General Education & Making Excellence Inclusive: Pedagogies of Possibilities



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General Education & Making Excellence Inclusive: Pedagogies of Possibilities Jose F. Moreno, Ed.D. CSU Long Beach AAC&U General Education & Assessment Institute June 5, 2015

Topics to Cover Organizational Framework Narratives, Data and The People Who Love Them MEIGE as a Subversive Act

Organized Anarchy

The American college or university is a prototypic organized anarchy. It does not know what it is doing. Its goals are either vague or in dispute. Its technology is familiar but not understood. Its major participants wander in and out of the organization. These factors do not make a university a bad organization or a disorganized one; but they do make it a problem to describe, understand, and lead [and as a result evaluate]. -- Michael D. Cohen & James G. March in Leadership and Ambiguity (1974)

Integrating MEI & GE is a matter of Pedagogy in the Guise of Institutional Research & Renewal A Pedagogy of Possibilities

MEI + GE = MEIGE THINK MEIGE!

BUT BEFORE WE GET TO MEIGE. WHO IS ABLE TO BENEFIT?

Reflective Questions What are your campus graduation rates? Disaggregated by race/ethnicity? Gender? Etc.? What is the demography of your faculty? Administrators? What are your campus narratives to explain successes and gaps? Do your relationships and social networks on campus reflect your values? Or the institutional culture? Both?

IGEA University Avg 6-Year Graduation Rates by Race/Ethnicity or Gender 100% 90% 80% 70% 60% 50% 40% 30% 55% 44% 53% 36% 26% 59% 57% 55% 58% 51% 20% 10% 9% 0% Source: College Results Online, www.collegeresults.org (Data download and constructed by author-dr. Jose Moreno)

www.collegeresults.org

WHERE WOULD YOU GO TO GET YOUR DATA? WWW.COLLEGERESULTS.ORG WWW.COLLEGE-INSIGHT.ORG

Exploring the Student Success Narrative 100% 6-Year Graduation Rates by Race/Ethnicity, 2008 Frosh Cohort 90% 80% 70% 60% 58% 72% 54% 67% 58% 65% 50% 40% 30% 20% 10% 0% Latino White Af Am Asian/PI Am Ind Overall

IS IT OUR DEMOGRAPHY? Undergraduates by Race/Ethnicity 2014 Undergraduate Enrollments by Race/Ethnicity, (%) 100% 90% 80% 70% 60% 50% 40% 38% 30% 20% 20% 23% 10% 0% 4% Latino White Af Am Asian/PI Am Ind 1% Total UG Enrollments = 31,523

IS IT OUR DEMOGRAPHY? Frosh by Race/Ethnicity 100% 2008 Frosh Cohort by Race/Ethnicity, (%) 90% 80% 70% 60% 50% 40% 30% 34% 29% 23% 20% 10% 0% 5% Latino White Af Am Asian/PI Am Ind 1%

IS IT OUR DEMOGRAPHY? Undergraduates by Pell 100% 90% 80% 70% 60% 50% 40% 30% 31% 32% 30% 32% 30% 20% 10% 0% Fall 2003 Fall 2004 Fall 2005 Fall 2006 Fall 2007

IS IT OUR DEMOGRAPHY? First Year Frosh on Pell by Race/Ethnicity, 2008 100% 90% 80% 70% 60% 55% 50% 40% 44% 41% 36% %Pell 30% 20% 10% 12% 15% 0% Latino White Af Am Asian/PI Am Ind Overall

Using Data to Complexify: 6-Yr Grad Rates by Race/Ethnicity & Pell 100 90 80 70 60 50 40 44 39 50 55 54 56 48 44 53 58 56 59 53 48 56 30 20 10 0 Af Am API Latino/a White Total Overall Pell Non-Pell

IS IT THE ACADEMIC PREPARATION? 100% Remediation Rates by Race/Ethnicity or Pell, 2008 Frosh Cohort 90% 80% 70% 70% 65% 69% 60% 50% 52% 47% 40% 33% 38% 30% 20% 10% 0% Latino White Af Am Asian/PI Am Ind Pell Overall

Latino & White 6-Year Graduation Rates by Remediation Type, Class of 2008 100% 90% Latino White 80% 70% 60% 50% 73% 67% 54% 70% 70% 79% 50% 63% 58% 72% 40% 37% 30% 28% 20% 10% 0% NR ER MR EMR Overall Within Coll Note: NR = No Remediation; ER = English Remediation; MR = Math Remediation; EMR = English & Math Remediation; Within Coll = Graduated within college started in e.g. liberal arts, engineering, business etc.

