Educators try to find ways to make education accessible to all students every day. As a fundamental human right (UN General Assembly, 1948), a one-size-fits-all system does not cater to every child (Consortium for School Networking, 2019). One pedagogical approach is to use personalised learning to ensure the needs of all students are met (Bernacki et al., 2021; Pane et al., 2017; Starasts, 2015; UNESCO International Bureau of Education, 2017; Walkington & Bernacki, 2020). Since 1762 when Jean-Jacques Rousseau advocated for student-centred education, personalised learning has come in various forms (UNESCO International Bureau of Education, 2017). Many personalised learning approaches, including the Montessori Method (1897), the Dalton Plan (1914) and the Keller Plan (1968), have built on and contributed to our understanding of what personalised learning is today (UNESCO International Bureau of Education, 2017).
In 2020, with the onset of the COVID-19 pandemic, schooling was forced online to ensure students continued their education (Yan et al., 2021). During the lockdowns in Australia, as a secondary school educator, it was hard to continue my usual practice of personalised learning for my students in the online environment. It is challenging enough to personalise learning in a face to face environment when, as a secondary school teacher, you teach up to 150 different students at a time, let alone in an online environment. This literature review aims to assess what is known about online personalised learning. In particular, this paper will focus on defining the key concepts, outlining drivers and challenges, and how online personalised learning can be implemented in an Australian secondary school. Since returning from COVID lockdowns, it is clear that online classes in secondary schools will be a significant disruption in education in future years as it allows for more flexible options for students (Kipp & Patrick, 2013).
As more and more students and educators have ubiquitous access to the internet, online learning has become a more reasonable option for completing studies (Kumi-Yeboah & Smith, 2013). Online learning has experienced success in tertiary studies for many years (Journell, 2012). As such, most research focuses on adult learners and the university setting (Harvey et al., 2014; Tucker, 2007). Adult-orientated programs are designed for independent learners, which is not often found in K-12 education (Yan et al., 2021). With the introduction of online learning in the K-12 realm, the experience of school for all students, especially at-risk students, has significantly changed (Kipp & Patrick, 2013; Tucker, 2007). As a result, online learning fills a need in the education sector by providing options to ensure at-risk students complete their secondary studies (Kipp & Patrick, 2013). As a new field of study in secondary education, online learning has a limited body of research that primarily focuses on the effectiveness in comparison with similar studies in tertiary education (Borup et al., 2014; Harvey et al., 2014; Journell, 2012; Kipp & Patrick, 2013; Tucker, 2007). This field is growing exponentially, and there is still a lot to learn (Harvey et al., 2014; Kipp & Patrick, 2013).
Understanding this new field of study needs to begin with defining online learning. Online learning encompasses a range of learning activities undertaken with electronic technologies and is often used interchangeably with e-learning (Neyland, 2011). The number of students who choose to learn online is rising steadily, with virtual schools and blended learning playing an important role (Beck & Beasley, 2020; Kumi-Yeboah & Smith, 2013; Neyland, 2011). Blended learning incorporates online learning into the traditional bricks and mortar classroom via multimedia, the internet, and a learning management system (Kumi-Yeboah & Smith, 2013). Virtual or cyber schools are online schools that offer a place for students to complete their secondary schooling either fully or partially online (Beck & Beasley, 2020). Both options have led to a change in teacher and student roles in the classroom.
Teaching in an online environment is different from teaching in a face-to-face environment. Online educators need different skills and characteristics to succeed (Journell, 2012). Unfortunately, the educators selected to teach online usually have exceptional classroom pedagogy or are fantastic with technology (Journell, 2012). Being effective in the classroom does not always translate into effective online pedagogy. Borup et al. (2014) outlined three roles teachers undergo when working in a virtual school program. Supported by Kumi-Yeboah and Smith (2013), the first is about designing course content and learning activities (designers), the second is about monitoring and assessing learning (assessor), and the last role is to provide support to students (mentors) (Borup et al., 2014). While this role is similar to that of an in-person educator, hundreds more variables have to be considered at any given moment in the online environment, including self-paced versus a cohort approach, full-time versus part-time students, or blended versus fully online learning (Kipp & Patrick, 2013). It is essential to ensure that an online course does not turn into a way to share information and content without providing any real learning opportunities, where students connect to content, connect with peers and connect with the teacher (Journell, 2012; Kipp & Patrick, 2013). For online learning to reach its full potential, new teaching and learning theories need to be researched, especially around what effective pedagogy looks like.
