[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123918-en":3,"doc-seo-123918-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123918,4398048950312,"Violet","https://ap-avatar.wpscdn.com/avatar/400002538284de19e3c?_k=1778320343897328908",8,"Research & Report","Identifying Digital Capabilities in University Courses - An Automated Machine Learning Approach","Digital capabilities have become increasingly important in higher education, and assessing them is central to curriculum design and curriculum mapping. Prior research has not systematically reported assessing digital capabilities across an entire university’s course portfolio, largely because manual review is impractical when thousands of courses must be checked. This study applies machine learning classifiers to automatically identify formally assessed digital capabilities from real university course rubric text. Experimental results show support vector machines achieve the strongest performance.","Identifying digital capabilities in university courses: An automated machine learning approach  \nZongwen Fan1,2 · Raymond Chiong2  \nReceived: 28 August 2021 / Accepted: 21 April 2022 / Published online: 6 October 2022 © The Author(s) 2022  \nAbstract  \nDigital capabilities have become increasingly important in this digital age. Within a university setting, digital capability assessment is key to curriculum design and curriculum mapping, given that digital capabilities not only can help students engage and communicate with others but also succeed at work. To the best of our knowledge, however, no previous studies in the relevant literature have reported the assessment of digital capabilities in courses across a university. It is extremely challenging to do so manually, as thousands of courses offered by the university would have tobe checked. In this study, we therefore use machine learning classifiers to automatically identify digital capabilities in courses based on real-world university course rubric data. Through text analysis of course rubrics produced by course academics, decision makers can identify the digital capabilities that are formally assessed in university courses. This, in turn, would enable them to design and map curriculumsto develop the digital capabilities of staff and students. Comprehensive experimental results reveal that the machine learning models tested in this study can effectively identify digital capabilities. Among the prediction models included in our experiments, the performance of support vector machines was the best, achieving accuracy and F-measure scores of 0.8535 and 0.8338, respectively.  \nKeywords Digital capability identification · University course rubrics · Machine learning models · Text pre-processing  \n* Raymond Chiong [raymond.chiong@newcastle.edu.au](raymond.chiong@newcastle.edu.au)  \nZongwen Fan  \n[zongwen.fan@hqu.edu.cn](zongwen.fan@hqu.edu.cn)  \n1 College of Computer Science and Technology, Huaqiao University, Xiamen 361021, China  \n2 School of Information and Physical Sicences, The University of Newcastle, Callaghan NSW 2308, Australia  \n1 Introduction  \nDigital capabilities – recognised as key skills that students must possess to learn and work in an increasingly digital world – have received increasing research attention in recent years (Crosby et al. , 2020 ; Wilson & Slade, 2020) . To thrive at university studies, students must be equipped with the skills necessary to use various technologies appropriately and effectively in different spaces, places and situations (Elphick, 2018) . Digital capabilities not only can help students to engage and communicate with others in personal life but also to succeed at their workplace later (Krasuska et al. , 2020) . For example, employers’ attention to the digital capabilities of their current and potential employees is rising, since almost every organisation is reliant on such capabilities in transitioning between the various maturity model levels (González-Rojas et al. , 2016) . The skills required to create documents, presentations and spreadsheets, and to communicate via email and social media, are crucial components of human capital because highly skilled users are better positioned to benefit from using the Internet (Zhong, 2011) .  \nGiven the above, it is crucial to include digital capabilities in courses offered by universities. One way to identify digital capabilities in university courses is through the assessment rubrics that course coordinators/academics produce (Pagani et al. , 2016) . Individual features of assessment rubrics comprise the most direct source of information available to quantify the range of digital capabilities assessed across the student journey (Whetstone & Moulaison-Sandy, 2020) . However, manual methods currently in place to quantify students’ attainment of digital capabilities, especially when thousands of courses need to be considered, are highly inadequate (Edwards & Fenwick, 2016) . Building an automa","cbCaitdrC3nB4Lqt","https://ap.wps.com/l/cbCaitdrC3nB4Lqt","pdf",1054846,1,16,"English","en",105,"# Abstract\n# Introduction\n## Why digital capability assessment matters in universities\n## Rubrics as a direct source for identifying assessed capabilities\n## Goal and scope of the study\n## Challenge of manual processing and need for automation\n## Expected outcomes from automated classification","[{\"question\":\"What is the main objective of this study?\",\"answer\":\"To automatically identify digital capabilities in all courses offered by the University of Newcastle by analyzing course rubric data using machine learning classifiers.\"},{\"question\":\"Why is manual assessment of digital capabilities across a university impractical?\",\"answer\":\"Because universities offer thousands of courses, and experts would need extensive time to process and label rubric data at that scale.\"},{\"question\":\"Which machine learning model performed best in identifying digital capabilities?\",\"answer\":\"Support vector machines delivered the best results, with an accuracy of 0.8535 and an F-measure of 0.8338.\"}]","Identifying Digital Capabilities in University Courses - An Automated Machine Learning Approach | PDF",1785819236,40,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"identifying-digital-capabilities-in-university-courses-an-automated-machine-learning-approach","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/identifying-digital-capabilities-in-university-courses-an-automated-machine-learning-approach/123918/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main objective of this study?","Question",{"text":75,"@type":76},"To automatically identify digital capabilities in all courses offered by the University of Newcastle by analyzing course rubric data using machine learning classifiers.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Why is manual assessment of digital capabilities across a university impractical?",{"text":80,"@type":76},"Because universities offer thousands of courses, and experts would need extensive time to process and label rubric data at that scale.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning model performed best in identifying digital capabilities?",{"text":84,"@type":76},"Support vector machines delivered the best results, with an accuracy of 0.8535 and an F-measure of 0.8338.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":29,"slug":118},7,"Healthcare","healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]