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Promoting Grit, Tenacity, and Perseverance - U.S. Department of ...

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Draft<br />

Ethical Considerations for New Types <strong>of</strong> Personal Data<br />

As new forms <strong>of</strong> measurement emerge <strong>and</strong> new types <strong>of</strong> personal data become available, the<br />

field must also deal with critical ethical considerations. Of course, privacy is always a concern,<br />

especially when leveraging data available in the “cloud” that users may or may not be aware is<br />

being mined. However, another emergent concern is the consequences <strong>of</strong> using new types <strong>of</strong><br />

personal data in new ways. Learners <strong>and</strong> educators have the potential to get forms <strong>of</strong> feedback<br />

about their behaviors, emotions, physiological responses, <strong>and</strong> cognitive processes that have never<br />

been available before. Measurement developers must carefully consider the impacts <strong>of</strong> releasing<br />

such data, sometimes <strong>of</strong> a sensitive nature, <strong>and</strong> incorporate feedback mechanisms that are<br />

valuable, respectful, <strong>and</strong> serve to support productive mindsets.<br />

Moving Forward<br />

The development <strong>of</strong> valid <strong>and</strong> reliable measures will be an important factor as we exp<strong>and</strong> the<br />

capacity to design <strong>and</strong> evaluate learning environments that promote <strong>and</strong>/or teach, grit, tenacity,<br />

<strong>and</strong> perseverance. In this chapter, we explored the many purposes <strong>of</strong> such measurement <strong>and</strong> how<br />

they may contribute to these goals, <strong>and</strong> the range measurement approaches—both current <strong>and</strong> on<br />

the horizon. While there a strong foundation <strong>of</strong> work already done in this area, there are<br />

important next steps for the field. Some <strong>of</strong> the most promising new directions are educational<br />

data mining <strong>and</strong> affective computing. The method <strong>of</strong> evidence-centered design can help<br />

measurement designers build strong validity arguments as we advance measurement <strong>of</strong> these<br />

complex variables.<br />

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