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The XAI Experience Quality (XEQ) Scale was developed to quantify the quality of XAI experiences across four dimensions: learning, utility, fulfilment and engagement. The paper details scale development and validation, including content validation with XAI experts and discriminant and construct validation via a large-scale pilot study. Results support XEQ as a comprehensive framework for assessing multi-shot, personalized XAI experiences.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/xeq-scale-for-evaluating-xai-experience-quality/270997/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/xeq-scale-for-evaluating-xai-experience-quality/270997.png","ImageObject",300,407,{"name":92,"@type":93},"Margaret","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-08","2026-09-15",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What problem does the XEQ Scale address in explainable AI evaluation?","Question",{"text":113,"@type":114},"It addresses the challenge of evaluating XAI experiences in a user-centered way, especially for interactive multi-shot explanations, where common objective metrics are insufficient.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How does XEQ quantify the quality of an XAI experience?",{"text":118,"@type":114},"XEQ quantifies experience quality across four dimensions: learning, utility, fulfilment, and engagement.",{"name":120,"@type":111,"acceptedAnswer":121},"What validation methods are used to establish the XEQ Scale?",{"text":122,"@type":114},"The paper includes content validation with XAI experts and discriminant and construct validation using results from a large-scale pilot study.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},270997,1789458996,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":130,"read_time":145,"preview_page_count":4},137451207643,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","arXiv :2407 . 10662v4 [ cs .AI] 17 Jan 2025  \nXEQ Scale for Evaluating XAI Experience Quality  \nAnjana Wijekoon1, *,†, Nirmalie Wiratunga2, David Corsar2, Kyle Martin2, Ikechukwu Nkisi-Orji2, Belen Díaz-Agudo3 and Derek Bridge4  \n1 University College London, London, England 2 Robert Gordon University, Aberdeen, Scotland 3 Universidad Complutense de Madrid, Spain 4 University College Cork, Ireland  \nAbstract  \nExplainable Artificial Intelligence (XAI) aims to improve the transparency of autonomous decision-making through explanations. Recent literature has emphasised users’ need for holistic “multi-shot” explanations and personalised engagement with XAI systems. We refer to this user-centred interaction as an XAI Experience. Despite advancesin creating XAI experiences, evaluating them in a user-centred manner has remained challenging. In response, we developed the XAI Experience Quality (XEQ) Scale. XEQ quantifies the quality of experiences across four dimensions: learning, utility, fulfilment and engagement. These contributions extend the state-of-the-art of XAI evaluation, moving beyond the one-dimensional metrics frequently developed to assess single-shot explanations. This paper presents the XEQ scale development and validation process, including content validation with XAI experts, and discriminant and construct validation through a large-scale pilot study. Our pilot study results offer strong evidence that establishes the XEQ Scale as a comprehensive framework for evaluating user-centred XAI experiences.  \nKeywords  \nExplanation Experience Quality, Multi-shot Explanation, Psychometric Theory, Scale Development  \n1. Introduction  \nExplainable Artificial Intelligence (XAI) describes a range of techniques to elucidate autonomous decision-making and the data that informed that AI system [1, 2, 3] . Each technique typically provides explanations focusing on a specific aspect of the system and its decisions, often answering a singular question fulfilling a specific intent [4, 5] . Accordingly, the utility of employing multiple techniques for a holistic explanation of a system becomes increasingly clear [3, 6] . The collection of explanations, provided by different techniques and describing different components of the system, forms what we describe as “multi-shot” explanations. Multi-shot explanation treats the elucidation of an AI system as a process which can invoke a variety of knowledge sources to construct explanations that comprehensively answer a user’s explanation needs. This is unlike single-shot, which provides a lone explanation that targets a specific aspect of an autonomous decision to resolve an individual query (see Figure 1) . Furthermore, viewing multi-shot explanations as an interactive process allows users to engage through graphical interfaces [3] or conversations [7, 6], enabling personalised experiences tailored to individual needs [8] .  \nWhile the utility of user-centred interactive multi-shot explanations is evident in recent literature, evaluating them remains a key research challenge. Current works primarily target the development of objective metrics for single-shot techniques [9, 10], emphasising the need for reproducible benchmarks on public datasets [11] . Such metrics are system-centred and model-agnostic, meaning they are compatible with a variety of XAI systems and giving the advantage of generalisability. However,  \nPreprint  \n* Corresponding author.  \n†  \nThis work was done while affiliated with Robert Gordon University, Aberdeen, Scotland.  \n$ [a.wijekoon@ucl.ac.uk](a.wijekoon@ucl.ac.uk) (A. Wijekoon)  \n􀀚 0000-0003-3848-3100 (A. Wijekoon); 0000-0003-4040-2496 (N. Wiratunga); 0000-0001-7059-4594 (D. Corsar); 00000-0003-0941-3111 (K. Martin); 0000-0001-9734-9978 (I. Nkisi-Orji); 0000-0003-2818-027X (B. Díaz-Agudo); 0000-0002-8720-3876 (D. Bridge)  \n © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0) .  \nFigure 1","cbCairQ6NRuNgy0g","https://ap.wps.com/l/cbCairQ6NRuNgy0g","pdf",28481263,25,"English","# Introduction\n## Multi-shot explanations and user interaction\n## Evaluation challenges and need for XEQ\n# XEQ scale development and validation\n## Content validation with XAI experts\n## Discriminant and construct validation","[{\"question\":\"What problem does the XEQ Scale address in explainable AI evaluation?\",\"answer\":\"It addresses the challenge of evaluating XAI experiences in a user-centered way, especially for interactive multi-shot explanations, where common objective metrics are insufficient.\"},{\"question\":\"How does XEQ quantify the quality of an XAI experience?\",\"answer\":\"XEQ quantifies experience quality across four dimensions: learning, utility, fulfilment, and engagement.\"},{\"question\":\"What validation methods are used to establish the XEQ Scale?\",\"answer\":\"The paper includes content validation with XAI experts and discriminant and construct validation using results from a large-scale pilot study.\"}]","XEQ Scale for Evaluating XAI Experience Quality | PDF",63]