Introduction
Big Data is everywhere in our daily lives whether we know it or not. Every movie we stream, course we plot and purchase we make is recorded. Giving up that data opens the door to amazing modern conveniences but also erodes our privacy little by little. There is even a new trend of coffee shops for college students where the coffee is free as long as you give up your data. As we try to navigate the delicate balance between modern convenience and privacy we begin to question the true costs of those conveniences. As “big data” makes its way into public education we must carefully assess whether the benefits the costs to student privacy. Big data in education is not new. For years we have collected tons of student data through standardized tests and surveys which has been used to improve instruction and conditions in schools. However, with more recent advances in technology, it is possible to take student data collection to a new level. This new level of data collection opens the door for adaptive student testing that gives a more holistic view of students abilities as well as the dream of personalized programs for students. These big ideas sound amazing but there is a price. Nothing is truly free. In this blog, I will take a look at the advantages of “big data” in education with an eye toward the ethical issues that new technologies bring.
New technologies and online curriculum have allowed teachers to look at data in a new way. For example, Khan Academy which started as a site for video lectures on math concepts now offers full courses in mathematics as well as science, history, economics, and more. The math lessons provide a teacher or “coach” with data on all problems a student attempted, where they sought help, what their answers were, and how long they spent on each problem. With so much data being collected on millions of users the analysis of the data could be a powerful tool to shape education as we know it. As the study of educational data has progressed over the past few years there are two distinct fields that have emerged.
The first is educational data mining (EDM). EDM is focused on the technical challenges of creating automated systems that diagnose trends and support learning. The second field is learning analytics. This field focuses more on using the data to understand how people learn to better inform teachers and learners (Dishon 2017).
Technology that exists today allows us as educators to collect so much more information about our students than ever before. In the past student scores on state tests and some other assessments were part of their permanent file that followed them throughout their educational experience. Imagine that today we could actually collect data on almost everything a student does on a daily basis and look at when the student is making progress, when they are not and analyze what trends there are in their learning to specifically tailor a program to that student's unique needs.
The Benefits:
Proponents of using big data in education point to four ways that big data can transform education as we know it. The first is personalization. Computer technology allows an educator to more precisely diagnose a students achievement and target new materials both toward that students need and interest. In this process, computers can be used to analyze how students answer and based on those answers assign the appropriate new material that the student either wants or needs. Computers can also use data from millions of users to predict the best path to success based on a student's current level and interest.
The second way that big data can enhance the educational experience of students is by improving student results. The analysis of data allows for frequent formative assessment and immediate feedback to students in a way similar to a private tutor. This consistent personalized feedback can improve the learning of students and help to find a path to success for all students. Cope and Kalantzis (2015) point out “Big data may be able to help us address education’s ‘wicked problems’: performance gaps, which produce cycles of underachievement; cultural-racial differences in educational experience and outcome; or the role of education in reproducing or breaking cycles of poverty”.
Another way that big data can benefit students is by allowing for real-time feedback to change the learning experience. In the past, most data that was collected from students was collected as assessments after learning had taken place. These assessments were used to judge the quality and amount of learning. Big data allows educators to see trends in student behavior and interests in real time and adjust accordingly. Data analysis like this in real time also allows students to receive immediate feedback that can enhance their learning process rather than just measure what they have learned. Software can go as far as to measure every keystroke a student makes to analyze what their learning process.
A fourth argument that proponents of big data in schools make more accessible to more students and improve graduation rates. The belief is that if students are provided with multiple varied experiences and multiple ways to show what they have learned more students will stick with school and graduate.
The drawbacks:
The first drawback of big data in education that comes to mind is privacy. Because of the rapid progress made in educational technology, there are many unanswered questions. As Colin Lynch (2017) points out “Big data requires deep and constant monitoring of students, classes, and instructors. Who consents to such monitoring, and how will student or instructor privacy be preserved? Data also has immense commercial value. Who owns it? And who is permitted to profit from its use?” We have very strict laws (FERPA) in place to protect students rights and the data we collect about them. The problem, however, is that with the rapid changes in educational technologies that have been adopted by schools we are collecting significantly more data every day and that data is being stored and sometimes analyzed by third-party sites. The problem is that the law was written for a time when student data was literally a physical collection of papers in a folder that followed the student. Now, however, data is collected and stored by a variety of programs and third parties and the laws about privacy have not kept up with the change. Teachers and school administrators are now in charge of investigating the services they use and protecting students to the best of their abilities in the choices that they make. The problem is that change is coming fast and capitalizing on the benefits of new technology can be so exciting that issues of privacy sometimes fall by the wayside. Parents are also wary of the risk to students privacy. One of the first examples of this was the in Bloom Data Warehouse. This project funded by the Gates Foundation ran into heavy resistance from a wide range of parent groups who feared that their children's educational destinies would be pre-determined by “big data”. There was also pushback from teacher groups who feared that the data would be used to evaluate teacher performance.
