{"id":106,"date":"2009-05-12T09:24:10","date_gmt":"2009-05-12T09:24:10","guid":{"rendered":"http:\/\/www.physiologicalcomputing.net\/wordpress\/?p=106"},"modified":"2021-12-22T20:22:10","modified_gmt":"2021-12-22T20:22:10","slug":"neurofeedback-in-education","status":"publish","type":"post","link":"http:\/\/www.physiologicalcomputing.net\/?p=106","title":{"rendered":"Neurofeedback in Education"},"content":{"rendered":"

FutureLab have published a discussion paper<\/a> entitled “Neurofeedback: is there a potential for use in education?”\u00a0 It’s interesting to read a report devoted to the practical uses of neurofeedback for non-clinical populations.\u00a0 In short, the report covers definitions of neurofeedback & example systems (including EEG-based games like Mindball<\/a> and MindFlex<\/a>) as background.\u00a0 Then, three potential uses of neurofeedback are considered: training for sports performance, training for artistic performance and training to treat ADHD.\u00a0 The report doesn’t draw any firm conclusions as might be expected given the absence of systematic research programmes (in education).\u00a0 Aside from flagging up a number of issues (intrusion, reliability, expense), it’s obvious that we don’t know how these techniques are best employed in an educational environment, i.e. how long do students need to use them? What kind of EEG changes are important?\u00a0 How might neurofeedback be combined with other training techniques?<\/p>\n

As I see it, there are a number of distinct application domains to be considered: (1) neurofeedback to shift into the desired psychological state prior to learning experience or examination (drawn from sports neurofeedback), (2) adapting educational software in real-time to keep the learner motivated (to avoid disengagement or boredom), and (3) to teach children about biological systems using biofeedback games (self-regulation exercises plus human biology practical).\u00a0 I’m staying with non-clinical applications here but obviously the same approaches may be applied to ADHD.<\/p>\n

(1) and (3) above both correspond to a traditional biofeedback paradigm where the user works with the processed biological signal to develop a degree of self-regulation, that hopefully with transfer with practice.\u00a0 (2) is more interesting in my opinion; in this case, the software is being adapted in order to personalise and optimise the learning process for that particular individual.\u00a0 In other words, an efficient psychological state for learning is being created in situ by dynamic software adaptation.\u00a0 This approach isn’t so good for encouraging self-regulatory strategies compared to traditional biofeedback, but I believe it is more potent for optimising the learning process itself.<\/p>\n","protected":false},"excerpt":{"rendered":"

FutureLab have published a discussion paper entitled “Neurofeedback: is there a potential for use in education?”\u00a0 It’s interesting to read a report devoted to the practical uses of neurofeedback for non-clinical populations.\u00a0 In short, the report covers definitions of neurofeedback & example systems (including EEG-based games like Mindball and MindFlex) as background.\u00a0 Then, three potential […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spay_email":""},"categories":[7],"tags":[9,19,28,61,81],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/pY315-1I","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"http:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/posts\/106"}],"collection":[{"href":"http:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/www.physiologicalcomputing.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=106"}],"version-history":[{"count":1,"href":"http:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/posts\/106\/revisions"}],"predecessor-version":[{"id":4755,"href":"http:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/posts\/106\/revisions\/4755"}],"wp:attachment":[{"href":"http:\/\/www.physiologicalcomputing.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=106"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.physiologicalcomputing.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=106"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.physiologicalcomputing.net\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=106"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}