: Open Court.

-  supports argument about the positive role of higher education in a democracy

-  Dewey’s claims that education is for the better good of the democracy

-  Dewey claimed that children’s learning is rooted in interest and experience (ties to Kolb’s Experiential Learning Theory…experience key in learning)

-  Hutchins view on education….for the elite and curriculum should be centered around the “great books”.

Evans, N. J., Forney, D. S., & Guido-DiBrito, F. (1998). Student development in college: Theory, research, and practice. San Francisco: Jossey-Bass.

-  Chickering’s 7 vectors (1: developing competency; 7: developing integrity….my argument: attending to 1 and 7 is key and 2-6 will happen on their own.

-  William Cross’ racial identity theory for African-Americans

-  Kolb’s Experiential Learning Theory (based on Dewey, Lewellen, Piaget…experience and doing are critical to learning)

-  Perry’s Learning Theory (dualism: taking knowledge from teacher, no questioning; multiplicity: recognizing different people have different viewpoints, however wrong they may be; relativism: OK, maybe other’s views are that wrong; commitment to relativism: I posses the efficacy to determine what is right/wrong, value/no value, and apply them to my life)

-  Alexander Astin: student involvement is key to successful educational outcomes

-  Baxter-Magolda: different ways of making meaning (absolute: analogous to Perry’s dualism stage;

Gall, M. D., Gall, J. P., & Borg, W. R. (2003). Educational research: An introduction (7th ed.). Boston: Allyn-Bacon.

-  various quantitative techniques (t-tests, ANOVA, regression, structural equation modeling, cross-tabulations)

-  various qualitative techniques (ethnography, focus group, interview, oral history)

-  various quantitative data collection techniques (Likert scale survey, database)

-  various qualitative data collection techniques (active participant, participant observer, going native, interview formats [open ended questions], audio/video)

-  research design (pre-test/post-test; treatment group/control group; Latin squares; planned contrast)

-  causality-must have intervention

Hamrick, F. A., Evans, N. J., & Schuh, J. H. (2002). Foundations of student affairs practice. San Francisco: Jossey-Bass.

- Helms and Phinney’s ethnic identity models

Henson, R. K. (2006). Effect size measures and meta-analytic thinking in counseling psychology research. The Counseling Psychologist, 34(5), 601-629.

-  effect size measured in typically 2 manners: standardized mean differences between groups, and variance accounted for

-  effect size measures are better descriptors of “practical” differences between groups or the magnitude of an association

-  effect size measure for t-test: Cohen’s d and Glass’ Delta (both are standardize mean differences)

-  effect size measure for ANOVA: eta square (SS within/between divided by SS total); Cohen’s d for post-hoc standardized mean differences between groups

-  effect size measure for regression: R² (variance accounted for); Ezekekial developed adjusted R²

-  effect size measure for descriptive discriminant analysis: 1-Wilks’ lambda

-  effect size measure for predictive discriminant analysis: Huberty’s Improvement Index

-  effect size measure for canonical correlation analysis: square canonical correlation

-  effect size measure for factor analysis: % variance explained for entire solution and each factor

Hinkle, D. E, Wiersma, W., & Jurs, S. G. (2003). Applied statistics for the behavioral sciences. Boston: Houghton Mifflin Company.

-  Type I error: the probability of rejecting a true null hypothesis; represented by a priori determined level of alpha (social sciences typically accept .05).

-  Type II error: the probability of failing to reject the false hypothesis: represented by a priori determined acceptable level of power

-  Power: the probability of not committing a Type II error (power is function of alpha level, sample size, effect size)

-  typically, as alpha increases (from .001 up), the power of a test increases (in other words, to minimize the possibility of committing a Type I error, you increase the risk of making a Type II error!!!)

Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis. Thousand Oaks, CA: Sage Publications.

-  qualitative methodologies and collection methods

-  building your dissertation upward (page 91 I believe)

Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students (2nd ed.). San Francisco: Jossey-Bass.

-  Astin’s I-E-O Model:

-  Tinto’s work on student attrition behavior (if a student does not become engaged, the likelihood of attrition increases…supports Astin’s Model)

-  Another source for Chickering

-  Another source for Baxter-Magolda

-  Pascarella and Terenzini’s work is the seminal synthesis of myriad research on the net effects of college when considering: student differences, institutional type, institutional governance, campus involvement, academic performance, financial aid, ethnicity

Pedhazur, E. J. (1997). Multiple regression in behavioral research: Explanation and prediction (3rd ed.). South Melbourne, Australia: Wadsworth.

-  reference to beta weight

-  structure coefficients??

Rudolph, R. (1962). The American college & university: A history. Athens, GA: The University of Georgia Press.

-  Yale Report of 1828

-  Morrill Act I of 1865 (westward expansion of higher education)

-  Morrill Act II (perpetuation of HBCUs…see Brown citation above)

-  Jolliet Junior College 1901 (William Rainy, founder and president of University of Chicago)

-  GI Bill 1945

-  Civil Rights Act 1963

Stevens, J. P. (2002). Applied multivariate statistics for the social sciences (4th ed.). Mahwah, NJ: Lawrence Erlbaum Associates.

-  MANOVA

-  Canonical correlation

-  Factor analysis

Texas House of Representatives. (2003). House bill 3015. Retrieved November 20, 2006 from http://www.capitol.state.tx.us/

-  tuition deregulation of 2003

-  increase board designated tuition

-  bottom line, perpetuated higher education as user expense

Wilkerson, L., & Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanation. American Psychologist, 54, 594-604.

-  the need to report effect sizes…should always report effect sizes

-  simply stating statistical significance does not provide reader with practical implications…something may be practically significant and not statistically significant and vice-a-versa