Better together: Could combining content-rich and personalized approaches be the future of literacy instruction?

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Lauren Gill, Nirvani Budhram, and Amber Oliver

Imagine a classroom environment designed to build students’ background knowledge and vocabulary (in other words, content-rich), with high standards for every child, and structured to meet the needs of students when, where, and how they need it most. Now imagine that this classroom is also using the power of technology to help differentiate learning and bring content to life.

High-quality curricula united with personalized learning*: This is a vision we have presented before. But, as in any marriage, compromise and flexibility are essential.

Thus, as we begin to test and operationalize the vision, we seek to find out: How can we create a new approach to unlock something even more powerful and still maintain what makes each strategy successful? 

Below we explore this question in two areas: time and pace, where we have some idea of what a content-rich approach and personalization fusion might look like; and data and assessments, where the idea is less clear.

Time and pace

A high quality curriculum is one of the most cost-effective ways of improving achievement and increasing equity, partly because it demands synchronization across a clear scope and sequence. When units and lessons are organized around topics and designed to provide students with foundational background knowledge, students have what they need to comprehend future areas of study.

Synchronization also allows for whole-class discussion related to a particular text. Student discussion has proven benefits; as students hear their peers reinforcing, challenging, and adding different perspectives, especially when using a shared text (rather than general strategies applied to separate texts), their learning deepens.

Personalized learning, on the other hand, prioritizes flexibility of time and pace, with students often engaging with different content and progressing at variable rates. Customization based on needs and interests of the individual student is key to accelerating learning in this approach. In a classroom of twenty students, it’s possible that twenty different learning experiences could be taking place at one time, each designed to deliver the right content and rigor to help a student progress toward his or her individual goal.

That’s not to say that a flexible classroom could not enhance the benefits of discussion, especially if strategic, multi-level student groups or differentiated content are designed with the goal of increasing rigor. The risk, however, is that students may be organized around ability, which research has shown to be less impactful and could inadvertently result in tracking students.

Despite these varying approaches, we have seen some schools try to merge the two strategies by segmenting out personalized learning time as a separate class that compliments the core curricular learning. We have also seen the use of multi-week and self-contained deep-dives into a topic where students work both independently and collaboratively. Other models have students cycle through a variety of content-specific learning stations on a fixed schedule, with one or more stations leveraging technology so students can engage with content based on their interests, knowledge base, and individual goals.

These more integrated approaches are rare, but they are the kind of models we are eager to explore, pilot and learn from to see if a true hybrid would make for even greater student gains than we have seen from either to date.

Data and assessment

In a personalized learning environment, technology makes it possible to use student-level data to deliver students the learning experiences that are just right for them, at that moment and in the future.

Although a rigorous, content-rich literacy curriculum is not in opposition with the use of real-time formative data, we must acknowledge that any data-collection tool, formative or summative, risks defaulting to a skills-focus. Why? Because assessing comprehension is hard and often leads to mistaken diagnoses.

If, for example, a third grader fails to satisfactorily summarize a passage or correctly select its main idea on a multiple-choice question, the inclination—whether in a formative or summative context and graded by a human or machine—is to conclude that the student has not mastered Grade 3 Common Core ELA standard RI.3.2: “Determine the main idea of a text; recount the key details and explain how they support the main idea.”

As Timothy Shanahan has commented, it is quite possible that this student indeed mastered the skill but encountered any number of problems that prevented her from properly answering the question. Perhaps she did not know the definitions of key words. Maybe she recognized the vocabulary but did not have the background knowledge to correctly make meaning out of the sequence of words. It is also possible she did not have the attention required to read the long passage. Or she was so excited for lunch that she rushed through her answer. If a computerized assessment misdiagnosed this problem and had a student practice finding the main idea for a week instead of addressing the actual cause of the problem (a vocabulary deficit, for example), the student would make less, not more, progress than if she engaged with the standard curriculum.

A tool that accurately pinpoints the cause of the student’s error—and in doing so, correctly diagnoses gaps in student learning to inform instruction—would be difficult to create but would have far-reaching benefits that would go beyond just student learning to teacher training, curricular rigor, and more. Until we can fill that gap, we can learn from programs that leverage teacher observations of small groups or use technology to assess across several dimensions to accommodate the nuance and complexity of learning to read and reading to learn.

Realizing the vision

Traditionally two separate camps, content-rich advocates and personalized learning enthusiasts are starting to come together to see if the sum can be greater than the parts. This work is hard, but the time is now, as Common Core and other similar college- and career-ready standards have brought the power of content to the forefront, and technology is ever more present and in-demand by students, teachers, administrators, and families.

Let’s figure out together how to leverage this opportunity and support all students in achieving the high expectations we have for them. Help us by sharing your questions, experiences, learnings, visions, and concerns. 

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* In this piece, when we reference “personalized learning,” we suggest a strategy that uses technology intentionally, in combination with traditional, teacher-led instruction, to tailor learning experiences to students’ individual needs through some flexibility of the time, place, and pace of learning. Ideally, student use of technology enables distinct practices and learning experiences that would not be feasible without it.

Lauren Gill is the Program Officer, Education for the Robin Hood Foundation. Amber Oliver is the Director and Nirvani Budhram is the Senior Program Officer of the Robin Hood Learning + Technology Fund, a collaboration between Robin Hood, Overdeck Family Foundation and Siegel Family Endowment. The goal of the Fund is to partner with new and existing high-poverty, public district and charter schools in New York City to leverage and model how technology can spark and deepen learning, specifically around literacy and computing. Michael Horn helped develop the strategy for the Fund and serves on its Advisory Board.