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).

Online Learning

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).

Drivers

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).

Challenges

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.

Personalised Learning

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).

Drivers

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).

Challenges

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).

Differentiated Learning

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.

Conclusion

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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Research Project – The Start of the Journey

April 18, 2022 MrsAngell

Tags: differentiation EDR8801 EDU8114 online learning Personalization Research

Reflection on My Masters Journey

My interest in online personalised learning, which is self-paced and differentiated, started when I was an eLearning Facilitator. At the time, my daughter was in Year 8 and became extremely ill. She spent the next few years in and out of hospitals and attended numerous medical appointments as we attempted to get a diagnosis. During this time, she tried to keep up to date with her schooling. This led me to think about my own classroom and how I catered to students’ needs. At the time, I was reading “The differentiated classroom” (Tomlinson, 2014) and started investigating ways I could achieve a self-paced personalised course for my economics students. My first attempts were manageable if I only had one academic class. This led me to enrol in my Master of Education with a specialisation in Online and Distributed Learning.

Each of the units I have enrolled in contributed to my thinking about how I could improve how students proceed through the course work and how to manage 25 different learning styles, needs, and points of learning while working a full-time teaching load. Knowing that students must complete the same assessment simultaneously is a sticking point for self-paced differentiated learning, as students should be able to show mastery when they are ready rather than when the assessment calendar indicates they should be ready. During the height of the Covid pandemic, I studied Online Pedagogy in Practice (EDU8114). As part of my studies, I choose to investigate my ideas on Online Personalised Learning. My early research brought up an initial issue that there are many definitions of what personalised learning is. All the research seemed to agree on that personalised learning was about the student. After that, some research suggested it was a process (Keefe, 2007), some suggested it was an approach or pedagogy (Johnson et al., 2012), and other research described it as a philosophy (UNESCO International Bureau of Education, 2017). This challenged some of my earlier ideas, especially as The Horizon Reports (K-12 Edition) (Adams Becker et al., 2016) suggested that it might not be possible to implement personalised learning without overhauling the education system. This was due to the process being exceptionally labour intentive (Jacobs, 2016) or being pushed along by suppliers without an educational background wanting to promote their latest tools (Adams Becker et al., 2016). A report by UNESCO International Bureau of Education (2017) on personalised learning and my understanding of how learning management systems can be utilised in schools provided me with renewed belief that personalised learning is a possibility. Creating or implementing a framework that would make online personalised learning, which is self-paced and differentiated, a reality, would take time.

My current thinking about online personalised learning is that my research needs to investigate a concrete definition and possible frameworks that can work in a high school environment. From my initial research, there is limited empirical evidence of online personalised learning in high schools, and this is the area I want to investigate.

Initial Research

N	Reference	3 Points Relevant to Research Topic
1	Adams Becker et al., 2016	– Challenge to define and address – Need for evidence-based frameworks – Implications for policy, leadership or practice
2	Bernacki et al., 2021	– Definition to policy to implementation – Adaptive learning technologies – The challenge for personalised learning designers
3	Bingham, 2017	– Case Study – Organisational change – Implications for a model of personalised learning
4	Bishop et al., 2020	– Practices that characterise teaching in a personal learning environment – Teacher Roles in personalised learning environments – Role conflict
5	Childress & Benson, 2014	– Definition of personalised learning – Teachers as curators – Approaches to personalised learning
6	Consortium for School Networking, 2022	– Defining personalisation – Pandemic as a driver – Tips and recommendations
7	Dagger et al., 2005	– Adaptive course construction methodology – Addressing the personalised eLearning problem – Course composition for personalised eLearning
8	Feldstein & Hill, 2016	– Personalised learning as a teaching practice – External forces – Steps for a successful strategy
9	Jacobs, 2016	– Case study of blended, personalised learning – Self-paced learning – Typical staff and student day
10	Johnson et al., 2012	– Defining personal learning environments – Relevance for teaching, learning or creative inquiry – Personal learning environments in practice
11	Keefe, 2007	– History of personalisation – Personalisation programs – Defining personalisation
12	Lee, 2014	– Levels of personalisation – Essential features – Design principles
13	Lin et al., 2019	– Effects of class size face to face – Optimal class size for online self-paced courses at high school – Effects of class size for specific subjects in online classes
14	Misko, 2000	– How information is learnt – Effectiveness of self-paced learning techniques – Model for implementing self-paced learning programs
15	Pane et al., 2017	– Case studies of personalised learning – Obstacles of implementation – Implications and policy recommendations
16	Shemshack et al., 2021	– Components of personalised learning models – Tools and systems – Data and Learning analytics
17	Thalmann, 2014	– Categorisation of learners – Relationship between adaptation needs and learning materials – Adaptive learning criteria in eLearning
18	Tomlinson, 2014	– Key principles of a differentiated classroom – Instructional strategies that support differentiation – Tools to guide planning
19	UNESCO International Bureau of Education, 2017	– Conceptual framework – Strategies for personalised learning – Use of creativity, inquiry and challenge
20	West, 2012	– Defining personalised learning – Studies on effectiveness – Importance of teachers

References

Adams Becker, S., Freeman, A., Giesinger Hall, C., Cummins, M., & Yuhnke, B. (2016). NMC/CoSn horizon report: 2016 (K-12 ed.). The New Media Consortium.

