There is a crisis engulfing the social sciences. What was thought to be known about psychology—based on published results and research—is being called into question by new findings and the efforts of individual groups like the Reproducibility Project. What we know is under question and so is how we come to know. Long institutionalized practices of scientific inquiry in the social sciences are being actively questioned, proposals put forth for needed reforms.
While the fields of academia burn with this discussion, education results have remained largely untouched. But education is not immune to problems endemic in fields like psychology and medicine. In fact, there’s a strong case that the problems emerging in other fields are even worse in educational research. External or internal critical scrutiny has been lacking. A recent review of the top 100 education journals found that only 0.13% of published articles were replication studies. Education waits for its own crusading Brian Nosek to disrupt the canon of findings. Winter is coming.
This should not be breaking news. Education research has long been criticized for its inability to generate a reliable and impactful evidence base. It has been derided for problematic statistical and methodological practices that hinder knowledge accumulation and encourage the adoption of unproven interventions. For its failure to communicate the uncertainty and relevance associated with research findings, like Value-Added Measures for teachers, in ways that practitioners can understand. And for struggling to impact educational habits (at least in the US) and how we develop, buy, and learn from (see Mike Petrilli’s summation) the best practices and tools.
Unfortunately, decades of withering criticism have done little to change the methods and incentives of educational research in ways necessary to improve the reliability and usefulness of findings. The research community appears to be in no rush to alter its well-trodden path—even if the path is one of continued irrelevance. Something must change if educational research is to meaningfully impact teaching and learning. Yet history suggests the impetus for this change is unlikely to originate from within academia.
Can edtech improve the quality and usefulness of educational research? We may be biased (as colleagues at a large and scrutinized edtech company), but we aren’t naïve. We know it might sound farcical to suggest technology companies may play a critical role in improving the quality of education research, given almost weekly revelations about corporations engaging in concerted efforts to distort and shape research results to fit their interests. It’s shocking to read efforts to warp public perception on the effects of sugar on heart disease or the effectiveness of antidepressants. It would be foolish not to view research conducted or paid for by corporations with a healthy degree of skepticism.
Yet we believe there are signs of promise. The last few years has seen a movement of companies seeking to research and report on the efficacy of educational products. The movement benefited from the leadership of the Office of Education Technology, the Gates Foundation, Learning Assembly, Digital Promise and countless others. Our own company has been on this road since 2013. (It’s not been easy!)
These efforts represent opportunities to foment long-needed improvements in the practice of education research. A chance to redress education research’s most glaring weakness: its historical inability to appreciably impact the everyday activities of learning and teaching.
Incentives for edtech companies to adopt better research practices already exist and there is early evidence of openness to change. Edtech companies possess a number of crucial advantages when it comes to conducting the types of research education desperately needs, including:
- access to growing troves of digital learning data;
- close partnerships with institutions, faculty, and students;
- the resources necessary to conduct large and representative intervention studies;
- in-house expertise in the diverse specialties (e.g., computer scientists, statisticians, research methodologists, educational psychologists, UX researchers, instructional designers, ed policy experts, etc.) that must increasingly collaborate to carry out more informative research;
- a research audience consisting primarily of educators, students, and other non-specialists
The real worry with edtech companies’ nascent efforts to conduct efficacy research is not that they will fail to conduct research with the same quality and objectivity typical of most educational research, but that they will fall into the same traps that currently plague such efforts. Rather than looking for what would be best for teachers and learners, entrepreneurs may focus on the wrong measures (p-values, for instance) that obfuscate people rather than enlighten them.
If this growing edtech movement repeats the follies of the current paradigm of educational research, it will fail to seize the moment to adopt reforms that can significantly aid our efforts to understand how best to help people teach and learn. And we will miss an important opportunity to enact systemic changes in research practice across the edtech industry with the hope that academia follows suit.
Our goal over the next three articles is to hold a mirror up, highlighting several crucial shortcomings of educational research. These institutionalized practices significantly limit its impact and informativeness.
We argue that edtech is uniquely incentivized and positioned to realize long-needed research improvements through its efficacy efforts.
Independent education research is a critical part of the learning world, but it needs improvement. It needs a new role model, its own George Washington Carver, a figure willing to test theories in the field, learn from them, and then to communicate them to back to practitioners. In particular, we will be focusing on three key ideas:
Why ‘What Works’ Doesn't: Education research needs to move beyond simply evaluating whether or not an effect exists; that is, whether an educational intervention ‘works’. The ubiquitous use of null hypothesis significance testing in educational research is an epistemic dead end. Instead, education researchers need to adopt more creative and flexible methods of data analysis, focus on identifying and explaining important variations hidden under mean scores, and devote themselves to developing robust theories capable of generating testable predictions that are refined and improved over time.
Desperately Seeking Relevance: Education researchers are rarely expected to interpret the practical significance of their findings or report results in ways that are understandable to non-specialists making decisions based on their work. Although there has been progress in encouraging researchers to report standardized mean differences and correlation coefficients (i.e., effect sizes), this is not enough. In addition, researchers need to clearly communicate the importance of study findings within the context of alternative options and in relation to concrete benchmarks, openly acknowledge uncertainty and variation in their results, and refuse to be content measuring misleading proxies for what really matters.
Embracing the Milieu: For research to meaningfully impact teaching and learning, it will need to expand beyond an emphasis on controlled intervention studies and prioritize the messy, real-life conditions facing teachers and students. More energy must be devoted to the creative and problem-solving work of translating research into useful and practical tools for practitioners, an intermediary function explicitly focused on inventing, exploring, and implementing research-based solutions that are responsive the needs and constraints of everyday teaching.
Ultimately education research is about more than just publication. It’s about improving the lives of students and teachers. We don’t claim to have the complete answers but, as we expand these key principles over coming weeks, we want to offer steps edtech companies can take to improve the quality and value of educational research. These are things we’ve learned and things we are still learning.
Nathan Martin is a manager for efficacy and innovation at Pearson in the Office of the Chief Education Advisor. Jay Lynch is Senior Academic Research Consultant for Course Design, Development, and Academic Research (CDDAR) at Pearson.