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While most public schools embody a one-size-fits-all approach to education , the theory of personalized learning purports students ought to be "active and responsible co-authors of their educational script" . "Personalized learning helps students see the meaning of things, and that makes a difference" . This model allows students to create their own learning goals, utilizes continuous self-assessment, and encourages learning to extend outside school walls and beyond the traditional school day. Built on cognitive and constructivist learning theories, personalized learning uses students' prior knowledge and cognitive structures to build new knowledge, while encouraging students to create their own pathways and understanding .
The Race to the Top-District (RTT-D) federal grant program provided competitive funding to local education agencies to test innovative new strategies for personalizing learning. Two competition cycles were held with 16 awards distributed in 2012 and 5 awards in 2013, totaling more than $500 million. This article focuses on how the 2012 grant applicants successfully explained their goals for personalized learning-highlighting schools, districts, and programs that are already making this happen across the country. We summarized the personalization strategies proposed in each school district application individually, and then synthesized the strategies to discern whether common personalization strategies could be found across the collected proposals. Six key strategies emerged that lay the groundwork for personalized learning.
More than 10 years ago, Miliband outlined five components of personalized learning, which has been widely adapted . During the assessment phase, teachers and students work together in a formative manner to identify strengths and weaknesses. With the effective teaching and learning phase, teachers and students select learning strategies. The curriculum choice phase allows students to select curriculum content-personalized learning tailors lessons to the individuals. Teachers hold high standards for the students to learn the basics, yet create pathways that allow for student choice. The fourth component of personalized learning consists of a radical departure from typical educational models. In this component, the framework of education is built upon student progress. It allows teachers to have discretion of flexible teaching strategies, and highlights safe and secure learning environments. The final component outlined by Miliband is the notion of education continuing beyond the classroom. By utilizing social services and community partnerships, the students' environment outside the school is an essential component of their learning environment.
Personalized learning is often equated with individualized learning, although the two terms are not synonymous. While personalized learning may encompass students working individually, they may also participate in whole class lessons or in cooperative groups . With the advent of information and communication technologies (ICT), students involved in personalized learning may engage in programs that are customized to fit their learning needs and styles . By using ICT, students can interact online with other students and teachers in media-rich interfaces at their own pace.
Bloom, well known for his taxonomy of educational objectives commonly referred to as "Bloom's Taxonomy," also contributed to the field of education with his learning for mastery instructional strategy . Through this form of mastery learning, Bloom noted all students could be successful if the instructional methods and pace were adjusted to the students' needs. This precursor to personalized learning theory increased not only students' knowledge, but also yielded improvements in affective attributes of learning, such as students' confidence, attendance, involvement, and attitudes toward learning.
Personalized learning also draws from Gardner's multiple intelligences theory. Rather than labeling children based on IQ measures, Gardner's multiple intelligence theory recognizes students have intelligence profiles consisting of linguistic, logical-mathematical, musical, spatial, kinesthetic, naturalistic, interpersonal, intrapersonal, and existential strengths and weaknesses . Although often misconstrued as a need for teachers to tailor learning to each student's unique profile, the multiple intelligences theory emphasizes the need to create diverse learning experiences accessible to a variety of intelligence profiles. While the notion of customizing education to learners' needs has been integral in a variety of educational models over the past century, Victor García Hoz coined the term "personalization" in the 1970s .
In 2013 Scott Benson developed a working definition for personalization, while he was a senior program officer at the Gates Foundation:
In 2012, the RTT-D program funded 16 school district applications in support of the personalization of learning. Table 1 provides links to district websites and the submitted applications. This section provides a brief overview of the major personalization strategies proposed in each application. Personalization strategies generally fell into the following themes:
Digital learning materials and courses, data and data systems, curriculum and teaching, and professional development were universally found across all 16 applications. Repurposed learning facilities and human capital were less prevalent, but still found in nine and 10 proposals respectively. Only seven applications met all themes. No doubt the request for proposals in this grant competition influenced these themes, as education agencies obviously wrote to certain competitive priorities to receive their grants. Personalization of learning, however, would be difficult to achieve without, for example, data systems that allow tracking of student progress in mastering curricular standards through a blend of regular instruction and digital learning materials; or leader-based professional development that prepares educators to differentiate instruction using data and repurposed facilities and class-day educational structures.
