Blended Learning: A Personalized Approach to Student Success

 

Rachel Hull

 

Lamar University  

 

EDLD 5305   

 

                             

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Introduction  

 

The technology we have in classrooms today is helping educators to personalize instruction for blended learning. Educators can now empower students using technology and personalized instruction in ways unimaginable before. Educational technology offers unique affordances as a learning tool and delivery system for enhancing and personalizing instruction. Over the past two decades, efforts by school districts and states to infuse technology into everyday K-12 education through one-to-one laptop initiatives have rapidly proliferated (Ross 2020).  According to the Horizon report, there is an increasing demand for instruction that is customized to each student’s unique needs and that provides more learner choice and control. It has become clear that one-size-fits-all teaching methods are neither effective nor acceptable for today’s diverse students. Technology can and should support individual choices about access to materials and expertise, amount and type of educational content, and methods of teaching (Horizon,10). 

The following literature review connects how blended learning is personalized,  data driven, encourages student ownership and improves student outcomes. Focus and attention will be given to the correlation between blended learning and student outcomes. 

 

Literature Review

 

Blended learning is not just a buzzword and it isn’t new. Although there are many definitions of blended learning, The Christensen Institute, a nonprofit, nonpartisan, think tank is most frequently referenced. It is also referenced in the book, Blended: Using Disruptive Innovation to Improve Schools, as “any 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.” (Horn and Staker. 2015, pg. 34). Blended Learning is personalized, data driven, encourages student ownership, and improves student outcomes.

 

Blended Learning is Personalized Learning

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Blended learning has a basic framework based on constructivist learning perspectives. Learning is active, not passive. Teachers have personalized learning in their classrooms for decades by meeting student’s individual needs and it is best practice in instruction.  Emerging technologies have made this easier to do. Using adaptive learning software to meet students where they are to close learning gaps as part of the blended learning model gives teachers more data for personalization. Advances in technology have transformed personalized learning (Collins & Halverson, 2009). The 1:1 interactions of students with devices like tablets, netbooks, and mobile devices afford increased opportunities for PL within and outside the school day. The data that students’ interactions with learning platforms produces can be leveraged to gain knowledge about students’ knowledge, interests, and preferences, and other functions can be used to deliver educational content to students based on such information (Walkington, C. & Bernacki, M. (2020).

The hard work in personalizing instruction is to thus correlate learning outcomes, instruction and digital tools on a dynamic continuum in order to enable students to move at their own pace. One way to overcome this challenge and ensure evidence of learning is to leverage student data from adaptive learning software and use it to inform instruction (Tucker, Wycoff, & Green, 2017). 

 

One of the more prominent adaptive learning platforms for math, Dreambox, states that the future of education involves customization and personalization. All students, regardless of ability, can benefit from blended learning. The high-achieving, self-directed students can learn at an accelerated pace. Struggling students can focus on difficult subjects at a more relaxed pace. Students today expect school to be as technology rich as the world around them (Piontak, 2013).

The adoption of adaptive learning programs in schools has increasingly allowed for more student-centered instruction and personalized learning (Chubb, 2012). 

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Implementing adaptive learning programs in blended learning environments allows for greater personalization due to the affordances of technology to differentiate and scaffold learning based on students’ needs (Horn & Staker, 2011). There are many tools for teachers to create a blended learning environment. The blend works in a symbiotic fashion. The technology provides the personalized path and the data to personalize small group instruction making most all the facets of blended learning personalized.

 

Data Driven

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Technology platforms and adaptive technology can give teachers real time, detailed data which drives instruction and helps teachers differentiate instruction. Adaptive technology gives instructors access to new kinds of data beyond traditional end-of-term assessment scores so they can better understand what students are learning and how they are learning it. Many adaptive platforms allow instructors to see a more complete picture of their students, including real-time study habits, engagement with course material, and patterns of error. This information empowers college instructors to design more targeted instruction and remediation (Vignare, Kelsey, & VanderHeiden Guney, 2019). 

