Education Drivers

Remote Learning

Remote forms of K-12 instruction have become increasingly prevalent as schools expand their use of educational technologies to allow for learning beyond that which takes place in brick and mortar classrooms. Remote instruction may offer a number of benefits, including reduced costs and increased student access to courses and instruction that would not be available otherwise. However, while research is limited, evidence to date suggests that fully remote instruction and virtual schools are not as effective as the face-to-face instruction that takes place in traditional schools, particularly for struggling students. Blended instructional models have shown more promise, particularly those that enable differentiated instruction through technologies such as intelligent tutoring. The success of remote instruction likely in part depends on a number of implementation factors, such as the degree to which equitable access to digital tools and resources is provided, whether and how students’ metacognitive skills that are essential for more independent, self-regulated learning are developed, the capacity of preparation and professional development to foster teachers’ technological pedagogical content knowledge, and the extent to which parents can engage in ways that allow them to effectively support their children’s learning at home.

Remote Learning Overview

Remote Learning PDF

Donley, J., Detrich, R., States, J., & Keyworth, (2020). Remote Learning Overview. Oakland, CA: The Wing Institute. https://www.winginstitute.org/effective-instruction-computers.

Digital technologies, required tools for most forms of remote instruction, are increasingly valued as a key component of K–12 education, and education stakeholders have devoted significant resources accordingly (Bulman & Fairlie, 2015). Some evidence suggests that these resources are well placed and that digital technologies have the potential to provide learning benefits for students. Hattie’s (2017) ongoing meta-analysis work, for example, shows a number of technologies, such as those used to support students with learning needs and those using intelligent tutoring and interactive video methods, have high potential to accelerate achievement.

            However, some experts argue that digital technologies have not yet substantially transformed teaching and learning in meaningful ways (Darling-Hammond, Zielezinski, & Goldman, 2014; Gewertz, 2020; Herold, 2016; McGivney & Foda, n.d.; OECD, 2015). In theory, the use of digital technologies in remote instruction can offer a variety of benefits, such as wider student access to courses and more individualized, personalized instructional time not necessarily bound to time spent in school buildings (Chatterji, 2018). Still, equity gaps between advantaged and disadvantaged students and between schools persist in the key tools and practices necessary for high-quality remote instruction, such as access to a computer at home and teachers who have the necessary technical and pedagogical skills to integrate digital devices into instruction (Bushweller, 2020; OECD, 2020).

            While remote instruction has been increasingly available and used in the past decade, the COVID-19 pandemic brought the issue sharply into focus, and many educators are seeking understanding of best practice. This overview examines the effectiveness of various forms of remote instruction, what is known about best practice, and critical issues that must be considered for effective implementation.

 

What Is Known About the Effectiveness of Remote Instruction

Background and Terminology. Remote instruction encompasses instructional environments and tools supported by the internet, and can be (1) fully remote, in which all instruction and assessment are carried out virtually (sometimes referred to as distance education); (2) supplemental, in which students may take one or more courses of their choice virtually while still taking courses in physical classrooms; or (3) blended, in which face-to-face interactions between teachers and students are combined with remote learning (Bakia, Shear, Toyama, & Lasseter, 2012; Delgado, Wardlow, McKnight, & O’Malley, 2015; Lowes & Lin, 2018).

            Remote instruction itself can be synchronous (students and teachers interact together in a specific virtual space at the same time) or asynchronous (students access content and learning activities on their own time) (Lowes & Lin, 2018). Synchronous instruction may include video conferencing (e.g., Zoom) and group project work in real time, while asynchronous instruction may include self-guided lesson modules and teacher-posted lecture slides and assignments. Digital learning is a term that can encompass remote/blended learning, and other uses of educational technology (Schwirzke, Vashaw, & Watson, 2018).

            Remote instruction “is often suggested as a means for improving educational outcomes, expanding access at lower costs than conventional approaches or allowing talented teachers to focus on what they do best by automating or offloading more routine tasks” (Bakia et al., 2012, p. 15). Although very little K–12 research on cost-effectiveness exists (Bakia et al., 2012), one study of blended learning schools found that while start-up costs were high, these schools spent an average of $1,100 less per student than traditional schools (Battaglino, Haldeman, & Laurans, 2012). K–12 administrators also reported that blended learning approaches provided an advantage through potential reductions in operation costs (Bernatek, Cohen, Hanlon, & Wilka, 2012). More research is needed to document the return on investment of these approaches in terms of student outcomes.

 

Research on the Effectiveness of Fully Remote Instruction. While a good deal of research evidence supports the use of educational technologies to increase student achievement (e.g., Tamim, Bernard, Borokhovski, Abrami, & Schmid, 2011), much less is known about the impact of using these technologies to support K–12 remote learning (Brodersen & Melluzzo, 2017; Escueta, Quan, Nickow, & Oreopoulos, 2017; Means, Toyama, Murphy, & Bakia, 2013; Sparks, 2015). Despite this lack of research, most states now offer fully remote schools (Digital Learning Collaborative, 2019). Enrollment in these schools has increased significantly in the past decade, growing by about 6% each year (Digital Learning Collaborative, 2019), and some states now require students to complete an online course for graduation (Molnar et al., 2017).

            Although supplemental remote learning is far more prevalent, with close to 1 million course enrollments (Digital Learning Collaborative, 2019), full-time remote learning has also increased over the past decade, with now nearly 300,000 students enrolled (Molnar et al., 2019). Most students who take online courses are in high school (80%), and nearly half of course enrollments are in English language arts, math, science, and social studies (Digital Learning Collaborative, 2019). While the distinction between fully remote and supplemental remote learning may seem simple, in reality the instructional models used in both are complex and make research on their impact difficult:

Both supplemental and full-time online learning can encompass different instructional models, from paced virtual classrooms with both student-teacher and student-student interaction, to self-paced courses that rely primarily on student-teacher interaction; from courses where most of the interaction is synchronous to those where it is almost entirely asynchronous. One of the weaknesses of the literature is that the model is often unspecified, although it clearly affects both teaching and learning. (Lowes & Lin, 2018, p. 91)

Virtual schools, which offer fully remote instruction, can offer cost savings in areas such as school operations, student support services, teacher and employee salaries and benefits, disability services, and efficiency of cost distribution over larger numbers of students (Miron & Urschel, 2012). They also provide the opportunity for anytime, anywhere learning to students, and can offer added supports for disabled students and those at risk of failing (Toppin & Toppin, 2016).

Recent comprehensive analyses have shown, however, that in the United States full-time virtual schools underperform academically in comparison with blended and traditional schools, despite enrolling primarily students not possessing typical risk characteristics such as minority status or English learners (Molnar et al., 2017, 2019). Molnar and colleagues (2019) found that district-operated virtual schools were much more likely to achieve acceptable state school performance ratings (57%) than charter-operated virtual schools (41%), and only approximately half of students in fully virtual schools graduated on time compared with the national average of 84% (Molnar et al., 2019). Virtual schools run by for-profit education management organizations (EMOs), which enroll far greater numbers of students, had particularly low school performance ratings (Molnar et al., 2019). This research echoes findings of other studies, including a report from the National Alliance for Public Charter Schools (2016) that found weaker academic growth for full-time virtual students compared with those receiving face-to-face instruction.

A recent comprehensive review of 126 high-quality studies similarly found that fully online instructional models generally were not as effective as traditional face-to-face classroom models (Escueta et al., 2017), particularly for students who were struggling (Rickles et al., 2018). In addition, some research has shown that teachers in virtual schools perceive a lack of collegial support and experience a sense of disconnection from their students and the profession (Hawkins, Barbour, & Graham, 2012; Toppin & Toppin, 2016). Such findings have led many researchers to recommend limiting expansion of these schools until additional research that addresses the specific instructional models used for remote instruction and their impact on learning is available (e.g., Molnar et al., 2017, 2019).

 

Research on the Effectiveness of Blended Learning. Christensen, Horn, and Staker (2013) have defined blended learning as

a formal education program in which a student learns at least in part through online learning, with some element of student control over time, place, path, and/or pace, and at least in part at a supervised brick-and-mortar location away from home… The modalities along each student’s learning path within a course or subject are connected to provide an integrated learning experience. (p. 10)

            In a 2015 report, the International Association for K–12 Online Learning (iNACOL) (subsequently renamed the Aurora Institute) summarized potentially positive aspects of blended and fully remote learning environments:

These new learning models are designed to enable richer student-teacher communication and interaction, either synchronous or asynchronous, and optimize each student’s learning experiences through robust personalized learning…. Collaboration and learning extend beyond the four walls of the classroom…These new learning models can help teachers personalize instruction and meet each student’s unique learning needs. (p. 4)

            In fact, blended learning is designed to be a “delivery mechanism” for personalized learning (Patrick, Kennedy, & Powell, 2013), providing students with a personalized educational path and flexible learning environments (Horn & Staker, 2011). Through their research on blended learning schools and programs, researchers at the Christensen Institute (2020) identified the four blended learning models most prevalent in K–12 schools: (1) rotation models, in which students rotate among learning modalities (e.g., online learning, whole-group class discussion, projects, small-group instruction) on either a fixed schedule or at the teacher’s discretion; (2) flex models, in which online learning at the brick-and-mortar campus is the core vehicle for student learning, and students progress along an individualized and fluid schedule among learning modalities; (3) à la carte models, in which students take entirely online a course that is designed to support and/or complement learning experiences at the brick-and-mortar school; and, (4) enriched virtual models, in which students are required to have face-to-face learning experiences with their teacher but to complete their remaining classwork remotely.

            Rotation models are more widely used than the other models, particularly at the elementary level, and offer the benefit of allowing teachers to work with smaller student groups, making differentiated instruction more cost-effective and efficient (Christensen et al., 2013; Staker, 2014). The flex, à la carte, and enriched virtual models involve more dramatic changes to traditional school models and are more often used at the middle and high school levels, where students are considered more capable of self-regulated online learning (Means et al., 2013). These models may enable students to learn at their own pace and engage with teachers more effectively; allow more students to take electives, foreign language, and advanced placement classes unavailable in their brick-and-mortar school; and recover more dropouts by removing traditional classroom barriers (Staker, 2014).

Much of the literature is descriptive and discusses the perceived benefits of blended learning, such as increased learner engagement and motivation (Stein & Graham, 2014), allowing for competency-based learning (Horn & Staker, 2015) and providing immediate formative feedback to students (Vanderkam, 2013). Blended learning is touted as offering the opportunity for differentiated learning tailored to students’ needs, which many proponents argue is essential to address the needs of learners with vastly different learning styles, knowledge, skills, and learning pace (Brodersen & Melluzzo, 2017; Tomlinson, 2000). Digital technology can help teachers use real-time data to differentiate instruction according to students’ varied progress (Hilliard, 2015), as well as allow for sufficient independent practice that often is not possible in a traditional classroom lacking digital support (Johnson, Perry, & Shamir, 2010).

In fact, some evidence suggests that students with access to blended learning models outperform those experiencing only one type of instruction (Bakia et al., 2012; Means et al., 2013; Means, Toyama, Murphy, Bakia, & Jones, 2010; Pane, Griffin, McCaffrey, & Karam, 2014; Pane, Steiner, Baird, & Hamilton, 2015), although the diversity of blended learning designs make it unclear which aspects of blended learning enhance achievement (Halverson, Spring, Huyett, Henrie, & Graham, 2017).

Brodersen & Melluzzo (2017) reviewed rigorous studies that evaluated the impact of blended learning programs incorporating differentiated instruction and found statistically significant positive results for several programs. For example, the Cognitive Tutor Algebra program, which combines an intelligent tutoring computer-based system with regular classroom instruction to provide personalized, mastery-based learning, was shown to significantly improve algebra proficiency after 2 years of implementation (e.g., Pane et al., 2014). Recent meta-analytic reviews of a variety of intelligent tutoring systems that differentiate instruction and provide for blended learning approaches suggest these systems generally offer powerful learning support, raising test scores the equivalent of approximately three quarters of a standard deviation beyond conventional levels, or from the 50th to 75th percentile (Escueta et al., 2017; Kulik & Fletcher, 2016).

Blended learning approaches are increasingly being used at the elementary level, with positive impacts shown in several studies examining reading instruction (Prescott, Bundschuh, Kazakoff, & Macaruso, 2018; Shannon, Styers, Wilkerson, & Peery, 2015; Wilkes et al., 2020). Prescott et al. investigated the impact of a schoolwide blended learning elementary reading program at a Title I school (Lexia Core 5), and found significant 1-year standardized reading assessment gains for students across grades and for both English learner and non-English learner low-income students. Indeed, evidence is emerging that blended learning approaches may be particularly effective for at-risk student populations, such as English learners and low-income students (Kazakoff, Macaruso, & Hook, 2017; Schechter, Macaruso, Kazakoff, & Brooke, 2015).

