Introduction: The Groton-Dunstable Regional School District (GDRSD) is a pre-kindergarten through twelfth-grade regional district located 45 miles northwest of Boston, Massachusetts. For the 2019-2020 school year, GDRSD enrolled 2,353 students and employed 181.8 teachers, accounting for a 13.2-to-1 student-to-teacher ratio (2019 Official Accountability Report, 2019). The GDRSD school committee approved a district vision committed to the belief that all students can achieve at high academic levels when instructed in a universally designed teaching and learning model. Furthermore, all personnel, including administration, instructional, and support staff, should strive to eliminate inequities for all students (About us – GDRSD district, 2020).
The responsibility for carrying out this vision was assigned to the district administration, and then to GDRSD’s teachers. The expectation for this transformational leadership was to embrace a growth mindset, push to eliminate inequities for all students, and foster innovative classroom environments. The GDRSD vision dovetails with existing district initiatives, such as the Strategic Technology Plan and Needs Assessment Report, to implement a universally designed, tiered instructional model that empowers students to be self-directed, creative problem-solvers. Additionally, as a part of a collaborative visioning process within the community, considerable energy has been expended in support of teachers, including refining the evaluation system, creating, and implementing professional learning communities centered around data-informed decision making, expectations of inclusive practices, and adoption of state standards, each in an effort to support learner variability and eliminate inequity when exposed. It remains a priority to support teachers in all facets of their positions because exemplary instruction is the most critical means to positively impact student achievement and ensure equitable outcomes (Elmore, 2004; Leithwood et al., 2004).
Continuing in this vein, synthesizing over 1,600 meta-analyses involving over 300,000,000 students, Hattie’s (2018) Visible Learning research focused on public schooling and the effect sizes that influence student achievement. With 252 factors listed and an average effect size of 0.4, collective teacher efficacy (1.57) is listed as having the most significant effect on student outcomes (Hattie, 2018). After technological infrastructure barriers have been overcome—ubiquitous access to the Internet and Internet-enabled devices—a teacher’s education and beliefs, or efficacy, on educational technology integration have the most significant influence and are central to the implementation of technology within the classroom (Drent & Meelissen, 2008; Gilmore & Ross, 2020; Hattie, 2018; Prestridge, 2012; Sang et al., 2011).
By most measures, GDRSD is a high-performing school district. Students arrive each day ready to learn. A dedicated staff of licensed instructional leaders, as well as non-instructional support personnel, allows students to meet or exceed nearly all accountability measures from annual assessments on the Massachusetts Comprehensive Assessment System (MCAS) (2019 Official Accountability Report, 2019). Regarding overall progress toward student growth targets, including English language arts and mathematics achievement indicators, GDRSD has a cumulative criterion-referenced target percentage of 84% (2019 Official Accountability Report, 2019). This target percentage signifies how GDRSD performs when compared to other districts across the state. In GDRSD’s situation, the district is meeting and/or exceeding its student growth targets better than 84% of districts within Massachusetts. However, accountability trends are declining for the high-needs subgroup, which includes economically disadvantaged students.
With a recent change in definition and move away from low-income status, the Massachusetts Department of Secondary and Elementary Education (DESE) defines economically disadvantaged as a student’s participation in one (or more) of the following state-administered programs: the Supplemental Nutrition Assistance Program (SNAP); the Transitional Assistance for Families with Dependent Children (TAFDC); the Department of Children and Families (DCF) foster care program; and MassHealth (Medicaid) (Redefining low income, n.d.). As a reference point, for a family of three to remain eligible for the TAFDC program, the monthly income allowance from the parent(s) of a child under 18 is $3,620.00 (Department of Transitional Assistance, 2020). By changing its poverty metric to economically disadvantaged, DESE intended to reduce paperwork and administrative burden. Instead, the changes have confused exactly who is contending with financial hardship. However, as Edward Moscovitch, a researcher who developed the Commonwealth funding formula that included a broader low-income definition, shared, “how can the state determine what’s working to improve low-income students’ performance if it can’t locate and track those students?” (Larkin, 2019, para. 8).
