20.500.12556/DKUM-87040 Assessing Perceived Trust and Satisfaction with Multiple Explanation Techniques in XAI-Enhanced Learning Analytics This study aimed to observe the impact of eight explainable AI (XAI) explanation techniques on user trust and satisfaction in the context of XAI-enhanced learning analytics while comparing two groups of STEM college students based on their Bologna study level, using various established feature relevance techniques, certainty, and comparison explanations. Overall, the students reported the highest trust in local feature explanation in the form of a bar graph. Additionally, master's students presented with global feature explanations also reported high trust in this form of explanation. The highest measured explanation satisfaction was observed with the local feature explanation technique in the group of bachelor's and master's students, with master's students additionally expressing high satisfaction with the global feature importance explanation. A detailed overview shows that the two observed groups of students displayed consensus in favored explanation techniques when evaluating trust and explanation satisfaction. Certainty explanation techniques were perceived with lower trust and satisfaction than were local feature relevance explanation techniques. The correlation between itemized results was documented and measured with the Trust in Automation questionnaire and Explanation Satisfaction Scale questionnaire. Master's-level students self-reported an overall higher understanding of the explanations and higher overall satisfaction with explanations and perceived the explanations as less harmful. explainable artificial intelligence learning analytics XAI techniques trust explanation satisfaction umetna inteligenca analitično učenje zaupanje zadovoljstvo true false true MDPI Angleški jezik Slovenski jezik https://www.mdpi.com/journal/electronics Članek v reviji 2024-02-12 14:10:44 2024-02-12 14:23:53 2024-05-21 13:19:07 0000-00-00 00:00:00 2023 0 0 Str. 1-23 Št. 12, št. članka 2594 Letn. 12 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2023-05-08 2023-06-06 2023-06-08 004.8 155107331 10.3390/electronics12122594 2079-9292 Brdnik-2023-Assessing_Perceived_Trust_and_Sati.pdf Brdnik-2023-Assessing_Perceived_Trust_and_Sati.pdf 1 BC82645F4AA7A1E80DF0AABDA635D227 164824a8f3cd65796765633ffc3f0141802b2164ef2722822b1b8765ff091157 cbae95de-c9a9-11ee-97b9-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=176086 https://www.mdpi.com/2079-9292/12/12/2594 0 dbdecc26-c9a9-11ee-97b9-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=176087 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0