Some schools are operating as full-time blended learning schools (as opposed to incorporating blended learning models, programs, or practices by some teachers or at some grade levels within a school); a recent analysis identified 300 of these schools in the United States serving approximately 133,000 students (Molnar et al., 2019). Similar to the fully remote schools described previously, fewer than half of these blended learning schools demonstrated acceptable school performance ratings, although they graduated a slightly higher percentage of students on time (61% versus 50%). The Molnar study also found that the academic performance pattern observed for fully virtual schools, in which district-run schools outperformed those operated by for-profit EMOs, also occurred for fully blended learning schools. Both types of schools evidenced higher student-to-teacher ratios than the national average, with full-time virtual schools averaging 2.7 times as many students per teacher, and full-time blended schools reporting slightly more than twice as many (Molnar et al., 2019). Whether this factor contributes to poor outcomes is uncertain; additional factors that may influence the outcomes of remote instruction are discussed below.

        

Important Considerations for Fostering Implementation With Fidelity and Ensuring Equity in Remote Instruction

The research to date, while far from conclusive, suggests that blended instruction is more effective than fully remote instruction. Clearer evidence shows that blended learning that includes technology to enable differentiated instruction can be effective, particularly for at-risk learners. It is likely that implementation factors influence the results seen regarding the effectiveness of fully remote and blended learning (Schwirzke et al., 2018); several key considerations for implementation are highlighted below.

 

Ensuring Equitable Digital Access for Remote Instruction and Learning. Digital access may vary greatly by school and by student socioeconomic status. While access to digital tools and broadband in schools is now widely available (EducationSuperHighway, 2019), many homes lack the high-speed connectivity and digital learning tools necessary for remote learning, leaving many children, particularly those in low-income, non-white, and rural communities, without the capacity to use digital tools for homework and school projects (OECD, 2020). Many educators and researchers have expressed legitimate concerns regarding the potential for remote learning environments to exacerbate educational inequalities (Lewis et al., 2014). A recent survey conducted by Education Week found that nearly two thirds of districts with high percentages of students from low-income families reported that a lack of basic technology at home was a major problem for remote learning, compared with just one in five districts with few economically disadvantaged students (Herold, 2020). Furthermore, the data showed that rural, urban, and high-poverty districts were far less able to provide online learning opportunities to all students. It is clear that ensuring all students have the digital tools and internet access they need for remote learning is a first step in enabling equitable remote instruction and learning outcomes.

 

Building Engagement and Metacognitive Competency. Students must be encouraged and supported to be active rather than passive learners in any learning environment, whether instruction is face-to-face, blended, or fully remote. The International Society for Technology in Education (Snelling & Fingal, 2020) recommends that remote instruction include ample opportunities for collaboration, frequent feedback, clear expectations for student participation, and plenty of human connection through, for example, virtual meetings or live chats. Engagement can also be fostered by building students’ metacognition. Educators must reconsider their roles and build students’ self-regulated learning to help students gain the agency and responsibility critical for personalized, remote/blended learning to be successful (Murphy et al., 2014; Powell, et al., 2015). Murphy et al. argued that for students to fully benefit from remote/blended learning, schools must establish a productive and self-directed learning culture through activities such as setting weekly progress goals.

            Metacognitive strategies that allow students to self-regulate their learning are strong contributors to student academic performance, and are essential for success in remote/blended learning environments in which students are expected to manage their own learning to some degree (Farrington et al., 2012; Hattie, 2017; Lewis et al., 2014; Redding, 2016). Self-regulated learners set goals, plan, organize, monitor their use of learning strategies, and evaluate their skills and knowledge as they construct new skills and knowledge (Zimmerman, 1990). Students in remote/blended learning environments must have these capacities, and “teachers must be skilled at differentiating instruction and providing customized supports for students to progress, as well as helping them to develop the metacognitive and self-regulation skills that will enable them to progress” (Lewis et al., 2014, p. 7), or inequitable outcomes between higher and lower income students may worsen.

Explicit teaching and guided practice with metacognitive strategies is essential for students functioning in online environments (Soto, 2016). For example, Pilegard & Fiorella (2016) found that middle schools students who used a cognitive tutor blended approach in pre-algebra classes and were engaged in generative learning strategies (e.g., summarizing or explaining what was learned to a peer) during instruction improved self-regulation behaviors (e.g., seeking help) compared with those not using these learning strategies. The researchers concluded that these simple paper-based metacognitive strategies offered an example of how computer-aided instruction can be effective in blended learning environments.

Lai and Hwang (2016) also found evidence that building metacognitive skills in the form of self-regulated learning strategies (e.g., setting goals, planning and using study time) into a flipped (i.e., a blended learning approach in which students access and learn content at home and work on extension and reinforcement of skills during face-to-face instruction) elementary math classroom resulted in increases in learning and self-efficacy. Their study provided evidence that metacognitive strategies can benefit students’ online learning outside of school.

 

Teacher Preparation and Professional Development. Remote and blended learning requires teachers to have a different skill set from than is provided through most teacher preparation programs (Rice, 2014), and the majority of teachers have not been prepared to engage students with remote instruction (Archambault & Kennedy, 2018). After reviewing teacher education programs, Kennedy and Archambault (2012a, 2012b) recommended that these programs incorporate coursework in online pedagogy, experience with designing instruction for online environments, and practicum experiences with blended and/or fully remote teaching. Cowan (2013) suggested that these programs also include extensive immersion in technology-rich coursework and observations of peers already skilled in technology integration and receiving support for embedding these skills in their classrooms.

            Professional organizations have developed standards for online teaching that reflect the skills and dispositions necessary for success (i.e., National Standards for Quality Online Teaching developed by the Virtual Learning Leadership Alliance and Quality Matters, 2019); these standards include themes such as online pedagogy (i.e., feedback and classroom management); instructional design that incorporates methods of accessibility and accommodation; assessment of student learning; technical expertise; and professionalism and ethics (Archambault & Kennedy, 2018). Mentors are also key in building both pre-service and in-service teachers’ capabilities in remote instruction, although little research on mentoring programs exists (Dawson & Dana, 2018a).

Professional learning for in-service teachers must improve technological pedagogical content knowledge, or TPACK (Harris, Mishra, & Koehler, 2009), while simultaneously empowering teachers to generate educational innovation that better meets students’ needs (Lafuente, 2018). Lafuente noted:

The goal is not to learn how to run technological devices to better meet student needs. There needs to be professional learning where practitioners form learning communities and share materials and best practices. Investing resources in technology is not enough if teachers do not have the competence to use them in a pedagogically sound fashion; otherwise, technology in the classroom can even have detrimental consequences (OECD, 2015). (pp. 108–109)

            Unfortunately, many teachers receive no training prior to beginning their teaching roles in online environments (Dawley, Rice, & Hinck, 2010), and most training is generic and not integrated within a content area (Dawson & Dana, 2018b). Little is known through research about what enables fully remote and blended teachers to have “not only an excellent grasp of their given content area but also an appreciation of how technology and the online environment affect the content and the pedagogy of what they are attempting to teach” (Archambault, Debruler, & Freidhoff, 2014, p. 87, as cited in Greene & Hale, 2017). Dawson and Dana (2018b) suggested that professional development for K–12 remote teaching incorporate but extend the five core features of effective professional development suggested by Desimone (2009) to address remote instruction:

  1. Content focus: Emphasize subject matter content and how students learn it, but also address the varying roles within remote learning contexts (i.e., administrators, content designers, counselors, etc.).
  2. Active learning: Include more options for active learning; the variety of media typically used in remote instruction can support simulations, modeling, role-playing, etc.
  3. Coherence: Align professional development with state and district goals but also with standards for online teaching and learning, content standards, and the type of media teachers will use for instruction.
  4. Duration: Optimize remote teaching by including both short- and long-term opportunities to prepare teachers for more technical, skills-based knowledge needed to be effective in online settings.
  5. Collective participation: Encourage teachers to work together to learn; remote professional development lends itself well to this cause due to greater teacher comfort working and collaborating together in online environments, and the geographic distance that often separates online teachers.

Fostering Parent Engagement. A substantial amount of research has documented the influential role of parents in student learning and educational attainment (e.g., De Fraja, Oliveira, & Zanchi, 2010; Dufur, Parcel, & Troutman, 2013), and particularly may benefit low-income and minority students the most (Henderson & Mapp, 2002). Much less is known about how parents can effectively be involved in K–12 fully remote or blended learning settings (Hasler Waters, Borup, & Menchaca, 2018); however, some research suggests that the level and type of engagement may be important to student outcomes, particularly when students are learning from home (Borup, Stevens, & Hasler Waters, 2015; Liu, Black, Algina, Cavanaugh, & Dawson, 2010).

            For example, Black (2009) found that parental praise of children’s schoolwork positively related to student performance in virtual schools, but the reported level of engagement in instructional activities by parents negatively related to student grades. Black suggested that parents often lack the knowledge and skills to help their children learn, but they may increase their involvement when their children’s performance is poor. Parents, particularly those with children enrolled in fully virtual schools, likely need help to develop the skills and knowledge to support their children’s learning at home remotely (Hasler Waters et al., 2018; Molnar et al., 2015). This finding may be particularly true for parents supporting children with disabilities (Curtis & Werth, 2015; Franklin, East, & Mellard, 2015).

            Research suggests that parents may underestimate the roles they need to assume and the commitments necessary to support their children’s success in remote learning environments, thinking they may only need to provide encouragement and support (Burdette & Greer, 2014; Molnar et al., 2015). Remote learning may require parents to assume the role of teacher for which they are not prepared or licensed, leading to student learning problems. In the role of teacher, a parent is often expected to be an organizer (planning a daily schedule and using a learning management system to access and track homework), instructor (tutoring), motivator (incentivizing with rewards), and manager (tracking and monitoring student progress and providing discipline) (Hasler Waters et al., 2018). Parents of students with disabilities have reported even greater responsibility (Burdette & Greer, 2014).

            Hasler Waters and colleagues (2018) reiterated that there was still much to be learned about how and under what conditions parent engagement can positively impact students’ remote learning:

More work needs to be done to develop a comprehensive understanding of the types of parental involvement that lead to student academic success or how to measure the quality of support parents are lending to their own students. Indeed, the [National Education Protection Council] NEPC (2015) has stated that research is critical given the lack of accountability and regulation of these schools and not just on connections to academic achievement but also to establish exemplars and models for virtual environments where parents serve as de facto educators and perform other educational support roles for their children. (p. 418)

            Curtis (2013) suggested that parental involvement in blended instruction could help mitigate the distance between student and teacher; however, research thus far has neglected to address the role of parent involvement in blended learning environments (Hasler Waters et al., 2018).

 

Summary

Remote instruction is touted as having a number of benefits, including enhanced and extended access to learning, the possibility of greater differentiation and personalized learning, and the potential for reduced costs. Remote instruction can be structured to be fully online, supplemental, or blended in a variety of ways to include face-to-face instruction with a teacher in a traditional classroom. While the research is still in its infancy, evidence is accumulating that fully online instruction is less likely to provide positive academic outcomes, leading many experts to urge caution in scaling up this type of program. Blended instructional models, however, show more promise. Particularly effective are models that use technology in the form of intelligent tutoring to provide differentiated instruction and supports for at-risk learners; however, thus far blended learning schools have not shown as much promise.

            A number of implementation factors likely impact the effectiveness of remote instruction. Students may not fully engage in virtual learning environments, but fostering students’ capacity for metacognition and self-regulated learning can boost engagement. Teachers need (and often don’t receive) adequate preparation and high-quality professional development that equips them not only with the competency to use digital tools effectively, but also with the technological pedagogical content necessary to deliver instruction successfully in virtual environments. Finally, parents are an important part of the equation for effective remote instruction, as they may be asked to fill a role for which they are not prepared. Additional research is needed to better understand how parent engagement can be optimized to support children’s learning in remote environments.