Bernacki, M. L., Greene, M. J., & Lobczowski, N. G. (2021). A systematic review of research on personalized learning: Personalized by whom, to what, how, and for what purpose(s)? Educational Psychology Review, 33(4), 1675-1715. https://doi.org/10.1007/s10648-021-09615-8

Bingham, A. J. (2017). Personalized learning in high technology charter schools. Journal of Educational Change, 18(4), 521-549. https://doi.org/10.1007/s10833-017-9305-0

Bishop, P. A., Downes, J. M., Netcoh, S., Farber, K., DeMink-Carthew, J., Brown, T., & Mark, R. (2020). Teacher roles in personalized learning environments. The Elementary School Journal, 121(2), 311-336. https://doi.org/10.1086/711079

Childress, S., & Benson, S. (2014). Personalized learning for every student every day. The Phi Delta Kappan, 95(8), 33-38. https://doi.org/10.1177/003172171409500808

Consortium for School Networking. (2022). Driving K-12 innovation: 2022 hurdles + accelerators. Consortium for School Networking. Retrieved April 5, 2022 from https://cosn.org/k12innovation/hurdles-accelerators

Dagger, D., Wade, V., & Conlan, O. (2005) Personalisation for all: Making adaptive course composition easy. Journal of Educational Technology & Society, 8(3), 9-25. www.jstor.org/stable/jeductechsoci.8.3.9

Jacobs, J. (2016). High school of the future. Education Next, 16(3), 45-50. http://ezproxy.usq.edu.au/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=115746810&site=ehost-live

Johnson, L., Adams, S., & Cummins, M. (2012). NMC horizon report: 2012 (K-12 ed.). The New Media Consortium.

Keefe, J. W. (2007). What is personalization? The Phi Delta Kappan, 89(3), 217-223. https://doi.org/10.1177/003172170708900312

Lee, D. (2014). How to personalize learning in K-12 schools: Five essential design features. Educational Technology, 54(3), 12-17. www.jstor.org/stable/44430266

Lin, C.-H., Kwon, J., & Zhang, Y. (2019). Online self-paced high-school class size and student achievement. Educational Technology Research and Development, 67(2), 317-336. https://doi.org/10.1007/s11423-018-9614-x

Misko, J. (2000). Getting to grips with self-paced learning. National Centre for Vocational Education Research.

Thalmann, S. (2014). Adaptation criteria for the personalised delivery of learning materials: A multi-stage empirical investigation. Australasian Journal of Educational Technology, 30(1). https://doi.org/10.14742/ajet.235

Tomlinson, C. A. (2014). The differentiated classroom: Responding to the needs of all learners (2nd ed.). Association for Supervision & Curriculum Development.

UNESCO International Bureau of Education. (2017). Personalized learning (IBE/2017/OP/CD/04). https://unesdoc.unesco.org/ark:/48223/pf0000250057

West, D. M. (2012). Personalized learning. In Digital schools: How technology can transform education (pp. 20-32). Brookings Institution Press. http://ebookcentral.proquest.com/lib/usq/detail.action?docID=967462

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Research and Planning

January 30, 2022 MrsAngell

Tags: Case Management Collaboration Consultation EDU8328 Reflection

Case Management Collaboration

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Rationale for Consultation and Collaboration

January 11, 2022 MrsAngell

Tags: coaching Collaboration Consultation EDU8328 mentoring Support

Teachers are constantly aiming to improve their pedagogy, ultimately to improve student outcomes (Australian Institute for Teaching and School Leadership, 2012). In an attempt to improve student outcomes, schools have engaged in school-based consultation. School-based consultation focuses on assisting consultees (usually teachers) to improve knowledge and skills through the use of a consultant (an internal or external specialist) in order to be more effective with their clients (usually students) (Brown et al., 2011a; Erchul & Martens, 2010; Warren, 2018). Within education, it is necessary to develop a rationale for consultation to support educators to build their capacity to employ instructional and behavioural interventions that are effective and sustainable (Truscott et al., 2012). This rationale will discuss solution-focused consultee centred (SFCC) approaches to consultation within an independent K-12 co-educational college on the southside of Brisbane. Section one will analyse the context and need for consultation, along with current trends and initiatives that impact the environment and the nature of the triadic relationship within consultation. Section two will critically review the SFCC model of consultation and finally section three will justify the need for collaborative consultation, potential barriers for implementation and possible solutions to these barrier.

