{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T11:39:08Z","timestamp":1774438748844,"version":"3.50.1"},"reference-count":58,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T00:00:00Z","timestamp":1729814400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Institute for Neuromarketing &amp; Intellectual Property"},{"name":"Oxford Business College"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>The rapid growth of e-learning increased the use of digital reviews to influence consumer purchases. In a pioneering approach, we employed AI-powered eye tracking to evaluate the accuracy of predictions in forecasting purchasing patterns. This study examined customer perceptions of negative, positive, and neutral reviews by analysing emotional valence, review content, and perceived credibility. We measured \u2018Attention\u2019, \u2018Engagement\u2019, \u2018Clarity\u2019, \u2018Cognitive Demand\u2019, \u2018Time Spent\u2019, \u2018Percentage Seen\u2019, and \u2018Focus\u2019, focusing on differences across review categories to understand their effects on customers and the correlation between these metrics and navigation to other screen areas, indicating purchasing intent. Our goal was to assess the predictive power of online reviews on future buying behaviour. We selected Udemy courses, a platform with over 70 million learners. Predict (version 1.0.), developed by Stanford University, was used with the algorithm on the consumer neuroscience database (n = 180,000) from Tobii eye tracking (Tobii X2-30, Tobii Pro AB, Danderyd, Sweden). We utilised R programming, ANOVA, and t-tests for analysis. The study concludes that AI neuromarketing techniques in digital feedback analysis offer valuable insights for educators to tailor strategies based on review susceptibility, thereby sparking interest in the innovative possibilities of using AI technology in neuromarketing.<\/jats:p>","DOI":"10.3390\/bdcc8110144","type":"journal-article","created":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T07:51:29Z","timestamp":1729842689000},"page":"144","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["AI-Powered Eye Tracking for Bias Detection in Online Course Reviews: A Udemy Case Study"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1495-3606","authenticated-orcid":false,"given":"Hedda Martina","family":"\u0160ola","sequence":"first","affiliation":[{"name":"Oxford Centre For Applied Research and Entrepreneurship (OxCARE), Oxford Business College, 65 George Street, Oxford OX1 2BQ, UK"},{"name":"Institute for Neuromarketing & Intellectual Property, Jurja Ves III spur no 4, 10000 Zagreb, Croatia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1305-9493","authenticated-orcid":false,"given":"Fayyaz Hussain","family":"Qureshi","sequence":"additional","affiliation":[{"name":"Oxford Business College, 65 George Street, Oxford OX1 2BQ, UK"}]},{"given":"Sarwar","family":"Khawaja","sequence":"additional","affiliation":[{"name":"Oxford Business College, 65 George Street, Oxford OX1 2BQ, UK"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,25]]},"reference":[{"key":"ref_1","first-page":"e290627","article-title":"Dise\u00f1o de un modelo de atenci\u00f3n visual para campa\u00f1as de comunicaci\u00f3n. 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