 

Citations

 

Archambault, l., Debruler, K., & Freidhoff, J. R. (2014). K–12 online and blended teacher licensure: Striking a balance between policy and preparedness. Journal of Technology and Teacher Education 22(1), 83–106.https://www.academia.edu/6459023/K-12_Online_ and_blended _Teacher_licensure_Striking_a_balance_between_Policy_ and_Preparedness

Archambault, L., & Kennedy, K. (2018). Teacher preparation for K–12 online and blended learning. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 221–245). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

Bakia, M., Shear, L., Toyama, Y., & Lasseter, A. (2012). Understanding the implications of online learning for educational productivity. Washington, DC: U.S. Department of Education. https://tech.ed.gov/files/2013/10/implications-online-learning.pdf

Battaglino, T. B., Haldeman, M., & Laurans, E. (2012). Creating sound policy for digital learning: The costs of online learning. Washington, DC: Thomas B. Fordham Institute. http://www.edexcellencemedia.net/publications/2012/20120110-the-costs-of-online-learning/20120110-the-costs-of-online-learning.pdf

Bernatek, B., Cohen, J., Hanlon, J., & Wilka, M. (2012). Blended learning in practice: Case studies from leading schools, featuring KIPP Empower Academy. Austin, TX: Michael and Susan Dell Foundation. https://www.heartland.org/_template-assets/documents/publications/kipp.pdf

Black, E. W. (2009). An evaluation of familial involvements’ influence on student achievement in K–12 virtual schooling [Doctoral dissertation, University of Florida, Gainesville]. University of Florida Digital Collections.https://ufdc.ufl.edu/UFE0024208/00001

Borup, J., Stevens, M. A., & Hasler Waters, L. (2015). Parent and student perceptions of parent engagement at a cyber charter high school. Online Learning, 19(5), 69–91. https://files.eric.ed.gov/fulltext/EJ1085792.pdf

Brodersen, R. M., & Melluzzo, D. (2017). Summary of research on online and blended learning pro­grams that offer differentiated learning options (REL 2017–228). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Central. https://files.eric.ed.gov/fulltext/ED572935.pdf

Bulman, G., & Fairlie, R. W. (2015). Technology and education: Computers, software, and the internet. Working Paper 22237. Cambridge, MA: National Bureau of Economic Research. https://www.nber.org/papers/w22237.pdf

Burdette, P. J., & Greer, D. L. (2014). Online learning and students with disabilities: Parent perspectives. Journal of Interactive Online Learning, 13(2), 67–88. https://www.ncolr.org/jiol/issues/pdf/13.2.4.pdf

Bushweller, K. (2020, June 2). How COVID-19 is shaping tech use. What that means when schools reopen. Education Week. https://www.edweek.org/ew/articles/2020/06/03/how-covid-19-is-shaping-tech-use-what.html

Chatterji, A. (2018). Innovation and American K–12 education. Working Paper 23531. Cambridge, MA: National Bureau of Economic Research. https://www.nber.org/papers/w23531.pdf

Christensen, C. M., Horn, M. B., & Staker, H. (2013). Is K–12 blended learning disruptive? An introduction to the theory of hybrids. Christensen Institute. http://www.christenseninstitute.org/wp-content/uploads/2013/05/Is-K-12-Blended-Learning-Disruptive.pdf

Christensen Institute (2020). Blended learning definitions. http://www.christenseninstitute.org/blended-learning-definitions-and-models/

Cowan, P. (2013). The 4I Model for scaffolding the professional development of experienced teachers in the use of virtual learning environments for classroom teaching. Contemporary Issues in Technology and Teacher Education, 13(1), 82–98. https://citejournal.org/volume-13/issue-1-13/current-practice/the-4i-model-for-scaffolding-the-professional-development-of-experienced-teachers-in-the-use-of-virtual-learning-environments-for-classroom-teaching/

Curtis, H. (2013). A mixed methods study investigating parental involvement and student success in high school online education [Doctoral dissertation, Northwest Nazarene University]. https://nnu.whdl.org/sites/default/files/Curtis%20Final%20Dissertation.pdf

 Curtis, H. & Werth, L. (2015). Fostering student success and engagement in a K–12 online school. Journal of Online Learning Research, 1(2), 163–190. https://files.eric.ed.gov/fulltext/EJ1148836.pdf

Darling-Hammond, L., Zielezinski, M. B., & Goldman, S. (2014). Using technology to support at-risk students’ learning. Stanford Center for Opportunity Policy in Education; Alliance for Excellent Education. https://edpolicy.stanford.edu/sites/default/files/scope-pub-using-technology-report.pdf

Dawley, L., Rice, K., & Hinck, G. (2010). Going Virtual! 2010: The status of professional development and unique needs of K–12 online teachers. Boise, ID: Boise State University. https://aurora-institute.org/wp-content/uploads/goingvirtual3.pdf

Dawson, K., & Dana, N. F. (2018a). Mentoring for online teachers. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 261–272). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

Dawson, K., & Dana, N. F. (2018b). Professional development for K–12 online teachers. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 247–260). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

DeFraja, G., Oliveira, T., & Zanchi, L. (2010). Must try harder: Evaluating the role of effort in educational attainment. The Review of Economics and Statistics, 92(3), 577–597.

Delgado, A. J., Wardlow, L., McKnight, K., & O’Malley, K. (2015). Educational technology: A review of the integration, resources, and effectiveness of technology in K–12 classrooms. Journal of Information Technology Education: Research, 14, 397–416. http://www.jite.org/documents/Vol14/JITEv14ResearchP397-416Delgado1829.pdf

Dufur, M. J., & Parcel, T. L., & Troutman, K. P. (2013). Does capital at home matter more than capital at school? Social capital effects on academic achievement. Research in Social Stratification and Mobility, 31, 1–21.

Desimone, L. M. (2009). Improving impact studies of teachers’ professional development: Toward better conceptualization and measures. Educational Researcher, 38(3), 181–199.

Digital Learning Collaborative. (2019). Snapshot 2019: A review of K-12 online, blended, and digital learning. https://static1.squarespace.com/static/59381b9a17bffc68bf625df4/t/5df14d464ba53f72845791b2/1576095049441/DLC-KP-Snapshot2019.pdf

EducationSuperHighway. (2019). 2019 state of the states: The classroom connectivity gap is closed. https://s3-us-west-1.amazonaws.com/esh-sots-pdfs/2019%20State%20of%20the%20States.pdf

Escueta, M., Quan, V., Nickow, A. J., & Oreopoulos, P. (2017). Education technology: An evidence-based review.Working Paper 23744. Cambridge, MA: National Bureau of Economic Research. https://www.nber.org/papers/w23744.pdf

Farrington, C. A., Roderick, M., Allensworth, E., Nagaoka, J., Keyes, T. S., Johnson, D. W., & Beechum, N. O. (2012). Teaching adolescents to become learners. The role of noncognitive factors in shaping school performance: A critical literature review. Chicago, IL: University of Chicago Consortium on Chicago School Research. https://files.eric.ed.gov/fulltext/ED542543.pdf

Franklin, T. O., East, T., & Mellard, D.F. (2015). Parent preparation and involvement in their child’s online learning experience: Superintendent Forum Proceedings Series. (Report No. 2). Lawrence, KS: Center on Online Instruction and Students with Disabilities, University of Kansas. http://www.centerononlinelearning.res.ku.edu/wp-content/uploads/2017/04/Superintendent_Topic_2_Summary_November2015.pdf

Gewertz, C. (2020, June 2). How technology, coronavirus will change teaching by 2025. Education Week.https://www.edweek.org/ew/articles/2020/06/03/how-technology-coronavirus-will-change-teaching-by.html

Greene, K., & Hale, W. (2017). The state of 21st century learning in the K–12 world of the United States: Online and blended learning opportunities for American elementary and secondary students. Journal of Educational Multimedia and Hypermedia, 26(2), 131–159.

Halverson, L. R., Spring, K. J., Huyett, S., Henrie, C., & Graham, C. R. (2017). Blended learning research in higher education and K–12 settings. In J. M. Spector, B. B. Lockee, & M. D. Childress (Eds.), Learning, design, and technology: An international compendium of theory, research, practice, and policy (pp. 1–30). Cham, Switzerland: Springer International Publishing.

Harris, J., Mishra, P., & Koehler, M. (2009). Teachers’ technological pedagogical content knowledge and learning activity types: Curriculum-based technology integration reframed. Journal of Research on Technology in Education, 41(4), 393–416.

Hasler Waters, L., Borup, J., & Menchaca, M. P. (2018). Parental involvement in K–12 online and blended learning. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 403–422). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

Hattie, J. (2017). Visible learning: 250+ influences on student achievement. https://visible-learning.org/wp-content/uploads/2018/03/VLPLUS-252-Influences-Hattie-ranking-DEC-2017.pdf

Hawkins, A., Barbour, M. K., & Graham, C. R. (2012). Everybody is their own island: Teacher disconnection in a virtual school. International Review of Research in Open and Distance Learning, 13(2), 123–144.

Henderson, A. T., & Mapp, K. (2002). A new wave of evidence: The impact of school, family, and community connections on student achievement. Austin, TX: Southwest Educational Development Laboratory. https://www.sedl.org/connections/resources/introduction.pdf

Herold, B. (2016, February 5). Technology in education: An overview. Education Week.https://www.edweek.org/ew/issues/technology-in-education/index.html

Herold, B. (2020, April 10). The disparities in remote learning under coronavirus (in charts). Education Week.https://www.edweek.org/ew/articles/2020/04/10/the-disparities-in-remote-learning-under-coronavirus.html

Hilliard, A. T. (2015). Global blended learning practices for teaching and learning, leadership and professional development. Journal of International Education Research, 11(3), 179–188. https://files.eric.ed.gov/fulltext/EJ1070786.pdf

Horn, M., & Staker, H. (2011). The rise of K–12 blended learning. Mountain View, CA: Innosight Institute.

Horn, M., & Staker, H. (2015). Blended: Using disruptive innovation to improve schools. San Francisco, CA: Jossey-Bass.

Johnson, E. P., Perry, J., & Shamir, H. (2010). Variability in reading ability gains as a function of computer-assisted instruction method of presentation. Computers and Education, 55(1), 209–217.

Kazakoff, E. R., Macaruso, P., & Hook, P. (2017). Efficacy of a blended learning approach to elementary school reading instruction for students who are English learners. Education Technology Research and Development, 66, 429–449.

Kennedy, K., & Archambault, L. (2012a). Design and development of field experiences in K–12 online learning environments. Journal of Applied Instructional Design, 2(1), 35–49. https://www.researchgate.net/profile/Leanna_Archambault/publication/272487804_Design_and_development_of_field_experiences_in_K-12_online_learning_environments/links/54fd16400cf2c3f524236996.pdf

Kennedy, K., & Archambault, L. (2012b). Offering preservice teachers field experiences in K–12 online learning: A national survey of teacher education programs. Journal of Teacher Education, 63(3), 185–200.

Kulik, J. A., & Fletcher, J. D. (2016). Effectiveness of intelligent tutoring systems: A meta-analytic review. Review of Educational Research, 86(1), 42–78.

Lafuente, M. (2018). Attuning pedagogies to the context of ‘new learners’ and technology. In A. Peterson, H. Dumont, M. Lafuente, & N. Law (Eds.), Understanding innovative pedagogies: Key themes to analyse new approaches to teaching and learning (pp. 94–115). OECD Education Working Paper No. 172. Organisation for Economic Co-operation and Development. http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=EDU/WKP(2018)8&docLanguage=En

Lai, C. L., & Hwang, G. J. (2016). A self-regulated flipped classroom approach to improving students’ learning performance in a mathematics course. Computers and Education, 100, 126–140.

Lewis, M. W., Eden, R., Garber, C., Rudnick, M., Santibañez, L., & Tsai, T. (2014). Equity in competency education: Realizing the potential, overcoming the obstacles. Students at the Center: Competency Education Research Series. Boston, MA: Jobs for the Future. https://studentsatthecenterhub.org/wp-content/uploads/2015/10/Equity-in-Competency-Education-103014-copy.pdf

Liu, F., Black, E., Algina, J., Cavanaugh, C., & Dawson, K. (2010). The validation of one parental involvement measurement in virtual schooling. Journal of Interactive Online Learning, 9(2), 105–132.

Lowes, S., & Lin, P. (2018). A brief look at the methodologies used in the research on online teaching and learning. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 91–110). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

McGivney, E., & Foda, K. (n.d.). Productivity measurement in the education sector. Washington, DC: Brookings Institution. https://www.brookings.edu/wp-content/uploads/2017/12/productivity-measurement-in-education.pdf

Means, B., Toyama, Y., Murphy, R., & Bakia, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record, 115(3), 1–47. https://archive.sri.com/sites/default/files/publications/effectiveness_of_online_and_blended_learning.pdf

Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2010). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. Washington, DC: U.S. Department of Education. http://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalreport.pdf

Miron, G., & Urschel, J. L. (2012). Understanding and improving full-time virtual schools: A study of student characteristics, school finance, and school performance in schools operated by K12, Inc. Boulder, CO: National Education Policy Center. http://files.eric.ed.gov/fulltext/ED533960.pdf

Molnar, A., Huerta, L., Shafer, S. R., Barbour, M.K., Miron, G., Shafer, S. R., & Gulosino, C. (2015). Virtual schools in the U.S. 2015: Politics, performance, policy, and research evidence. Boulder, CO: National Education Policy Center. http://nepc.colorado.edu/publication/virtual-schools-annual-2015

Molnar, A., Miron, G., Elgeberi, N., Barbour, M. K., Huerta, L., Shafer, S. R., & Rice, J. K. (2019). Virtual schools in the U.S. 2019. Boulder, CO: National Education Policy Center. https://nepc.colorado.edu/sites/default/files/publications/Virtual%20Schools%202019.pdf

Molnar, A., Miron, G., Gulosino, C., Shank, C., Davidson, C., Barbour, M. K.,… Nitkin, D. (2017). Virtual schools in the U.S. 2017. https://files.eric.ed.gov/fulltext/ED574702.pdf

Murphy, R., Snow, E., Mislevy, J., Gallagher, L., Krumm, A., & Wei, X. (2014). Blended learning report. Austin, TX: Michael and Susan Dell Foundation. https://www.msdf.org/wp-content/uploads/2016/01/MSDF-Blended-Learning-Report-May-2014.pdf

National Alliance for Public Charter Schools (2016). A call to action to improve the quality of full-time virtual charter public schools. http://www.publiccharters.org/sites/default/files/migrated/wp-content/uploads/2016/06/Virtuals-FINAL-06202016-1.pdf

OECD (2015). Students, computers and learning: Making the connection. Paris, France: OECD Publishing. https://www.oecd-ilibrary.org/docserver/9789264239555-en.pdf?expires=1591112620&id=id&accname=guest&checksum=E108C3D7C7CC829D93048D0ED6CB4635

OECD (2020). Learning remotely when schools close: How well are students and schools prepared? Insights from PISA. https://read.oecd-ilibrary.org/view/?ref=127_127063-iiwm328658&title=Learning-remotely-when-schools-close

Pane, J. F., Griffin, B. A., McCaffrey, D. F., & Karam, R. (2014). Effectiveness of Cognitive Tutor Algebra I at scale. Educational Evaluation and Policy Analysis, 36(2), 127–144.