The second issue of the use of big data in schools is the dehumanization of our educational system. It is terrifying to think that someday a students educational experience may come down to plugging into a personalized education plan that is all delivered through a computer screen. By individualizing the experience do we lose the social aspects of education that are so important? Do we sacrifice the humanity of the educational experience in favor of a more efficient content delivery system?
The third major issue to big data is the assessment of what is really effective and what is not. Because most innovations in educational technology come from third-party entities with an eye on cracking into the lucrative field of educational tech there are some concerns about how effective programs are. Lynch(2017) warns “the presence of large, rich datasets may encourage us to fall into the information technology fallacy by assuming more, and more perfect information than we really have.” In effect, we could end up making poor decisions on educational policy based on faulty data.
Conclusion:
The advantages to big data in schools are pretty hard to ignore. The thought that someday students could have a personalized educational program that addresses their specific needs and interests seems almost too good to be true. Maybe it is. But, we must as educators look at the facts. Big Data is everywhere. We live in a world that is rapidly changing and the educational practices that we have used for a hundred years may not be effective for today's students. The use of data in school allows us to focus our work specifically and efficiently to meet the needs of our students. Having said that, we also have to be smart about what we allow and how we use technology with our students. Educators must take the time to investigate resources and protect the privacy of our students as much as possible. “And while we can enshrine some protections in law, those laws must be backed by good standards of practice for institutions and system developers that guide the design of contracts and the development of secure auditable systems so that we can offer perspective guarantees.” Because education is a compulsory public endeavor it is the job of educators and educational communities to ensure safety so that we can harness the power of big data to make the educational process as good as it can be for our students.
Resources For Data in Schools:
Summit Learning - A for-profit online learning platform that promises “personalized teaching and learning” concentrating on students personal needs and abilities.
Khan Academy - A free online education for all. Offers a wide range of courses with practice and individual feedback.
Mathia - A math program from Carnegie Learning that delivers differentiated support to students
to meet their needs.
Google Apps -The suite of Google Apps for education offers a variety of ways to collect and use data about student performance.
ASSISTments - A free online math program from Worcester Polytechnic Institute that provides differentiated math tasks with immediate feedback for students, and is endorsed by Common Sense Media.
Sources:
Chaffel C. (2018) No Cash Needed At This Cafe. Students Pay The Tab With Their Personal Data. NPR Retrieved From: https://www.npr.org/sections/thesalt/2018/09/29/643386327/no-cash-needed-at-this-cafe-students-pay-the-tab-with-their-personal-data
Cope B. and Kalantzis M. (2015) Sources of Evidence-of-Learning: Learning and assessment in the era of big data, Open Review of Educational Research, 2(1), pp. 194-217, Retrieved from: https://www.tandfonline.com/doi/full/10.1080/23265507.2015.1074869
Cope B. and Kalantzis M. (2016) Big Data Comes to School: Implications for Learning, Assessment, and Research. AERA Open 2(2) pp. 1-19 Retrieved from: https://journals-sagepub-com.prxy4.ursus.maine.edu/doi/pdf/10.1177/2332858416641907
Dishon G. (2017) New data, old tension: Big data, personalized learning, and the challenges of progressive education. Theory and Research in Education 15(3) pp. 272-289 Retrieved from: https://journals-sagepub-com.prxy4.ursus.maine.edu/doi/pdf/10.1177/1477878517735233
Hartong S. (2016) Between assessments, digital technologies and big data: The growing influence of hidden data mediators in education. European Educational Research Journal 15(5) pp. 523-536 Retrieved from: https://journals-sagepub-com.prxy4.ursus.maine.edu/doi/pdf/10.1177/1474904116648966
Koedinger, K. R., D'Mello, S., McLaughlin, E. A., Pardos, Z. A. and Rosé, C. P. (2015), Data mining and education. Wiley Interdisciplinary Reviews: Cognitive Science, 6(4), pp. 333-353. Retrieved from http://onlinelibrary.wiley.com.prxy4.ursus.maine.edu/doi/10.1002/wcs.1350/full.
Lynch C. (2017) Who prophets from big data in education? New insights and new challenges. Theory and Research in Education 15(3) pp. 249-271 Retrieved from: https://journals-sagepub-com.prxy4.ursus.maine.edu/doi/pdf/10.1177/1477878517738448
McCambridge R. (2014) Legacy of a Failed Foundation Initiative: inBloom, Gates and Carnegie. Non-Profit Quarterly Retrieved from: https://nonprofitquarterly.org/2014/07/02/legacy-of-a-failed-foundation-initiative-inbloom-gates-and-carnegie/
[TED] (2016, September 26) Let's teach for mastery -- not test scores | Sal Khan [video file] Retrieved From: https://www.youtube.com/watch?v=-MTRxRO5SRA
[euronews] (2015, May 22) Knowledge is power: how Big Data is transforming education -learning world [video file] Retrieved From: https://www.youtube.com/watch?v=f0twZnOlBqA
[Ashley Armstrong] (2016, June 18) big data and student privacy final [video file] retrieved from: https://www.youtube.com/watch?v=3HVo9SBMpeA
Comments
Post a Comment