Students are in a similar position and must learn what to expect from online learning. There is a misconception that online learning has been designed for students to avoid social interactions when online learning requires an exceptional ability to communicate with peers and teachers daily (Journell, 2012). This different set of skills and intrinsic motivation are required to succeed (Journell, 2012; Yan et al., 2021). Unfortunately, from the research in China and the United States of America, online courses have a higher dropout rate than face-to-face classes; some of this is due to a lack of maturity and the reduced physical presence of the classroom teacher (Journell, 2012; Yan et al., 2021). Regardless of the learning environment (online or face-to-face), secondary school teachers must cater to all students’ needs (Beasley & Beck, 2017; Beck & Beasley, 2020). Online courses either offer a one size fits all approach or a tailored pathway, with the former being the most common option (Journell, 2012; Tucker, 2007). What online courses do offer is the flexibility for students to work through it at their own pace. Virtual schools allow students to learn outside of the traditional school day, and this flexibility prepares them for further education and lifelong learning. (Tucker, 2007; Yan et al., 2021).
Money is always a key driver in decisions made within the educational sphere. Online learning is generally cheaper than traditional schooling in the long run (Journell, 2012). While it can be expensive to develop and deploy once established, enrollments can increase without the need for additional infrastructure (Journell, 2012; Kumi-Yeboah & Smith, 2013). Students can take courses not offered at their school with online learning, reducing costs and space required in overcrowded schools (Journell, 2012). Additionally, as technology improves and more students have access, the cost of online learning will decrease rapidly (Journell, 2012).
Overall the research suggests that students who engage in online classes have a positive experience and perform better than their counterparts in face-to-face classrooms (Harvey et al., 2014; Kipp & Patrick, 2013; Kumi-Yeboah & Smith, 2013; Tucker, 2007). This driver, along with improved skills, led Kumi-Yeboah and Smith (2013) to discover that learning online could enhance oral and written communication skills, while Tucker (2007) found that virtual schools blurred the line between learning during the school day and learning after hours. The research agrees that online learning attracts students who dislike social interactions and prefer to learn independently (Harvey et al., 2014; Journell, 2012; Kumi-Yeboah & Smith, 2013). It is also often utilised by at-risk students, as they have time and opportunity to access class materials regardless of absence (Journell, 2012; Kumi-Yeboah & Smith, 2013). However, an area that needs further research is accessibility for students with disabilities and their engagement with online learning (Harvey et al., 2014). The final driver of online learning has been the COVID-19 pandemic. In the wake of forced online learning and its mass adoption globally, virtual schools have seen an expansion in enrollment (Yan et al., 2021).
The perception of online learning is educators’ most significant challenge (Journell, 2012; Kipp & Patrick, 2013; Tucker, 2007). The belief is that it is an easy way to complete high school and cheat the system due to the quality of the online programs (Journell, 2012; Kipp & Patrick, 2013). There is much variation in the quality of online secondary school programs in America (Journell, 2012; Kipp & Patrick, 2013; Tucker, 2007). Some programs just distribute content and measure students’ knowledge, while others encourage students to participate in online discussions (Journell, 2012; Tucker, 2007). The second challenge outlined in the literature is the equity and social justice issues. The COVID-19 pandemic brought attention to just how big the gap between the rich and poor, the digital divide and digital readiness, and technology and infrastructure availability within and between countries (Chiu et al., 2021; Yan et al., 2021). Further investigation is required to see how to help bridge the gap caused by income, wealth and disability.
