It is no secret that educational institutions generate huge amounts of data around learning and outcomes. It is also no secret that many schools feel overwhelmed by the volume of data, and feel ill-equipped with the time and or tools to properly analyse the data and leverage it in any useful or meaningful way. If we refer to NMC’s 2014 K12 Horizon Report, we are currently moving through BYOD and Cloud Computing and it certainly appears evident in the industry that many schools have really embraced this development in technology. The next frontier, according to the same NMC report, is a look towards Learning Analytics. So what exactly are Learning Analytics, how can they best be leveraged to positively impact teaching and learning, and how can we avoid some of the common speed bumps along the way? By no means do we have all the answers, but we start the conversation below to head towards effectively utilising 'big data' in education.
What are Learning Analytics?
In a broad sense, learning analytics is the educational application of the science of analysing activities and trends, and leveraging the information to better understand causal relationships and predict behaviours or outcomes. The original commercial intent has been largely linked to marketing, and focused on understanding consumer behaviours through analysis of vast reserves of information collected over time.
When applied in education the focus shifts to the student and the way that they learn. When executed well, learning analytics can help to identify at-risk students, measure and assess the effectiveness of pedagogy and policy, and ultimately assist in creating a high quality and personalised learning journey for the student. In essence, learning analytics can help a school to unpack the many variables that impact student learning. For example, is a new classroom strategy resulting in the desired outcomes? How are specific cohorts of students progressing? Is there a relationship between an individual student’s co-curricular engagement and her academic achievement? Learning analytics provides data-supported evidence that can inform everyday decision-making to improve how a school can best support its students. For these reasons many make the link between learning analytics and adaptive learning, with improved curriculum and instructional design driving organisational change.
Thus schools now operate in a world full of bench-marking, whether it is NAPLAN or any number of external measures. What is not always so clear is how best to easily harness and make sense of all of the data so that it can help to inform policy and ultimately achieve what we are all here for – improved student outcomes.
Why use learning analytics
Learning analytics goes well beyond formal reporting or collation of results, enabling a deeper understanding of your students by harnessing longitudinal data and cross-referencing with multitude of different data-sets both internal and external to the school.
Have you ever wrestled with how exactly to measure the value-add of your school beyond delivering the prescribed curriculum? What about understanding how your pedagogical framework is driving improvement in outcomes, or greater engagement? Learning analytics can help to de-mystify some of these questions, providing quantitative data to measure and assess the success of various programs in your school.
Using various data-sets, and supported by the right tools, it becomes easier to cross-reference aspects such as how students who learn a language compare against overall English scores. Or to look at the academic progression of students who are involved in school sport. Predicting and then evaluating actual performance against widely-recognised bench-marking also becomes more simple, and an activity that a school can undertake of their own accord where once a consultant was almost always required. Learning analytics has been crucial to building better pedagogies based on insights into student interactions with such things as new curriculum content, online learning and new technology platforms. Learning Analytics helps leaders measure whether changes have been effective and should be sustained.
One common fear associated with learning analytics in schools is the concern it will become a tool to put teachers under the microscope and a way of attacking their performance. In actual fact, the positive information and analysis associated with learning analytics far outweighs any of these concerns, most of which go unfounded. Teachers and school leadership alike genuinely want to find better ways to support their students on their learning journeys – and all the better if the pedagogy or policy is informed by real data, rather than guesswork. None of this is to say that a professional educator’s eye is still not a key piece of the puzzle, it is in fact imperative as anyone will tell: data itself does not provide the answers, but points savvy educators toward sharper questions and deeper understanding. Thus empowered with new hypotheses, educators and leaders alike can scrutinise data and apply their professional judgments to further enrich the data, and encourage a culture of continuous improvement across the board.
Students are also beginning to experience the benefits of learning analytics as they engage with mobile and online platforms that track data to create responsive, personalised learning experiences with adaptive learning and assessment. This can then help students to monitor their own progress and take ownership for their learning, which, according to Hattie and others, has significant positive effect on achievement.