Section 1 Contextual Analysis

Contextual Description

The Year 9 Heath and Physical Education (HPE) subject coordinator (consultee) is an experienced teacher who is new to the college. The teacher works in the secondary school within the HPE and Science faculties. They had attended multiple professional learning (PL) sessions provided by the Microsoft Innovative Educator (MIE) Expert on staff. After reviewing the Year 9 HPE course in line with the Australian Curriculum, it was believed that the General Capabilities were not incorporated to the extent that they should be, especially the Information and Communication Technology (ICT) Capability (Australian Curriculum Assessment and Reporting Authority, 2021). As a result, the consultee approached the MIE Expert (consultant) about improving the safe partying unit. The focus of the improvement was to change the assessment piece from an essay to a multimedia response which would align with what students (client) might use outside of their school environment. The consultee had gathered many ideas from the various PL sessions they had attended on infographics, movie making, social media, digital inking, rotoscoping, web design, and problem-based learning. The main reason for the collaboration was that the HPE teacher had the subject area knowledge while the MIE Expert had the technological knowledge and skills. The nature of the triadic relationship was to provide the consultee with the knowledge, skills and confidence to determine the best course of action to incorporate ICT into the unit (Truscott et al., 2012).

Current Trends and Influences

Legislation, policies, and current trends in technology, teaching and learning impact the use of consultation in this context. As a Queensland school, teaching and learning programs must be prepared using the Australian Curriculum and the P-12 curriculum, assessment and reporting framework (CARF) (Education Queensland, 2020; Queensland Curriculum and Assessment Authority, 2021). This includes embedding general capabilities, cross-curricular priorities, and 21^st-century skills (Education Queensland, 2020). For this consultation, the need to include the ICT capability into health and wellbeing education is a priority to meet the legislative requirements. Likewise, the school’s policies outline that the Australian curriculum and the Queensland CARF influence its curriculum, incorporating student interest and abilities while preparing them to be socially capable and globally mindful citizens (John Paul College, 2021). Over the last ten years, many trends have influenced technology use in education. The main trends include personalisation, learners as creators and authentic learning experiences (Adams Becker et al., 2016; Consortium for School Networking, 2019, 2020, 2021; Dahlstrom et al., 2017; International Society for Technology in Education, 2021; Johnson et al., 2014, 2015). The impact of authentic assessment was a focus for this consultation as the consultee wanted to improve students’ higher-order thinking while offering choice, personalisation and real-world experience using technology (Dahlstrom et al., 2017; Koh, 2017; Koh et al., 2012). The other area of focus for the consultee was that students would construct their knowledge and create an artifact that was meaningful for themselves and their peers while ensuring learning was active and improved knowledge retention (Adams Becker et al., 2016; Consortium for School Networking, 2019).

Section 2 Theoretical Model for Integrated Service Delivery

Service Delivery Assumptions and Approach

The model for integrated service delivery being utilised in this scenario is SFCC. SFCC is a consultee centred, solution-based approach to consultation where the consultant acts more like a coach or facilitator to help the consultee achieve their goal (Brown et al., 2011c; Lloyd et al., 2016). It is an economical, time-sensitive, practical and rational technique to solving the problem a consultee has identified (Simmonds, 2019). In this case, the HPE teacher identified that the problem was in meeting the curriculum requirements for the Year 9 unit. Characterised as a short term, interactional intervention with the aim to improve a consultee’s knowledge, skills and ability to work with a client by utilising the strengths, abilities and successes the consultee already possesses (Bond et al., 2013; Lloyd et al., 2016). The consultant supports the consultee by encouraging them to explore the ideal future using the miracle question, scaling, and looking for exceptions tools (Lutz, 2014; Simmonds, 2019; Visser, 2013). The HPE teacher already possessed the knowledge to devise the assessment and required the consultant to improve their skills and confidence. The problem-solving process involves five main steps (Scott et al., 2015). The process begins with the consultee explaining the issue, including what has been tried so far to solve the problem and the consultant determining if there is a motivation for change by the consultee (Scott et al., 2015; Simmonds, 2019; Visser, 2013). This leads to goal setting and exploration of perspectives, exceptions and potential solutions (Brown et al., 2011c; Scott et al., 2015). Step four is an opportunity for the consultant to provide feedback, praise, and ideas about the next steps (Brown et al., 2011c; Scott et al., 2015). The last step in the process is for the consultee to evaluate their progress using a rating scale and identify their next step (Scott et al., 2015). The consultation continues until the consultee has achieved their goals (Brown et al., 2011c). For SFCC to be successful, it relies on several assumptions. As there is no one way to solve any problem, the central assumption is that the consultee is the expert and has the capacity and resources to solve the issue (Simmonds, 2019; Wheeler & Vinnicombe, 2011). SFCC also assumes that the client will be enriched due to the consultee advancing their skills, knowledge and abilities (Brown et al., 2011c).