Time is constantly a constraint for educators. Teachers need time to learn new ideas, skills and concepts; this will only be accomplished if teachers have release time to complete their design, assess and mentor roles (Borup et al., 2014; Kumi-Yeboah & Smith, 2013; Neyland, 2011). Nearly all the research identified a lack of training as a stumbling block due to time constraints (Beck & Beasley, 2020; Chiu et al., 2021; Harvey et al., 2014; Journell, 2012; Kumi-Yeboah & Smith, 2013). A majority of the studies found that teachers need more opportunities to explore the various intricacies of online instruction to create a better connection between theory and practice (Chiu et al., 2021; Harvey et al., 2014; Journell, 2012). One of these nuances of online instruction is facilitating a collaborative environment. Both Harvey et al. (2014) and Chiu et al. (2021) investigated the need to include peer support within the online learning environment as an area of concern was the lack of social interaction. During the pandemic, students in China reported the heavy workload and fatigue caused by online learning were caused by teachers not understanding the complexities of online learning and the dissemination of content they were providing (Yan et al., 2021). The research to date suggests that online learning does not meet the needs of all students within secondary school.
Education is constantly evolving to build a better, more progressive system that focuses on student outcomes (Consortium for School Networking, 2022; Feldstein & Hill, 2016). During the 2010s, personalisation became the aspirational standard in schools, believing that students would take ownership of their learning and become lifelong learners (Bernacki et al., 2021; Tomlinson, 2017; UNESCO International Bureau of Education, 2017). For personalised learning to be successful, it needs to incorporate effective pedagogy; this is best done with teachers being a part of the development process (Adams Becker et al., 2016). Regrettably, when schools in America adopt personalised learning, it is based on their governing educational policy (Bernacki et al., 2021). The same applies in Australia, as the national curriculum directs teachers to use personalised learning strategies to meet the needs of diverse students (Adams Becker et al., 2016).
Regardless of whether the learning environment is face-to-face or online, all research agrees that learning is personalised for the individual student (Bernacki et al., 2021; Bingham, 2017; Feldstein & Hill, 2016; Feldstein et al., 2015; Johnson et al., 2015; Johnson et al., 2012; Johnson et al., 2011; Keefe, 2007; Shemshack et al., 2021; Steiner et al., 2020; Tomlinson, 2017; UNESCO International Bureau of Education, 2017). What the researchers cannot agree on is if it is a learning model (Bingham, 2017; Feldstein et al., 2015), a learning approach (Feldstein & Hill, 2016; Johnson et al., 2015; Johnson et al., 2012; Shemshack et al., 2021; Steiner et al., 2020; Tomlinson, 2017), a process (Bernacki et al., 2021; Johnson et al., 2011; Keefe, 2007), a way of thinking (Tomlinson, 2017), or a philosophy (Keefe, 2007; UNESCO International Bureau of Education, 2017). Learning can be personalised for each student by tailoring instruction based on many factors. These factors can be categorised into curricular elements, readiness, interest or learner profile (Smith & Throne, 2009). Curricular elements include personalising by content, process, product or choice (Bingham, 2017; Consortium for School Networking, 2019; UNESCO International Bureau of Education, 2017). Personalising by readiness covers capabilities, skills, pacing, experiences, prior knowledge, performance, flexibility, competency and motivation (Bernacki et al., 2021; Bingham, 2017; Consortium for School Networking, 2019; Johnson et al., 2015; Shemshack et al., 2021; Walkington & Bernacki, 2020). Interests and goals form part of personalising by interest (Bernacki et al., 2021; Bingham, 2017; Consortium for School Networking, 2019; Johnson et al., 2015; Pane et al., 2017; Tomlinson, 2017; Walkington & Bernacki, 2020). In contrast, learner profile includes personalising by needs, cultural background, learning preferences, strengths, learning styles, beliefs and student data (Bernacki et al., 2021; Bingham, 2017; Consortium for School Networking, 2019; Feldstein & Hill, 2016; Johnson et al., 2015; Pane et al., 2017; Shemshack et al., 2021; Tomlinson, 2017; UNESCO International Bureau of Education, 2017; Walkington & Bernacki, 2020).