Using Data to Complexify: 6-Yr Grad Rates by Race/Ethnicity, Gender & Pell Men Women White M White W API M API W Af Am M Af Am W Latino Latina 52 43 58 49 54 51 62 58 54 47 58 59 49 43 51 38 46 39 57 46 0 10 20 30 40 50 60 70 80 90 100 Non-Pell Pell

IS IT INSTITUTIONAL ISM? Exploring the Data 100 90 80 70 60 50 40 57 47 30 20 10 0 yes no Racial cultural awareness workshop

Exploring the Data 100 90 80 70 60 50 62 56 73 80 62 60 70 60 40 30 46 38 Racial/Cultural Wksh 20 10 Asian/Pacific Island Latino/a yes 0 White American Indian African American Other no Race/Ethnicity

Course Course PHIL 144 Top 20 "Unsatisfactory Performance" Courses Letters & Arts Top 20 "Unsatisfactory Performance" Courses PHIL 210 ENSC 283 PHIL XX1 MATH 100 HIST 288 EASC 202 MATH PHIL 150 110 PHYS PSYC 321 325 MATH ECON 152 105 LING IAT 352 290 ENSC IS 240 280 CHEM PHIL 151 460 COGS MATH 151 100 PHIL EASC 120W 106 ECON EASC 301 201 CMPT 126 PSYC 303 MACM 201 PHIL 100W MATH 408 HIST 151 STAT 270 LING 482W PHIL 144 HIST 252 BISC 101 HIST 130 MATH 251 ECON 103 PHIL 210 0.0% 0.0% 5.0% 10.0% 10.0% 20.0% 15.0% 30.0% 20.0% 25.0% 40.0% 30.0% 50.0% 35.0% 60.0% % of Awarded Grades that were C- or Less

General Studies Level I Courses, % of D and F Grades Assigned to Each Ethnicity, 2001-02 through 2003-04 Percentage 35.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0 31.4 29.4 22.5 26.1 20.2 19.2 18.6 9.1 African American Native American Asian/ Pacific Islander Hispanic Total Caucasian Other International Ethnicity Source: Metropolitan State College of Denver Equity Scorecard Project: Report to the President, Submitted by Metropolitan State College of Denver Scorecard Team

Elements of Making Excellence Inclusive (MEI) A focus on student intellectual and social development A purposeful development and utilization of organizational resources to enhance student learning Attention to the cultural differences learners bring to educational experiences, and how that diversity can enhance the enterprise A welcoming community that engages all of its diversity in the service of student and organizational learning Source: Susan Albertine & Tia Mcnair, An Evolving Framework for Student Success. Making Excellence Inclusive: A Vision for Equity in Student Success and Quality Learning, AAC&U, Fall 2011.

MEI is Centered on EQUITY AND EQUITY-MINDEDNESS The priority of equity the critical importance of action for equity as we seek to provide high-quality education for all students Acknowledging, not ignoring, the power of race, ethnicity, and socioeconomic class as elements of identity that continue to influence access to quality education Seeking inclusive excellence calls for us to examine institutional policies, procedures, and data as well as to address individual and collective beliefs and prejudices. Source: Susan Albertine & Tia Mcnair, An Evolving Framework for Student Success. Making Excellence Inclusive: A Vision for Equity in Student Success and Quality Learning, AAC&U, Fall 2011.

Digging into Institutional Narratives

How Is Student Success Defined? Graduation Rates? Persistence Rates? GPA? Honors? STEM? Campus Engagement? Learning Outcomes? Community Engagement? Alumni professions? Cross-Institutional indicators? Rankings?

Who Defines Student Success? Have you defined student success? How do you define student success? How do varied constituencies define student success? Executives? Faculty? Staff? Students? Public? How does the institution define student success? Driven by Internal Values? External agencies? Balanced? Is Student Success a Process or Outcome? Or Both? ARE THE GE FOLKS STUDENT SUCCESS-MINDED? AND ARE THE STUDENT SUCCESS FOLKS GE-MINDED?

And On What Basis Do We Decide to Institutional Data? Act? IR just reported that our graduation rates have slipped Cutting Edge Research? AAC&U just published a study that Campus, Regional, National Incident? Student newspaper just published sexist cartoon What is the Institution s Imperative to Act? And is the Action Mission Driven? Or Management Driven that is to Manage the Situation?

Reasons for the Gap? Member of At-Risk Category? (Demography) 1 st Generation; Minority-status; Low-income? Academic (Remedial)? Lack of adequate preparation Of Students? Of Faculty? Of Staff? Institutional Climate Academic; Social; Geographic? Other dimensions?