Direct and Indirect Services

Within the SFCC model, the triadic relationship is evident as the consultant provides indirect services to the client through the consultee (Brown et al., 2011a). The needs of all stakeholders are met by improving the teacher’s skills, thus benefiting the students (Scott et al., 2015; Truscott et al., 2012). In this scenario, both direct and indirect services are provided; however, the focus is on indirect services. The indirect services include the PL sessions provided by the MIE Expert (consultant), which the consultee attended, along with the consultation sessions where the consultant and the subject coordinator collaborated to improve the unit assessment piece utilising the information they had learnt in the PL sessions (Scott et al., 2015). Followup sessions were also utilised to upskill and ensure the comfort of the consultee to present the assessment task to the Year 9 cohort. During the SFCC process, the consultee identified that they were unsure how to explicitly teach the assessment task’s technology component. As such, the consultant offered direct services to the students (client) by modelling the correct pedagogy and language in a co-teaching scenario and providing in-class support to troubleshoot where the consultee was missing the skill set (Brown et al., 2011a).

Section 3 Justification of Professional Practice

Professional Standards and Expectations

No teacher has the knowledge or skill to serve all students they teach (King-Sears et al., 2015). However, according to AITSL (2011), teachers have the most significant influence on student learning than any other program or policy. As a result, all Australian governments, universities, schools, and teachers are responsible for working together to support high-quality teaching (Australian Institute for Teaching and School Leadership, 2011). Collaborative consultation encourages and empowers all stakeholders to work together in an interactive process to utilise the diverse expertise to find and generate creative solutions to support students (King-Sears et al., 2015; Simmonds, 2019). The professional standards for teachers encourages collaborative consultation through the Professional Engagement domain, which looks at the interactions between colleagues, parents/carers and the community (Australian Institute for Teaching and School Leadership, 2011). In this scenario, both subject and technological expertise were pooled, benefiting students by bringing the expertise to them (Brown et al., 2011a; King-Sears et al., 2015). The benefits of this collaborative consultation include the new assessment piece being more successful than if only the consultee had developed it, leading to long term sustainability (King-Sears et al., 2015). All team members advocated for the client’s needs, leading to ownership of student learning (King-Sears et al., 2015; Scott et al., 2015). As there was a willingness by all stakeholders to participate, teacher confidence and skill improved, leading to the client’s overall success (King-Sears et al., 2015; Scott et al., 2015).

Barriers to Implementation

There are three main barriers to implementing collaborative consultation within SFCC in this scenario. The first is a lack of knowledge by the consultee (Brown et al., 2011b; Erchul & Martens, 2010). Essentially, the HPE teacher does not know what they do not know; the solution is for the MIE Expert to supply the missing knowledge (Brown et al., 2011b). Another is a lack of self-confidence; this can be resolved through the provision of support, assurance and, if required finding other colleagues who can support the consultee as required (Brown et al., 2011b; Erchul & Martens, 2010). The last barrier is the additional responsibilities for the consultee due to the consultation (Erchul & Martens, 2010). Teachers have limited time in their day to find time for lengthy collaborative consultation; with SFCC, the solution can be a 15-minute consultation which is followed up with an email conversation so the ideas can be fleshed out and the consultee has time to process the ideas (Erchul & Martens, 2010). Additionally, the consultant can assist by actively finding resources or offering peer coaching (Erchul & Martens, 2010).

Conclusion

If teachers are to continue to improve their skills, knowledge and student outcomes, they need to embrace school-based consultation. Within the context of the HPE teacher needing to improve a Year 9 unit to meet the national curriculum requirements, SFCC was the best model for integrated service delivery. The consultee knew what they needed to do and required the consultant’s expertise to improve their skills and confidence. Though there were three barriers to implementing collaborative consultation, the consultant offered solutions, including offering support, resourcing and peer coaching. By undertaking collaborative consultation, the HPE teacher has met the requirements of the professional standards for teachers.

References

Adams Becker, S., Freeman, A., Giesinger Hall, C., Cummins, M., & Yuhnke, B. (2016). NMC/CoSn horizon report: 2016 (K-12 ed.). The New Media Consortium.

Australian Curriculum Assessment and Reporting Authority. (2021). Information and communication technology (ICT) Capability: The Australian curriculum. Australian Curriculum Assessment and Reporting Authority. Retrieved 29th December from https://www.australiancurriculum.edu.au/f-10-curriculum/general-capabilities/information-and-communication-technology-ict-capability/

Australian Institute for Teaching and School Leadership. (2011). Australian professional standards for teachers. https://www.aitsl.edu.au/docs/default-source/national-policy-framework/australian-professional-standards-for-teachers.pdf

Australian Institute for Teaching and School Leadership. (2012). Australian charter for the professional learning of teachers and school leaders. https://www.aitsl.edu.au/docs/default-source/national-policy-framework/australian-charter-for-the-professional-learning-of-teachers-and-school-leaders.pdf?sfvrsn=6f7eff3c_6

Bond, C., Woods, K., Humphrey, N., Symes, W., & Green, L. (2013). Practitioner review: The effectiveness of solution focused brief therapy with children and families: A systematic and critical evaluation of the literature from 1990–2010. Journal of Child Psychology and Psychiatry, 54(7), 707-723.

Brown, D., Pryzwansky, W. B., & Schulte, A. C. (2011a). Introduction to consultation and collaboration. In D. Brown, W. B. Pryzwansky, & A. C. Schulte (Eds.), Psychological consultation and collaboration: Introduction to theory and practice (7th ed., pp. 1-15). Pearson Education Inc.