Pane, J. F., Steiner, E. D., Baird, M. D., & Hamilton, L. S. (2015). Continued progress: Promising evidence on personalized learning. Santa Monica, CA: RAND Corporation. http://www.rand.org/pubs/research_reports/RR1365.html

Patrick, S., Kennedy, K., & Powell, A. (2013). Mean what you say: Defining and integrating personalized, blended and competency education.  https://files.eric.ed.gov/fulltext/ED561301.pdf

Pilegard, C., & Fiorella, L. (2016). Helping students help themselves: Generative learning strategies improve middle school students’ self-regulation in a cognitive tutor. Computers in Human Behavior, 65, 121–126.

Powell, A., Watson, J., Staley, P., Patrick, S., Horn, M., Fetzer, L.,…Verma, S. (2015). Blended learning: The evolution of online and face-to-face education from 2008–2015. http://www.inacol.org/wp-content/uploads/2015/07/iNACOL_Blended-Learning-The-Evolution-of-Online-And-Face-to-Face-Education-from-2008-2015.pdf

Prescott, J. E., Bundschuh, K., Kazakoff, E. R., & Macaruso, P. (2018). Elementary school-wide implementation of a blended learning program for reading intervention. Journal of Educational Research, 111(4), 497–506.

Redding, S. (2016). Competencies and personalized learning. In M. Murphy, S. Redding, & J. Twyman (Eds.), Handbook on personalized learning for states, districts, and schools (pp. 3–18). Philadelphia, PA: Temple University, Center on Innovations in Learning. http://www.centeril.org/2016handbook/resources/Redding_chapter_web.pdf

Rice, K. (2014). Research and history of policies in K–12 online and blended learning. In R. E. Ferdig & K. Kennedy (Eds.), Handbook of research on K–12 online and blended learning (pp. 51–82). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://pdfs.semanticscholar.org/cfcb/578ede7dc55b6ea97bdb1a37fe6243bb2bc9.pdf

Rickles, J., Heppen, J., Allensworth, E., Sorenson, N., Walters, K., & Clements, P. (2018). Getting back on track: The effect of online versus face-to-face credit recovery in Algebra I on high school credit accumulation and graduation. American Institutes for Research, Washington, DC; University of Chicago Consortium on School Research, Chicago, IL. https://www.air.org/system/files/downloads/report/Effect-Online-Versus-Face-to-Face-Credit-Recovery-in-Algebra-High-School-Credit-Accumulation-and-Graduation-June-2017.pdf

Schechter, R., Macaruso, P., Kazakoff, E. R., & Brooke, E. (2015). Exploration of a blended learning approach to reading instruction for low SES students in early elementary grades. Computers in the Schools, 32, 183–200.

Schwirzke, K., Vashaw, L., & Watson, J. (2018). A history of K–12 online and blended instruction in the United States. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 7–20). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

Shannon, L. C., Styers, M. K., Wilkerson, S. B., & Peery, E. (2015). Computer-assisted learning in elementary reading: A randomized control trial. Computers in the Schools, 32(1), 20–34.

Snelling, J., & Fingal, D. (2020, March 16). 10 strategies for online learning during a coronavirus outbreak. Washington, DC: International Society for Technology in Education. https://www.iste.org/explore/learning-during-covid-19/10-strategies-online-learning-during-coronavirus-outbreak

Soto, M. S. (2016). Flipped learning as a path to personalization. In M. Murphy, S. Redding, & J. Twyman (Eds.), Handbook on personalized learning for states, districts, and schools (pp. 73–87). Philadelphia, PA: Temple University, Center on Innovations in Learning. http://www.centeril.org/2016handbook/resources/Sota_flipped_chapter_web.pdf

Sparks, S. (2015, April 13). Blended learning research yields limited results. Education Week.https://www.edweek.org/ew/articles/2015/04/15/blended-learning-research-yields-limited-results.html

Staker, H. (2014, January 10). Which blended model should K–12 schools choose? Christensen Institute. http://www.christenseninstitute.org/which-blended-model-should-schools-choose/

Stein, J., & Graham, C. (2014). Essentials for blended learning: A standards-based guide. New York, NY: Routledge.

Tamim, R., Bernard, R., Borokhovski, E., Abrami, P., & Schmid, R. (2011). What forty years of research says about the impact of technology on learning: A second-order meta-analysis and validation study. Review of Educational Research, 81(1), 4–28. https://pdfs.semanticscholar.org/f8fa/160a2552568e102b0cac11ad0a48fc635b0e.pdf?_ga=2.248632325.343379521.1591299854-1379934943.1547574243

Tomlinson, C. A. (2000). Reconcilable differences: Standards-based teaching and differentiation. Educa­tional Leadership, 58(1), 6–11. http://eric.ed.gov/?id=EJ614602

Toppin, I. N., & Toppin, S. M. (2016). Virtual schools: The changing landscape of K–12 education in the U.S. Education and Information Technologies, 21(6), 1571–1581.

Vanderkam, L. (2013). Blended learning: A wise giver’s guide to supporting tech-assisted teaching. Washington, DC: Philanthropy Roundtable. https://www.philanthropyroundtable.org/docs/default-source/guidebook-files/blended_learning_guidebook.pdf?sfvrsn=afaba740_0

Virtual Learning Leadership Alliance and Quality Matters. (2019). National standards for quality online teaching (3rd ed.). https://www.nsqol.org/wp-content/uploads/2019/02/National-Standards-for-Quality-Online-Teaching.pdf

Wilkes, S., Kazakoff, E. R., Prescott, J. E., Bundschuh, K., Hook, P. E., Wolf, R.,… Macaruso, P. (2020). Measuring the impact of a blended learning model on early literacy growth. Journal of Computer Assisted Learning. Advance online publication. https://onlinelibrary.wiley.com/doi/full/10.1111/jcal.12429

Zimmerman, B. J. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist, 25(1), 3–17.

 

 

Presentations

TITLE
SYNOPSIS
CITATION
TEST TEST TEST

TEST TEST

TEST TEST

TITLE
SYNOPSIS
CITATION
International Experiences with Technology in Education: Final Report

The U.S. Department of Education Office of Educational Technology funded this study of international policy and programmes supporting information and communications technologies (ICTs) in education across 21 countries at primary and secondary levels. The final report includes an overview of international programmes and priorities as well as individual reports for each of the 21 countries. Findings suggest focusing on data collections at international level in order to compare the type and impact of ICT policies and programmes in education as well as improving the understanding of ICT in education best practices.

 

U.S. Department of Education, Office of Educational Technology, International Experiences with Educational Technology: Final Report, Washington, D.C., 2011.

Must try harder: Evaluating the role of effort in educational attainment.

This paper is based on the simple idea that students’ educational achievement is affected by the effort put in by those participating in the education process: schools, parents, and, of course, the students themselves.

DeFraja, G., Oliveira, T., & Zanchi, L. (2010). Must try harder: Evaluating the role of effort in educational attainment. The Review of Economics and Statistics92(3), 577–597. Retrieved from https://art.torvergata.it/retrieve/handle/2108/55644/108602/De%20Fraja%20Zanch%20Oliveira%20REStats%202010.pdf

A Powerful Hunger for Evidence-Proven Technology.

Schools in the United States now spend more than $2 billion each year on education technology. But what are schools getting in return for this significant investment in technology learning? Robert Slavin examines the results from five studies designed to answer this question.

Slavin, R. (2019). A Powerful Hunger for Evidence-Proven Technology. Baltimore, MD: Robert Slavin’s Blog. https://robertslavinsblog.wordpress.com/2019/11/14/a-powerful-hunger-for-evidence-proven-technology/.

Fostering student success and engagement in a K–12 online school

 This study explored student achievement in a K-12, full-time, online learning environment and the effect parents had on student success.

 Curtis, H. & Werth, L. (2015). Fostering student success and engagement in a K–12 online school. Journal of Online Learning Research, 1(2), 163–190. https://files.eric.ed.gov/fulltext/EJ1148836.pdf

One-to-one Computing: Literature Review

This paper examines the factors affecting the successful implementation of a laptop program, classroom uses of laptops and the support required for schools from current research almost exclusively from the United States.

 

State of NSW, Department of Education and Training, Curriculum K-12 Directorate. (2009, March). One-to-one computing: literature review. Retrieved from http://www.dec.nsw.gov.au/detresources/about-us/how-we-operate/national-partnerships/digital-education-revolution/rrql/support/lit_review.pdf

The Future Ready District: Professional Learning Through Online Communities of Practice and Social Networks to Drive Continuous Improvement

The U.S. Department of Education Office of Educational Technology published this brief that summarizes research on the role of online communities of practice and social networks in supporting the professional performance of educators.

U.S. Department of Education. (2014, November). The Future Ready District: Professional Learning Through Online Communities of Practice and Social Networks to Drive Continuous Improvement. Retrieved from http://tech.ed.gov/wp-content/uploads/2014/11/Section7-FutureReadyDistrictBrief-Final.pdf.

Characteristics of Future Ready Leadership: A Research Synthesis

The U.S. Department of Education’s Office of Educational Technology, in partnership with the American Institutes for Research (AIR), developed a research-based synthesis defining a set of policies and practices implemented by successful Future Ready district leaders. The resulting rubric provides a basis for personalized professional learning to expand the capacity of district superintendents to effectively transition to digital learning.

U.S. Department of Education. (2015, December). Characteristics of Future Ready Leadership A Research Synthesis. Retrieved from http://tech.ed.gov/files/2015/12/Characteristics-of-Future-Ready-Leadership.pdf.

Teacher preparation for K–12 online and blended learning.

This chapter reviews the state of the field as it pertains to the preparation of preservice teachers
for K-12 online and blended learning.

Archambault, L., & Kennedy, K. (2018). Teacher preparation for K–12 online and blended learning. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 221–245). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

 
K–12 online and blended teacher licensure: Striking a balance between policy and preparedness.

This article explores the theoretical underpinnings surrounding quality teaching in online settings as well as practical considerations for what teachers should know and be able to do in online environments. 

Archambault, L., DeBruler, K., & Freidhoff, J. (2014). K-12 online and blended teacher licensure: Striking a balance between policy and preparedness. Journal of Technology and Teacher Education22(1), 83-106. Retrieved from

https://www.academia.edu/6459023/K-12_Online_ and_blended _Teacher_licensure_Striking_a_balance_between_Policy_ and_Preparedness

A meta-analysis of the effects of feedback in computer-based instruction

A quantitative research synthesis (meta-analysis) was conducted on the literature concerning the effects of feedback on learning from computer-based instruction (CBI).

Azevedo, R., & Bernard, R. M. (1995). A meta-analysis of the effects of feedback in computer-based instruction. Journal of Educational Computing Research, 13(2), 111-127.

Understanding the implications of online learning for educational productivity

The report provides foundational knowledge needed to examine and understand the potential contributions of online learning to educational productivity, including a conceptual framework for understanding the necessary components of rigorous productivity analyses, drawing in particular on cost-effectiveness analysis as an accessible method in education.

Bakia, M., Shear, L., Toyama, Y., & Lasseter, A. (2012). Understanding the implications of online learning for educational productivity. Washington, DC: U.S. Department of Education. https://tech.ed.gov/files/2013/10/implications-online-learning.pdf

Creating sound policy for digital learning: The costs of online learning

In these pages, we estimate the costs of blendedlearning models and fulltime virtual schools as currently operated in the U.S.

Battaglino, T. B., Haldeman, M., & Laurans, E. (2012). Creating sound policy for digital learning: The costs of online learning. Washington, DC: Thomas B. Fordham Institute. http://www.edexcellencemedia.net/publications/2012/20120110-the-costs-of-online-learning/20120110-the-costs-of-online-learning.pdf

 
Proceed With Caution: Using Web-Based Resources for Instructing Students With and at Risk for EBD.

This article examines issues relating to the use of websites popular with educators. This article offers guidelines for maximizing the usefulness of such sites and for avoiding many of the pitfall educators may face.

Beahm, L. A., Cook, B. G., & Cook, L. (2019). Proceed With Caution: Using Web-Based Resources for Instructing Students With and at Risk for EBD. Beyond Behavior28(1), 13-20.

Blended learning in practice: Case studies from leading schools, featuring KIPP Empower Academy

A report about blended learning programs analyzes the instruction, operational, and financial models of Knowledge is Power Program (KIPP) schools. KIPP focuses on blending technology with in-class education to provide small group instruction and to meet the needs of each individual student.

Bernatek, B., Cohen, J., Hanlon, J., & Wilka, M. (2012). Blended learning in practice: Case studies from leading schools, featuring KIPP Empower Academy. Austin, TX: Michael and Susan Dell Foundation. https://www.heartland.org/_template-assets/documents/publications/kipp.pdf

 
An evaluation of familial involvements’ influence on student achievement in K–12 virtual schooling

The purpose of this study is to investigate the role of familial participation in student's achievement in K-12 virtual schools.

