{"id":3412,"date":"2025-03-18T06:35:49","date_gmt":"2025-03-18T11:35:49","guid":{"rendered":"https:\/\/wordpress.cs.vt.edu\/3digroup\/?p=3412"},"modified":"2025-03-18T06:35:50","modified_gmt":"2025-03-18T11:35:50","slug":"eyest-eye-enhanced-immersive-space-to-think-with-gaze-driven-recommendations","status":"publish","type":"post","link":"https:\/\/wordpress.cs.vt.edu\/3digroup\/2025\/03\/18\/eyest-eye-enhanced-immersive-space-to-think-with-gaze-driven-recommendations\/","title":{"rendered":"EyeST: Eye-Enhanced Immersive Space to Think with Gaze-Driven Recommendations"},"content":{"rendered":"\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"506\" src=\"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2025\/03\/paper_teaser-1024x506.jpg\" alt=\"\" class=\"wp-image-3413\" srcset=\"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2025\/03\/paper_teaser-1024x506.jpg 1024w, https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2025\/03\/paper_teaser-300x148.jpg 300w, https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2025\/03\/paper_teaser-768x380.jpg 768w, https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2025\/03\/paper_teaser.jpg 1207w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The advancements in AI have raised intriguing possibilities for personalized experiences. Imagine if AI could anticipate your interests by analyzing your gaze patterns from the last hour of reading. What if it could recommend insights not just based on the pages you visited but on the specific parts of those pages that held your attention? The concept extends into immersive spaces. In XR, even though you get more space to organize massive amounts of information, you\u2019d still have to exhaustively go through all that information to make any sense. The challenge persists. Could a gaze-driven intelligent system alleviate this by providing personalized context as you navigate the data?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The answer is a resounding yes!<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">However, the key to such human-AI collaboration lies in user acceptance. Our research underscores that regardless of AI sophistication, trust and effectiveness hinge on context. Explainability and transparency are pivotal; users must comprehend not just the AI\u2019s actions, but also the rationale behind its recommendations. Without these elements, even the most intelligent systems may fall short.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">So, what should we keep in mind for AI-mediated sensemaking in the immersive space? Below is a brief look at our proposed approach and findings from this study. Read our paper to know more!<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe loading=\"lazy\" title=\"Real Time Recommendation Agent in Immersive Space Learning from User&#039;s Eye Gaze\" width=\"1778\" height=\"1000\" src=\"https:\/\/www.youtube.com\/embed\/fc9HAB93rNA?modestbranding=1\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><div class=\"teachpress_pub_list\"><form name=\"tppublistform\" method=\"get\"><a name=\"tppubs\" id=\"tppubs\"><\/a><\/form><div class=\"teachpress_publication_list\"><h3 class=\"tp_h3\" id=\"tp_h3_inproceedings\">Proceedings Articles<\/h3><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\">Ibrahim Tahmid; Chris North; Kylie Davidson; Kirsten Whitley; Doug A Bowman<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('215','tp_links')\" style=\"cursor:pointer;\">Enhancing Immersive Sensemaking with Gaze-Driven Recommendation Cues<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the 30th International Conference on Intelligent User Interfaces, <\/span><span class=\"tp_pub_additional_pages\">pp. 641\u2013659, <\/span><span class=\"tp_pub_additional_organization\">ACM <\/span><span class=\"tp_pub_additional_year\">2025<\/span>, <span class=\"tp_pub_additional_isbn\">ISBN: 979-8-4007-1306-4\/25\/03<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_215\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('215','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_215\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('215','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_215\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('215','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_215\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{tahmid2025enhancing,<br \/>\r\ntitle = {Enhancing Immersive Sensemaking with Gaze-Driven Recommendation Cues},<br \/>\r\nauthor = {Ibrahim Tahmid and Chris North and Kylie Davidson and Kirsten Whitley and Doug A Bowman},<br \/>\r\ndoi = {10.1145\/3708359.3712103},<br \/>\r\nisbn = {979-8-4007-1306-4\/25\/03},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-03-24},<br \/>\r\nurldate = {2025-03-24},<br \/>\r\nbooktitle = {Proceedings of the 30th International Conference on Intelligent User Interfaces},<br \/>\r\npages = {641--659},<br \/>\r\norganization = {ACM},<br \/>\r\nabstract = {Sensemaking is a complex task that places a heavy cognitive demand on individuals. <br \/>\r\nWith the recent surge in data availability, making sense of vast amounts of information has become a significant challenge for many professionals, such as intelligence analysts. <br \/>\r\nImmersive technologies such as mixed reality offer a potential solution by providing virtually unlimited space to organize data.