Affect-based, multimodal, video tutoring system for a neuromarketing
Peržiūrėti/ Atidaryti
Data
2020Autorius
Kaklauskas, Artūras
Ubartė, Ieva
Bučinskas, Vytautas
Skirmantas, Darius
Raupys, Dainius
Metaduomenys
Rodyti detalų aprašąSantrauka
Considerable research has been conducted globally showinghow study results are substantially conditional to the interest and productivity of a learner in the studies and the emotions and stress the learner experiences. Scholars emphasize that learning should be pleasing, enticing, and emotionally positive leading to increased effectiveness of the studying. Tests were conducted regarding the effectiveness of the MSc Property management studies process among students. Development of the ARTSY Model involved five iterative phases over the course of the research. ARTSY Model, intelligent and physiological technologies that had helped as the foundation for creating the Affect-based, Multimodal, Video Tutoring System for a Neuromarketing (ARTSY) were applied for this research. The research motivation and one of the main purposes areto increasestudents learning productivity, interest, emotions and decrease stress levels. According to this research motivation, ARTSY was developed.Upon comparison with the most advanced, existing affective tutoring systems, two innovative elements aredistinguishing ARTSY. First, automatic means to develop and select the most effective variants from thousands of textual and video learning material alternatives by considering learner interest, productivity and stress levels. Secondly, exams or tests are unnecessary for assessing student knowledge levels by employing the newly developed Calculating a Student’s Self-assessment Grade.ARTSY’s future betterments are expected to achieve comprehensive and dependable, real-time information, not only about student needs but also about existing opportunities. A consequent outcome could be greater flexibility in the study process for students. This paper composed of Introduction (Section 1), Research background (Section 2), ARTSY Model description(Section 3) and the Construction of ARTSY (Section 4). The conclusions and notes for future study provide the ending to this article in Section 5.