Brown, D., Pryzwansky, W. B., & Schulte, A. C. (2011b). Mental health consultation. In D. Brown, W. B. Pryzwansky, & A. C. Schulte (Eds.), Psychological consultation and collaboration: Introduction to theory and practice (7th ed., pp. 16-44). Pearson Education, Inc.

Brown, D., Pryzwansky, W. B., & Schulte, A. C. (2011c). Solution-focused consultee centered consultation and collaboration. In D. Brown, W. B. Pryzwansky, & A. C. Schulte (Eds.), Psychological consultation and collaboration: Introduction to theory and practice (7th ed., pp. 71-80). Pearson Education, Inc.

Consortium for School Networking. (2019). Driving K-12 innovation: 2019 accelerators. Consortium for School Networking. https://cosn.org/k12innovation/hurdles-accelerators

Consortium for School Networking. (2020). Driving K-12 2020 hurdles and accelerators. Consortium for School Networking.

Driving K-12 Innovation 2020 Hurdles and Accelerators

Consortium for School Networking. (2021). Driving K-12 2021 hurdles and accelerators. Consortium for School Networking.

Driving K-12 2021 Hurdles and Accelerators

Dahlstrom, E., Krueger, K., Freeman, A., Adams Becker, S., & Cummins, M. (2017). NMC/CoSn horizon report: 2017 (K-12 ed.). The New Media Consortium.

Education Queensland. (2020). P–12 curriculum, assessment and reporting framework. Department of Education Queensland. Retrieved 14th December from https://education.qld.gov.au/curriculum/stages-of-schooling/p-12

Erchul, W. P., & Martens, B. K. (2010). School consultation: Conceptual and empirical bases of practice (3rd ed.). Springer Science+Business Media.

International Society for Technology in Education. (2021). ISTE standards: Students. Retrieved 30th December from https://www.iste.org/standards/iste-standards-for-students

John Paul College. (2021). College handbook: Organisation. John Paul College. Retrieved 29th December from https://www.jpc.qld.edu.au/handbooks/organisation

Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2014). NMC horizon report: 2014 (K-12 ed.). The New Media Consortium.

Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2015). NMC horizon report: 2015 (K-12 ed.). The New Media Consortium.

King-Sears, M. E., Janney, R., & Snell, M. E. (2015). Collaborative teaming (Third edition. ed.). Paul H. Brookes Publishing Co.

Koh, K. H. (2017). Authentic assessment. In Oxford research encyclopedia of education. https://doi.org/https://doi.org/10.1093/acrefore/9780190264093.013.22

Koh, K. H., Tan, C., & Ng, P. T. (2012). Creating thinking schools through authentic assessment: The case in Singapore. Educational assessment, evaluation and accountability, 24(2), 135-149. https://doi.org/10.1007/s11092-011-9138-y

Lloyd, H. F., Macdonald, A., & Wilson, L. (2016). Solution-focused brief therapy. In Psychological therapies and people who have intellectual disabilities. The British Psychological Society.

Lutz, A. B. (2014). Learning solution-focused therapy: An illustrated guide. American Psychiatric Publishing, a division of American Psychiatric Association.

Queensland Curriculum and Assessment Authority. (2021). Prep-year 10: Queensland curriculum and assessment authority. Queensland Government. Retrieved 29th December from https://www.qcaa.qld.edu.au/p-10

Scott, J., Boylan, J. C., & Jungers, C. M. (2015). Practicum and internship: Textbook and resource guide for counselling and psychotherapy. Routledge. https://doi.org/10.4324/9781315754895

Simmonds, S. (2019). A critical review of teachers using solution-focused approaches supported by educational psychologists. Educational Psychology Research and Practice, 5(1), 1-8.

Truscott, S. D., Kreskey, D., Bolling, M., Psimas, L., Graybill, E., Albritton, K., & Schwartz, A. (2012). Creating consultee change: A theory-based approach to learning and behavioral change processes in school-based consultation. Consulting Psychology Journal: Practice and Research, 64(1), 63.

Visser, C. F. (2013). The origin of the solution-focused approach. International Journal of Solution-Focused Practices, 1(1), 10-17.

Warren, J. M. (2018). School consultation for student success: a cognitive-behavioral approach. Springer Publishing Company.

Wheeler, J., & Vinnicombe, G. (2011). Some assumptions of solution-focused practice. Context, 118(December), 40-42.

