The rich use cases of technology in the classroom and education are well-documented. Technology can be used to enable personalized learning, save educators time, and equip students with the digital literacy skills that they need to succeed in 21st-century careers.
However, students, parents, teachers, and school leaders must be aware of when, where, and how specific technologies are best suited to specific learning goals and outcomes. Missteps by parents, teachers, and school leaders in the digital tools students are using can widen existing inequities among our nation’s youth.
In 2009, McKinsey estimated that education gaps between white students and black and Hispanic students led to productivity losses of between $300 billion and $500 billion every year, while income disparities led to even larger losses – between $400 billion over $650 billion every year. Had we closed these gaps over the last decade, US GDP would have been between $700 billion and $1.2 trillion higher today.
Below we provide an outline of how we can use technology to prevent existing inequities from worsening and even close the digital gap via viable, effective equity initiatives.
Using Technology to Support Equity Initiatives
Technology solutions in education should only be deployed once we have a thorough understanding of how technology is being used today, what outcomes we are seeing, and what gaps are emerging. From there, we can work on solutions aimed at improving student outcomes across the board and outcomes, especially for at-risk and marginalized students.
Let’s discuss data and metrics to consider as you seek to improve equity and student outcomes.
A good place to start is to gather data on device type and device usage across different students for different subjects. Usage data can include time spent on assignments, websites visited, and resources accessed. Cross-referencing this data with data on the overall school population will provide insights into which students have or do not have certain devices and which students are seeing improved vs. worsening results that can be linked to device usage.
Local geography matters to student success rates. Data on student performance, device access, and device usage – as gathered and tabulated in the step above – can be used to flag students who may fall in a high-risk category based on race, ethnicity, home address, or parents’ occupation. Personalized learning plans, assignments, and teacher focus can then be provided as needed.
Student SES Data
Likewise, socioeconomic, demographic, and financial data – from student enrollment forms and self-reported surveys – can be used to identify students who face access issues or other financial hurdles when it comes to using and leveraging different tech tools that are – or should be – at their disposal. School- and district-level leaders can then take proactive steps to close these gaps and deliver connectivity and resources to the students who need them most.
Opportunities for Personalized Learning
Creating personalized learning plans based on students’ usage patterns is an important step to take for any education-focused tech initiative. Many apps provide usage, engagement, and screen time metrics to parents and authorized school personnel. This data can be used in conjunction with performance metrics and test results to preempt downward patterns in outcomes as soon as a given student shows signs of being at risk of falling behind.
When used correctly, technology can become a great equalizer. Poorly performing students and schools – when given the right tools and guidance – can quickly catch up to their better-performing peers, and students and schools without access can make proportionately greater improvements in outcomes per hour spent with the right tools than students and schools that are already performing well. Device usage data can inform teachers and other decision-makers about when, where, how, and with whom more technology will be beneficial, thereby helping to improve the outcomes of the most disadvantaged and poorly performing students in a school or district.
Putting it All Together
We’ve covered a lot of ground. What are the key takeaways here?
Firstly, and most importantly, school leaders must recognize that technology must be used correctly to be effective. You cannot simply add technology as a missing ingredient to your instructional design. Tech choices and lesson plans must be aligned with learning goals, and they must be based on the curriculum being taught.
Secondly, tech choices must also match the local environment and context, and they must consider where specific users, schools, and districts are along the learning and achievement spectrums. Using one set of technologies at a high-performance school will lead to drastically different outcomes from using the same set of tools in a low-performance district.
What the points above suggest is that a comprehensive, data-driven approach is required to deliver real learning gains by using technology inside and outside the classroom.
Making the Right Tech Choices
There are many examples of how tech rollouts in the education space can go wrong. Consider the following:
- Too much data can overwhelm the user. Unless you can clean and prioritize your data, there is no need to gather data on every measurable metric.
- Getting data collection right requires discipline and a long-term approach to iteratively making incremental improvements to how things are done.
- Data interpretation can be time-consuming and may require advanced technical and analytical skills.
In addition to the above, you must ensure that the technologies you choose are easily accessible to all teachers and learners, and that data collection is consistent and methodical. Student data must also be adequately safeguarded and secured per local laws.
Students, parents, teachers, and schools must understand the different technologies used for learning and how such use impacts student outcomes. Time spent on assignments versus entertainment, hours logged in to specific apps, device pickups, test scores, and similar usage data can be collected to generate reports on what’s going well for students and where interventions may be needed.
Students who may be falling behind can only be helped if they are identified and supplied with personalized learning support to the extent possible.
To learn more about how technology can help your students, your school, and your district, and how data can help you create and roll out a student-centric program aimed at addressing the most critical learning obstacles your students face, speak with a Kajeet Solutions Architect today. Visit us at https://www.kajeet.net/contact-us/ for a confidential consultation.