Within the last decade, GDRSD has experienced substantial cuts to staffing and programming. Budget shortfalls within the local funding process and the failure of operational overrides at local town meetings have led to larger class sizes and the loss of programs, which are likely catalysts for lower academic achievement. Only over the past several fiscal years was staffing restored to adequate levels to support the vision for educational programming and Universal Design for Learning (UDL) infused instruction. With limited financial resources, the district administration’s recommendations in the Needs Assessment Report identified priorities the district must take action on. The cost-saving analysis performed by an outside consultant, captured in the Needs Assessment report, supported programmatic changes to staffing levels, curriculum and assessment materials, school committee communication methods, and management and operations cuts to provide additional funding to grow academic achievement for all students further. However, there are still subgroups of students, specifically economically disadvantaged students, failing to close the educational achievement gap between all students, which will be reviewed during this exploration.
Statement of Problem
Fourth-grade students labeled economically disadvantaged are performing significantly lower on the Massachusetts Comprehensive Assessment System (MCAS) in English Language Arts than fourth-grade students without this label. Overall, financially underprivileged students face a range of adverse consequences and, in recent history, have experienced inadequate improvement (Ander et al., 2016). Furthermore, just some of the consequences facing economically disadvantaged students include lower academic outcomes on testing (Freedberg, 2019), concerns with self-regulation (Howse et al., 2003), increases to the reading achievement gap during school breaks (Allington et al., 2010; Schacter & Jo, 2005), gaps in preparedness for kindergarten, with impacts felt through an entire academic career (Garcia & Weiss, 2017) and many more.
Purpose of the Study
The purpose of this study is to examine (and elicit further discussions) how district and instructional staff can better deliver pedagogical and technological principles of Universal Design for Learning (UDL) in an effort to align best practices that will close the academic achievement gaps in MCAS testing among economically disadvantaged students in the fourth grade. Further research is needed to examine the systemic and instructional root causes of the widening achievement gap for economically disadvantaged students. The district’s commitment to a standards-focused curriculum across all subjects of the Massachusetts Curriculum Frameworks, particularly English language arts, and to incorporating the UDL framework is essential to note, but only with a modicum of success for this subgroup of students.
Research Question
How does universally designed instruction at GDRSD impact the academic outcomes of economically disadvantaged fourth-grade students in the subject area of English language arts?
Significance
Beginning in 2014, GDRSD has sought ways to sustain and provide a context for UDL-infused instruction across all subject areas, particularly English language arts and literacy. Instructional approaches, along with lags in curriculum development and incomplete adoption of standards, are likely at play in recent drops in academic achievement. Since the implementation of the Common Core State Standards, adopted as the Massachusetts Curriculum Framework for English Language Arts and Literacy in 2010 and updated in 2017, literacy has declined nationwide (Barnum, 2019), and these declines have also occurred at GDRSD. As included in the district visioning process, eliminating inequities for all students, especially economically disadvantaged students, is a priority, with a universally designed, tiered instructional model at its core. UDL instructional approaches, alongside essential English language arts standards, should be symbiotic and have a positive impact on learning outcomes.
UDL principles have a foundation entrenched in modern neuroscience and can be best defined as a framework that eliminates barriers and a “framework to improve and optimize teaching and learning for all” (Cast, 2018, para. 2). The approach to district-level UDL implementation requires consideration for not only student variability but also technology-related obstacles and consideration for the necessary time and learning styles amongst staff. There is consensus that educational organizations need to build capacity for managing high-level changes that UDL adoption, and secondarily technology integration, demand (Hall et al., 2015; Meyer & Stensaker, 2006). Through a universally designed lens, GDRSD seeks to support, as Meyer et al. (2014) have shared, a curriculum and instructional approach that develops expertise as a learner and maintains innovative learning environments that support continuous self-development. Further, as the instructional staff who have received training in the UDL framework and have subsequently retired (or left) from GDRSD, teacher preparation in higher education does not mandate or incorporate UDL best practices infused with technology (Moore et al., 2018; Nepo, 2017). GDRSD pre-service and current teachers often lack a practical approach or “hook” to integrating technology into their classrooms, which aligns well with the UDL framework (Russell et al., 2003).
