{"id":187697,"date":"2012-05-10T00:00:00","date_gmt":"2012-05-11T14:48:30","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/modeling-and-inspecting-the-question-asking-process-in-educational-dialogues\/"},"modified":"2016-08-22T11:26:14","modified_gmt":"2016-08-22T18:26:14","slug":"modeling-and-inspecting-the-question-asking-process-in-educational-dialogues","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/modeling-and-inspecting-the-question-asking-process-in-educational-dialogues\/","title":{"rendered":"Modeling and Inspecting the Question-Asking Process in Educational Dialogues"},"content":{"rendered":"<div class=\"asset-content\">\n<p>While many studies have demonstrated that dialogue-based tutoring systems have a positive effect on learning, the significant amount of human effort required to author, design, and tune system behaviors still provides a major barrier towards widespread deployment and adoption of these systems.  Machine learning presents a path towards reduced human effort, however the custom-built nature of these systems means that any learned behavior is strictly tied to a single implementation.  Ideally these behaviors should be able to extend to a variety of materials and concepts.  To enable this kind of generalization will require a meta-level model of the dialogue that abstracts utterances to their action, function, and content.<\/p>\n<p>In this talk, I describe the DISCUSS dialogue move taxonomy, an intermediate representation that allows for lesson-independent modeling of dialogue behavior.  To demonstrate the utility of this representation, I explore how DISCUSS-based features assist in the process of ranking and selecting follow-up questions within the context of the My Science Tutor (MyST) intelligent tutoring system.   Moreover, I show how DISCUSS enables us to model and identify the factors driving the decisions made by experienced human tutors when teaching.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>While many studies have demonstrated that dialogue-based tutoring systems have a positive effect on learning, the significant amount of human effort required to author, design, and tune system behaviors still provides a major barrier towards widespread deployment and adoption of these systems. Machine learning presents a path towards reduced human effort, however the custom-built nature [&hellip;]<\/p>\n","protected":false},"featured_media":196821,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_hide_image_in_river":0,"footnotes":""},"research-area":[],"msr-video-type":[],"msr-locale":[268875],"msr-post-option":[],"msr-session-type":[],"msr-impact-theme":[],"msr-pillar":[],"msr-episode":[],"msr-research-theme":[],"class_list":["post-187697","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/QaDypJzrdzg","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/187697","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":0,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/187697\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/196821"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=187697"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=187697"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=187697"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=187697"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=187697"},{"taxonomy":"msr-session-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-session-type?post=187697"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=187697"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=187697"},{"taxonomy":"msr-episode","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-episode?post=187697"},{"taxonomy":"msr-research-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-theme?post=187697"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}