Disruptive technology and the Covid-19 pandemic have shifted the education paradigm around the world. Many educators have evolved their teaching paradigm into more technology-mediated since the traditional classroom suddenly shifted into an online classroom. The demand for online education, such as e-learning platforms, has developed as the urge for remote collaboration rises during the pandemic. Therefore, embracing technology in the classroom is required to engage students in online classroom interaction. This way, a pivotal permissive factor of technology drives a new pedagogy to retain students deeper and personalize learning. Remarkably, the upcoming Industrial Revolution 5.0 is personalization. This way, teachers and educators must implement a personalized approach to teaching and training based on each individual’s unique competencies and learning preferences. This fact aligns with the ISTE Standards for Educators, particularly an educator as a designer (ISTE, 2022), point 2.5.a, 2.5.b, and 2.5.c:
2.5.a Use technology to create, adapt and personalize learning experiences that foster independent learning and accommodate learner differences and needs.
2.5.b Design authentic learning activities that align with content area standards and use digital tools and resources to maximize active, deep learning.
2.5.c Explore and apply instructional design principles to create innovative digital learning environments that engage and support learning.
What is Personalized Learning?
In the 21st century, personalization in instruction is defined as an instruction that tailors learners’ learning styles, intelligence, and interest preferences (Gilbert and Han, 2002, cited in Samah et al., 2011). This way, all learners will be provided with the critical challenges and opportunities for self-development and learning if these differences are taken into account (Aviram et al., 2008; Jung and Graf, 2008, cited in Samah et al., 2011). Moreover, Bray and McClaskey (2015, cited in Netcoh, 2017) define a “personalized learning environment” as one in which students “have a voice in what they are learning based on how they learn best” and “have a choice in how they demonstrate what they know and provide evidence of their learning. In a learner-centered environment, learners own and co-design their learning” (p. 14).
At the classroom level, PL teachers leverage technology (e.g., online curricula, learning management systems, videos) to deliver a more student-centered experience (Bingham, 2017, cited in Bingham, 2019). Bingham (2019) further elaborates that PL uses technology to tailor instruction to students’ needs and interests (Bill & Melinda Gates Foundation, 2014; Miller, Gross, & Lake, 2014). These technologies can house all information about students, such as current progress, past achievement, social-emotional comments, and behavioral information. All these are to free up better teachers’ time to address individual student needs (Bingham, 2017). Technology can be used as a classroom management tool. Classroom management may be an issue when classrooms rely on technology, particularly new teachers (Bingham, 2016).
Regarding the role of the teacher in personalized learning environments, Bishop et al. (2020) discuss the following main points. Whereas in traditional classroom settings, the teacher primarily determines learning objectives, teachers in PLEs base the learning objectives on individual students’ questions, interests, and aspirations. Therefore, teachers in PLEs are expected to serve as facilitators of “inquiry, problem-solving, and creative expression” by transferring “control over learning toward the students themselves” (DiMartino & Clarke, 2008, p. 74, cited in Bishop et al., 2020). Similarly, rather than preparing resources based on teacher-identified learning goals, teachers may become curators in PLEs, helping students access appropriate resources suited to their unique projects (Keefe & Jenkins, 2005, cited in Bishop et al., 2020). Finally, because personalized learning focuses on tailoring instruction to individual students rather than an entire class, teachers in PLEs may find themselves acting as coaches to an individual or small groups on project tasks, goals, and standards, as they forgo whole group instruction (Bray & McClaskey, 2015; Clarke, 2013; DiMartino & Clarke, 2008, cited in Bishop et al., 2020).
Personalized Learning in Higher Education
The use of technology has provided new opportunities to make higher education more flexible and student-centered (Palmer & Devitt, 2008, 2014, cited in Wanner & Palmer, 2015). Also, many university leaders see that technology provides new ways to meet the challenges of the higher education sector in the context of economic constraints, increasing globalization of education, and changing pedagogical approaches (OECD, 2005; Allen & Seaman, 2013; OECD, 2005, cited in Wanner & Palmer, 2015). In other words, technology is not the primary determinant of flexibility, but a crucial enabling factor as technology and new pedagogies need to be harnessed to engage students on a deeper level and personalize students’ learning. Importantly, Bingham, Pane, Steiner, and Hamilton (2018, in Lokey-Vega & Stephens, 2019) consider technology the critical differentiator. This significant point is in line with Alhawiti and Abdelhamid (2017), claiming that current technology has the potential to construct an e-learning environment capable of acquiring learners’ preferences, building and managing sharable and reusable semantically modeled learning entities, and providing customized e-learning services for each learner according to his/her preferences and personal characteristics.
