We know that evidence and data help us make better decisions. But when it comes to EdTech, how can that evidence be flexible enough to meet the demands of innovation?
The importance of evidence in educational technology (EdTech) is crucial. Incorporating evidence ensures that the adoption of new technologies in education is grounded in reliable data sets rather than just trends, novelty, or opinion. When we use evidence to make decisions and, more importantly, craft visions for learning organizations, the credibility of EdTech initiatives has a foundation to build upon. Evidence in EdTech, like other aspects of education, allows for informed decision-making, improving learning outcomes (academic and otherwise), and ensuring resources are used efficiently to support goals for learners.
But it’s not that simple. EdTech has the potential to really change education as we know it. Given that, we have to think twice about how we create, model, and use evidence.
Evidence-based practices in EdTech can lead to everything from continuous improvement to personalized educational experiences. The evidence in EdTech serves as a driver behind meaningful progress in education.
The importance of a continuum for using evidence in educational technology cannot be understated.
Thinking about how we have seen technologies enter, exit, impact, change, bolster, and flat-out change education over the past twenty years is daunting at best.
But using the existing knowledge base around meaningful data, systems change, evidence, action research, empirical research, rapid cycle research, and more, we can conceptualize a scale that is both hierarchical and integrative. This type of scale can allow us a comprehensive view of evidence at various stages of application and innovation in education.
The point of such a scale would be to identify what type of evidence is needed for what type of decision, challenge, opportunity, situation, story, etc.
See what you think of this first draft.
This is the foundational level, where evidence is primarily used for understanding the current state of educational technology and its impact. At this stage, evidence informs educators, policymakers, and stakeholders about what exists, what works, and what doesn’t. It’s a stage of gathering and interpreting data to build a knowledge base. This is broad, integrative of different types of research (mixed methods, if you will), and inclusive of qualitative data that might be more narrative in nature.
Evidence at this stage is used to develop and refine educational technologies. This includes piloting new approaches, using evidence to inform the design and implementation of technology-based interventions, and iteratively improving these interventions based on ongoing data collection and analysis. While this can be used in educational settings, it is used as a feedback loop to improve products, scale impact, deliver quality packages, and design relevant and necessary supports (like training).
At this level, evidence is utilized to affirm or validate the effectiveness and efficiency of educational technologies. Rigorous methodologies, such as randomized controlled trials or longitudinal studies, are employed to provide strong evidence of impact. This stage helps in solidifying the use of certain technologies in education by proving their worth. Validation studies like Randomized Control Trials and implementation studies with an expected use case would fit in here.
In this stage, evidence is used to fuel innovation. This involves looking beyond what is known and established, using evidence to identify gaps, unmet needs, or novel approaches. It’s about challenging the status quo and experimenting with new ideas that have the potential to transform educational technology. This can be observational, market-based, rapid cycle, or other types of research that dive into what isn’t yet in use to inform what could work, what could scale, and what could afford the field a new opportunity to deliver to learners.
The pinnacle of the continuum, where evidence is used to break barriers and redefine norms. At this stage, evidence leads to groundbreaking changes in how technology is integrated into education. It could involve disruptive innovations or paradigm shifts that redefine educational practices and outcomes. This is the implementation of new ideas at scale. Tools that fundamentally shift our approaches and deliver multiple outcomes. This is multifaceted research that is long-term yet rapid, rigorous yet multifaceted and delivers data and the study of change alongside that data.
I’ve thought about this for some time, but this is my first pass at creating something that gives somewhat of a multi-faceted discussion of evidence in EdTech. The challenge is how multi-faceted EdTech is. Given that educational technologies span every content area, every grade, and multiple stakeholders (ranging from students to teachers, developers, policymakers, venture capital, and more). My hope is that the broad strokes of a framework can support the refinement in practice because we have to start somewhere.
Would love to know what you think.