Each of the themes includes a summary, exemplars from the districts representative of that theme, and a list of resources (research, websites, and video) that can be used to move toward more personalized learning in any district/program. Please note these themes lay the groundwork for personalized learning. Not one of these themes on its own will make for personalized learning, but when combined in a meaningful way that makes sense for the context of the learning environment, personalized learning has the potential to transform students' experience.
Digital Learning Materials and Courses. All districts described plans to enhance student access to digital learning materials and courses. The most common examples across the applications included:
Online resources provide districts an opportunity to reinforce learning and reach students who may have missed or misunderstood a concept in their regular classroom, as well as an opportunity to help advanced students learn at a greater depth than usual.
A few districts described plans to set up learning management systems (LMSs) or single sign-on portals to access a variety of computer-based programs, online subscriptions, and student data systems. One district noted the need for a friendly meeting space for student teams so they could work online inside and outside of school.
About two-thirds of the winning districts described plans to increase student access to laptops or tablets-tools that would shift the physical spaces, times, and manner in which students learn. A few districts described projects with a one-to-one student-to-computer ratio, although just as common were ubiquitous projects providing one computer for every two or three students. Tablets were far more popular than laptops in district applications, perhaps owing to their lower prices and the availability of free or low-cost educational applications. Districts noted enhanced access to technology would allow their students to learn anytime and anywhere without the restrictions of computer lab hours, and that specialized software programs could be loaded onto hardware for high-need students (e.g., read-aloud, speech-to-text conversion).
For districts without ubiquitous computing, loaner equipment was commonly made available for checkout from school media centers for both students and parents. One district allowed for checked out laptops with cellular-based Internet access, enhancing access to online educational resources for high-need students without Internet access in the home. Another district described a collaborative project with a local Internet service provider that agreed to provide free Internet service for families eligible for free or reduced meals.Exemplars
Data and Data Systems. Many of the districts used data derived from prior pilot work and/or needs assessment within their learning environments. For example, many of them proposed expanding on programs already running, including project-based learning programs, blended learning models, or continuous improvement approaches already proven successful in their districts. At least a third of the districts mentioned completing needs assessment prior to submitting their application to determine the current status of personalized learning before implementing the project, get input from stakeholders, or identify best practices in using technology for personalization in peer schools/districts.
Every district application included the creation of a longitudinal/historical student data system and/or the creation of a formative student data system, and, most applications included both. These systems are so comprehensive that they require separate descriptions below. However, in practice, they typically function as a single data system.
Longitudinal/historical student data systems.These systems store data on a student's academic and career goals and progress toward those goals over their entire academic career. Typically a student will work with teachers and parents to create a personalized learning plan that contains his or her learning and developmental goals to meet college and career-ready standards. Plans often link courses, career clusters, and learning experiences to a student's college and workforce pathway so students and parents can view the curricular and experiential requirements needed to meet targets. Longitudinal systems archive student testing and achievement data over time and generate proficiency dashboards, learning graphs, report cards, and transcripts useful in helping teachers and parents understand individual student progress. A few districts noted their longitudinal systems would follow students into college to track enrollment, matriculation, and completion (although this was not the primary purpose for most). A few districts also noted their longitudinal systems would track behavioral data, such as truancy, to help identify and implement appropriate interventions. Again, this use of the longitudinal system was less common than academic tracking.
Formative student data systems. These systems store data on how well students have mastered individual units in different classes. Teachers typically define day-to-day pathways for their individual classes, and class-related assessment data is used to populate the formative data system. While more than two-thirds of RTT-D funded districts proposed formative data systems, the timeframe for collecting data varied from daily to weekly to biweekly. Teachers use formative data systems as the basis for remediating and adapting instruction, with a goal of getting all students performing to standards of college and career readiness. Some systems provide teachers with actionable recommendations useful in grouping students for differentiated activities. Parents can typically access formative data systems for weekly progress reports or report cards, and serve to provide ongoing communication with parents. One district mentioned using formative data as a basis for training students to set learning goals on the basis of their progress.