A previous study conducted by Sáiz-Manzanares et al. (2019) reveals that a personalized Moodle-based e-learning system has improved student learning outcomes. In this study, hypermedia resources and active methodologies such as PBL and process-oriented feedback appeared to facilitate learning outcomes. Student satisfaction with teaching practice appears to be related to the LMS’s design, level of personalization, and the use of process-oriented feedback (Zacharis, 2015; Hattie and Timperley, 2007, cited in Sáiz-Manzanares et al., 2019). In summary, this study concludes that best practice in implementing Blended Learning is related to a careful pedagogical design of the LMS. The effectiveness of e-personalization designs has been demonstrated in this study, consisting of hypermedia resources and active methodologies such as PBL process-oriented feedback and self-assessment quizzes that facilitate learning outcomes and the acquisition of deep learning.
Personalized Learning Instruction Model
1. Genius Hour
Genius Hour is a project during school that allows students to explore their passions or wonders and make a product based on that within a set amount of time, usually 1 hour a week. It is an idea coined by Google, where their employees are given 20% of their time at work to work on their projects (Daim, 2021). Daim further elaborates on the six steps for Genius Hour, as shown in my Presentation 1 (Please click the number icon to see the detailed information).
Presentation 1. 6 Steps of Genius Hour
Simos (2015) discusses that Genius Hour’s curricular concept embodies an optimal learning relationship: students embracing their power and responsibility in the learning process work with educators who can facilitate and guide that learning to ever-greater heights. In the Genius Hour model, instructors allocate a portion of class time—often the 20 percent that gives the approach an alternate name (20% Time)—for student exploration of a self-selected and given topic. Students turn to various sources in their explorations and consider the topic from various angles before synthesizing all of their research into a central understanding. This process culminates in a final product, project, or artifact shared with the class and potentially the larger school community (Kirr, 2014, cited in Simos, 2015).
A significant body of research supports the need for the increased focus on differentiation that the Genius Hour model fosters. Student interests, both existing and burgeoning, are brought to the forefront of the classroom when a differentiated model is implemented, allowing teachers to “use time flexibly, call upon a range of instructional strategies, and become partners with their students to see that both what is learned and the learning environment are shaped to the learner” (Tomlinson, 1999, cited in Simos, 2015).
Carter (2017) elaborates on six basic tenets of personalized instruction employed in the Genius Hour model, covering:
- Dual Teacher Role
- Learn About Your Students
- Create a Culture of Collaboration
- Create an Interactive Learning Environment
- Build Flexible Pacing, But With Structure
- Create Authentic Assessments
2. The QUEST Inquiry-Based Learning
The QUEST model for inquiry-based learning (Wicks, 2017) uses language better aligned with assignment expectations, eliminates confusing terminology, e.g., triggering events, and introduces a separate fifth step to help educators and students practice connected learning, as illustrated in my Presentation 2. Please click the arrow icon to see the before and after steps.
- Ask a Question about the standard being studied related to a topic of interest. (Personalize the question for your discipline or field.)
- Understand the standard and topic better by conducting research and sharing a resource. (Practice and improve information literacy skills.)
- Educate and learn from others about the standard and your topics. (Collaborate with your peers to resolve problems.)
- Find a Solution or resolution for your question, even if the solution is to ask more questions. (Reflect on what you have learned during your inquiry.)
- Teach others about what you have learned by blogging about it and sharing it on social media. (Practice connected learning by engaging an authentic audience with your solution and seeking their feedback.)
Presentation 2. 5 Steps of QUEST Inquiry-Based Learning
Based on my experience as an online learner, I found that QUEST Inquiry-Based Learning employs personalized learning by leveraging digital tools. Throughout the whole steps of online learning, the learner can ask questions, investigate a topic, and share their findings. This model allows students to explore a topic in-depth and share their discoveries with others to maximize active and deep learning. This way, leveraging technology to create, adapt, and personalize learning experiences that foster independent learning and accommodate learner differences and needs.
On the other hand, the Genius Hour model implemented in online learning is an innovative learning environment that engages and supports learning. Throughout the whole steps of Genius Hour, the learner explores a self-selected and given topic. This way, learners turn to various sources in their explorations and consider the topic from various angles before synthesizing all of their research into a central understanding. Again, similar to the QUEST model, the Genius Hour model leverages technology to create, adapt, and personalize learning experiences that foster independent learning and accommodate learner differences and needs.