In every aspect of life, people have come to expect choice and personalisation in all products and services, from entertainment to fashion to social media (Consortium for School Networking, 2019). This demand puts pressure on schools to offer the same (Feldstein et al., 2015). However, while personalised learning has much potential, there is a causality dilemma with both technology and practice. Improvement in technology in online learning environments and adaptive technologies, along with the decrease in costs for personal computers in recent years, has ensured that educators can provide more choice and deliver differentiated content (Adams Becker et al., 2016; Johnson et al., 2015; Pane et al., 2017; Starasts, 2015; Walkington & Bernacki, 2020). At the same time, the personalisation of learning is driving the development of new technology and software to support students (Johnson et al., 2015; Pane et al., 2017). However, in most schools, the focus is on redesigning pedagogy and changing the traditional narrative (Johnson et al., 2015). As best practice takes teachers from being the sage on the stage to the guide on the side; personalised learning strategies are moving content broadcast out of the classroom to ensure that this time is better spent having discussions, applying content, tutoring, coaching and mentoring students (Feldstein & Hill, 2016; Johnson et al., 2015). Teachers themselves are also driving personalised learning as they share their pedagogy with colleagues and the field matures and grows (Walkington & Bernacki, 2020). Finally, some subjects, such as mathematics and science, are more conducive to personalised learning; however, there is a place for personalisation in subjects like English and history (Feldstein et al., 2015).
Personalized learning requires students to take responsibility for their learning and have a high degree of autonomy (Bingham, 2017; Johnson et al., 2015). This can be difficult for teenagers, who are often not mature enough to act independently. While governments require students to complete standardised assessments, personalised learning will be undermined by the need to be compliant (Johnson et al., 2015). For personalised learning to be appropriately implemented, educators require evidenced-based frameworks, professional development, time to build the curriculum and individualised pathways, examples of best practice, pedagogical and technology support, equipment, support staff, and opportunities to fail (Adams Becker et al., 2016; Bingham, 2017; Feldstein & Hill, 2016). Current research shows that schools may struggle in implementing personalised learning as educators ultimately need the opportunity to slowly and systematically create a successful program for their context (Bingham, 2017; Feldstein & Hill, 2016; Feldstein et al., 2015). In 2015, Feldstein et al. and Johnson et al. identified that personalised learning had a scalability problem that potentially could be solved with technology. Even if this was the case, if each student receives a truly individualised plan, educators need to tailor these plans, which is not possible when you teach 150 students in a secondary school setting (Feldstein et al., 2015).
While personalised learning has been around for 260 years, the biggest challenge is that there is no set definition (Bernacki et al., 2021; UNESCO International Bureau of Education, 2017; Walkington & Bernacki, 2020). With the use of personalisation and personalised learning as educational buzzwords, you can be forgiven for believing that research has defined them (Tomlinson, 2017; Walkington & Bernacki, 2020). What has become even more challenging with the implementation of personalised learning is the slightly different definitions and sometimes interchangeable terms used (Culatta, 2016).
Defining Personalised Learning
Personalised learning is often used interchangeably with adaptive learning, individualised learning, differentiated learning, competency-based learning, demonstration of learning, blended learning, community-based learning, student voice, project-based learning, inquiry learning, computer-based learning, and anything-anywhere-anytime student-designed learning (Culatta, 2016; Tomlinson, 2017). Personalised learning is a broad term that includes adaptive learning, individualised learning, differentiated learning, competency-based learning and learner agency (Adams Becker et al., 2016; Culatta, 2016; Feldstein et al., 2015; Tomlinson, 2017). Predominately, personalised learning is about adjusting pace and approach to meet the needs of individual students (Walkington & Bernacki, 2020), with the variation being to add in a student’s interests (Culatta, 2016) and learning preferences (Bernacki et al., 2021). According to Tomlinson (2017), “personalisation is a kind of differentiation” (p. 15). Reflecting on the literature and my pedagogical practice, differentiated online learning needs to be the focus (Angell, 2020).
Differentiation ensures that all students have the access and opportunity to be successful by placing them at the centre of the learning process (Maeng, 2016). Without differentiation, learning is unfair; by providing learning opportunities set at the right level for students to be able to access them, students can be supported to succeed (Cash, 2011; Cowley, 2018; Narvaez & Brimijoin, 2010; Tomlinson, 2014). Within a differentiated classroom, goals are defined, learning differences acknowledged, and assessment utilised to ensure personalised learning occurs (Cash, 2011; Crawford, 2008; Haelermans, 2022; Maeng, 2016). As with personalised learning, how teachers differentiate can be categorised into curricular elements, readiness, interest or learner profile (Gregory et al., 2015; Kryza et al., 2007; Maeng, 2016; Smith & Throne, 2009; Tomlinson, 2014). Differentiation is a model to help all students achieve excellence in the classroom (Tomlinson, 2014).