The hurdles along the way
We have already touched briefly on some of the fears associated with learning analytics, and whilst largely unfounded there is always the risk of data being used to scrutinise teachers instead of teaching practice. By keeping learning analytics as exactly that, and not allowing it to become ‘people’ analytics, teachers, leaders and students will all stand to benefit.
Most other ‘fears’, or resistance to change, traces back to two central points that come up time and again in our research. The first is ease of use. With the mass of data at our fingertips already, generally only a very small piece of it is being used. This is largely due to inadequate ways of representing and manipulating the data. Here is the first place that technology can help to support and improve existing analytical processes.
The second point that regularly impacts adoption of change or technology is the user-perceived value-add, or the ‘what’s in it for me’ factor. Teaching is widely recognised as one of the most time-poor professions, with greater demands placed on our teachers almost daily. For this reason, in order to have a process adopted or embraced successfully, it must clearly demonstrate added value both in saving the teacher time, and hopefully also improving student outcomes which is something everyone can get excited about. When the tools are user-friendly, teachers simply need time, support, and a little encouragement to embrace learning analytics and to deploy them in an effective and sustainable way.
With these two points in mind, a school can really start to tap into transformational change when a learning analytics tool is used to support and simplify the process of analysing and understanding the data, which then informs policy and shapes instructional design.
Looking forward with technology
In recent years, bolstered by the internet and web-based platforms, we have seen significant developments in the range of learning analytics tools available, changing the way school leaders think about data. These tools have made achievement data more actionable and have provided a more holistic portfolio of students’ performance.
While test scores are an important measure of student progress and allow school leaders to better understand achievement gaps, they only capture a limited component of a student’s academic strengths and weaknesses. Similarly, an issue that plagues many schools, eager to reap the benefits of learning analytics, is that the critical questions that school leaders want answered are rarely captured in a single data set. Data on related issues such as student performance, behaviour and attendance, and extra-curricular activity are typically housed in multiple systems that have limited functionality and lack integration.
In 2015, Edumate AMS launches a new learning analytics tool for reporting on any aspect of information within the database, simply and easily, designed to supplement existing longitudinal and formal reporting modules. Significant work has been done on charting student results to measure school improvement, followed by simple-to-use reporting tools around the entire school ecosystem to provide teachers and leaders with deeper insights into their students’ personal learning journeys. Edumate’s analytics tool makes this information actionable to school leaders and teachers by creating data-rich student profiles, highlighting academic success and readiness for the next round of rich learning. Edumate also supports continuous reporting and progressive student feedback, elevating the student voice and empowering the student to track progress and take responsibility for their own development.
It’s also important not to confuse learning analytics with institutional analytics. While learning analytics is the use of data to inform and improve instruction and learning, institutional analytics uses data to make better decisions about how to improve operations. When it comes to data analytic tools, many will generally support one or the other. Edumate recognises the need for both forms of insight and helps to improve instructional outcomes by identifying more effective pedagogies, while isolating efficiencies for delivery and administration.
By developing a completely integrated, simple-to-use K12 learning analytics tool, Edumate continues to strive to support school leaders and teachers in their ultimate mission – improving student outcomes and engagement. Longitudinally focused, Edumate helps foster continuous improvement for teachers today, and supports and drives systemic change to educate the leaders of tomorrow.
The world of learning analytics is still evolving and as a sector we have only explored the surface. There are still a great number of opportunities to further realise the potential of data analytics in education, including greater levels of integration across a variety of systems and actionable data for parents. Learning analytics will remain a prominent storyline in education technology, particularly as we see a focus on measuring value-add and the evaluation of many evolving pedagogical frameworks across our schools. The sector should be excited about the current developments for high-quality data tools that will help school leaders, teachers and administrators answer pressing and challenging questions – here at Edumate, we certainly are.
For more information about Hobsons’ Academic Management System, Edumate AMS, please contact Hannah at firstname.lastname@example.org.