Practical Strategies for Successful Personalized Learning
A successful personalized learning initiative has the following characteristics (Grant & Basye, 2014):
• Students’ interests and abilities are engaged in authentic, real-world activities to promote the learning of content area standards.
• Teachers take on the roles of facilitators and coaches in the classroom rather than the dispensers of knowledge.
• Students control the learning paths to achieve established goals, building self-efficacy, critical thinking, and creativity skills.
• Technology enables students to choose what they learn, how they learn, and how they demonstrate their learning.
• Formative assessment throughout the learning cycle, supported by digital tools, helps teachers and students address weaknesses and build on strengths.
• Progress through subject area content is measured by demonstrating proficiency in identified skills and understanding.
• Technology is integrated throughout teachers’ and students’ experiences to support learning.
To sum up, technology, teacher, and learner play a pivotal role in implementing personalized learning in online classrooms. Some previous studies have revealed that technology has the potential to construct an e-learning environment capable of acquiring learners’ preferences. Also, particular learning models, such as the Genius Hour and the QUEST Model, are excellent examples of employing personalized learning in higher education since the current technology is a crucial enabling factor as technology and new pedagogies need to be harnessed to engage students on a deeper level and personalize students’ learning. Some practical strategies should be implemented to create successful personalized learning in higher education.
Alhawiti, M. M., & Abdelhamid, Y. (2017). A Personalized e-Learning Framework. Journal of Education and E-Learning Research, 4(1), 15–21. https://doi.org/10.20448/journal.509.2017.41.15.21
Bingham, A. J. (2016). Drowning digitally? How disequilibrium shapes practice in a blended learning charter school. Teachers College Record, 118(1), 1–30.
Bingham, A. J. (2017). Personalized learning in high technology charter schools. Journal of Educational Change, 18(4), 521–549.
Bingham, A. J. (2019). A Look at Personalized Learning: Lessons Learned. Kappa Delta Pi Record, 55(3), 124–129. https://doi.org/10.1080/00228958.2019.1622383
Bishop, P. A., Downes, J. M., Netcoh, S., Farber, K., Demink-Carthew, J., Brown, T., & Mark, R. (2020). Teacher roles in personalized learning environments. Elementary School Journal, 121(2). https://doi.org/10.1086/711079
Carter, N. (2017). Genius Hour and the 6 Essentials of Personalized Education | Edutopia. http://www.edutopia.org/blog/genius-hour-essentials-personalized-education-nichole-carter?utm_source=facebook&utm_medium=post&utm_campaign=blog-genius-hour-essentials-personaized-education-link
Daim, L. A. M. (2021). Genius Hour Online Edition Step By Step Guide. https://techfulofprimary.com/2021/08/genius-hour-online-edition-step-by-step-guide/
Grant, P., & Basye, D. (2014). Personalized learning: A Guide for Engaging Students with Technology (First). International Society for Technology in Education.
ISTE. (2022). ISTE Standards: Educators. https://www.iste.org/standards/iste-standards-for-teachers
Keefe, J. W., & Jenkins, J. M. (2005). Personalized instruction. Phi Delta Kappa. KnowledgeWorks.
Lokey-Vega, A., & Stephens, S. (2019). A Batch of One: A Conceptual Framework for the Personalized Learning Movement. Journal of Online Learning Research, 5(3), 311–330.
Netcoh, S. (2017). Balancing freedom and limitations: A case study of the choice provision in a personalized learning class. Teaching and Teacher Education, 66, 383–392. https://doi.org/10.1016/j.tate.2017.05.010
Sáiz-Manzanares, M. C., García Osorio, C. I., Díez-Pastor, J. F., & Martín Antón, L. J. (2019). Will personalized e-Learning increase deep learning in higher education? Information Discovery and Delivery, 47(1), 53–63. https://doi.org/10.1108/IDD-08-2018-0039
Samah, N. A., Yahaya, N., & Ali, M. B. (2011). Individual differences in online personalized learning environment. Educational Research and Reviews, 6(7), 516–521.
Simos, E. (2015, August). Genius Hour: Critical Inquiry and Differentiation. English Leadership Quarterly, 1–3. https://library.ncte.org/journals/elq/issues/v38-1/27416
Wanner, T., & Palmer, E. (2015). Personalizing learning: Exploring student and teacher perceptions about flexible learning and assessment in a flipped university course. Computers and Education, 88, 354–369. https://doi.org/10.1016/j.compedu.2015.07.008
Wicks, D. (2017). The QUEST model for inquiry-based learning. https://davidwicks.org/iste-2-design-and-develop-digital-age-learning-experiences-and-assessments/quest-model-for-inquiry-based-learning/