Black, E. W. (2009). An evaluation of familial involvements’ influence on student achievement in K–12 virtual schooling [Doctoral dissertation, University of Florida, Gainesville]. University of Florida Digital Collections.https://ufdc.ufl.edu/UFE0024208/00001

 
Parent and student perceptions of parent engagement at a cyber charter high school

Researchers have hypothesized that parental engagement is even more critical when online students learn from home, but few researchers have examined parents’ engagement behavior—especially parents of adolescent learners. In this case study, we addressed this gap using parent and student interviews at a full-time online charter school.

Borup, J., Stevens, M. A., & Hasler Waters, L. (2015). Parent and student perceptions of parent engagement at a cyber charter high school. Online Learning19(5), 69–91. https://files.eric.ed.gov/fulltext/EJ1085792.pdf

 
Summary of research on online and blended learning pro­grams that offer differentiated learning options

This report summarizes the methodology, measures, and findings of research on the influence on student achievement outcomes of K–12 online and blended face-to-face and online learning programs that offer differentiated learning options.

Brodersen, R. M., & Melluzzo, D. (2017). Summary of research on online and blended learning pro­grams that offer differentiated learning options (REL 2017–228). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Central. https://files.eric.ed.gov/fulltext/ED572935.pdf

 
Technology and education: Computers, software, and the internet.

This paper explores the theoretical and empirical literature on the impacts of technology on educational outcomes. The literature focuses on two primary contexts in which technology may be used for educational purposes: i) classroom use in schools, and ii) home use by students.

Bulman, G., & Fairlie, R. W. (2015). Technology and education: Computers, software, and the internet. Working Paper 22237. Cambridge, MA: National Bureau of Economic Research. https://www.nber.org/papers/w22237.pdf

 
Online learning and students with disabilities: Parent perspectives.

While research has been conducted on parental involvement in K-12 online learning, none of this research relates specifically to the parents of students with disabilities. Thus, researchers developed a survey around the following constructs: parental roles, instruction and assessment, communication and support from the school, and parental challenges. 

 

Burdette, P. J., & Greer, D. L. (2014). Online learning and students with disabilities: Parent perspectives. Journal of Interactive Online Learning, 13(2), 67–88. https://www.ncolr.org/jiol/issues/pdf/13.2.4.pdf

How COVID-19 is shaping tech use. What that means when schools reopen.

Education Week is learning as it surveys educators across the country about the impact school closures have had on their morale, student engagement, technology skills, and many other factors.

 

Bushweller, K. (2020, June 2). How COVID-19 is shaping tech use. What that means when schools reopen. Education Week. https://www.edweek.org/ew/articles/2020/06/03/how-covid-19-is-shaping-tech-use-what.html

 
Innovation and American K–12 education

The author reviews the economics literature at the intersection between innovation and K-12 education from two different, but related perspectives.

Chatterji, A. (2018). Innovation and American K–12 education. Working Paper 23531. Cambridge, MA: National Bureau of Economic Research. https://www.nber.org/papers/w23531.pdf

Blended Learning Definitions

This article briefly describes blending learning definition and models.

Christensen Institute (2020). Blended learning definitions. http://www.christenseninstitute.org/blended-learning-definitions-and-models/

 
Is K–12 blended learning disruptive? An introduction to the theory of hybrids.

The Clayton Christensen Institute, formerly Innosight Institute, has published three papers describing the rise of K−12 blended learning. This fourth paper is the first to analyze blended learning through the lens of disruptive innovation theory to help people anticipate and plan for the likely effects of blended learning on the classrooms of today and schools of tomorrow. 

Christensen, C. M., Horn, M. B., & Staker, H. (2013). Is K–12 blended learning disruptive? An introduction to the theory of hybrids. Christensen Institute. http://www.christenseninstitute.org/wp-content/uploads/2013/05/Is-K-12-Blended-Learning-Disruptive.pdf

Examining high quality online teacher professional development: Teachers’ voices.

This study aimed to look into this by asking, “Which features of high quality online professional development were noted by participating educators in a statewide online teacher professional development program?” A survey was used to collect educators’ voices in this FIP professional development (PD) program.

Collins, L. J., & Liang, X. (2015). Examining high quality online teacher professional development: Teachers’ voices. International Journal of Teacher Leadership, 6(1), 18–34. https://files.eric.ed.gov/fulltext/EJ1137401.pdf

 
“I don’t have enough time”—Teachers’ interpretations of time as a key to learning and school change

This study investigated inner-city middle school teachers' perceptions of the importance of time in learning and sharing information. The survey identified ways that teachers shared what they had learned and discussed factors that helped or hindered them in sharing. Teacher interviews examined: knowledge, skills, and insights gained by participating in the EELC.

Collinson, V., & Fedoruk Cook, T. (2001). “I don’t have enough time”—Teachers’ interpretations of time as a key to learning and school change. Journal of Educational Administration39(3), 266–281.

The 4I Model for scaffolding the professional development of experienced teachers in the use of virtual learning environments for classroom teaching.

This paper discusses an adapted-Continuous Practice Improvement model, which qualitative findings indicate was effective in facilitating the transfer of creative and innovative teaching approaches from the expert or Resident Teacher’s school to the novice or Visiting Teachers’ classrooms over the duration of the project. 

Cowan, P. (2013). The 4I Model for scaffolding the professional development of experienced teachers in the use of virtual learning environments for classroom teaching. Contemporary Issues in Technology and Teacher Education, 13(1), 82–98. https://citejournal.org/volume-13/issue-1-13/current-practice/the-4i-model-for-scaffolding-the-professional-development-of-experienced-teachers-in-the-use-of-virtual-learning-environments-for-classroom-teaching/

A mixed methods study investigating parental involvement and student success in high school online education

This mixed-methods study investigates student achievement in the full-time, online learning environment and the effect parents have on student success.

Curtis, H. (2013). A mixed methods study investigating parental involvement and student success in high school online education [Doctoral dissertation, Northwest Nazarene University]. https://nnu.whdl.org/sites/default/files/Curtis%20Final%20Dissertation.pdf

 
Using technology to support at-risk students’ learning.

Based on a review of more than seventy recent studies, this brief describes these approaches, particularly as they apply to high school students who have been at risk of failing courses and exit examinations or dropping out due to a range of personal factors and academic factors. The brief then outlines policy strategies that could expand the uses of technology for at-risk high school youth.

Darling-Hammond, L., Zielezinski, M. B., & Goldman, S. (2014). Using technology to support at-risk students’ learning. Stanford Center for Opportunity Policy in Education; Alliance for Excellent Education. https://edpolicy.stanford.edu/sites/default/files/scope-pub-using-technology-report.pdf

 
Going Virtual! 2010: The status of professional development and unique needs of K–12 online teachers.

Going Virtual! 2010 is a follow-up report to the Going Virtual! Research series started in 2007. The purpose of the series is to describe current trends on the status of professional development for K-12 online teachers, as well as identify the unique needs and challenges faced by these instructors.

Dawley, L., Rice, K., & Hinck, G. (2010). Going Virtual! 2010: The status of professional development and unique needs of K–12 online teachers. Boise, ID: Boise State University. https://aurora-institute.org/wp-content/uploads/goingvirtual3.pdf

 
Handbook of research on K–12 online and blended learning

The Handbook of Research on K-12 Online and Blended Learning is an edited collection of chapters that sets out to present the current state of research in K-12 online and blended learning. 

Dawson, K., & Dana, N. F. (2018a). Mentoring for online teachers. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 261–272). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

 
Professional development for K–12 online teachers.

This chapter provides a survey of what is known about professional development for both brick and mortar and online teachers and uses this knowledge as a springboard to suggest policy and research implication of professional development and K-12 online teacher. 

Dawson, K., & Dana, N. F. (2018b). Professional development for K–12 online teachers. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 247–260). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

Educational technology: A review of the integration, resources, and effectiveness of technology in K–12 classrooms.

This article presents a critical review of the transitions that technology integration has made over the years; the amount of resources and funding that has been allocated to immerse school with technology; and the conflicting results presented on effectiveness of using is technology in education.

Delgado, A. J., Wardlow, L., McKnight, K., & O’Malley, K. (2015). Educational technology: A review of the integration, resources, and effectiveness of technology in K–12 classrooms. Journal of Information Technology Education: Research14, 397–416. http://www.jite.org/documents/Vol14/JITEv14ResearchP397-416Delgado1829.pdf

 
Improving impact studies of teachers’ professional development: Toward better conceptualization and measures.

This article offers ideas to improve the quality of inquiry into teacher learning, one of the most critical targets of education reform. 

Desimone, L. M. (2009). Improving impact studies of teachers’ professional development: Toward better conceptualization and measures. Educational Researcher, 38(3), 181–199.

Snapshot 2019: A review of K-12 online, blended, and digital learning.

Online, blended, and digital learning in K–12 schools in the United States includes an assortment of schools, programs, tools, and resources. These range from the fully online schools in which students receive their entire education, to the digital platforms and content that mainstream teachers are using to bolster instruction in their physical classrooms. 

 

Digital Learning Collaborative. (2019). Snapshot 2019: A review of K-12 online, blended, and digital learning. https://static1.squarespace.com/static/59381b9a17bffc68bf625df4/t/5df14d464ba53f72845791b2/1576095049441/DLC-KP-Snapshot2019.pdf

 
Remote Learning Overview

The Covid-19 pandemic has resulted in school closings for the remainder of the year in 48 of 50 states and a sharp turn toward remote instruction in order to finish the year as best as possible. Understanding best practice in remote instruction and learning will be key as schools look to the future.

Donley, J., Detrich, R., States, J., & Keyworth, (2020). Remote Learning Overview. Oakland, CA: The Wing Institute. https://www.winginstitute.org/effective-instruction-computers.

Does capital at home matter more than capital at school? Social capital effects on academic achievement.

The authors examine whether social capital created at home and at school has differing effects on child academic achievement. They hypothesize that children derive social capital from both their families and their schools and that capital from each context promotes achievement.

 

Dufur, M. J., & Parcel, T. L., & Troutman, K. P. (2013). Does capital at home matter more than capital at school? Social capital effects on academic achievement. Research in Social Stratification and Mobility31, 1–21.

Regular computer users perform better in key school subjects, OECD study shows

This study is the first internationally comparative data analysis of the impact of computer use of student performance, based on OECD’s PISA 2003 assessment of educational performance by 15-year olds. It backs up previous OECD analysis about the importance of computers in schools

E. C. D. (2006). Regular computer users perform better in key school subjects. Organization for Economic Co-operation and Development (OECD).

2019 state of the states: The classroom connectivity gap is closed.

The analysis in this report is based on 2019 application data from the FCC’s Schools and Libraries Program (“E-rate”). This data represents the best national source of current information on school district connectivity; specifically, what broadband services schools are buying and how much they are paying for these services

EducationSuperHighway. (2019). 2019 state of the states: The classroom connectivity gap is closed. https://s3-us-west-1.amazonaws.com/esh-sots-pdfs/2019%20State%20of%20the%20States.pdf

 
Education technology: An evidence-based review

This review paper synthesizes and discusses experimental evidence on the effectiveness of technology-based approaches in education and outlines areas for future inquiry. While this review focuses on literature from developed countries, it also draws upon extensive research from developing countries. 

Escueta, M., Quan, V., Nickow, A. J., & Oreopoulos, P. (2017). Education technology: An evidence-based review.Working Paper 23744. Cambridge, MA: National Bureau of Economic Research. https://www.nber.org/papers/w23744.pdf

 
Teaching adolescents to become learners. The role of noncognitive factors in shaping school performance: A critical literature review

This report grew out of the understanding that it is not enough to know that noncognitive factors matter for learning. Researchers from a range of disciplines have provided evidence that such factors are important to students' grades and long-term educational outcomes. 

Farrington, C. A., Roderick, M., Allensworth, E., Nagaoka, J., Keyes, T. S., Johnson, D. W., & Beechum, N. O. (2012). Teaching adolescents to become learners. The role of noncognitive factors in shaping school performance: A critical literature review. Chicago, IL: University of Chicago Consortium on Chicago School Research. https://files.eric.ed.gov/fulltext/ED542543.pdf

 
Comparing the impact of online and face to face professional development in the context of curriculum implementation.

This study employed a randomized experiment to examine differences in teacher and student learning from professional development (PD) in two modalities: online and face-to-face. 

Fishman, B., Konstantopoulous, S., Kubitskey, B., Vath, R., Park, G., Johnson, H., & Edelson, D. C. (2013). Comparing the impact of online and face to face professional development in the context of curriculum implementation. Journal of Teacher Education, 64(5), 426–438.

Parent preparation and involvement in their child’s online learning experience: Superintendent Forum Proceedings Series. (Report No. 2).

Research that claims to focus on students with disabilities in online learning environments should be designed and carried out with particular attention to educational and social outcomes. The Center on Online Learning and Students with Disabilities (COLSD) conducts research in alignment with these goals.

Franklin, T. O., East, T., & Mellard, D.F. (2015). Parent preparation and involvement in their child’s online learning experience: Superintendent Forum Proceedings Series. (Report No. 2). Lawrence, KS: Center on Online Instruction and Students with Disabilities, University of Kansas. http://www.centerononlinelearning.res.ku.edu/wp-content/uploads/2017/04/Superintendent_Topic_2_Summary_November2015.pdf

 
How technology, coronavirus will change teaching by 2025

In early March, Education Week caught up with them by phone when they were in Paris to speak at an ed-tech conference. We asked them how their 2015 predictions had fared. Then, we talked again in late April, when the coronavirus had suddenly transformed K-12 education into a massive remote learning system.