<br \/>\r\nHowever, the difficulty of processing, filtering relevant information, and synthesizing insights remains.<br \/>\r\nWe proposed using eye-tracking data from mixed reality head-worn displays to derive the analyst&#039;s perceived interest in documents and words, and convey that part of the mental model to the analyst.<br \/>\r\nThe global interest of the documents is reflected in their color, and their order on the list, while the local interest of the documents is used to generate focused recommendations for a document.<br \/>\r\nTo evaluate these recommendation cues, we conducted a user study with two conditions: a gaze-aware system, EyeST, and a ``Freestyle&#039;&#039; system without gaze-based visual cues. <br \/>\r\nOur findings reveal that the EyeST helped analysts stay on track by reading more essential information while avoiding distractions. <br \/>\r\nHowever, this came at the cost of reduced focused attention and perceived system performance.<br \/>\r\nThe results of our study highlight the need for explainable AI in human-AI collaborative sensemaking to build user trust and encourage the integration of AI outputs into the immersive sensemaking process. <br \/>\r\nBased on our findings, we offer a set of guidelines for designing gaze-driven recommendation cues in an immersive environment.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('215','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_215\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Sensemaking is a complex task that places a heavy cognitive demand on individuals. <br \/>\r\nWith the recent surge in data availability, making sense of vast amounts of information has become a significant challenge for many professionals, such as intelligence analysts. <br \/>\r\nImmersive technologies such as mixed reality offer a potential solution by providing virtually unlimited space to organize data.<br \/>\r\nHowever, the difficulty of processing, filtering relevant information, and synthesizing insights remains.<br \/>\r\nWe proposed using eye-tracking data from mixed reality head-worn displays to derive the analyst&#039;s perceived interest in documents and words, and convey that part of the mental model to the analyst.<br \/>\r\nThe global interest of the documents is reflected in their color, and their order on the list, while the local interest of the documents is used to generate focused recommendations for a document.<br \/>\r\nTo evaluate these recommendation cues, we conducted a user study with two conditions: a gaze-aware system, EyeST, and a ``Freestyle&#039;&#039; system without gaze-based visual cues. <br \/>\r\nOur findings reveal that the EyeST helped analysts stay on track by reading more essential information while avoiding distractions. <br \/>\r\nHowever, this came at the cost of reduced focused attention and perceived system performance.<br \/>\r\nThe results of our study highlight the need for explainable AI in human-AI collaborative sensemaking to build user trust and encourage the integration of AI outputs into the immersive sensemaking process. <br \/>\r\nBased on our findings, we offer a set of guidelines for designing gaze-driven recommendation cues in an immersive environment.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('215','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_215\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1145\/3708359.3712103\" title=\"Follow DOI:10.1145\/3708359.3712103\" target=\"_blank\">doi:10.1145\/3708359.3712103<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('215','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><\/div><\/div><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The advancements in AI have raised intriguing possibilities for personalized experiences. Imagine if AI could anticipate your interests by analyzing your gaze patterns from the last hour of reading. What if it could recommend insights not just based on the pages you visited but on the specific parts of those pages that held your attention? <a