In the draft “Promoting Grit, Tenacity, and Perseverance: Critical Factors for Success in the 21st Century” report released in February by the Department of Education is a section detailing how to measure such qualities in a student through Behavioral Task Performance.
“Behavioral task performance measures are the broad set of methods used to capture behaviors consistent with perseverance or lack thereof—and in many cases, associated emotional experiences, physical movements or facial expressions, physiological responses, and thoughts— that students do in response to a particular challenge,” the report states.
It goes on to say that laboratory experiments have long been useful in gaining information about behavioral task performance, but “new technological opportunities offer potential for new methods and approaches.” This includes data collected about students using online learning systems but also “affective computing” methods, which is defined as “the study and development of systems and devices that can recognize, interpret, process, and simulate aspects of human affect.”
Understanding the emotions or physiological state of a student while they’re presented with a challenge, the report said, can be measured through “analysis of facial expressions, EEG brain wave patterns, skin conductance, heart rate variability, posture and eye- tracking.”
The report presents this figure showing a variety of sensors that could be used to determine the emotional state of a student while performing a certain task:
Glenn Beck Talks About Technology That Mines Data About Students
Figure from the draft “Promoting Grit, Tenacity, and Perseverance” report (Image:
“Sensors provide constant, parallel streams of data and are used with data mining techniques and self-report measures to examine frustration, motivation/flow, confidence, boredom and fatigue,” the report states.
It presents MIT’s Mood Meter — a device that captures facial expression through a camera on a laptop while software analyses the mood — as an example of technology that can conduct these measurements. The Mood Meter was deployed on MIT’s campus to get a sense of the general mood during the Festival of Art, Science and Technology in 2011. By tracking smiles as a metric of happiness, the Mood Meter would provide real-time information that could “help with answers to questions such as ‘Do midterms lower the mood?’, ‘Does warmer weather lead to happiness?’, and ‘Are people from one department happier than others?’”
Watch this video to see the Mood Meter in action:
You can see how such technology could be used to answer questions about a student’s behavior to certain situations or topics in the classroom.
“While this type of tool may not be necessary in a small class of students, it could be useful for examining emotional responses in informal learning environments for large groups, like museums,” the report says of the use of technology like the Mood Meter.
study in 1999 published by MIT researchers delved into the use of a posture-sensing chair to evaluate a student. The experiment using a chair with pressure sensors on the seat and back evaluated student interest in order to better learn how to improve the experience for students in a computer-learning situation.
But a camera, chair, mouse and wristband equipped with sensors to track different metrics isn’t not all. The report also highlights the value of FMRI (functional magnetic resonance imagery), which would reveal different areas of activity in the brain through scans.
The report notes that use of such a machine is impractical in the school setting — equipment is large and expensive to use — but includes the following idea:
Ed Dieterle and Ash Vasudeva of the Bill & Melinda Gates Foundation point out that researchers such as Jon Gabrieli and Richard Davidson are beginning to use multiple methods to explore how specific brain activity is correlated with other cognitive and affective indicators that are practical to measure in school settings.
Some technology to track students in some ways is already being implemented in schools. A student in a Texas school has fought against the school’s requirement of an RFID (radio-frequency identification) tag in her student I.D. With the RFID enabled tags in the I.D.’s schools would be able to track where students were on campus — not off — but the student viewed it as an invasion of privacy and “the mark of the beast.”
The report goes on to acknowledge the drawbacks of using some data mining technologies, which includes being intrusive or simply impractical for use in a traditional classroom setting.
“[...] many of these types of measures are dependent on the use of highly constrained tasks in digital learning environments, which may be difficult to translate into use in the classroom or informal learning environment.”
And what of privacy (emphasis added)?
Of course, privacy is always a concern, especially when leveraging data available in the “cloud” that users may or may not be aware is being mined. However, another emergent concern is the consequences of using new types of personal data in new ways. Learners and educators have the potential to get forms of feedback about their behaviors, emotions, physiological responses, and cognitive processes that have never been available before. Measurement developers must carefully consider the impacts of releasing such data, sometimes of a sensitive nature, and incorporate feedback mechanisms that are valuable, respectful, and serve to support productive mindsets.
Our children are being used as an experimental test subjects without your consent.
This is a social engineer's bonanza. If it’s allowed to be in our schools in any form and become the common core of America’s next generation it will destroy our privacy, individual liberty and democratic rights.