Gewertz, C. (2020, June 2). How technology, coronavirus will change teaching by 2025. Education Week. https://www.edweek.org/ew/articles/2020/06/03/how-technology-coronavirus-will-change-teaching-by.html

 
Teachers’ Use of Technology for School and Homework Assignments: 2018–19 First Look

This report was generated in response to the enormous role technology is, and will increasingly be, playing in providing remote learning opportunities for students, whether in supporting part-time “school based” education or temporarily replacing it altogether.  

Gray, L., and Lewis, L. (2020). Teachers’ Use of Technology for School and Homework Assignments: 2018–19 (NCES 2020-048). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved [date] from https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2020048

Teachers' Use of Educational Technology in U.S. Public Schools: 2009. First Look

This National Center for Education Statistics report provides national data on the availability and use of educational technology among teachers in public elementary and secondary schools during the winter and spring of 2009. The data are the results of a national teacher-level survey that is one of a set that includes district, school, and teacher surveys on educational technology.

 

Gray, L., Thomas, N., and Lewis, L. (2010). Teachers’ Use of Educational Technology in U.S. Public Schools: 2009 (NCES 2010-040). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

The state of 21st century learning in the K–12 world of the United States: Online and blended learning opportunities for American elementary and secondary students.

This paper is an examination of the current state of blended and online learning throughout
the K-12 world in the United States. 

Greene, K., & Hale, W. (2017). The state of 21st century learning in the K–12 world of the United States: Online and blended learning opportunities for American elementary and secondary students. Journal of Educational Multimedia and Hypermedia26(2), 131–159.

 
Blended learning research in higher education and K–12 settings.

This chapter synthesizes and categorizes current blended learning research, with recommendations for future directions. Issues addressed in HE blended learning and K-12 blended learning are identified, compared, and evaluated by reviewing major research on the topic.

Halverson, L. R., Spring, K. J., Huyett, S., Henrie, C., & Graham, C. R. (2017). Blended learning research in higher education and K–12 settings. In J. M. Spector, B. B. Lockee, & M. D. Childress (Eds.), Learning, design, and technology: An international compendium of theory, research, practice, and policy (pp. 1–30). Cham, Switzerland: Springer International Publishing.

 
Student Login Records at Ohio E-Schools Spark $80 Million Dispute.

This article examines issues in the Ohio’s state funded online schools. In the fall of 2016 the Ohio education department completed attendance audits of 13 e-schools. Nine were found to have over reported their student enrollment. This issue takes on added significance with the selection of Betsy DeVos, U.S. education secretary, a prominent advocate of school choice who supports expanding online school options.

Harold, H. and Harwin, A. (2017). Student Login Records at Ohio E-Schools Spark $80 Million Dispute. Education Week. Retrieved March 16, 2017 from http://www.edweek.org/ew/articles/2017/03/08/student-login-records-at-ohio-e-schools-spark.html?cmp=eml-enl-dd-news2.

Teachers’ technological pedagogical content knowledge and learning activity types: Curriculum-based technology integration reframed.

This paper critically analyzes extant approaches to technology integration in teaching,
arguing that many current methods are technocentric, often omitting sufficient consideration
of the dynamic and complex relationships among content, technology, pedagogy, and
context.

Harris, J., Mishra, P., & Koehler, M. (2009). Teachers’ technological pedagogical content knowledge and learning activity types: Curriculum-based technology integration reframed. Journal of Research on Technology in Education41(4), 393–416.

 
Parental involvement in K–12 online and blended learning

Research indicates children generally fare better in traditional schools when parents are
involved. However, scant research exists in alternative settings such as blended and online
schooling

Hasler Waters, L., Borup, J., & Menchaca, M. P. (2018). Parental involvement in K–12 online and blended learning. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 403–422). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

 
Visible learning

This influential book is the result of 15 years research that includes over 800 meta-analyses on the influences on achievement in school-aged students. This is a great resource for any stakeholder interested in conducting a serious search of evidence behind common models and practices used in schools.

Hattie, J. (2009). Visible learning. A synthesis of over, 800.

Visible learning: 250+ influences on student achievement

The Visible Learning research synthesizes findings from 1,400 meta-analyses of 80,000 studies involving 300 million students, into what works best in education.

Hattie, J. (2017). Visible learning: 250+ influences on student achievement. https://visible-learning.org/wp-content/uploads/2018/03/VLPLUS-252-Influences-Hattie-ranking-DEC-2017.pdf

Everybody is their own island: Teacher disconnection in a virtual school.

Using qualitative interviews of eight virtual high school teachers, this study explored teachers' perceptions of their online teaching role. Teachers expressed a sense of disconnection from their students, the profession, and their peers as a result of limited interactions due to significant institutional barriers.

Hawkins, A., Barbour, M. K., & Graham, C. R. (2012). Everybody is their own island: Teacher disconnection in a virtual school. International Review of Research in Open and Distance Learning, 13(2), 123–144.

 
Amid Pandemic, Support Soars for Online Learning, Parent Poll Shows:

The survey was conducted in May 2020. While this was early in the Covid-19 pandemic, unemployment was already 14.7%, the economy in recession, and the schools were shutdown.  This survey provides one of the first opportunities to evaluate the public’s views on education in this context

Henderson, M. B., Houston, D. M., Peterson, P. E.,  West, M. R. & Shakeel, M. D. (2020). Amid Pandemic, Support Soars for Online Learning, Parent Poll Shows Results from the 2020 Education Next Survey of Public Opinion.  Education Next20(13), 8-19. https://www.educationnext.org/amid-pandemic-support-soars-online-learning-parent-poll-shows-2020-education-next-survey-public-opinion/

Amid Pandemic, Support Soars for Online Learning, Parent Poll Shows:

 The survey was conducted in May 2020.  While this was early in the Covid-19 pandemic, unemployment was already 14.7%, the economy in recession, and the schools were shutdown.  This survey provides one of the first opportunities to evaluate the public’s views on education in this context.

Henderson, M. B., Houston, D. M., Peterson, P. E.,  West, M. R. & Shakeel, M. D. (2020). Amid Pandemic, Support Soars for Online Learning, Parent Poll Shows Results from the 2020 Education Next Survey of Public Opinion.  Education Next20(13), 8-19.

 

Technology in education: An overview.

Technology is everywhere in education: Public schools in the United States now provide at least one computer for every five students. And in 2015-16, for the first time, more state standardized tests for the elementary and middle grades will be administered via technology than by paper and pencil.

Herold, B. (2016, February 5). Technology in education: An overview. Education Week.https://www.edweek.org/ew/issues/technology-in-education/index.html

 
The disparities in remote learning under coronavirus (in charts)

The messy transition to remote learning in America’s K-12 education system as a result of the COVID-19 pandemic has been marked by glaring disparities among schools, according to nationally representative surveys of U.S. teachers and school district leaders administered by the EdWeek Research Center.

Herold, B. (2020, April 10). The disparities in remote learning under coronavirus (in charts). Education Week.https://www.edweek.org/ew/articles/2020/04/10/the-disparities-in-remote-learning-under-coronavirus.html

 
Global blended learning practices for teaching and learning, leadership and professional development.

This study will discuss a guiding definition for blended learning, benefits, team support, policy, management issues, rationale for expansion, professional development, purchasing, funding, evaluation, and lenses of the future and implications.

Hilliard, A. T. (2015). Global blended learning practices for teaching and learning, leadership and professional development. Journal of International Education Research11(3), 179–188. https://files.eric.ed.gov/fulltext/EJ1070786.pdf

The rise of K–12 blended learning.

Online learning is sweeping across America. In the year 2000, roughly 45,000 K–12 students took an online course. In 2009, more than 3 million K–12 students did. What was originally a distance-learning phenomenon no longer is. Most of the growth is occurring in blended-learning environments, in which students learn online in an adult-supervised environment at least part of the time. As this happens, online learning has the potential to transform America’s education system by serving as the backbone of a system that offers more personalized learning approaches for all students.

Horn, M., & Staker, H. (2011). The rise of K–12 blended learning. Mountain View, CA: Innosight Institute.

 
Blended: Using disruptive innovation to improve schools.

this hands-on guide expands upon the blended learning ideas presented in
that book to provide practical implementation guidance for educators seeking to incorporate
online learning with traditional classroom time

Horn, M., & Staker, H. (2015). Blended: Using disruptive innovation to improve schools. San Francisco, CA: Jossey-Bass.

 
Virtual Learning Leadership Alliance and Quality Matters.

The purpose of the National Standards for Quality (NSQ) revision initiative is to provide the K-12 online and blended learning community with an updated set of openly licensed standards to help evaluate and improve online courses, online teaching and online programs.

irtual Learning Leadership Alliance and Quality Matters. (2019). National standards for quality online teaching (3rd ed.). https://www.nsqol.org/wp-content/uploads/2019/02/National-Standards-for-Quality-Online-Teaching.pdf

 
Variability in reading ability gains as a function of computer-assisted instruction method of presentation

This study examines the effects on early reading skills of three different methods of
presenting material with computer-assisted instruction.

Johnson, E. P., Perry, J., & Shamir, H. (2010). Variability in reading ability gains as a function of computer-assisted instruction method of presentation. Computers and Education55(1), 209–217.

 
Do Computers in the Classroom Boost Academic Achievement?

This report analyzes computer usage in the classrooms of teachers who are at least moderately well-prepared in the use of computers for reading instruction. Data from the 1998 National Assessment of Educational Progress (NAEP) database were used to analyze the influence of computers on academic achievement.

Johnson, K. A. (2000). Do Computers in the Classroom Boost Academic Achievement? A Report of the Heritage Center for Data Analysis.

Efficacy of a blended learning approach to elementary school reading instruction for students who are English learners.

This study examined whether a personalized, adaptive blended learning approach can support reading development in ELs and non-ELs. 

Kazakoff, E. R., Macaruso, P., & Hook, P. (2017). Efficacy of a blended learning approach to elementary school reading instruction for students who are English learners. Education Technology Research and Development66, 429–449.

 
Design and development of field experiences in K–12 online learning environments.

This article describes the instructional design of field experiences in K-12 online learning environments. Couched in the theory of situated cognition and based on established K-12 online teaching standards, these field experiences are slowly gaining popularity in teacher education programs.

Kennedy, K., & Archambault, L. (2012a). Design and development of field experiences in K–12 online learning environments. Journal of Applied Instructional Design2(1), 35–49. https://www.researchgate.net/profile/Leanna_Archambault/publication/2724

 
Offering preservice teachers field experiences in K–12 online learning: A national survey of teacher education programs

This study shares the results of a national survey targeting teacher education programs’ efforts to help prepare preservice teachers for K-12 online learning. Data show that only 1.3% of responding teacher education programs are addressing this need via field experiences in virtual schools. Implications for policy and practice in the field of teacher education are examined

Kennedy, K., & Archambault, L. (2012b). Offering preservice teachers field experiences in K–12 online learning: A national survey of teacher education programs. Journal of Teacher Education, 63(3), 185–200.

 
Effectiveness of intelligent tutoring systems: A meta-analytic review.

This review describes a meta-analysis of findings from 50 controlled evaluations of
intelligent computer tutoring systems. 

Kulik, J. A., & Fletcher, J. D. (2016). Effectiveness of intelligent tutoring systems: A meta-analytic review. Review of Educational Research86(1), 42–78.

 
Attuning pedagogies to the context of ‘new learners’ and technology

To address the importance and challenges of implementing new pedagogies, this paper brings together leading experts to reflect on key areas of pedagogy. In particular, each chapter addresses a pedagogical dimension that together offers a conceptual framework for action

Lafuente, M. (2018). Attuning pedagogies to the context of ‘new learners’ and technology. In A. Peterson, H. Dumont, M. Lafuente, & N. Law (Eds.), Understanding innovative pedagogies: Key themes to analyse new approaches to teaching and learning (pp. 94–115). OECD Education Working Paper No. 172. Organisation for Economic Co-operation and Development. http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=EDU/WKP(2018)8&docLanguage=En

 
A self-regulated flipped classroom approach to improving students’ learning performance in a mathematics course.

In this paper, a self-regulated flipped classroom approach is proposed to help students schedule their out-of-class time to effectively read and comprehend the learning content before class, such that they are capable of interacting with their peers and teachers in class for in-depth discussions.

Lai, C. L., & Hwang, G. J. (2016). A self-regulated flipped classroom approach to improving students’ learning performance in a mathematics course. Computers and Education100, 126–140.

 
Equity in competency education: Realizing the potential, overcoming the obstacles.

This report sought to review a wide set of research findings and integrate insights relevant to potential equity issues that could arise as competency education evolves and begins to be implemented more broadly.

Lewis, M. W., Eden, R., Garber, C., Rudnick, M., Santibañez, L., & Tsai, T. (2014). Equity in competency education: Realizing the potential, overcoming the obstacles. Students at the Center: Competency Education Research Series. Boston, MA: Jobs for the Future. https://studentsatthecenterhub.org/wp-content/uploads/2015/10/Equity-in-Competency-Education-103014-copy.pdf

 
The validation of one parental involvement measurement in virtual schooling.