Data is a powerful tool to drive small group instruction in blended learning. It can also help students along their personalized pathway. Data can be collected fast and efficiently with technology. This data also eases the workload for educators. Teachers are recognizing the data value narrative from adaptive learning platforms to inform instruction and personalize learning. Not only do such platforms foster student agency by allowing some amount of control over pace and content, they also increase student motivation by enabling awareness of progress towards mastery through an instant feedback loop. Where time in between assessment and feedback used to rely on the ability of the teacher to review rapidly and provide such feedback, students and teachers are now able to track achievement benchmarks instantaneously (Tucker, Wycoff, & Green, 2017). Research indicates that feedback response time can increase higher achievement.

 

Student Ownership

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At the National Institute for Excellence in Teaching, student ownership is defined as the state when students can articulate what they are learning, why they are learning, strategies that support their learning, and how they will use strategies in the future. Blended learning can support student ownership by giving them choice and a more personalized path of learning.

In a study focused on learner engagement in blended learning environments it states that learner engagement correlates with educational outcomes. Student ownership can increase engagement. Blended learning may diversify the learning pathways available to accomplish a task; this increased flexibility and personalization abets curiosity, absorption, and attention (Esteban-Millat et al., 2014). At the same time, personalization and flexibility may require learners to employ greater effort and cognitive strategy use. When time on task is accompanied by effort (even absorption), deep learning occurs. At the same time, blended learning preserves the benefits of humanness (Graham, 2006), which encourages cognitive engagement while mediating the varied emotions that inevitably arise during learning (Halverson, Graham, 2019).

In the book, Blended Learning in Action, there are many examples of how blended learning lends itself to student ownership. Giving students autonomy can increase motivation and learner engagement. Blended learning gives students ample time to learn on their own. This leads to student ownership. In a blended learning culture, stakeholders are empowered to take greater ownership of their respective responsibilities. Students become agents and owners of their learning process (Tucker, Wycoff, & Green, 2017). 

PL can vary with respect to ownership – the degree to which learners are given control and choice in the learning situation (Walkington, C. & Bernacki, M., 2020).

Personalization, student ownership, and data driven instruction, all part of blended learning, can lead to positive student outcomes and achievement. 

 

Learning Outcomes

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Blended learning can improve learning outcomes. The International Journal of Research in Education and Science, published an article, The Effects of Blended Learning on STEM achievement in Elementary School Students. Their study had positive conclusions on blended learning in STEM education. As indicated by these results, students from low socioeconomic backgrounds tend to achieve higher STEM scores when placed in a blended learning environment. These findings are supported by Bidarra and Russman (2015) who also claimed that blended learning bridged gaps for students. Blended learning has the benefit of hands-on learning, as well, as independent, self-motivated learning. In the blended curricular approach, students have first-hand experience with the content and take ownership of their learning. If implemented with fidelity, the blended learning method of instruction should be taken seriously by administrators and other decision makers who serve low-socioeconomic areas ( Seage, S.J., Turegun, 2020).

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In another study focusing on blended learning to support reading instruction in elementary students, positive learning outcomes were found. Conclusions were positive. 

To conclude, this study extends the findings of previous work demonstrating benefits of blended learning for elementary school students. Significant outcomes were obtained using large samples of students across multiple treatment and control schools. In addition, benefits were found not only for students in younger grades (see Schechter et al. 2015) but for students in upper grades, and for students with different ethnic backgrounds (Marusco, Wilkes, & Prescott, 2020). 

In these studies different adaptive learning software were used coupled with small group instruction led by a teacher to improve learning outcomes, which is the goal of blended learning. 