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Capacity Building for Professional Learning: A Collective Intelligence Construct

November 4, 2021 MrsAngell

Tags: Collective Intelligence EDU8721 Engagement Leadership Professional development Professional Learning Reflection

My workplace is an independent K-12 co-educational college grounded in traditional values. The current professional learning program is underpinned by a performance and development framework developed for the college based on the AITSL documents – Australian Teacher Performance and Development Framework (Australian Institute for Teaching and School Leadership, 2012b) and the Australian Charter for the Professional Learning of Teachers and School Leaders (Australian Institute for Teaching and School Leadership, 2012a). The program centres around a professional growth program and an appraisal process. I have successfully undertaken the AITSL HALT Certification, and I am a Lead Teacher in the secondary school. As an informal leader, I am a member of the Humanities Faculty and the Year 11 Academic Welfare Team. I am also a recognised Microsoft Innovative Educator Expert and on the management committee of the Queensland Economics Teachers’ Association. This paper will discuss the strengths and areas of improvement of the professional learning within my workplace in relation to Dr Joan Conway’s (2008) six forms of engagement, an interrogation into the Collective Intelligence of my organisation and how I, as an informal leader, can add to the professional learning culture of the college.

Strengths of Professional Learning

The professional learning process at my school has strengths in four forms of engagement. The first of these is recognising, valuing and engaging diversity. Our workplace values are centred on mutual respect, where accepting and celebrating diversity and individuality is key. Everyone is different and has something to contribute based on their professional experiences (Conway, 2008). Staff are encouraged to share their knowledge and expertise through student-free days, professional learning communities (PLCs), instructional rounds and whole staff sessions. Leadership within a teacher’s area of expertise is about passion, commitment and energy (Snell & Swanson, 2000). At the college, many staff have become experts in an area they are passionate about and regularly share this with colleagues in formal and informal professional learning settings. Within the secondary school this year, we have had teachers who are passionate specialists in technology, feedback, differentiation, Indigenous perspectives, teaching boys, metacognition, and cognitive verbs provide workshops to staff who want to learn more.

The second area of strength is forming relationships and seeking harmony of differences. The use of support networks and professional learning communities within the workplace allows learning from each other (Conway, 2008; Harper-Hill et al., 2020; Stoll & Seashore Louis, 2007). The sharing of achievements and concerns, and interactions between colleagues, lead to a culture of openness that improves teachers’ pedagogical practice, regardless of the stage of their career (DeJesus, 2021; Durksen et al., 2017; Harrison & Killion, 2007). Within our workplace, this is achieved both formally and informally. Each year PLCs are built around the areas of school improvement, and teachers participate in their chosen communities. As time is built into our Monday afternoon meeting program, teachers have the opportunity to share their understandings and build on the experience of their peers regularly. In the secondary school, all staff share a single open-plan office space; as a natural consequence, there are frequent ad hoc conversations around pedagogy and student achievement. I know that if there is an issue I am experiencing with a student, there will be up to seven other teachers of that student who may have strategies or ideas I can leverage.

The next area of strength is responding to the unexpected with resilience and persistence. By using the unexpected as an opportunity to learn more and improve practice, the interactions between individuals and the environment will create new meanings (Conway, 2008). It requires teaching staff to be patient and persistent. Within an effective professional learning culture, collaboration and supportive environments need to be encouraged as they promote teacher resilience as teachers persevere and even have the opportunity to thrive despite setbacks (Australian Institute for Teaching and School Leadership, 2021a; Durksen et al., 2017). At the college, staff can engage in instructional rounds where teachers open up their classrooms in the hope to build a culture of learning rather than criticism. These instructional rounds are a four-part process. It starts with an observing teacher identifying an area of their practice that requires improvement, participation in an instructional round where they view four colleagues, participate in a debrief and then reflect upon their instructional practices in light of those they observe. The idea is that it builds resilience into their own practice. Having participated as an observing teacher and an observed teacher, it relies on the observing teachers to believe that their pedagogy isn’t perfect and that they can learn from others in the process. The only area of improvement would be to give the observed teacher feedback from the observe so that further professional conversations can occur.

An area that my workplace does exceptionally well is planning and monitoring procedure. The use of data and the action research cycle to identify the next area for school improvement (Australian Institute for Teaching and School Leadership, 2020; Conway, 2008; Nixon, 2016; Tichnor-Wagner et al., 2017). Individual teachers regularly use plan-do-study-act cycles to improve their practice. Our Performance and Development Framework includes a future focus where teachers are encouraged to participate in action research to ensure they are exposed to new and emerging practices and the literature that goes with them. Data is central to all we do; we have access to a data wall for each year level in the secondary school. This data wall has every student in the year level ranked with their grade point average (GPA), NAPLAN results, predicted ATAR score. For my classes, I have created a spreadsheet with their previous subject results that impact the subject I am teaching them, their GPA, IEP/PLP details, and the learning support tier. The data wall, my spreadsheet and the anecdotal information I have collected inform my teaching practice to improve overall student achievement. Without data and a cycle of inquiry, it is tough to measure the impact on student achievement (Gordon, 2013; New South Wales Government, 2021b).

