In the aftermath of disruption to classrooms brought on by the pandemic, schools across the country are recognizing the need for lasting, structural change.
The lingering effects of learning loss have made it clear that if schools aim to meet every student鈥檚 needs, empower educators to succeed, or take on systemic changes to district-wide instructional models, such as implementing competency-based education, then it鈥檚 time to commit to personalized instruction at scale.
But from application in one student鈥檚 learning journey to a full-scale instructional remodel, any degree of impactful personalization requires clear, accurate, and actionable student learning data.
McGraw Hill has developed technology that can transform a district鈥檚 approach to leveraging student data, enabling teachers to carve out a unique path to growth for every student and setting administrators up to illuminate those paths for every learner through lasting structural change. Here鈥檚 a look at the innovations on the horizon.
The state of student learning data today
In most districts, valuable student learning data are fragmented across various assessments and instructional solutions. Quality data certainly exist鈥攁 plethora of information is collected in every digital interaction students have with online learning systems, and each of those interactions can tell us something important about their growth and needs. But these data are spread across classes, accounts, and platforms. As educators continue to leverage more solutions to reach more learners, such as intervention and acceleration programs, these data only risk becoming more disconnected.
Agam Altyyev, Director of Academics at LISA Academy in Arkansas, describes the state of student data in his district: 鈥淢ost of the time, raw data is what鈥檚 been thrown out to teachers鈥攚ithout colors, shapes, or dynamic elements, and they鈥檙e expected to make meaningful data points from it and use it frequently. For example, I鈥檓 a data guru in my district. In parent-teacher conferences, I don鈥檛 want my teachers hunting for information across different software to share grades and benchmark assessments. To solve that issue, I created dynamic student-friendly holistic reports for teachers using multiple data points and data analytics.鈥� After manually collecting and interpreting the data, Agam sends reports to his staff in the form of meticulously created charts.
Agam鈥檚 work is deeply valuable鈥攈is staff uses the insights he collects to drive conversations with students and parents and to individualize instruction. But in a time when all educators are constantly being asked to do more with less, the kind of above-and-beyond manual work Agam takes on to collect, manipulate, and make sense of disparate data to illustrate student needs simply isn鈥檛 a realistic expectation to ask of any educator.
In this fragmented environment where educators are taking on the role of data scientists, technology must fill the gap to translate data into meaningful stories about students鈥� learning journeys.
McGraw Hill鈥檚 vision for the next era of personalized learning
, an innovative new tool that connects fragmented data sources from multiple digital solutions into a holistic view of each student, leverages advanced automation and data science to transform the current state of student data. McGraw Hill Plus for PreK 鈥� 12 combines data from core, intervention, acceleration, and even summative assessment sources into a single view of student progress, comparing against state standards and corresponding skills.
As students carve out their own paths by exploring concepts and demonstrating growth in a digital learning ecosystem, educators can watch those paths unfold with remarkable clarity.
McGraw Hill Plus for PreK 鈥� 12 goes a step beyond making data accessible to making it actionable. By drawing from learning resources in a vast content library, the tool鈥檚 recommendation engine suggests enrichment and intervention resources that educators can assign to students with just a few clicks. The richness and precision of the collected data allow the learning scientists and data scientists behind McGraw Hill Plus for PreK 鈥� 12 to map the suggested remediation and enrichment skills right to Vygotsky鈥檚 Zone of Proximal Development, meeting students just where they need to be to achieve mastery.
Dr. Shawn Smith, Chief Innovation Officer at McGraw Hill School, believes McGraw Hill Plus for PreK 鈥� 12 will be an empowering tool for educators looking to personalize learning at scale. 鈥淓ducators need to be able to validate their own instincts in the classroom. They know the context of their students鈥� complex needs better than anyone. If we can provide them with the right data at the right time and automate the information they need to make informed instructional decisions, the sky鈥檚 the limit for the innovation that any district can pursue.鈥�
A step closer to district-wide teaching and learning transformations
On an individual or classroom level, McGraw Hill Plus for PreK 鈥� 12 will open personalized pathways, foster student agency, and enhance insights available to educators. But at a larger scale, this kind of innovation could be a key factor to drive the transformative, systemic changes district leaders are looking for post-pandemic.
Mastery-based and competency-based learning models are receiving a , and for good reason. It鈥檚 clearer than ever that seat time is a poor indicator of students鈥� place on their learning journeys, and that learning needs vary more widely within student populations than perhaps ever before. But moving an entire school鈥攍et alone a district鈥攖o a competency-based model is no small feat. It requires a scalable, effective approach to personalized learning and quick access to actionable data.
Dr. Katie McClarty, Chief Academic Officer at McGraw Hill School, believes that new approaches to data are vital for schools to pursue these innovative instructional models.
鈥淐ompetency-based education requires educators to target clearly defined competencies, use specific measurements of competencies, and adapt instruction to help every student reach mastery.
Most of the time, however, a lesson will address multiple competencies at the same time and multiple approaches are used to determine whether a student has truly achieved mastery. McGraw Hill Plus for PreK 鈥� 12 provides a point-of-use visual of students鈥� growth in individual competencies down to the skill level, using multiple data sources to provide detailed insights about what a student has mastered and where more learning is needed. This allows educators to focus their time on instructing and helping students, rather than assessing, combining, and interpreting data.鈥�
Implementing a mastery or competency-based model is inherently reliant upon scalable personalization, which, Dr. McClarty argues, comes back to the data. 鈥淭o get to the point of true personalization at scale, there must be an easy way to integrate information across a variety of sources and provide a quick snapshot of student progress.鈥�
To learn more about McGraw Hill Plus for PreK 鈥� 12, visit: