DEVELOPMENTAL MATH Changing Student Outcomes with Adaptive Learning Technologies LaVerne W. Ellerbe August 3, 2011

Introduction Mathematics is a basic requirement for most community colleges students (Lutzer, et al., 2007) By the end of 12th grade, only 25% of Blacks, 20% of Hispanics, and 39% of Whites are prepared for college- level math (Rose & Betts, 2001). As it is impractical to send adults back to high school, remediation is indispensable to obtaining postsecondary credentials (Roberts, 1986). A combination of innovative instruction and adaptive learning technologies promise to improve student outcomes in developmental math, but empirical evidence remains sparse (Epper & Baker, 2009).

Purpose This research proposes to study the effect of adaptive learning technologies on student success in developmental math and its impact on college advancement rates. Issues related to technology, student populations, faculty, curriculum, pedagogy, and policy will be explored. Potential paths include:

Theoretical Support: Scaffolding Linked to Soviet psychologist Lev Vygotsky ( ) Defined by Wood, Brunner, and Ross (1976) as an adult controlling those elements of the task that are essentially beyond the learners capacity, thus permitting him to concentrate upon and complete only those elements that are within his range of competence

Scaffolding: Zone of Proximal Development

Model for Combined Technology & Innovative Instruction

Dependencies and Resources

Issues & Information to be Developed Human instruction and technology complement each other o Faculty and administrative support are essential o Instructional culture may be resistant to change All key factors must be considered o Student population characteristics (ethnicity, age, gender, enrollment status, and SES) o Faculty perceptions (student capabilities and limitations, viability of technology) o Cost/benefit of technology (time and dollars to implement and recover investment) o Policy and organizational politics Required math courses (developmental, gatekeeper, by degree/certificate) Institutional funding driven by enrollments, not completions Student financial aid versus pass rates and success in developmental courses o College Advancement Rates Enrollment, persistence, transfer and degree/certificate completion rates Impact of technology on system wide developmental math goals

Timeline

Conclusions & Expected Outcomes Anticipated benefits from incorporating Adaptive Learning Technologies into the developmental math curriculum include: o Ability to address individual student needs, thereby reducing many of the challenges associated with traditional online learning o Improved diagnostic capabilities for student placement o Fewer students retaking developmental math courses resulting in a reduction in time to complete the developmental math sequence o Higher pass rates and fewer retakes, allowing students to take for–credit courses sooner

Limitations & Unknowns Start date (data collection) Time constraints (research design, observation, data management) Approvals (Proposal, IRB) Budget

Appendix Research Praxis Journal Entries 2, 4

Appendix FOCUS: Effect of Adaptive Learning Technologies on Student Success in Developmental Math & Community College Advancement Rates Overarching Question DATA SOURCES Source 1Source 2Source 3 To what extent are student expectations for success in developmental math shaped by academic, socioeconomic, and demographic factors? Student survey to measure perceptions & behaviors associated with success in math, i.e., mathematics self-concept, attitude toward problem solving, etc. Instrument: Views About Mathematics Survey (Carlson, 1999) Student assessment of math performance and mastery. Instrument: Patterns of Adaptive Learning Scales (Midgley et.al., 2000) Grade in last high school math course completed, pre-test: placement/diagnostic scores, and post-test: grade in developmental math course. Group by age, gender, SES, ethnicity, HS District, enrollment status, financial aid status What instructional factors affect student engagement and success? Faculty interviews to determine the level professor involvement, professional development, and teaching status, along with the extent to which instruction can be differentiated based on student attainment, mastery, and goals. Evaluation of technology-based developmental math curricula and course offerings to determine and fidelity of delivery, validity, reliability, and generalizability Monitor and measure the amount of time required for student mastery based on level of differentiation, study time, progression to higher level math courses, transfer and completion rates. What policies impact student success in developmental math and institutional advancement rates? State policy: Research and report on math requirements for high school graduation, and how college advancement rates factor into the higher education funding formula Virginia Community College System: Cut scores for recommending placement in developmental math. Policy on by-passing developmental courses. Institutional Policy: Research the structure and organization of developmental math programs. Interview administrators and faculty to document organizational culture, accepted norms, benchmarks for success in terms of student outcomes and program goals.

What are student expectations of math requirements prior to enrolling in community college, are these perceptions related to high school experiences with math? To what extent does curriculum and course design affect student engagement in developmental math? Is design a factor in student persistence? How does professor involvement, training, and attitude contribute to student persistence and college advancement metrics? Do students who successfully complete a sequence of developmental math courses persist, transfer, or complete a degree or certificate? What are student expectations of math requirements prior to enrolling in community college, are these perceptions related to high school experiences with math? To what extent does curriculum and course design affect student engagement in developmental math? Is design a factor in student persistence? How does professor involvement, training, and attitude contribute to student persistence and college advancement metrics? Do students who successfully complete a sequence of developmental math courses persist, transfer, or complete a degree or certificate? Adaptive Learning Technologies: Effect on Student Success in Developmental Math and Community College Advancement Rates Appendix