Advocating for Students’ Unfinished Learning Needs

Overview

Since the start of the COVID-19 pandemic, much of the research around learning has centered on “learning loss,” or gaps in knowledge and performance. In contrast, The Learning Accelerator (TLA) has advocated for an asset-based approach. Instead of focusing on gaps in scores, we have advocated for the examination of patterns of growth to deeply understand where differences in progress occurred, or the degree to which learning remained “unfinished.”

Unfinished learning is a term used to define the learning that students have yet to complete, have not had access to, and have not yet had the opportunity to demonstrate at the intended level of mastery. While it has been several years since the onset of the pandemic, the research that we completed to address the urgent unfinished learning needs of the sector remains relevant and should be used as a springboard to advocate for current students. Data plays a critical role in this work and should be used to advocate for the continuation of accelerated learning practices, ongoing experiential and relevant professional learning, as well as the creation of learning environments that celebrate student progress and growth.

Through our work, we have found that leveraging data to advocate for student’s unfinished learning needs should include the following considerations.

• Educators should incorporate the use of frequent data cycles to accelerate learning. While assessments such as i-Ready, Dynamic Indicators of Basic Early Literacy Skills (DIBELS), and the Independent Reading Level Assessment (IRLA) may vary in frequency and assessment type, they can directly inform how teachers plan, deliver, and evaluate student learning.

• Relatedly, our research found that a key accelerant for individual student growth and progress includes using data to personalize learning experiences. In doing so, educators can meet both the academic and social-emotional needs of each learner – instead of using a single, one-size-fits-all approach. Personalization includes a constellation of strategies that allow teachers to respond to the unique needs, strengths, identities, motivations, and contexts of their students. It also emphasizes the importance of understanding what individual learners already know and understand, what they are ready to learn, and where they need support.

• Professional learning implemented to address unfinished learning should continue to support and equip teachers with needed skills and knowledge to effectively utilize data-driven approaches. It should also be evaluated by assessing participants’ reactions and learning progression as well as the effects on organizational change and student outcomes.

• Effective use of data can support the implementation of targeted and relevant, actively engaging, socially connected, and growth-oriented learning environments. To advocate for students, data should be leveraged to tailor instruction and educational experiences to meet the unique needs, preferences, and learning approaches of individual students. Data collection should include students’ academic performance, learning preferences, interests, and progress over time.

Critical to meeting students’ needs, collecting ongoing data to measure progress enables educators to identify areas of needed support and make iterative improvements. When performed responsibly, data-driven advocacy to address ongoing unfinished learning has the potential to enhance student engagement and achievement as well as identify effective systems and supports.