Areas of Professional Learning Improvement

While there are areas of strength, there are areas in which my school needs to improve. For school-wide improvement to occur, there needs to be mutual trust, shared purpose and respect and freedom for individual teachers to investigate and try new things (Conway, 2008; Conway, 2015; Conway & Abawi, 2013). According to Conway (2008), the third engagement area is fostering a culture of trust and hope. The trust that new ideas and skills are being learnt and refined by the teaching staff and the hope that it will work (Conway, 2008). According to Tschannen-Moran and Hoy (1998), trust is confidence, hope and reliance on the words and actions of colleagues are in the best interest of all involved. The degree of trust within the teaching staff and between teachers and the principal affects the success of school improvement (DeJesus, 2021; Tschannen-Moran & Hoy, 1998). The trust that the principal will act in the best interest of the teachers and the teaching staff believe they can rely on their colleagues’ integrity when difficulties arise (Tschannen-Moran & Hoy, 1998).

The second area of professional learning improvement is the sixth form of engagement, capturing a heightened consciousness of the creation of significant new meaning. Teachers must have the opportunity to experience the aha moment, express what has been learnt and the implications with colleagues (Conway & Andrews, 2016; Conway, 2008; DeJesus, 2021). It is also about capturing the collective intelligence and continuously creating and advancing ways of improving student achievement (Australian Institute for Teaching and School Leadership, 2020; Conway, 2008; Conway & Abawi, 2013; New South Wales Government, 2021a). Many great moments occur at the college; however, many go unnoticed, and as such, not all teachers get the opportunity to share their learning with colleagues. In most cases, those who are the most vocal about their epiphany get noticed and asked to share. It is not to say that their understandings are not valuable; it means that those who like to keep their accomplishments to themselves do not get the opportunity to discuss their discoveries and contribute to creating significant meaning for the organisation. It also potentially means that the proverbial wheel gets reinvented by other teachers over and over again. Capturing best practice is essential for the organisation to continue to grow collective intelligence (Conway, 2008).

Collective Intelligence

According to Conway (2008), collective intelligence within a school context is achieved when all six forms of engagement converge. A community of teachers develops the ability to create new knowledge, meaning, and pedagogy to improve student achievement (Conway, 2008; Meza et al., 2018). The ability to solve the problem is more efficient and effective when working collaboratively than as isolated professionals in our classrooms (Cornu, 2013; Secundo et al., 2016). Often the solution to improving student achievement lies within our colleagues. However, when working in isolation, we often do not realise that the answer lies in a conversation between colleagues about how best to work with a particular student or group of students. It is the conversation that creates the know-how (Conway, 2008; Cornu, 2013). It is hard not to improve student outcomes by harnessing the ‘wisdom of the crowd’ and the teachers’ years of experience at the college (Salminen, 2012).

Within our professional learning program, the professional learning communities (PLCs) allow collective intelligence to exist on a small scale. Within these PLCs, better decisions are made as all perspectives, ideas, and feedback are accepted (Friedrich et al., 2016; Wilson, 2018). While improving the teacher efficacy of those involved, it is not ‘captured’; the benefits are not as far-reaching as is believed as individuals are not inclined to share what they have learnt (Cornu, 2013; Eckert, 2018; Organisational Psychology Degrees, 2021). With efficacy comes increased motivation and self-direction; this, in turn, becomes infectious, and responsibility becomes shared for the solutions to be implemented (Wilson, 2018). As a result, the outcome is successful and sustainable (Cornu, 2013; Wilson, 2018).

For collective intelligence to thrive at the college, the organisation needs to move away from a hierarchical leadership structure to a more distributed style of leadership where teachers are leaders (Wilson, 2018). Interactions need to be fostered outside of the department walls so that authentic relationships can thrive (Conway, 2008; Wilson, 2018). These relationships would ensure that innovations could be implemented quickly as the power structures are not in play (Friedrich et al., 2016; Wilson, 2018). When communication becomes multi-directional, transparent, and inclusive, the community feels like a team; the six forms of engagement can be activated and sustained, leading to collective intelligence (Conway, 2008; Cornu, 2013; Friedrich et al., 2016; Wilson, 2018).

While the benefits of collective intelligence far outweigh any of the costs, there are some unavoidable issues. According to Noubel (2007), there is a point when collective intelligence becomes ineffective as it meets a natural limit. Once that limit is reached, the interactions become complex and create distractions rather than results (Klein, 2007; Noubel, 2007). With a large staff, we may have reached that natural limit. The secondary school staff currently share a single open-plan staffroom, while the primary school staff are in small staffrooms in each year level building. A strong argument for the success of collective intelligence is that the college staff need to be physically close in order to interact naturally and adjust their behaviour as the circumstances require (Klein, 2007; Noubel, 2007). Noubel (2007) says that as we continue to seek knowledge and technology improves, these limitations are hastily diminishing, provided the participants see personal growth and the value to both themselves and society. Other conditions that need to be met include creating an essential agreement and an information system connected to the internet that can capture the group’s collective memory (Noubel, 2007).

The ultimate aim in my workplace is to continue to improve NAPLAN and ATAR results; as such, a collective intelligence framework needs to be utilised. As action research and plan-do-study-act cycles are currently used, an adapted version of the collective intelligence framework proposed by Elia and Margherita (2018) alongside Conway’s (2008) six forms of engagement (discussed above) would need to be implemented for us to build capacity. Elia and Margherita (2018) have a two-part framework; part one is a problem resolution process that defines, analyses, investigates, brainstorms, prototypes and tests, before evaluating and implementing the solution (Elia & Margherita, 2018). Part two is the problem resolution matrix which informs the stakeholders of their responsibilities concerning the phases of the problem resolution process (Elia & Margherita, 2018).

