Posted: September 19th, 2023

Using Data to Drive Cross-Curricular Instruction

ASSIGNMENT

Data should drive instruction and as a best practice teachers should gather formal and informal data before, during, and after every lesson. This is especially important when integrating cross-curricular content into English language arts (ELA) lessons. Students who face learning challenges related to literacy skills often have similar struggles in other content areas such as math, social studies, and science. Since students’ reading, writing, speaking, and listening skills and abilities vary widely in all classrooms, it is important to identify how poor literacy skills can negatively affect performance in other curricular areas and select intervention, remediation, and differentiation strategies that can be applied across disciplines. This can support teachers to meet the unique literacy needs of each student and help them work toward becoming proficient in literacy and more successful in all the content areas.

From the “Class Profiles” topic Resource, select the grade level you are most interested in teaching. Carefully review the data for each student in the profile and then complete the “Cross-Curricular Unit Plan” template as directed.

While APA Style is not required for the body of this assignment, solid academic writing is expected, and documentation of sources should be presented using APA formatting guidelines, which can be found in the APA Style Guide, located in the Student Success Center.

This assignment uses a rubric. Review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. A link to the LopesWrite technical support articles is located in Class Resources if you need assistance.

Using Data to Drive Cross-Curricular Instruction
Teachers are tasked with the challenging job of meeting the diverse needs of all students in their classrooms. With varied literacy abilities, learning styles, cultural backgrounds, and more, differentiation is crucial. One best practice is using formative and summative assessment data to inform instruction across subject areas. By analyzing data from before, during, and after lessons, teachers can gain valuable insights into how to support students’ continued growth.
This article will explore how teachers can leverage data to design cross-curricular lessons that strengthen literacy while teaching other content. Subtitles include gathering data, identifying needs, and applying strategies. Examples from social studies, science, and math will illustrate data-driven approaches. The conclusion restates the importance of data in planning multi-disciplinary instruction tailored for each student.
Gathering Data
The first step is collecting data from various assessments, both formal and informal. Teachers should analyze results from standardized tests, classroom assignments, observations, conferencing, and more (National Center for Learning Disabilities, 2023). This provides a well-rounded picture of students’ current performance levels, challenges, and strengths across subject areas. Data specifically related to reading, writing, speaking, listening, and language usage helps identify literacy-based barriers.
Identifying Needs

Once assessment data is compiled, teachers can identify overarching needs as well as those of individual students. Patterns may emerge showing how certain skills deficiencies negatively impact multiple classes. For example, weak comprehension skills could hinder success in social studies, science, and other content-heavy courses (Snow and Matthews, 2016). Data also pinpoints the specific needs of students with learning disabilities or those learning English. This informs the selection of targeted interventions.
Applying Strategies
With a clear sense of student needs, teachers are equipped to design cross-curricular lessons integrating supportive strategies. In math, incorporating literacy stations allows extra practice with skills like comparing and contrasting (Shanahan and Shanahan, 2017). In science, embedding explicit vocabulary instruction boosts content acquisition (Fang and Schleppegrell, 2010). Social studies lessons can incorporate close reading of primary sources and written responses to develop both discipline knowledge and writing proficiency (Ness, 2016).
Conclusion
In summary, using formative and summative assessment data to understand students’ performance levels empowers teachers to plan targeted, multi-disciplinary instruction. This approach ensures literacy barriers are addressed while teaching other subject matter. With data-driven differentiation embedded across the curriculum, all students receive support to strengthen skills in reading, writing, and more – equipping them for success in school and beyond.
Fang, Z. and Schleppegrell, M.J., 2010. Disciplinary literacies across content areas: Supporting secondary reading through functional language analysis. Journal of Adolescent & Adult Literacy, 53(7), pp.587-597.
Ness, M., 2016. Reading comprehension strategies in secondary content area classrooms: Teacher use of and attitudes towards reading comprehension instruction. Reading Horizons: A Journal of Literacy and Language Arts, 55(1), p.58.
National Center for Learning Disabilities. (2023, January 25). Using Data to Drive Instruction. National Center for Learning Disabilities. https://www.ncld.org/research/state-of-learning-disabilities/using-data-to-drive-instruction
Shanahan, T. and Shanahan, C., 2017. Disciplinary literacy: Just the FAQs. Educational Leadership, 74(5), pp.18-22.
Snow, C.E. and Matthews, T.J., 2016. Reading and language in the early grades. The Future of Children, 26(2), pp.57-74.

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