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| Content Provider | ACM Digital Library |
|---|---|
| Author | Saxberg, Bror |
| Abstract | There's a lot of excitement about how technology can transform education, and how the data created by all this technology can create a new era of amazingly motivating personalized instruction. However, the history of technology in education suggests we need to be skeptical: radio in the 1930's, film in the 1950's, on and on through the decades. -- all promised much, but never reached traction. What makes this time different? A key difference, if we choose to put it to work, is the availability of good, evidence-based principles about how learning seems to work, derived in many laboratories using randomized controlled trials over many years. Unfortunately, as with any set of deeply researched ideas, the narrowly specific conditions of most research studies don't answer the question, "How do I build a better math/composition/history course" in any direct way. What we need is an engineering approach -- a way to take evidence-based principles and ideas, and apply them at scale to solve (with plenty of uncertainties and iterative tweaking) real-world situations -- "learning engineering." Doing this in an organization that is itself at scale is non-trivial: you may have hundreds of people who should alter their thinking and practice around learning, making this a major change project on top of the series of new engineering challenges that evidence-based work creates. One approach involves taking a series of steps within the organization over time: Exposure Education Effort Evaluation By drawing from the evidence that exists already, showing examples within the organization of how these principles make a difference, training developers to use the principles for design and managers to use a version of the principles to evaluate resource priorities, and building continuous evaluation into the whole operation, we can move down the path to becoming a "learning engineering" organization. |
| Starting Page | 1 |
| Ending Page | 1 |
| Page Count | 1 |
| File Format | |
| ISBN | 9781450344500 |
| DOI | 10.1145/3051457.3054019 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2017-04-12 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | E-learning Education technology Applied cognitive science Learning engineering Evidence-based instructional design |
| Content Type | Text |
| Resource Type | Article |
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