This paper provides an overview of parental involvement in traditional education, discusses its role in K-12 virtual schooling, and describes a study that validates a parental involvement assessment with a virtual school population.

Liu, F., Black, E., Algina, J., Cavanaugh, C., & Dawson, K. (2010). The validation of one parental involvement measurement in virtual schooling. Journal of Interactive Online Learning9(2), 105–132.

 
A brief look at the methodologies used in the research on online teaching and learning.

This chapter looks at the research methods used during the first ten years of research on
online teaching and learning

Lowes, S., & Lin, P. (2018). A brief look at the methodologies used in the research on online teaching and learning. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 91–110). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

 
Productivity measurement in the education sector

This note provides a brief review of work to address the challenges of measuring output and productivity in the education sector, with attention also to issues related to the increasing use of technology in the provision of education services.

McGivney, E., & Foda, K. (n.d.). Productivity measurement in the education sector. Washington, DC: Brookings Institution. https://www.brookings.edu/wp-content/uploads/2017/12/productivity-measurement-in-education.pdf

 
The effectiveness of online and blended learning: A meta-analysis of the empirical literature.

This meta-analysis was designed to produce a statistical synthesis of studies contrasting learning outcomes for either fully online or blended learning conditions with those of face-to-face classroom instruction.

Means, B., Toyama, Y., Murphy, R., & Bakia, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record115(3), 1–47. https://archive.sri.com/sites/default/files/publications/effectiveness_of_online_and_blended_learning.pdf

 
Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies

A systematic search of the research literature from 1996 through July 2008 identified more than a thousand empirical studies of online learning.

Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2010). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. Washington, DC: U.S. Department of Education. http://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalreport.pdf

 
Understanding and improving full-time virtual schools: A study of student characteristics, school finance, and school performance in schools operated by K12

This report provides a new perspective on the nation’s largest virtual school provider through a systematic review and analysis of student characteristics, school finance, and school performance of K12-operated schools.

Miron, G., & Urschel, J. L. (2012). Understanding and improving full-time virtual schools: A study of student characteristics, school finance, and school performance in schools operated by K12, Inc. Boulder, CO: National Education Policy Center. http://files.eric.ed.gov/fulltext/ED533960.pdf

 
Virtual schools in the U.S. 2015: Politics, performance, policy, and research evidence.

This 2015 report is third in a series of annual reports on virtual education in the U.S.. It is organized in three major sections. 

Molnar, A., Huerta, L., Shafer, S. R., Barbour, M.K., Miron, G., Shafer, S. R., & Gulosino, C. (2015). Virtual schools in the U.S. 2015: Politics, performance, policy, and research evidence. Boulder, CO: National Education Policy Center. http://nepc.colorado.edu/publication/virtual-schools-annual-2015

 
Virtual schools in the U.S. 2019

This report provides disinterested scholarly analyses of the characteristics and performance of fulltime, publicly funded K-12 virtual schools; reviews the relevant available research related to virtual school practices; provides an overview of recent state legislative efforts to craft virtual schools policy; and offers policy recommendations based on the available evidence.

Molnar, A., Miron, G., Elgeberi, N., Barbour, M. K., Huerta, L., Shafer, S. R., & Rice, J. K. (2019). Virtual schools in the U.S. 2019. Boulder, CO: National Education Policy Center. https://nepc.colorado.edu/sites/default/files/publications/Virtual%20Schools%202019.pdf

 
Virtual schools in the U.S. 2017

The 2017 NEPC Annual Report contributes to the existing evidence related to virtual education, and so to debates surrounding it. It provides objective analysis of the characteristics and performance of full-time, publicly funded K-12 virtual schools; available research on virtual school practices and policy; and an overview of recent state efforts to craft new policy

Molnar, A., Miron, G., Gulosino, C., Shank, C., Davidson, C., Barbour, M. K.,… Nitkin, D. (2017). Virtual schools in the U.S. 2017. https://files.eric.ed.gov/fulltext/ED574702.pdf

 
Blended learning report

This research report presents the findings of this formative and summative research effort.

Murphy, R., Snow, E., Mislevy, J., Gallagher, L., Krumm, A., & Wei, X. (2014). Blended learning report. Austin, TX: Michael and Susan Dell Foundation. https://www.msdf.org/wp-content/uploads/2016/01/MSDF-Blended-Learning-Report-May-2014.pdf

 
A call to action to improve the quality of full-time virtual charter public schools

This report provides basic information about full-time virtual charter public schools, presents data about their results, and outlines a set of policy recommendations that states should adopt to improve the performance of full-time virtual charter schools across the country.

National Alliance for Public Charter Schools (2016). A call to action to improve the quality of full-time virtual charter public schools. http://www.publiccharters.org/sites/default/files/migrated/wp-content/uploads/2016/06/Virtuals-FINAL-06202016-1.pdf

 
Regular computer users perform better in key school subjects

This correlational study is the first internationally comparative data analysis of the impact of computer use of student performance, based on OECD’s PISA 2003 assessment of educational performance by 15-year olds. It backs up previous OECD analysis about the importance of computers in schools.

O. E. C. D. (2006). Regular computer users perform better in key school subjects. Organization for Economic Co-operation and Development (OECD)

Students, computers and learning: Making the connection.

The report highlights the importance of bolstering students’ ability to navigate through digital texts. It also examines the relationship among computer access in schools, computer use in classrooms, and performance in the PISA assessment. 

OECD (2015). Students, computers and learning: Making the connection. Paris, France: OECD Publishing. https://www.oecd-ilibrary.org/docserver/9789264239555-en.pdf?expires=1591112620&id=id&accname=guest&checksum=E108C3D7C7CC829D93048D0ED6CB4635

Learning remotely when schools close: How well are students and schools prepared? Insights from PISA.

That being said, the Covid-19 crisis strikes at a point when most of the education systems covered by the OECD’s latest round of the Programme for International Student Assessment (PISA) are not ready for the world of digital learning opportunities. Below are some sobering numbers.

OECD (2020). Learning remotely when schools close: How well are students and schools prepared? Insights from PISA. https://read.oecd-ilibrary.org/view/?ref=127_127063-iiwm328658&title=Learning-remotely-when-schools-close

Students, Computers and Learning Making the Connection

Based on results from PISA 2012, this Organisation for Economic Cooperation and Development (OECD) report examines how students’ access to and use of information and communication technology (ICT) devices has evolved in recent years, and explores how education systems and schools are integrating ICT into students’ learning experiences.

 

 

OECD (2015), Students, Computers and Learning: Making the Connection, OECD Publishing, Paris.
DOI: http://dx.doi.org/10.1787/9789264239555-en

Effectiveness of Cognitive Tutor Algebra I at scale.

This article examines the effectiveness of a technology-based algebra curriculum in a wide
variety of middle schools and high schools in seven states. 

Pane, J. F., Griffin, B. A., McCaffrey, D. F., & Karam, R. (2014). Effectiveness of Cognitive Tutor Algebra I at scale. Educational Evaluation and Policy Analysis36(2), 127–144.

 
Continued progress: Promising evidence on personalized learning

This report examines achievement in 62 public charter and district schools that are pursuing a variety of personalized learning practices, and examines implementation details in 32 of those schools

Pane, J. F., Steiner, E. D., Baird, M. D., & Hamilton, L. S. (2015). Continued progress: Promising evidence on personalized learning. Santa Monica, CA: RAND Corporation. http://www.rand.org/pubs/research_reports/RR1365.html

Digital game-based learning in high school computer science education: Impact on educational effectiveness and student motivation

This study assesses the learning effectiveness and motivational appeal of a computer game for learning computer memory concepts, which was designed according to the curricular objectives and the subject matter of the Greek high school Computer Science (CS) curriculum, as compared to a similar application, but lacking the gaming aspect.

Papastergiou, M. (2009). Digital game-based learning in high school computer science education: Impact on educational effectiveness and student motivation. Computers & Education, 52(1), 1-12.

Mean what you say: Defining and integrating personalized, blended and competency education.

The purpose of the personalized learning framework is to open student pathways and encourage student voice and choice in their education. Personalized learning is enabled by instructional environments that are competency-based. By tapping into modalities of blended and online learning using advanced technologies, personalized learning is enhanced by transparent data and abundant content resources flowing from redesigned instructional models to address the standards.

Patrick, S., Kennedy, K., & Powell, A. (2013). Mean what you say: Defining and integrating personalized, blended and competency education.  https://files.eric.ed.gov/fulltext/ED561301.pdf

 
Students, Computers and Learning. Making the Connection.

Are there computers in the classroom? Does it matter? Students, Computers and Learning: Making the Connection examines how students’ access to and use of information and communication technology (ICT) devices has evolved in recent years.

Peña-López, I. (2015). Students, Computers and Learning. Making the Connection. OECD Publishing.

Helping students help themselves: Generative learning strategies improve middle school students’ self-regulation in a cognitive tutor

The current study investigated whether prompting students to engage in generative learning strategies improves students' subsequent judgments of learning and self-regulation. Seventy- eight middle school students in a pre-algebra class completed worksheets in between problem-solving sessions in a computer-based cognitive tutor. 

Pilegard, C., & Fiorella, L. (2016). Helping students help themselves: Generative learning strategies improve middle school students’ self-regulation in a cognitive tutor. Computers in Human Behavior65, 121–126.

Blending Learning: The Evolution of Online and Face-to-Face Education from 2008–2015

This paper discusses definitions of blended learning and explores ways in which blended learning is being developed by a number of schools

Powell, A., Watson, J., Staley, P., Patrick, S., Horn, M., Fetzer, L.,…Verma, S. (2015). Blended learning: The evolution of online and face-to-face education from 2008–2015. http://www.inacol.org/wp-content/uploads/2015/07/iNACOL_Blended-Learning-The-Evolution-of-Online-And-Face-to-Face-Education-from-2008-2015.pdf

Elementary school-wide implementation of a blended learning program for reading intervention.

The authors examined the implementation of a blended learning program for literacy instruction across kindergarten through Grade 5 in a Title I urban elementary school, including a population of students (18%) who are English learners.

Prescott, J. E., Bundschuh, K., Kazakoff, E. R., & Macaruso, P. (2018). Elementary school-wide implementation of a blended learning program for reading intervention. Journal of Educational Research111(4), 497–506.

How Teachers Are Using Technology at Home and in Their Classrooms

A survey of 2,462 Advanced Placement (AP) and National Writing Project (NWP) teachers finds that digital technologies have helped them in teaching their middle school and high school students in many ways. At the same time, the internet, mobile phones, and social media have brought new challenges to teachers.

Purcell, K., Heaps, A., Buchanan, J., & Friedrich, L. (2013). How teachers are using technology at home and in their classrooms. Washington, DC: Pew Research Center’s Internet & American Life Project. Retrieved from http://www.pewinternet.org/2013/02/28/how-teachers-are-using-technology-at-home-and-in-their-classrooms/

Competencies and personalized learning

This chapter elaborates on a definition of personalized learning, delineates aspects of competency inherent in the definition, traces the evolution of personalized learning, and explores the complementarity of the personal and the interpersonal in personalized education.

 

Redding, S. (2016). Competencies and personalized learning. In M. Murphy, S. Redding, & J. Twyman (Eds.), Handbook on personalized learning for states, districts, and schools (pp. 3–18). Philadelphia, PA: Temple University, Center on Innovations in Learning. http://www.centeril.org/2016handbook/resources/Redding_chapter_web.pdf

 
Research and history of policies in K–12 online and blended learning

This handbook is meant to be a resource for anyone interested in research, practice, or policy in the field of K-12 online and blended learning. This handbook is a collection of what we currently know about research in the field. 

Rice, K. (2014). Research and history of policies in K–12 online and blended learning. In R. E. Ferdig & K. Kennedy (Eds.), Handbook of research on K–12 online and blended learning (pp. 51–82). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://pdfs.semanticscholar.org/cfcb/578ede7dc55b6ea97bdb1a37fe6243bb2bc9.pdf

 
Getting back on track: The effect of online versus face-to-face credit recovery in Algebra I on high school credit accumulation and graduation

This research brief is one in a series for the Back on Track Study that presents the findings regarding the relative impact of online versus face-to-face Algebra I credit recovery on students’ academic outcomes, aspects of implementation of the credit recovery courses, and the effects over time of expanding credit recovery options for at-risk students.

Rickles, J., Heppen, J., Allensworth, E., Sorenson, N., Walters, K., & Clements, P. (2018). Getting back on track: The effect of online versus face-to-face credit recovery in Algebra I on high school credit accumulation and graduation. American Institutes for Research, Washington, DC; University of Chicago Consortium on School Research, Chicago, IL. https://www.air.org/system/files/downloads/report/Effect-Online-Versus-Face-to-Face-Credit-Recovery-in-Algebra-High-School-Credit-Accumulation-and-Graduation-June-2017.pdf

 
The impact of education technology on student achievement: What the most current research has to say

This study analyzes five large-scale studies of education technology: (1) "Meta-Analytic Studies of Findings on Computer-Based Instruction" (J.A. Kulik); (2) "Report on the Effectiveness of Technology in Schools, 1990-1997" (J. Sivin-Kachala); (3) "Evaluating the Apple Classrooms of Tomorrow" (E.L. Baker, M. Gearhart, & J.L. Herman) ; (4) "West Virginia's Basic Skills/Computer Education Program: An Analysis of Student Achievement" (D. Mann, et al.); and (5) "Does It Compute? The Relationship between Educational Technology and Student Achievement in Mathematics.