What Data is Necessary? Course Passage Rates over time (3 Yrs) Is there pattern across multiple sections? Is this pattern consistent? And within a Dept? Disaggregated by college and department Introductory courses? Upper division? Disaggregated by race/ethnicity, gender, class etc. depending on focus Are there differential course passage rates by race/ethnicity? Gender? Academic background?

And at What Level is Data University-wide? Necessary? College-Wide? Department-Wide? Multiple Sections?

Change & Disaggregated Analysis Must Occur on Multiple Institutional Levels Classroom Level (Micro) Pedagogy, Learning Competencies, Active Learning Environment, Curricular Creativity Department Level (Meso) Identify low completion gatekeeper courses; Course scheduling and assignments; Supplemental Instruction efforts; Department selfstudies; Learning Communities within Dept. College and/or University (Macro) Resource allocation; Learning Communities across Departments/Colleges linking courses; Student Support Services; Require as part of Department selfstudy; Include as part of Campus Assessment efforts / supports; Faculty Development Support

MEI Requires Understanding that GE Courses Impact Everyone and at Multiple Levels Artifacts, Routine Behaviors, Deep Structures at micro, meso and macro levels of an institution

When do factors become excuses? Driven by anecdotal or simplified data I talked to a faculty member and he said ; I had a black student who shared with me that 60% of our students are remedial ; We have many urban students Driven by one s own personal experience When I was in college ; In my other institution where I worked Driven by campus or social myths Students have always struggled adapting ; It s the economy Driven by institutional mission It can t be our institutional climate we have a history and mission of diversity/service/humanity We are an access institution therefore

Types of Data Quantitative Data Helps us explore the what and the who (e.g. campus-based surveys) Qualitative Data Helps us understand the why and the how (e.g. focus groups; interviews; observations; document analyses) Process Data Helps us understand and explore where pockets of resistance, inertia, or hope are located And, whether IT is resistance inertia or hope

Effective Student Success Programs (WASC Task Force on Student Success) Elements of an effective program Data based Collaboratively developed Targeted and strategic Accountability established Tracking, assessing and adjusting planned Samples Built on analysis of data Proven effective by data Goal is not to become data-driven but data-guided 38

Institutional Data (Disaggregated by Demographic Variables e.g. race/ethnicity, gender, ses, etc. and At Varied Institutional Levels e.g. University, School/College, Dept/Program, Classroom) Enrollment (Frosh, Transfer, Overall, Graduate) Degrees Conferred College GPA Retention/Graduation Rates Pell Grants Gatekeeper Courses Academic Preparation Campus support program Student Surveys Engagement (campus, dept, classroom) Embedded Practices / Programs Types of Organizations

Possible Institutional Data Sites Institutional Research Office Vice-President for Planning / Research Varied Campus Offices (e.g. Admissions, Registrar, Financial Aid) Past Strategic Plans Accreditation Self-Studies Past Diversity Initiatives Integrated Postsecondary Education Data System (IPEDS) www.nces.ed.gov/ipeds/ College Results Online www.collegeresults.org

Evaluate the Process Identify the place of limitations not just whether there were limitations Data Limitations? Not disaggregated or based in actual point of inquiry Analytic Limitations? Involving decision-makers, analysts AND implementers Process Limitations? Transparent, accessible, collaborative? What are measures that allow you to know it was?

Research As a Tool for Cultural Democracy The utilization of diverse approaches to the study of institutional diversity can assist institutions to understand the relationships that exist across the spectrum of human experiences, particularly concerning issues related to social injustice in addition, a participatory approach that begins and ends with those who are the subjects of study is strongly encouraged. This approach encourages participants to be involved in the planning and development of the study, the collection of data, the final analysis of the information gathered, and the development of a set of recommendations for institutional action Inherent in this approach is not an attempt to learn about people, but to come to know with them the reality that challenges them. Antonia Darder

Web-Based Data Resources Education Trust, Education Trust-West, Education Trust Midwest National & Regional Educational Policy & Data Sites www.edtrust.org (National educational issues) www.west.edtrust.org www.midwest.edtrust.org Institute for College Access & Success Proportion of Pell and Racial/Ethnic Demographics in Higher Education www.college-insight.org Institute for Higher Education Policy Higher Education policy & data sites with focus on underserved populations www.ihep.org/ Pew Hispanic Research Center National & Regional Demographic Reports www.pewhispanic.org U.S. Census Site Library (Infographics, Snapshots etc.) www.census.gov/library.html United States Department of Education www.ed.gov (DOE homepage) www.nces.ed.gov (National Center for Education Statistics) Condition of Education Digest of Education Statistics

Questions? Ideas? Thoughts? Jose F. Moreno, Ed.D. CSU Long Beach Jose.Moreno@csulb.edu