Differentiated Online Learning in Secondary School
While extensive research into differentiation has occurred in face-to-face classrooms, minimal research has occurred in the online environment (Beasley & Beck, 2017; Beck & Beasley, 2020). Differentiation in the online environment sets out to achieve the same thing as a face-to-face classroom; all that changes is how it affects pedagogy in the online classroom (Beasley & Beck, 2017). Currently, two small studies have been carried out in the United States which have focused exclusively on differentiation in an online classroom (Beasley & Beck, 2017; Beck & Beasley, 2020). The 2017 study (118 teachers from two cyber schools) found that online teachers differentiated their instruction by learning styles only instead of focusing on the best practice of differentiating by content, process and product (Beasley & Beck, 2017; Tomlinson, 2014). However, they recognised that they needed to differentiate by content, process, and product in the online environment but were unsure how they could do this. (Beasley & Beck, 2017). The 2020 study (92 teachers from three cyber schools) found that a large majority of the online teachers had a novice understanding of differentiation, confirming a lack of professional development in differentiation in an online environment (Beck & Beasley, 2020). Beck and Beasley (2020) concluded that newer virtual schools could have difficulty finding teachers who have the expertise needed to effectively teach students in a differentiated online environment.
In making education accessible to all students, educators, regardless of whether they teach in a traditional school or an online school, should use pedagogical approaches that personalise the learning experience. This was made evident during the COVID-19 pandemic when traditional schools were forced online. Online learning, blended learning, e-learning, virtual schools and cyber schools have increased the number of secondary students choosing to study online, leading to a change in roles for both students and teachers. Being an accomplished educator or good with technology does not mean that you will be a success teaching online, as the role requires you to be mindful of a different kind of pedagogy. Online courses provide flexibility for students, although they have a higher dropout rate as students require good communication skills, maturity, and intrinsic motivation to succeed. Money, course offerings, technology improvements, positive student experiences, better outcomes, improved skills, and the COVID-19 pandemic have all been drivers of online learning. The perception of online learning surrounding the quality of online secondary school programs, equity and social justice issues, time, professional learning, especially around creating and facilitating a collaborative environment, and workloads for students are all challenges requiring further research.
Within the traditional classroom setting, personalised learning has become an aspirational standard. Currently, personalised learning is based on a country’s education policy in an attempt to meet the needs of diverse students. The research agrees that personalised learning focuses on the individual student; after this, it splinters off about whether it is a model, approach, process, way of thinking or philosophy. Personal learning can be tailored for each individual by curricular elements, readiness, interest or learner profile. Demand from student expectations, new and improved technology, redesigned pedagogy, best practices, and academics drive personalised learning in classrooms. Challenges for personalised learning include student responsibility and autonomy, government standardised testing, professional learning, evidence-based frameworks, time, pedagogical and technological support, equipment, scalability and the opportunity to create a truly individualised plan. The biggest challenge for personalised learning is a lack of an agreed-to definition. The closest thing to an agreed-to definition is that personalised learning is an approach to learning where individual students’ needs are met by adjusting pace and learning activities. It is a broad-based term that includes adaptive learning, individualised learning, differentiated learning, competency-based learning and learner agency. Personalised learning is used interchangeably with these terms along with seven other terms in the literature. On reflection, differentiated learning is the correct term to be investigated.
Differentiation is a model that
provides learning opportunities for students to access learning and be
supported to succeed. Focused on defining goals, acknowledging differences and
using student data to ensure personalised learning occurs. Similarly,
personalised learning differentiation can occur based on curricular elements,
readiness, interest or learner profile. Currently, there is limited research
into differentiated online learning in secondary schools, with only two small
studies being undertaken in America. This limited research means there is only
a basic understanding of differentiation in an online environment. Evolving
from the massive gap in the literature brought to light by the global pandemic,
future studies need to focus on the use of data for differentiation in online
learning. Thus the research question for further investigation is: How can
educators deliver better outcomes for students in an online learning
environment using data to differentiate?
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