Setting accessibility preferences about learning objects within adaptive elearning systems: User experience and organizational aspects

Abstract

Higher and further education providers are facing the challenge of supporting the interaction needs of an increasing number of students who feature accessibility preferences to use both elearning contents and services. In the next future, we can expect that, within adaptive elearning systems, both automatic and manual procedures will interoperate to elicit users' interaction needs for ensuring accessibility. In this paper, we report findings from the user experience with the self‐assessment of interaction needs, as part of a content personalization system, which tackles possible mismatches in the interaction between the user and the learning objects. All stakeholders involved in providing this service along with intended user groups (students with visual, auditory or mobility impairments, and without impairments) participated in the evaluation with over 100 users described in this paper. From the evaluation, results follow that our approach allows students to self‐assess and report adequately their interaction preferences. Furthermore, the paper describes findings of interest and open issues about how massive online courses may address the accessibility needs of an increasing number of elearning users.

Research challenges in accessible MOOCs: a systematic literature review 2008–2016

“…The existing relevant studies have sufficiently explained the general concepts of accessibility, disability, diversity, universal access as well as the demographics [22][23][24][25][26][27]29,30,33,35,38,[42][43][44]46,54,56,57,60,61]. In the same way, the Convention of the Rights of Persons with Disabilities [29,44,59] and related legislation had also been addressed, both in general [29,44,61] and countryspecific level, e.g.…”

Proposal of an Architecture for the Integration of a Chatbot with Artificial Intelligence in a Smart Campus for the Improvement of Learning

“…Unlike other AI models, the Chatbot is constantly interacting with students and obtaining information from them. Therefore, the development of, in addition to recommending activities, seeks to learn from each student by identifying their needs directly [27].…”

“…The most common models of AI are expert systems, recognition systems, behavior-based intelligence, etc. Ideally, it should focus on a type of model that fits the needs of the students and whose interaction contributes to the motivation of the students [27]. One of the tools that most enhances the handling and interaction with users is the Chatbot.…”

Intelligence in educational environments

“…Aspects" (Rodriguez-Ascaso, Boticario, Finat, & Petrie, 2017), where the authors have reported the experience acquired by students as users of a content personalization systems, which tackles possible mismatches in the interaction between the user and the learning objects. This work concludes that the selected approach permit students to report their…”

“…Another key aspect of artificial intelligence (AI) in education is accessibility. In this respect, content personalization is in the focus of the paper “Setting Accessibility Preferences About Learning Objects Within Adaptive elearning Systems: User Experience and Organizational Aspects” (Rodriguez‐Ascaso, Boticario, Finat, & Petrie, ), where the authors have reported the experience acquired by students as users of a content personalization systems, which tackles possible mismatches in the interaction between the user and the learning objects. This work concludes that the selected approach permit students to report their interaction preferences and open the issue of how to solve different accessibility needs in massive online courses.…”