Tangential to the statewide assessment data, GDRSD captures other internal measures in English language arts to adjust UDL-infused instruction and develop academic interventions. Teachers must raise their grading practices and increase expectations for all students as an important measure toward increasing academic achievement on MCAS. Research by Gershenson (2020) shares that awarding higher report-card grades to students who score poorly on statewide assessments indicates a weak curriculum and low academic standards. Gershenson (2020) continues that all student subgroups have significantly improved learning outcomes when teachers set higher grading standards, placing a great deal of responsibility on teachers. “We must learn how to make high expectations and high grading standards a part of the teaching culture through hands-on teaching, optimized incentives, and stronger professional development” (Gershenson, 2020, p. 35).
Status of UDL Implementation
GDRSD seeks to increase academic achievement as an expected outcome for all students, with an emphasis on the high-needs population, including economically disadvantaged students and the variability in learning inherent to all students. By adopting UDL and a multi-tiered system of support (MTSS), district leadership implemented foundational, research-supported systems grounded in best practices and national research. Rather than remain stagnant, district leadership has been proactive in implementing both academic support systems and is likely years ahead of some comparably located and sized districts. “Good leaders know when it is time to change and when it is not—when inertia should be left alone and when it should be challenged” (Marion & Gonzalez, 2014, p. 361).
Although reliant upon Universal Design (UD), which originated in the 1970s, UDL was only expanded upon in the realm of effective pedagogy and learning in the early 2000s (Meyer & Rose, 2000). With UDL only scratching the surface and a relatively new framework in public education, GDRSD has made significant strides in offering professional development opportunities throughout the year focused on instructional and technology integration strategies on the principle that “all students are capable of success” (Massachusetts Department of Elementary & Secondary Education, n.d., p. 2). With foundational development of MTSS infused with UDL, GDRSD is no longer reactive to student achievement declines and is instead supporting “a comprehensive continuum of evidence-based, systemic practices to support a rapid response to students’ needs, with regular observation to facilitate data-based instructional decision making” (ESSA, 2015, p. 2093).
The district professional development committee has allocated scarce time and resources to a more meaningful implementation of UDL, including in-service sessions, graduate-level courses, and continued direction and leadership from district personnel, including principals, technology support staff, curriculum coordinators, and coaches. Also, considerable time and resources have been spent on informal discussions about effective teaching practice and the reflection required to implement a change in practice. Papa (2010) notes the importance of providing teachers with time to reflect on their own practices when implementing a change initiative by providing sufficient “opportunities to practice and observe, and opportunities to be coached and coach others” (p. 15).
Research by Meyen (2015) raises the bar by showing that both technological and educational advancements are meshing to meet the needs of diverse learners. Further, incorporating digital tools in the classroom can anticipate learner variability and reduce barriers by using UDL as an effective instructional delivery method (Nepo, 2017). GDRSD instructional staff are working to embrace technology as an instructional delivery method in conjunction with the UDL framework; however, achievement gaps persist.
Economically Disadvantaged Students and Assessment Data
Economically disadvantaged students represent 8.9% of the GDRSD student population and are outperformed by all students at all grade levels using the Massachusetts Comprehensive Assessment System (MCAS) metric (2019 Official Accountability Report, 2019). When examining student achievement, the district considers other assessments. However, MCAS is given the most significant weight in the student academic profiles. In grade four, among all students who are not economically disadvantaged, 77% are meeting or exceeding the ELA MCAS assessment in 2019. In contrast, 38% of economically disadvantaged students are meeting or exceeding the ELA MCAS assessment. Important to consider are the similar downward trends in Mathematics MCAS and the slight declines in Science MCAS achievement results. With DESE creating a new MCAS assessment, including formula changes to accountability measures and updates to subgroup definitions, it is challenging to identify overarching trends in MCAS data before 2018, especially when accounting for different grade-level cohorts. However, prior MCAS assessment data from 2018 can be compared with the current 2019 data, and a downward trend is noted. In grade four, in 2018, 69% of non-economically disadvantaged students met or exceeded the ELA MCAS assessment, and 55% of economically disadvantaged students did so. Compared with 2018, the achievement of non-economically underprivileged students increased by 8%, while the achievement of economically disadvantaged students decreased by 17% on the ELA MCAS assessment.
