This is the second post in a series from our Southwest College and Career Readiness Research Partnership with the Arkansas Department of Education (ADE). This post focuses on the impacts and implementation of individual learning plans (ILPs) and builds on a REL Southwest webinar held in April 2019 that explored the research base for ILPs and statewide supports for implementation. View the webinar recording and resources, and for an overview of the partnership’s work, read Part 1 of this blog series.
Individual learning plans (ILPs) are gaining traction as a strategy for promoting students’ college and career readiness and success. ILPs (alternatively called student success plans, academic and career plans, individual career and academic plans) are student-directed plans developed in collaboration with teachers, counselors, and parents that document students’ academic and career interests.
ILPs represent both a process and a tool to document that process. As a process, ILPs allow students to explore postsecondary options, identifying and defining career interests and the skills needed for career success. Together with the guidance of a caring adult, students set intentional course-taking and out-of-school learning goals that align with career and life goals, charting a pathway to success.
ILPs are also a tool to document and track student progress and attainment of skills. Examples of the range of information that an ILP may document include current and past classes, activities, and hobbies; grades, test scores, and results from career interest assessments; personal goal statements; and even college financial planning activities.
Currently, 34 states—including Arkansas, Louisiana, and New Mexico—mandate ILPs for all students with an additional 10 states that strongly encourage their use.1 In our April 2019 webinar, REL Southwest explored the research base for ILPs and featured three states—Arkansas, Colorado, and Wisconsin—that are in different stages of their implementation journey.
Despite widespread use of ILPs, there is currently no rigorous causal research documenting their impacts. Much of what we know about their effects has been documented through qualitative and mixed-methods studies that show ILPs as a potentially powerful tool that can help students become more intentional and engaged in their educational experiences.
One study commissioned by the U.S. Department of Labor’s Office of Disability Employment Policy concludes that ILPs represent a “promising practice”2 for college and career readiness.3 The study researchers recommend several practices that might support ILP implementation, including achieving whole school buy-in, access to online career information systems, professional development, ILP curricula, and inclusion support. The research also points to the importance of ensuring family engagement.
Although currently there is no empirical evidence regarding what constitutes quality ILP implementation, some evidence does exist to support specific practices associated with ILP implementation, such as the development of positive adult-student relationships and student goal-setting.4 According to Belasco,5 students who attend one advising session were more likely to enroll in higher education than students with no advising, and more likely to attend a 4-year than a 2-year institution. In addition, students who are economically disadvantaged who visited an advisor at least once experienced a much larger increase—nearly twofold—in the probability of enrollment than students from higher income families.
Another study examined differences between two goal orientations—mastery goal orientation (which is an essential element in ILP implementation) versus performance goal orientation6—in mathematics.7 The study found more positive math performance, self-efficacy, and persistence for students assigned to the mastery-oriented goals group. Furthermore, research suggests that the specific practices embedded in ILP implementation increase personalization and relevance for students, resulting in higher aspirations and greater engagement in school,8 and that greater engagement is linked with positive student achievement as measured by grades, standardized test scores,9 and increased graduation rates.10
REL Southwest will continue to support ILP implementation in Arkansas, and through the Southwest College and Career Readiness Research Partnership, maintain our focus on ADE’s goal that each student will be engaged in college, career preparation, military service, or competitive employment one year after graduation.
For more information about school transformation, REL Southwest suggests these resources:
Balfanz, R., & Legters, N. (2006). Closing ‘dropout factories’: The graduation-rate crisis we know, and what can be done about it. Education Week, 25(42), 42–43. Retrieved from https://www.edweek.org/ew/articles/2006/07/12/42balfanz.h25.html
Belasco, A. S. (2013). Creating college opportunity: School counselors and their influence on postsecondary enrollment. Research in Higher Education, 54(7), 781–804. http://eric.ed.gov/?id=EJ1039149
Croninger, R. G., & Lee, V. E. (2001). Social capital and dropping out of high school: Benefits to at-risk students of teachers’ support and guidance. Teachers College Record, 103(4), 548–581. Retrieved from https://www.tcrecord.org/content.asp?contentid=10776
Dweck, C. S., & Leggett, E. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95(2), 256–273. https://doi.org/10.1037/0033-295X.95.2.256
Dynarski, M., Clarke, L., Cobb, B., Finn, J., Rumberger, R., & Smink, J. (2008). Dropout Prevention: A Practice Guide (NCEE 2008–4025). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education. http://eric.ed.gov/?id=ED502502
Gibson, D., & Clarke, J. (2000). Growing toward systemic change: Developing personal learning plans at Montpelier high school. Providence, RI: Northeast and Islands Regional Educational Laboratory, Brown University. http://eric.ed.gov/?id=ED445200
Goodenow, C. (1993). Classroom belonging among early adolescent students: Relationships to motivation and achievement. The Journal of Early Adolescence, 13(1), 21–43. https://doi.org/10.1177/0272431693013001002
McDonough, P. M. (2005). Counseling matters: Knowledge, assistance, and organizational commitment in college preparation. In W. G. Tierney, Z. B. Corwin, & J. E. Colyar (Eds.), Preparing for college: Nine elements of effective outreach, (pp. 69–87). Albany, NY: State University of New York Press.
Roderick, M., & Engel, M. (2001). The grasshopper and the ant: Motivational responses of low-achieving students to high-stakes testing. Educational Evaluation & Policy Analysis, 23, 197–227. https://doi.org/10.3102/01623737023003197
Schunk, D. H. (1996). Goal and self-evaluative influences during children’s cognitive skill learning. American Educational Research Journal, 33, 359–382. http://eric.ed.gov/?id=EJ569582
Solberg, V. S., Gresham, S., & Huang, Tsu-Lun. (2010). Individual learning plans: Anacoco High School. Madison, WI: The Center on Education and Work, University of Wisconsin, Madison.
Solberg, V. S., Phelps, L. A., Haakenson, K. A., Durham, J. F., & Timmons, J. (2011). The nature and use of individualized learning plans as a promising career intervention strategy. Journal of Career Development. Advance online publication. https://doi.org/10.1177/0894845311414571
Solberg, V. S., Wills, J., Redmond, K., & Skaff, L. (2014). Use of individualized learning plans as a promising practice for driving college and career readiness efforts: Findings and recommendations from a multi-method, multi-study effort. Washington, DC: National Collaborative on Workforce and Disability for Youth, Institute for Educational Leadership. http://eric.ed.gov/?id=ED588651
U.S. Department of Education. (2016). Non-regulatory guidance: Using evidence to strengthen education investments. Retrieved from http://www2.ed.gov/policy/elsec/leg/essa/guidanceuseseinvestment.pdf
Willingham, W. W., Pollack, J. M., & Lewis, C. (2002). Grades and test scores: Accounting for observed differences. Journal of Educational Measurement, 39(1), 1–37. Retrieved from https://onlinelibrary.wiley.com/toc/17453984/2002/39/1