 

Conclusion

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Though sometimes daunting, a thoughtful blended learning transformation is not only worth the time, energy, and effort, but necessary to keep pace with the rapidly evolving educational landscape (Tucker, Wycoff, & Green). Blending technology with instruction allows teachers to provide students with a more personalized learning experience as they work with small groups or target individual students’ needs (Chubb, 2012). Implementing adaptive learning programs in blended learning environments allows for greater personalization due to the affordances of technology to differentiate and scaffold learning based on students’ needs (Horn & Staker, 2011). Blended learning models, developed from early experimentation, place the student at the center of the learning process, harnessing the power of technology to create more engaging, efficient, and success-oriented learning environments. In these models, educators quickly identify gaps in learning and differentiate instruction to ensure that failure is not an option. Strong student supports, bolstered by teachers employing technology to transform learning, create powerful next generation models that prepare students for success

 ( iNACOL 2015). 

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In conclusion, the literature supports the correlation between blended learning and positive student outcomes and achievement. Personalizing instruction, a part of blended learning, is a major contributor to student success. The data provided by adaptive learning platforms, also a part of blended learning, contributes to student success.  

 

 References

 

Collins, A., & Halverson, R. (2009). Rethinking education in the age of technology:

              The digital revolution and schooling in America. Teachers College Press.

 

Chubb, J. (2012). Inside a blended learning environment. [Policy Innovators in Education Network]. Retrieved from                              http://pie-network.org/buzz/summit-2012/inside-ablendedLearning environment.
 

Fazal, M. & Bryant, M. (2019). Blended Learning in Middle School Math: The Question of Effectiveness. Journal of Online                 Learning Research, 5(1), 49-64. Waynesville, NC USA: Association for the Advancement of Computing in Education              (AACE). Retrieved November 25, 2021 from https://www.learntechlib.org/primary/p/183899/.

 

Graham, C.R. (2006). Blended learning systems:Definition, current trends, and future directions.I n C. J. Bonk & C. R.                         Graham (Eds.), The handbook of blended learning: Global perspectives, local designs (pp. 3–21). San Francisco,                   CA: Pfeiffer Publishing.

 

Halverson, L.R. & Graham, C.R. (2019). Learner Engagement in Blended Learning Environments: A Conceptual Framework.               Online Learning, 23(2), 145-178

 

Horizon. 2012. The NMC Horizon Report. 2012 K-12 Edition, 10. Retrieved from http://www.nmc.org/pdf/2012-horizon-         report-K12pdf

 

Horn, M., & Staker, H. (2011). The rise of blended learning. Mountain View, CA: Innosight Institute, Inc. Retrieved from                      http://www.innosightinstitute.org /innosight/wp content/uploads/2011/01/The-Rise-of-K-12-Blended-Learning.pdf

 

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

 

International Association for K-12 Online Learning (iNACOL) (2015) Promising Practices in Blended and Online Learning

 

Marusko, P., Wilkes, S., & Prescott, J. (2020) An investigation of blended learning to support reading instruction in                          elementary schools.Educational Technology Research and Development: A bi-monthly publication of the                             Association for Educational Communications & Technology. 68(6):2839-2852
 

Piontek, Jeff. (2013) Guide to Blended Learning for Elementary Mathematics. A District Web Seminar Digest.

 

Ross, Steven (2020). Technology infusion in K-12 classrooms: a retrospective look at three decades of challenges and                    advancements in research and practice.Educational Technology Research & Development. Oct2020, Vol. 68 Issue 5,            p2003-2020. 18p.

 

Seage, S.J., & Türegün, M. (2020). The effects of blended learning on STEM achievement of elementary school students. I            International Journal of Research in Education and Science (IJRES), 6(1), 133-140.

 

Tucker, C., Wycoff, T., & Green, J. (2017) Blended Learning in Action: A Practical Guide Toward Sustainable Change.                      Thousand Oaks:Corwin

 

Vignare, K., Kelsey, R., & VanderHeiden Guney, S. (2019) Improving Student Outcomes with Adaptive Courseware: The                  Every Learner Everywhere Network. Educause Review.

Walkington, C. & Bernacki, M. (2020) Appraising research on personalized learning: Definitions, theoretical alignment,                    advancements, and future directions, Journal of Research on Technology in Education, 52:3, 235-252, DOI: 10.1080/15391523.2020.1747757