District applications described numerous assessment types that would feed into these systems, including: classroom-level unit and diagnostic assessments; district-level measures of academic progress on skills, such as math and reading; and state-level, criterion-referenced measures of academic proficiency in different subjects. Many districts mentioned investing in auto-scored assessments that would provide teachers with rapid data, which could be used immediately to provide intervention strategies for individual students.Exemplars
Curriculum and Teaching. A majority of RTT-D winning districts are adopting mastery- or competency-based learning in which students learn and remediate until they can demonstrate understanding of content, most typically Common Core-aligned standards. This is not a time-based model where credit is awarded for spending a year in the ninth or 10th grade. Instead, it is a performance-based model where credit is awarded for actual learning. Many districts described training teachers to develop learning paths to specify goals or expectations for their classes as well as performance-based tasks aligned with standards, which could be used to track individual student mastery. In these districts, students are given multiple means of assessment to demonstrate mastery, including: performance tasks, projects, oral presentations, traditional tests, tests embedded in software, and portfolios.
Many districts also proposed plans for differentiating struggling learners from those who are advancing at a faster pace. One district described a flex model, where all students spend about 50 percent of classroom time with digital learning resources and struggling students are pulled out during digital time for remediation. Another district described daily 30-minute "success periods" during which content-area teachers tutored students in need. A third district noted two hours of daily, individualized enrichment that would provide teachers the time to target remediation or advancement, depending on the student.
More than two-thirds of districts proposed using an integrated strategy of placing students in collaborative teams and tasking these teams with project-based learning to solve problems and inquiries. It was suggested small groups could be differentiated by ability level and projects could tie into students' personal interests. Other districts' approaches would expose students to a diverse set of instructional groupings, including not only small teams, but also individual, peer-to-peer, and online communities.
A majority of district applications also included college and career pathway experiences, where students take courses and participate in off-campus experiences to explore different career clusters. Some programs include career readiness training with computer programs designed to build interviewing skills, resume writing skills, professionalism, and technology and media literacy. Other programs emphasize community internships, job shadowing, and service learning, requiring students to work on projects with community businesses and agencies that could support career development. Out-of-school experiences were commonly associated with non-academic outcomes such as character development, civic-mindedness, and social and emotional development. Some district initiatives provide students with a supplemental service-learning diploma if they complete a certain number volunteer hours, while other districts count community activities for credit as part of alternate pathways for students to graduate.Exemplars
Repurposed Learning Facilities. Several districts proposed plans to repurpose existing learning facilities, either physically in terms of function, temporally in terms of when the facility was utilized for educational activities, or obligatory in terms of the audience they served.
Physical repurposing involves investments in different-sized classroom tables and chairs to better support project-based work and collaboration: renovations to computer labs to better support team and individualized learning; and new technology and wireless capabilities for non-traditional learning spaces such as school buses and community locations frequented by students. Expanding the hours in which students can access school facilities and resources is one example of temporal repurposing. Some districts proposed expanding the hours of the school media center and school-based Internet access to as late as 7 p.m. with after-school support, homework help, and enrichment activities. Others expanded the class day until 5 p.m. or added Saturday sessions, inter-sessions, and summer sessions for students in need of academic support or desiring enrichment. Obligatory repurposing involves expanding who the school serves. A few districts described revisioning their media center as a community-learning center with parent/community education opportunities and technology made available for checkout. One district described providing social, emotional, and behavioral support for recent alumni as students face the difficult transition from school to college or the workforce.Exemplars
Human Capital. In order to support their projects, most district proposals considered the need for new positions or other non-paid human resources. Half of the districts described the use of personalized learning coaches-new educators who would help train and support teachers as they transformed their classrooms to more personalized learning environments. In some instances, personalized learning teams were referenced, suggesting multiple persons fulfilling this role. A few districts noted these coaches were drawn from existing school staff or teacher leaders who would mentor their peer teachers in the design of performance-based tasks and implementation of personalized learning.
Also in support of teachers implementing personalized learning, some districts described innovative models involving teaching partnerships between a lead teacher responsible for whole class instruction and a developing teacher responsible for working with small groups of students on personalization and enrichment. A few referred to partner teachers as "residents" and the establishment of collaborations with local colleges of education to bring in student teachers, who could reinforce the program with enhanced differentiation and one-on-one student support.