href=\"https:\/\/wordpress.cs.vt.edu\/3digroup\/2025\/03\/18\/eyest-eye-enhanced-immersive-space-to-think-with-gaze-driven-recommendations\/\" class=\"more-link\">&#8230;<\/a><\/p>\n","protected":false},"author":330,"featured_media":3413,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9,11],"tags":[14,20,553,27,509,552,47],"ppma_author":[395,402,396,391],"class_list":["post-3412","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-featured","category-projects","tag-3d-interaction-techniques","tag-adaptive-ar","tag-ai-mediated-sensemaking","tag-augmented-reality","tag-eye-tracking","tag-human-centered-ai","tag-immersive-analytics"],"jetpack_featured_media_url":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2025\/03\/paper_teaser.jpg","authors":[{"term_id":395,"user_id":330,"is_guest":0,"slug":"iatahmid","display_name":"Ibrahim Tahmid","avatar_url":{"url":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2020\/12\/ibrahim.jpg","url2x":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2020\/12\/ibrahim.jpg"},"author_category":"","user_url":"https:\/\/www.iatahmid.com\/","last_name":"Tahmid","first_name":"Ibrahim","job_title":"","description":"Ibrahim is a fifth year Ph.D. Student advised by Dr. Doug Bowman. His research interest focuses on assisted sensemaking in virtual reality. More specifically, he works on how eye gaze can be used to infer the user-perceived relevance of information during sensemaking and how to leverage that inference to build intelligent recommender models for the immersive space to think."},{"term_id":402,"user_id":0,"is_guest":1,"slug":"chris-north","display_name":"Chris North","avatar_url":"https:\/\/secure.gravatar.com\/avatar\/?s=96&d=mm&r=g","author_category":"","user_url":"","last_name":"","first_name":"","job_title":"","description":""},{"term_id":396,"user_id":302,"is_guest":0,"slug":"kyliedavidson","display_name":"Kylie Davidson","avatar_url":{"url":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2020\/10\/20181228_113322-1-copy-scaled-1.jpeg","url2x":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2020\/10\/20181228_113322-1-copy-scaled-1.jpeg"},"author_category":"","user_url":"","last_name":"","first_name":"","job_title":"","description":""},{"term_id":391,"user_id":331,"is_guest":0,"slug":"dbowman","display_name":"Doug Bowman","avatar_url":{"url":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2021\/01\/professional_photo2_2019-cropped-square-smaller-scaled.jpg","url2x":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-content\/uploads\/sites\/141\/2021\/01\/professional_photo2_2019-cropped-square-smaller-scaled.jpg"},"author_category":"1","user_url":"","last_name":"Bowman","first_name":"Doug","job_title":"","description":"Doug A. Bowman is the Frank J. Maher Professor of <a href=\"http:\/\/www.cs.vt.edu\">Computer Science<\/a> at <a href=\"http:\/\/www.vt.edu\">Virginia Tech<\/a>. He is the principal investigator of the <a href=\"http:\/\/wordpress.cs.vt.edu\/3digroup\/\">3D Interaction Group<\/a>, focusing on the topics of three-dimensional user interfaces, VR\/AR user experience, and the benefits of immersion in virtual environments.\r\n\r\nDr. Bowman is one of the co-authors of <a href=\"https:\/\/www.pearson.com\/us\/higher-education\/program\/La-Viola-3-D-User-Interfaces-Theory-and-Practice-2nd-Edition\/PGM101825.html\">3D User Interfaces: Theory and Practice<\/a>. He has served in many roles for the <a href=\"http:\/\/ieeevr.org\">IEEE Virtual Reality Conference<\/a>, including program chair, general chair, and steering committee chair. He also co-founded the IEEE Symposium on 3D User Interfaces (now part of IEEE VR). He received a CAREER award from the National Science Foundation for his work on 3D Interaction, and has been named an ACM Distinguished Scientist. He received the Technical Achievement award from the IEEE Visualization and Graphics Technical Committee in 2014 and the Career Impact Award from IEEE ISMAR in 2021.\r\n\r\nHis undergraduate degree in mathematics and computer science is from Emory University, and he received his M.S. and Ph.D. in computer science from the Georgia Institute of Technology.\r\n\r\n<a href=\"http:\/\/people.cs.vt.edu\/~bowman\/cv.pdf\">Curriculum vitae (PDF)<\/a>"}],"_links":{"self":[{"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/posts\/3412","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/users\/330"}],"replies":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/comments?post=3412"}],"version-history":[{"count":4,"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/posts\/3412\/revisions"}],"predecessor-version":[{"id":3417,"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/posts\/3412\/revisions\/3417"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/media\/3413"}],"wp:attachment":[{"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/media?parent=3412"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/categories?post=3412"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/tags?post=3412"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/wordpress.cs.vt.edu\/3digroup\/wp-json\/wp\/v2\/ppma_author?post=3412"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}