UDL, Digital Tools Can Support Meeting the Needs of All Students
As Director of the Department of Technology & Digital Learning, this author seeks to better align the integration of technology with universally designed learning principles to increase academic achievement for economically disadvantaged students. As instructional practices shift towards UDL, the Department seeks to be involved in the creation of standards-based lessons and assessments, and to support staff in best teaching practices. The Department and Director must increase knowledge on the integration of UDL and technology-enhanced learning, which can promote practical approaches in delivering instruction to meet the needs of all students in all educational environments (Hall et al., 2015). As Moore et al. (2018) have noted in their research, UDL principles often fall short due to their complexity, the knowledge required of teachers, and the lack of a clear issue to address. With recent MCAS data highlighting an unfavorable achievement gap widening for economically disadvantaged students, the critical issue is now front and center.
Many students from economically disadvantaged backgrounds underperform their peers in reading and literacy assessments, which has been linked to intrinsic motivation and self-efficacy (Guthrie et al., 2009; Ng, 2018). Schmoker (2020) concisely shares that literacy “is the single most important goal of schooling and the key to academic and career success.” When a teacher supports motivation and students’ voice, sharing of ideas and perspectives, through purposeful reading engagement, for example, allowing reading materials to be brought in from home, a stronger student-teacher relationship can be formed, and school outcomes improved for economically disadvantaged students (Ng, 2018). Further, Ng (2018) interprets engaging financially underprivileged students by carefully listening to their views and establishing “contexts that give rise to the life histories, personal experiences, and beliefs which underpin their voices” (p. 703). Continuing to promote reading engagement and student choice is significant as it contributes to the teacher’s knowledge to continue to develop more engaging reading practices (Rudduck & Fielding, 2006).
Since the adoption of the Massachusetts Curriculum Frameworks and subsequent updates, the major focus of English language arts instruction has been teaching students to write well across a variety of genres and formats, both digital and analog, while using technology for collaboration. The application of writing across the curriculum, for example, in science, is worthwhile, with outcomes that support economically disadvantaged students in “acquire academic language and conceptual understanding” (Huerta et al., 2014, p. 1850). Further, economically disadvantaged students who participated in writing interventions obtained higher scores on statewide standardized writing tests than those students who did not participate in the academic interventions during the same time (Amaral et al., 2002).
At GDRSD, all students are provided a classroom-based Google Chromebook in a 1:1 computing environment, allowing access to creative and innovative learning experiences throughout the school day. Research has found positive conclusions about the benefits of ubiquitous 1:1 technology access in the classroom, with consistent effects on English language arts achievement (Clariana, 2009; Zheng et al., 2016). According to Calkins et al. (2015), “writing is a subject in which the quality of students’ work can improve in only a matter of weeks in ways that are visible to both (the teacher) and students” (p. 3). Similarly, in another study, Lee et al. (2005) found that elementary-aged, economically disadvantaged students participating in science and literacy interventions exhibited substantial gains in writing achievement measures over the course of a year. Given the visible growth shown in such a relatively short period of time, it is important to identify methods that leverage improvements measured in weeks, not years or longer. A standards-aligned focus requires students to demonstrate their understanding and mastery of the Massachusetts Curriculum Framework for English Language Arts and Literacy in Writing, and this ideal can be bolstered across all subjects through adjustments to instructional practice, including research-supported academic interventions and stronger teacher-student relationships, which are shown to increase academic achievement.