Other roles mentioned by districts included the following:
Professional Development. The final element common to every district application was professional development for teachers. Topics for training varied by district, but commonly included support for:
As noted, some districts proposed to adopt teaching partnerships as a form of professional development for training teachers who partnered with effective teachers in cohorts and engaged in co-teaching. In addition, more than a third of districts described professional learning communities (PLCs) of teachers working together to identify resources and best practices for personalizing learning and to review data and student learning plans to plan for adapting content and instruction. Given a key focus on data, some districts referred to their PLCs as "data teams."
Given the data-driven nature of winning district applications, it is not surprising a few districts not only proposed the development of student data systems, but also teacher data systems. In these systems, teachers develop their own personalized learning plans. Observational and evaluative data will be used to suggest activities teachers should complete to meet their goals. Coaching tools enable principals and coaches to individualize feedback to teachers and suggest tailored professional development.
Although less common, a few districts did refer to professional development and coaching support for principals as part of their overall personalization programs.Exemplars
The 16 districts exhibited healthy plans for personalization. By using digital learning materials and courses, including a learning management system for single sign-on portals for multiple vendor resources, the pressure is not on the school to reinvent the wheel and develop their own resources. The personalized piece of this particular theme is evident in the adaptive technology that is used to cater to each student's learning needs. The variety of resources that are available also helps teachers differentiate representations of knowledge for each student dependent on the student's preference of learning. Data and data systems are another large component of personalized learning for students because this information, when collected and synthesized in meaningful ways, can help provide teachers and students guidance as to where the student is, where the student needs to be, and what needs to happen for the students to get there.
Curriculum and teaching was another theme and mastery- or competency-based learning was a major component for the majority of district plans reviewed. Students will only progress when they can know and show what they've mastered. This feature of the programs really integrates well with the immediate data that comes out of the data and data systems. These curricular and instructional modifications help teachers differentiate for each learner's needs. Varying styles of student work and interaction with one another is important for personalization, allowing them ways to work on meaningful projects that have impact on societal issues and preparing them for whatever pathway might work for them, whether college or career bound. The space used for learning environments needs to be changed often to be more conducive with personalized learning, hence the need to repurpose learning facilities.
Also, human capital is one of the most essential components of personalized learning environments, especially when it comes to defining new roles and preparing educators to serve in those new roles. One of the key roles is a leadership coach, who helps administrators through the change management process when switching to a new learning environment. A coach can act as a confidant for administrators to avoid feelings of tackling personalization alone. It is essential for this coach to leverage other stakeholders to avoid the silo effect. For example, facilitators who work to involve community organizations and serve as outreach liaisons for developing internship opportunities for students to apply their learning in authentic contexts. Facilitators and digital learning technicians can also help transition teachers and other educators into this new space in a sustainable way. Moving past singular, fleeting professional development opportunities, these education professionals will be a continuous resource for teachers as they shift their roles to being more of a facilitator in their students' learning paths.
Key implications for personalization projects include access and equity issues, making sure that every student has access to the tools they need and the Internet access that is necessary to do their work both in school and at home. Additionally, it is essential that data and data systems be designed to collect the data needed for teachers to make the most comprehensive decisions for the student's learning path. Aligned with that is making sure that the teacher has all of the necessary training up front in order to understand the data and also continuous professional development to continue to feel more and more comfortable with the process of using data to inform students' learning paths and their instructional strategies. Another key piece to data systems is making sure the assessments that feed into it are meaningful to student learning, displaying the students' practical application of the knowledge that they have gained. When transitioning to competency-based learning, every stakeholder involved must be involved in understanding the true systemic change that needs to happen in order to apply this feature at scale.
Essentially, any change can be daunting. For educators, change happens on a daily basis, whether it stems from policy, practice, or research. What educators must keep in mind is to use change as a learning process. An emphasis should be made on trying new things, and a comfort zone should be established where it is okay to fail. When it comes to personalization, students need to have a voice and choice in their learning path. They also need to feel ownership of their learning and be part of a space that fosters creativity and meaningful application of learning. Adaptive, continuous, low-stakes assessment can help give teachers the tools they need to differentiate. As Priest, Rudenstine, and Weisstein said, "As personalization occurs in every aspect of modern life, it will no doubt permeate education more fully…" . Change is happening, albeit slowly.
The authors would like to acknowledge the International Association for K-12 Online Learning (iNACOL) for their guidance and support of this article.