Schacter, J. (1999). The impact of education technology on student achievement: What the most current research has to say. Milken Exchange on Education Technology.

Exploration of a blended learning approach to reading instruction for low SES students in early elementary grades.

This study investigated the potential benefits of a blended learning approach on the reading skills of low socioeconomic status students in Grades 1 and 2.

Schechter, R., Macaruso, P., Kazakoff, E. R., & Brooke, E. (2015). Exploration of a blended learning approach to reading instruction for low SES students in early elementary grades. Computers in the Schools32, 183–200.

A history of K–12 online and blended instruction in the United States.

This chapter will cover the history and progression of online and blended learning in K-12 education in the United States. Program categories covered include state virtual schools, fully online schools, and blended learning. 

Schwirzke, K., Vashaw, L., & Watson, J. (2018). A history of K–12 online and blended instruction in the United States. In K. Kennedy & R. E. Ferdig (Eds.), Handbook of research on K–12 online and blended learning (2nd ed., pp. 7–20). Pittsburgh, PA: Carnegie Mellon University, ETC Press. https://www.academia.edu/37013644/Handbook_of_Research_on_K-12_and_Blending_Learning_Second_Editio.pdf

 
Computer-assisted learning in elementary reading: A randomized control trial.

This study evaluated the efficacy of Accelerated Reader, a computer-based learning program, at improving student reading. 

Shannon, L. C., Styers, M. K., Wilkerson, S. B., & Peery, E. (2015). Computer-assisted learning in elementary reading: A randomized control trial. Computers in the Schools32(1), 20–34.

 
10 strategies for online learning during a coronavirus outbreak.

Members of ISTE’s professional learning networks have been hard at work identifying key practices for successful online learning. Here are some of the best ideas from educators from around the world, many of whom have already been teaching during coronavirus closures. 

Snelling, J., & Fingal, D. (2020, March 16). 10 strategies for online learning during a coronavirus outbreak. Washington, DC: International Society for Technology in Education. https://www.iste.org/explore/learning-during-covid-19/10-strategies-online-learning-during-coronavirus-outbreak

 
Flipped learning as a path to personalization.

One-to-one computing and bring-your-own-device (BYOD) initiatives are helping to ensure that each student has a device with which to work. Although these technologies can support personalized learning, they haven’t yet transformed our schools into 21st-century utopias where students engage in interactive, individualized learning applications and access information in order to collaboratively solve problems while teachers roam the learning space, coaching and mentoring as their engaged and self-directed students happily work.

Soto, M. S. (2016). Flipped learning as a path to personalization. In M. Murphy, S. Redding, & J. Twyman (Eds.), Handbook on personalized learning for states, districts, and schools (pp. 73–87). Philadelphia, PA: Temple University, Center on Innovations in Learning. http://www.centeril.org/2016handbook/resources/Sota_flipped_chapter_web.pdf

 
Blended learning research yields limited results.

Blended learning is gaining considerable popularity in American classrooms, but the question remains: Is there strong evidence that the strategy helps K-12 students?

Sparks, S. (2015, April 13). Blended learning research yields limited results. Education Week.https://www.edweek.org/ew/articles/2015/04/15/blended-learning-research-yields-limited-results.html

 
Which blended model should K–12 schools choose?

Which blended-learning model should they choose? Are Station Rotations the ideal, or Flex studios? Is Carpe Diem’s Individual Rotation the gold standard, FirstLine’s Lab Rotation, Summit’s Flex model, or Woodland Park’s Flipped Classroom?

Staker, H. (2014, January 10). Which blended model should K–12 schools choose? Christensen Institute. http://www.christenseninstitute.org/which-blended-model-should-schools-choose/

 
Essentials for blended learning: A standards-based guide

This book provides a practical, streamlined approach for creating effective learning experiences by blending online activities and the best of face-to-face teaching.

Stein, J., & Graham, C. (2014). Essentials for blended learning: A standards-based guide. New York, NY: Routledge

Using the U.S. PISA results to investigate the relationship between school computer use and student academic performance

Using the U.S. PISA results to investigate the relationship between school computer use and student academic performance

Sun, L., & Bradley, K. D. (2003). Using the US PISA results to investigate the relationship between school computer use and student academic performance.

What forty years of research says about the impact of technology on learning: A second-order meta-analysis and validation study

This research study employs a second-order meta-analysis procedure to summarize 40 years of research activity addressing the question, does computer technology use affect student achievement in formal face-to-face classrooms as compared to classrooms that do not use technology? A study-level meta-analytic validation was also conducted for purposes of comparison.

Tamim, R., Bernard, R., Borokhovski, E., Abrami, P., & Schmid, R. (2011). What forty years of research says about the impact of technology on learning: A second-order meta-analysis and validation study. Review of Educational Research81(1), 4–28. https://pdfs.semanticscholar.org/f8fa/160a2552568e102b0cac11ad0a48fc635b0e.pdf?_ga=2.248632325.343379521.1591299854-1379934943.1547574243

 
Reconcilable differences: Standards-based teaching and differentiation.

Standards-based instruction and differentiated learning can be compatible approaches in today's classrooms.

Tomlinson, C. A. (2000). Reconcilable differences: Standards-based teaching and differentiation. Educa­tional Leadership, 58(1), 6–11. http://eric.ed.gov/?id=EJ614602

 
Virtual schools: The changing landscape of K–12 education in the U.S.

This paper examines some of the challenges and strengths of virtual schools, it offers questions to consider when deciding whether or not a virtual school option would be ideal, and it draws conclusions, which provide an outlook for the future of virtual schools in k-12 education.

Toppin, I. N., & Toppin, S. M. (2016). Virtual schools: The changing landscape of K–12 education in the U.S. Education and Information Technologies21(6), 1571–1581.

Isolating the effects of active responding in computer‐based instruction

This experiment evaluated the effects of requiring overt answer construction in computer-based programmed instruction using an alternating treatments design.

Tudor, R. M. (1995). Isolating the effects of active responding in computer‐based instruction. Journal of Applied Behavior Analysis28(3), 343-344.

Computer‐programmed instruction: The relation of required interaction to practical application.

A group experimental design compared passive reading, covert responding to frame blanks, and actively typing answers to blanks with and without immediate confirmation of correctness. Results strongly supported the effectiveness of requiring the student to supply fragments of a terminal repertoire while working through a program. 

Tudor, R. M., & Bostow, D. E. (1991). Computer‐programmed instruction: The relation of required interaction to practical application. Journal of Applied Behavior Analysis24(2), 361-368.

Ed Tech Developer’s Guide: A primer for Software Developers, Startups, and Entrepreneurs

The U.S. Department of Education Office of Educational Technology created this guide to assist software developers, startups and entrepreneurs in gaining specialized knowledge and is designed to help apply technology in smart ways to solve persistent problems in education.

 

U.S. Department of Education, Office of Educational Technology, Ed Tech Developer’s Guide, Washington, D.C., 2015.

Enhancing Teaching and Learning Through Educational Data Mining and Data Analytics

The U.S. Department of Education Office of Educational Technology published this brief that is intended to help policymakers and administrators understand how analytics and data mining have been—and can be—applied for educational improvement while rigorously protecting student privacy.

U.S. Department of Education, Office of Educational Technology, Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics: An Issue Brief, Washington, D.C., 2012.

Future Ready Learning: Reimagining the Role of Technology in Education

This report is the 2016 National Education Technology Plan. It is the latest policy document on educational technology from the U.S. Department of Education Office of Educational Technology. It sets a national vision and plan for learning enabled by technology through building on the work of leading education researchers; district, school, and higher education leaders; classroom teachers; developers; entrepreneurs; and nonprofit organizations.

 

Category: 172, 173, 174, 175, 180, 189, 192, 194, 196

U.S. Department of Education, Office of Educational Technology, Future Ready Learning: Reimagining the Role of Technology in Education, Washington, D.C., 2016.

Future Ready Schools: Building Technology Infrastructure for Learning

The Future Ready Schools: Building Technology Infrastructure for Learning guide provides practical, actionable information intended to help district leaders (superintendents, principals, and teacher leaders) navigate the many decisions required to deliver cutting-edge connectivity to students. It presents a variety of options for district leaders to consider when making technology infrastructure decisions, recognizing that circumstances and context vary greatly from district to district.

U.S. Department of Education, Office of Educational Technology, Future Ready Schools: Building Technology Infrastructure for Learning, Washington, D.C., 2014. 

Early Learning and Educational Technology Policy Brief

The U.S. Department of Education and U.S. Department of Health and Human Services collaborated in the development of the Early Learning and Educational Technology Policy Brief to promote developmentally appropriate use of technology in homes and early learning settings.

 

U.S. Department of Education, Office of Educational Technology, Policy Brief on Early Learning and Use of Technology, Washington, D.C., 2016.

Designing Online Communities of Practice for Educators to Create Value

The U.S. Department of Education Office of Educational Technology published this report that details the results of exploratory research on how to design and manage online communities of practice for educators.

 

U.S. Department of Education. (2014, April). Designing Online Communities of Practice for Educators to Create Value. Retrieved from http://tech.ed.gov/wp-content/uploads/2014/10/Exploratory-Research-on-Designing-Online-Communities-FINAL.pdf.

Blended learning: A wise giver’s guide to supporting tech-assisted teaching.

In this book, we’ll briefly explore why we’re still only in the early stages of the educational technology revolution. Then we’ll look at how some innovative schools and other organizations are pioneering new methods of personalized learning built on new technology

Vanderkam, L. (2013). Blended learning: A wise giver’s guide to supporting tech-assisted teaching. Washington, DC: Philanthropy Roundtable. https://www.philanthropyroundtable.org/docs/default-source/guidebook-files/blended_learning_guidebook.pdf?sfvrsn=afaba740_0

 
Measuring the impact of a blended learning model on early literacy growth.

In the context of trying to improve reading proficiency in elementary school students, this study investigated the use of digital technology as part of a blended learning program, Core5, in kindergarten and first grade classes. 

Wilkes, S., Kazakoff, E. R., Prescott, J. E., Bundschuh, K., Hook, P. E., Wolf, R.,… Macaruso, P. (2020). Measuring the impact of a blended learning model on early literacy growth. Journal of Computer Assisted Learning. Advance online publication. https://onlinelibrary.wiley.com/doi/full/10.1111/jcal.12429

 
Learning in one-to-one laptop environments: A meta-analysis and research synthesis.

This paper examines the impact of computers on student achievement has concluded that providing each student with a computer has a modest but positive effect on student achievement. This meta-analysis included 10 studies from more than 15 years of research on the topic.

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.

Self-regulated learning and academic achievement: An overview.

This overview presents a general definition of self-regulated academic learning and identifies the distinctive features of this capability for acquiring knowledge and skill.

Zimmerman, B. J. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist25(1), 3–17.

 
Hard Wiring: What the Next Decade in Education Policy Means for Educational Technology
This article is a speculation on the use of technology in the future of education.
Rotherham, A., J. (2006). Hard Wiring: What the Next Decade in Education Policy Means for Educational Technology. American Institutes of Research (AIR).
A systematic review and meta-analysis of the effectiveness of information and communication technology (ICT) on the teaching of spelling
This study suggests that the teaching of spelling by using computer software may be as effective as conventional teaching of spelling.
Torgerson, C. J. and Elbourne, D. (2002). A systematic review and meta-analysis of the effectiveness of information and communication technology (ICT) on the teaching of spelling. Journal of Research in Reading, 25(2):129-43.
Software Enabling School Improvement Through Analysis of Student Data
This paper considers issues surrounding the use data and data based decision-making in schools. It describes the state of the field and possible future directions in school based technology.
Wayman, Jeffrey C., Sam Stringfield, and Mary Yakimowski. "Software enabling school improvement through analysis of student data." (2004).
TITLE
SYNOPSIS
American Institutes for Research (AIR)
AIR is one of the world's largest behavioral and social science research and evaluation organizations. Its research focus includes most aspects of K-12 education.
Balefire Labs

Balefire Labs provides an online educational app review service for mobile apps. It helps teachers and parents to find the highest quality educational apps for kids, ages 0-19 years. It uses rigorous, science-based, review criteria and publishes a detailed rubric on its site.

Center on Teaching and Learning (CTL)
CTL is research center that conducts and disseminates research that focuses on practical solutions to serious problems in school systems.
EdTech Strategies
EdTech Strategies (Doug Levin) provides strategic research and counsel on issues at the intersection of education, public policy, technology, and innovation.
Education News
EducationNews provides coverage, commentaries, and comprehensive views on education issues from all sides of the political spectrum.
Education Policy Center
This site is the education division of the American Institute of Research.
Pew Research Center's Internet and American Life Project
Pew Research Center informs the public about the issues, attitudes and trends shaping America and the world through public opinion polling, demographic research, content analysis and other data-driven social science research.
Back to Top