Conclusion
Rooted in adopting district-wide UDL implementation to close achievement gaps, there is a need to strategically connect pedagogical and curricular development to eliminate inequities for all students. UDL instructional practices account not only for student variability in engagement, purpose, and motivation within the classroom but also for providing educationally diverse learning environments so that all students may benefit from and access grade-level standards and academic rigor. General digital tools, from Internet-enabled devices to assistive software, support UDL principles that enable self-differentiated learning and authentic assessments and should be considered in a comprehensive curriculum (Kurtts et al., 2012). As directed by the school committee, GDRSD must pursue radical new measures to close the academic achievement gaps among subgroups of students, including economically disadvantaged students. These actions will require a strategic shift to increase the rigor of grading practices, further develop data-driven decision-making in support of instructional changes, define programming for the whole child, including social and emotional learning, and expand special subject program offerings. Also considered are the programmatic changes aimed at supporting all students in a growth mindset, where each child understands that their talents and abilities can be developed through effort, quality teaching, and persistence (Dweck, 2006).
Definition of Terms
Academic Intervention: An academic or behavioral instructional scaffold to support students’ improvement with a specified task (i.e., reading, writing) to meet the needs of all learners (tier 1). In addition, there is a range of tier 2 and 3 academic interventions targeted to specific skills/needs of the student and identified by assessment data (Massachusetts Department of Elementary & Secondary Education, n.d.).
Economically disadvantaged: Defined as a student’s participation in one or more of the following state-administered programs: the Supplemental Nutrition Assistance Program (SNAP); the Transitional Assistance for Families with Dependent Children (TAFDC); the Department of Children and Families (DCF) foster care program; and MassHealth (Medicaid) (Redefining low income, n.d.).
Inequality: Unfairness, a lack of equality or justice.
Multi-Tiered System of Support (MTSS): ESSA (2015) notes this system is “a comprehensive continuum of evidence-based, systemic practices to support a rapid response to students’ needs, with regular observation to facilitate data-based instructional decision making’’ (p. 2093).
Massachusetts Curriculum Framework: Provides all stakeholders with expectations for what all students understand and can perform at the end of each grade level. The standards formalize expectations that all students have access to similar academic content, regardless of location or ability (English Language Arts and Literacy, 2017).
Universal design for learning (UDL): A “framework to improve and optimize teaching and learning for all people based on scientific insights into how humans learn” (Cast, 2018).
Variability: An understanding that all individuals have a unique learning profile, and educators, when incorporating universally designed instruction, would embrace these differences and create ways for all students to become expert learners (Stanford Schwab Learning Center, n.d.).
References
- 2019 Official Accountability Report. (2019). School and District Report Cards – Massachusetts Department of Elementary and Secondary Education. DESE. http://profiles.doe.mass.edu/accountability/report/district.aspx?linkid=30&orgcode=06730000&orgtypecode=5&
- About us – GDRSD district. (2020). GDRSD.org. http://gdrsd.org/about-us/
- Allington, R., McGill-Franzen, A., Camilli, G., Williams, L., Graff, J., Zeig, J., Zmach, C., & Nowak, R. (2010). Addressing Summer Reading Setback Among Economically Disadvantaged Elementary Students. Reading Psychology, 31(5), 411–427. https://doi-org.une.idm.oclc.org/10.1080/02702711.2010.505165
- Ander, R., Guryan, J. & Ludwig, J. (2016, March). Improving academic outcomes for disadvantaged students: Scaling up individualized tutorials. Brookings Institute. https://www.brookings.edu/wp-content/uploads/2016/07/Full-Paper-1.pdf
- Amaral, O. M., Garrison, L., & Klentschy, M. (2002). Helping English learners increase achievement through inquiry-based science instruction. Bilingual Research Journal, 26(2), 213–239.
- Barnum, M. (2019, April 12). Nearly a decade later, did the Common Core work? New research offers clues. Chalkbeat. https://chalkbeat.org/posts/us/2019/04/29/common-core-work-research
- Calkins, L., Hohne, K. B., & Robb, A. K. (2015). Writing pathways: performance assessments and learning progressions, Grades K-8. Heinemann.
- CAST (2018). Universal design for learning guidelines version 2.2. http://udlguidelines.cast.org
- Clariana, R. (2009). Ubiquitous wireless laptops in upper elementary mathematics. The Journal of Computers in Mathematics and Science Teaching, 28(1), 5–21.