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Kevin Oliver is an associate professor of digital learning and teaching in the Department of Teacher Education and Learning Sciences at North Carolina State University. He holds a M.Ed. in educational media and instructional design from UNC-Chapel Hill and a Ph.D. in instructional technology from the University of Georgia, Athens. Oliver teaches graduate online courses in digital leadership, online collaborations, and distance education. He is also co-leader of a popular study abroad program for in-service teachers promoting cultural understanding through integrated writing and technology activities. He conducts research on distant/online learning environments and social/collaborative teaching strategies with implications for policy and teaching practice.
Kathryn Kennedy is a senior researcher at MVU's Michigan Virtual Learning Research Institute. The goal of the Institute is to "expand Michigan's capacity to support new learning models, engage in active research to inform new policies in online and blended learning and strengthen the state's infrastructures for sharing best practices." MVLRI conducts research in K-12 online and blended learning. Kennedy's research and practical experiences, in particular, include pre-service and in- service teacher, technology specialist, and school librarian professional development for technology integration and instructional design in traditional, blended, and online learning environments. She holds a Ph.D. from the University of Florida (2010) in curriculum and instruction, with a concentration in educational technology. Connect with here at http://www.kathrynmkennedy.com.
Laura Hibbard is currently in her 10th year teaching fifth grade at an online, public K-12 school. Prior to working in a full-time online school, Hibbard taught for four years in a traditional school. Laura holds a doctorate in instructional technology from Ohio University. Her dissertation focused on online students' access to literature, and examined the roles of both physical book libraries and e-book libraries in online schools. Her research interests include online K-12 learning with a focus on student literacy and student-centered instruction as well as exposing teacher candidates to online K-12 teaching and learning. Hibbard teaches part time in Ohio University's instructional technology department.
Bonnie Swan is an expert in program evaluation and applied social research. She is currently the director for program evaluation and educational research group (PEER) at the University of Central Florida (UCF) where she has been responsible for conducting contract evaluations and research both on campus and with outside agencies and institutions for the last decade. She received her Ph.D. in education and M.Ed. in mathematics education from UCF, and her undergraduate degree was in business/economics. Her research interests in evaluation, online learning, teacher-labor markets, educational equity, and professional development—as well as her experience teaching at the secondary and post-secondary levels—give her a unique perspective as an educational researcher and an evaluation consultant. She is a Past President for both the Florida Educational Research Association (FERA) and the National Association of Test Directors (NATD) and currently serves as a board member of NATD and the Southeast Evaluation Association.
Tom Clark, president of Clark Consulting, a recognized source of expertise in digital learning, has been an educational consultant for over 20 years, providing evaluation, research, and policy analysis services for a wide variety of organizations. Clark has led evaluations of state virtual schools in four states and in Chicago Public Schools, and served as lead evaluator for a $9.1 million federal digital learning grant. He has many related publications, such as Distance Education: Foundations of Effective Practice (Jossey-Bass, 1991), co-authored with John R. Verduin; "Virtual Schools: Status and Trends" (WestEd, 2001); Virtual Schools: Planning for Success (Teachers College Press. 2005), co-edited with Zane Berge; and Online, Blended, and Distance Education in Schools: Building Successful Programs (Stylus, 2015), co-edited with Michael K. Barbour. Clark holds a Ph.D. in educational administration and MsED in adult education from Southern Illinois University at Carbondale.
Jason LaFrance is an associate professor of educational leadership at Florida Southern College. His previous experiences include teaching at the elementary and middle school levels. He then served in leadership roles for seven years in public and private schools ranging from 250 to 1,550 students. In his last K-12 school he was a member of the administrative team that built a K-6 school that was recognized nationally as an Apple Distinguished School and statewide as a Florida Positive Behavior Support Model School. From 2010 through 2015 he served as the Director of the Center for Educational Leadership and Service and as an associate professor at Georgia Southern University.
Jonathan Oglesby is an independent education consultant with a focus on strategy and communications around transformation and innovation in the K-12 space. He has held senior public affairs and communications positions with iNACOL, Houghton Mifflin Harcourt, and the Center for Education Reform. A previous phase of Jonathan's career found him exploring the U.S. (and beyond) as a television producer. Oglesby holds a B.A. From The Catholic University of America and lives in Maryland.
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