Adding Value to the Professional Learning Culture

Since being made redundant from my eLearning position, I have questioned myself as an informal leader. As part of my transition back to the classroom full time, I successfully underwent the exemplary teacher process at my school, followed by the AITSL HALT certification as a lead teacher (Australian Institute for Teaching and School Leadership, 2021d). As part of this process, I was told I was not a teacher leader, and I didn’t have the support of some of my mentors. According to Tschannen-Moran (2014), trust between colleagues is based on perceived competency, commitment to students, and availability. As an informal leader, my first step to adding value to the professional learning culture is to take responsibility for my part in the trust breakdown (Tschannen-Moran, 2014). This includes building more trust with my mentor and mentee within our appraisal process and aspiring HALT program by being more available to support staff.

Crowther et al.’s (2009) teachers as leaders framework outlines the key areas to add value to the professional learning culture as an informal leader. When working with students and staff, I will strive for pedagogical excellence and demonstrate that teaching makes a difference and helps create a positive future and a better world for all students (Crowther et al., 2009). This involves nurturing a culture of success with my students and colleagues (Australian Institute for Teaching and School Leadership, 2021c; Conway, 2014). By continuing to reflect and use research to improve my classroom practice, I will also take a more active role within the professional learning communities to encourage collective intelligence with the aim to improve student outcomes (Bauman, 2015; Conway, 2008; Crowther et al., 2009; Meza et al., 2018). In particular, as an area of passion, I will continue to work with the cybersafety committee alongside all staff and students to find solutions to the issues the cyber world presents us with every year to ensure safety. By demonstrating the teachers as leaders framework, I can add value to the professional learning culture at my organisation.

Ultimately I will be the most effective and add value to the professional learning culture by being relevant, collaborative, reflective and student outcome-focused (Australian Institute for Teaching and School Leadership, 2021b). According to Bauman (2015), for sustained school success to be achieved, teacher leaders need to use autono-collaboration. The cyclical process of working collaboratively with colleagues and then taking the time to reflect on how it will work in my classroom and altering it to suit my students (Bauman, 2015). Thus aligning classroom practice with research and theory. The value will be seen as a curriculum specialist or instructional specialist as I open up my classroom and practice for feedback from colleagues (Australian Institute for Teaching and School Leadership, 2021b; Bauman, 2015; Harrison & Killion, 2007). I will also take the time to observe others and what they do in the classroom (Australian Institute for Teaching and School Leadership, 2021b; Harrison & Killion, 2007). I will also build a learning community between schools to help focus on best practice with economics teachers around the state (Australian Institute for Teaching and School Leadership, 2021b). Lastly, I will draw on my expertise as a Microsoft Innovative Educator Expert and provide professional learning opportunities on using technology and data in the classroom. By doing so, I hope to be a catalyst for change (Harrison & Killion, 2007).

Conclusion

Working in an independent co-educational college, the professional learning program aims to centre around professional growth in all staff. This paper has analysed the strengths and areas of improvement based on Dr Joan Conway’s six forms of engagement and discussed my workplace’s collective intelligence. The strengths of the professional learning program centre around recognising, valuing and engaging diversity; forming relationships and seeking harmony of differences; responding to the unexpected with resilience and persistence, and planning and monitoring procedures. The areas of professional learning improvement are fostering a culture of trust and hope and capturing a heightened consciousness for the creation of significant new meaning. While we are working towards collective intelligence, we still have a lot of ground to cover. In particular, we need to foster more conversations between colleagues about our classroom practices and take the time to try new things with our classes to see what works and what doesn’t. This paper finished with a discussion on how I can add to the professional learning culture. It is evident from the research and my practice that we have a long way to go if we will utilise collective intelligence to improve student outcomes.

References

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Mrs A's Blog

My Rambling Thoughts on Teaching and Learning

Online Personalised Learning In Secondary Schools

Online Learning

Drivers

Challenges

Personalised Learning

Drivers

Challenges

Defining Personalised Learning

Differentiated Learning

Differentiated Online Learning in Secondary School

Conclusion

References

Research Project – The Start of the Journey

Reflection on My Masters Journey

Initial Research

References

Research and Planning

Case Management Collaboration

Rationale for Consultation and Collaboration

Section 1 Contextual Analysis

Contextual Description

Current Trends and Influences

Section 2 Theoretical Model for Integrated Service Delivery

Service Delivery Assumptions and Approach

Direct and Indirect Services

Section 3 Justification of Professional Practice

Professional Standards and Expectations

Barriers to Implementation

Conclusion

References

Capacity Building for Professional Learning: A Collective Intelligence Construct

Strengths of Professional Learning

Areas of Professional Learning Improvement

Collective Intelligence

Adding Value to the Professional Learning Culture

Conclusion

References