- Department of Transitional Assistance. (2020). Mass.gov. https://www.mass.gov/economic-assistance-cash-benefits
- Drent, M., & Meelissen, M. (2008). Which factors obstruct or stimulate teacher educators to use ICT innovatively? Computers & Education, 51(1), 187–199. https://doi-org.une.idm.oclc.org/10.1016/j.compedu.2007.05.001
- Dweck, C. (2006). Mindset: The new psychology of success. Random House.
- Elmore, R. (2004). School reform from the inside out: Policy, practice, and performance. Harvard Education Press.
- English Language Arts and Literacy. (2017). Massachusetts curriculum framework for English language arts and literacy: Grades pre-kindergarten to 12. Department of Education. http://www.doe.mass.edu/frameworks/ela/2017-06.pdf
- ESSA (2015). Every Student Succeeds Act of 2015, Pub. L. No. 114-95 114 Stat. 1177 (2015-2016). U.S. Department of Education. https://www.congress.gov/114/plaws/publ95/PLAW-114publ95.pdf
- Freedberg, L. (2019, September 19). Poverty levels in schools key determinant of achievement gaps, not racial or ethnic composition, study finds. EduSource.org. https://edsource.org/2019/poverty-levels-in-schools-key-determinant-of-achievement-gaps-not-racial-or-ethnic-composition-study-finds/617821
- Garcia, E. & Weiss, E. (2017, September 27). Reducing and averting achievement gaps: Key findings from the report ‘Education inequalities at the school starting gate’ and comprehensive strategies to mitigate early skills gaps. Economic Policy Institute. https://www.epi.org/files/pdf/130888.pdf
- Gershenson, S. (2020). Great expectations: The impact of rigorous grading practices on student achievement. Fordham Institute. https://fordhaminstitute.org/national/research/great-expectations-impact-rigorous-grading-practices-student-achievement
- Gilmore, S., & Ross, D. (2020). Integrating technology: A school-wide framework to enhance learning. Heinemann.
- Guthrie, J.T., Coddington, C.S. & Wigfield, A. (2009). Profiles of reading motivation among African American and Caucasian students. Journal of Literacy Research, 41(3), 317–353.
- Hall, T. E., Cohen, N., Vue, G., & Ganley, P. (2015). Addressing Learning Disabilities With UDL and Technology: Strategic Reader. Learning Disability Quarterly, 38(2), 72–83. https://doi.org/10.1177/0731948714544375
- Hattie, J. (2018). Hattie ranking: 252 influences and effect sizes related to student achievement. VisableLearning.org. https://visible-learning.org/hattie-ranking-influences-effect-sizes-learning-achievement/
- Huerta, M., Lara-Alecio, R., Tong, F., & Irby, B. J. (2014). Developing and Validating a Science Notebook Rubric for Fifth-Grade Non-Mainstream Students. International Journal of Science Education, 36(11), 1849–1870. https://doi-org.une.idm.oclc.org/10.1080/09500693.2013.879623
- Howse, R. B., Lange, G., Farran, D. C., & Boyles, C. D. (2003). Motivation and Self-Regulation as Predictors of Achievement in Economically Disadvantaged Young Children. Journal of Experimental Education, 71(2), 151. https://doi-org.une.idm.oclc.org/10.1080/00220970309602061
- Kurtts, S., Dobbins, N., & Takemae, N. (2012). Using assistive technology to meet diverse learner needs. Library Media Connection, 30(4), 22–23. http://search.ebscohost.com.une.idm.oclc.org/login.aspx?direct=true&db=a9h&AN=70426672&site=ehost-live&scope=site
- Larkin, M. (2019). How Massachusetts lost count of its poor students. WBUR. https://www.wbur.org/edify/2019/08/01/low-income-count
- Lee, O., Deaktor, R. A., Hart, J. E., Cuevas, P., & Enders, C. (2005). An instructional intervention’s impact on the science and literacy achievement of culturally and linguistically diverse elementary students. Journal of Research in Science Teaching, 42(8), 857 –887.
