{"id":1624,"date":"2011-06-17T06:43:42","date_gmt":"2011-06-17T06:43:42","guid":{"rendered":"http:\/\/www.physiologicalcomputing.net\/?p=1624"},"modified":"2021-12-22T20:21:14","modified_gmt":"2021-12-22T20:21:14","slug":"chi-2011-workshop-session-3-evaluating-the-user-experience-videos-online","status":"publish","type":"post","link":"https:\/\/www.physiologicalcomputing.net\/?p=1624","title":{"rendered":"CHI 2011 Workshop \u2013 Session 3 \u201cEvaluating the User Experience\u201d Videos Online"},"content":{"rendered":"<p>This week see&#8217;s the release of the talks presented during the <em>Evaluating the User Experience <\/em>session. To view these talks and more please <a title=\"Workshop Media\" href=\"http:\/\/www.physiologicalcomputing.net\/wordpress\/?page_id=903#media\">click here<\/a>. For guidance about the session 3 talks please consult the abstracts listed below.<\/p>\n<p><!--more--><\/p>\n<p>(Mirza-Babaei, P., McAllister, G.) <span style=\"text-decoration: underline;\">Biometric Storyboards: visualising meaningful gameplay events <\/span>(<strong><a title=\"Biometric Storyboards: visualising meaningful gameplay events\" href=\"http:\/\/physiologicalcomputing.net\/bbichi2011\/Biometric%20Storyboards%20-%20visualising%20meaningful%20gameplay%20events.pdf\">PDF<\/a><\/strong>) (<strong><a title=\"Biometric Storyboards: visualising meaningful gameplay events\" href=\"http:\/\/vimeo.com\/24917921\">Video<\/a><\/strong>)<em><\/em><\/p>\n<blockquote><p>Due to the specific characteristics of video games most of the established HCI methods of user research cannot be used the same way for video games. One of the challenges is to gain insight into how players feel and behave when playing a game. This paper explores a technique on using Biometrics measure and Storyboards where we graph the player&#8217;s experience journey over a longer period. The graph could visualise a meaningful relationship between the changes in a player\u2019s biometric signal and game events. This would enable game developers to have a better understanding of players\u2019 gameplay behaviour and eventually help them optimise the experience of their game.<\/p><\/blockquote>\n<p>(Nacke, L. E.) <span style=\"text-decoration: underline;\">Directions in Physiological Game Evaluation and Interaction<\/span> (<strong><a title=\"Directions in Physiological Game Evaluation and Interaction\" href=\"http:\/\/physiologicalcomputing.net\/bbichi2011\/Directions%20in%20Physiological%20Game%20Evaluation%20and%20Interaction.pdf\">PDF<\/a><\/strong>) (<a title=\"Directions in Physiological Game Evaluation and Interaction\" href=\"http:\/\/vimeo.com\/24918221\"><strong>Video<\/strong><\/a>)<\/p>\n<blockquote><p>Physiological sensors are becoming cheaper and more available to game players. This has led to their increased usage in game research and the game industry, where applications range from biofeedback games to design evaluation tools supporting game user researchers in creating more engaging gameplay experiences. This paper gives a brief overview of these current directions of game industry and research threads.<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>This week see&#8217;s the release of the talks presented during the Evaluating the User Experience session. To view these talks and more please click here. For guidance about the session 3 talks please consult the abstracts listed below.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spay_email":""},"categories":[6],"tags":[99,16,19,97,98,96,95],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/pY315-qc","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/posts\/1624"}],"collection":[{"href":"https:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.physiologicalcomputing.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1624"}],"version-history":[{"count":13,"href":"https:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/posts\/1624\/revisions"}],"predecessor-version":[{"id":1691,"href":"https:\/\/www.physiologicalcomputing.net\/index.php?rest_route=\/wp\/v2\/posts\/1624\/revisions\/1691"}],"wp:attachment":[{"href":"https:\/\/www.physiologicalcomputing.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1624"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.physiologicalcomputing.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1624"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.physiologicalcomputing.net\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1624"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}