- Leithwood, K., Louis, K.S., Anderson, S., & Wahlstrom, K. (2004). How leadership influences student learning. The Wallace Foundation.
- Massachusetts Department of Elementary & Secondary Education. (n.d.). Multi-tiered system of support blueprint. Systems for Student Success Office. http://www.doe.mass.edu/sfss/mtss/blueprint.pdf
- Marion, R. & Gonzales, L.D. (2014). Evolution of the organizational animal. In Leadership in Education: Organizational Theory for the Practitioner. Waveland Press.
- Meyen, E. (2015). Significant Advancements in Technology to Improve Instruction for all Students: Including Those With Disabilities. Remedial and Special Education, 36(2), 67–71. https://doi.org/10.1177/0741932514554103
- Meyer, A., Rose, D., & Gordon, D. (2014). Universal design for learning: Theory and practice. CAST Professional Publishing.
- Meyer, C. B., & Stensaker, I. G. (2006). Developing capacity for change. Journal of Change Management, 6(2), 217-231. https://10.1080/14697010600693731
- Moore, E. J., Smith, F. G., Hollingshead, A., & Wojcik, B. (2018). Voices From the Field: Implementing and Scaling-Up Universal Design for Learning in Teacher Preparation Programs. Journal of Special Education Technology, 33(1), 40–53. https://doi.org/10.1177/0162643417732293
- Nepo, K. (2017). The Use of Technology to Improve Education. Child & Youth Care Forum, 46(2), 207–221. https://doi-org.une.idm.oclc.org/10.1007/s10566-016-9386-6
- Ng, C. (2018). Using student voice to promote reading engagement for economically disadvantaged students. Journal of Research in Reading, 41(4), 700–715. https://doi-org.une.idm.oclc.org/10.1111/1467-9817.12249
- Prestridge, S. (2012). The beliefs behind the teacher that influences their ICT practices. Computers & Education, 58(1), 449–458. https://doi-org.une.idm.oclc.org/10.1016/j.compedu.2011.08.028
- Rose, D. H., & Meyer, A. (2002). Teaching every student in the digital age: Universal design for learning. Association for Supervision and Curriculum Development (ASCD).
- Rudduck, J. & Fielding, M. (2006). Student voice and the perils of popularity. Educational Review, 58(2), 219–231.
- Redefining low income – A new metric for K-12 education. (n.d.). Department of Education. http://www.doe.mass.edu/infoservices/data/ed.html
- Russell, M., Bebell, D., & Higgins, J. (2004). Laptop learning: A comparison of teaching and learning in upper elementary classrooms equipped with shared carts of laptops and permanent 1:1 laptops. Journal of Educational Computing Research, 30, 313–330. https://doi:10.2190/6E7K-F57M-6UY6-QAJJ
- Sang, G., Valcke, M., van Braak, J., Tondeur, J., & Zhu, C. (2011). Predicting ICT integration into classroom teaching in Chinese primary schools: Exploring the complex interplay of teacher-related variables. Journal of Computer Assisted Learning, 27(2), 160–172. https://doi-org.une.idm.oclc.org/10.1111/j.1365-2729.2010.00383.x
- Schacter, J., & Jo, B. (2005). Learning when school is not in session: a reading summer day-camp intervention to improve the achievement of exiting First-Grade students who are economically disadvantaged. Journal of Research in Reading, 28(2), 158–169. https://doi-org.une.idm.oclc.org/10.1111/j.1467-9817.2005.00260.x
- Schmoker, M. (2020). Radical reset: The case for minimalist literacy standard. Educational Leadership, 77(5), 44-50. http://www.ascd.org/publications/educational-leadership/feb20/vol77/num05/Radical-Reset@-The-Case-for-Minimalist-Literacy-Standards.aspx
- Stanford Schwab Learning Center. (n.d.). Learner variability. Stanford University. https://slc.stanford.edu/learner-variability
- Zheng, B., Warschauer, M., Lin, C.-H., & Chang, C. (2016). Learning in one-to-one laptop environments: A meta-analysis and research synthesis. Review of Educational Research, 86(4), 1052–1084. https://doi.org/10.3102/0034654316628645