A Bibliometric Analysis of Smart Learning Environments Under the Digital Pedagogy Paradigm DOI
Dana Rad, Gavril Rad

Advances in educational technologies and instructional design book series, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 26

Published: Dec. 20, 2024

Focusing on the identification of important themes, new trends, and essential elements that define subject, this report offers a thorough bibliometric analysis research terrain surrounding Smart Learning Environments (SLEs). Three main clusters were found by means investigation keyword co-occurrence network visualization: learner-centric technologies methods, artificial intelligence adaptive learning systems, assessment results. Driven developments in mobile learning, virtual reality, intelligence, analytics, study exposes growing focus tailored, immersive, data-driven educational experiences. The also looks at affecting SLE adoption: technology infrastructure, instructional efficacy, personal attitudes, organizational support. results underline dynamic changing character provide understanding how these settings may be efficiently used into teaching strategies to improve outcomes for learning.

Language: Английский

Insights into Gen Z online food ordering behavior: leveraging eye-tracking and AI for cognitive analysis DOI
Salim Khubchandani, Ramakrishnan Raman

Benchmarking An International Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 28, 2025

Purpose The purpose of this paper is to gain deeper understanding the online food ordering behavior Generation Z when online, and their attention towards nutrition information provided on menus. Their state hunger was used as a moderating variable also understand if altered level attention. Design/methodology/approach Data were collected from 181 university students belonging Gen in city Pune India, with help Tobii (Model: X2-30), screen-based eye-tracking device. Participants invited through offered participate. sample comprised both, male female different states being hungry versus satiated. An AI-powered visual analytics tool analyze relevant metrics. Findings Calorie nutritional menus did not alter consumers’ even among those who claimed be conscious calorie intake. This suggests an attitude–behavior gap consciousness. same case participants claiming satiated, compared hungry. Research limitations/implications study highlights need for innovative strategies effectively communicate Z. Marketers should consider redesigning menu styles content make details more engaging intuitive. Furthermore, leveraging neuromarketing tools can identify subconscious consumer preferences. Health professionals policymakers use these insights bridge consciousness, ensuring that awareness campaigns resonate better Z, regardless state. Practical implications accentuate re-assess style targeting India draw greater Social reveals critical pays information, emphasizing socially impactful foster healthier choices. Educational institutions public health leverage findings design effective education programs tailored Z’s By drivers choices, society promote eating habits combat rising issues like obesity malnutrition. Moreover, incorporating technology-driven into initiatives improve relevance impact interventions, encouraging health-conscious future generation. Originality/value Eye-tracking AI-based has been first time comprehend attitudes behaviors displayed by delve variables consciousness hunger. Neuromarketing consumers.

Language: Английский

Citations

0

Human-Centred Design Meets AI-Driven Algorithms: Comparative Analysis of Political Campaign Branding in the Harris–Trump Presidential Campaigns DOI Creative Commons
Hedda Martina Šola, Fayyaz Hussain Qureshi, Sarwar Khawaja

et al.

Informatics, Journal Year: 2025, Volume and Issue: 12(1), P. 30 - 30

Published: March 18, 2025

This study compared the efficacy of AI neuroscience tools versus traditional design methods in enhancing viewer engagement with political campaign materials from Harris–Trump presidential campaigns. Utilising a mixed-methods approach, we integrated quantitative analysis employing AI’s eye-tracking consumer behaviour metrics (Predict, trained on 180,000 screenings) an AI-LLM neuroscience-based marketing assistant (CoPilot), 67,429 areas interest (AOIs). The original flyer, Al Jazeera article, served as baseline. Professional graphic designers created three redesigned versions, and one was done using recommendations CoPilot. Metrics including total attention, engagement, start end percentage seen were evaluated across 13–14 (AOIs) for each design. Results indicated that human-enhanced Design 1 achieved superior overall performance multiple metrics. While AI-enhanced 3 demonstrated strengths optimising specific AOIs, it did not consistently outperform human-touched designs, particularly text-heavy areas. underscores complex interplay between algorithms human-centred branding, offering valuable insights future research neuromarketing communication strategies. Python, Pandas, Matplotlib, Seaborn, Spearman correlation, Kruskal–Wallis H-test employed data visualisation.

Language: Английский

Citations

0

AI-Powered Eye Tracking for Bias Detection in Online Course Reviews: A Udemy Case Study DOI Creative Commons
Hedda Martina Šola, Fayyaz Hussain Qureshi, Sarwar Khawaja

et al.

Big Data and Cognitive Computing, Journal Year: 2024, Volume and Issue: 8(11), P. 144 - 144

Published: Oct. 25, 2024

The rapid growth of e-learning increased the use digital reviews to influence consumer purchases. In a pioneering approach, we employed AI-powered eye tracking evaluate accuracy predictions in forecasting purchasing patterns. This study examined customer perceptions negative, positive, and neutral by analysing emotional valence, review content, perceived credibility. We measured ‘Attention’, ‘Engagement’, ‘Clarity’, ‘Cognitive Demand’, ‘Time Spent’, ‘Percentage Seen’, ‘Focus’, focusing on differences across categories understand their effects customers correlation between these metrics navigation other screen areas, indicating intent. Our goal was assess predictive power online future buying behaviour. selected Udemy courses, platform with over 70 million learners. Predict (version 1.0.), developed Stanford University, used algorithm neuroscience database (n = 180,000) from Tobii (Tobii X2-30, Pro AB, Danderyd, Sweden). utilised R programming, ANOVA, t-tests for analysis. concludes that AI neuromarketing techniques feedback analysis offer valuable insights educators tailor strategies based susceptibility, thereby sparking interest innovative possibilities using technology neuromarketing.

Language: Английский

Citations

2

Green Investments Promotions and Future Trends in Neuromarketing and Sustainable Finance DOI
Harshi Garg, Mohammad Kashif,

Priyank Sharma

et al.

Advances in business strategy and competitive advantage book series, Journal Year: 2024, Volume and Issue: unknown, P. 245 - 284

Published: Oct. 18, 2024

Green investments provide a major effect on neuromarketing by increasing consumer engagement in sustainable companies selecting for activities that improve permanent ecosystem and fiscal resilience. It analyzes the application of investment, to carry out studies finance green investment. This chapter offers an extensive context while describing neuromarketing, how it might help investors, researchers enable beginning new era. The findings showed positive correlation between age promotion investment trends. tries find these complex intricacies encourage discussion educate general people, researchers, scholars, advertisers since they offer understanding several applications tools, along with their importance making choices; such awareness may commercial efficacy finance.

Language: Английский

Citations

0

A Bibliometric Analysis of Smart Learning Environments Under the Digital Pedagogy Paradigm DOI
Dana Rad, Gavril Rad

Advances in educational technologies and instructional design book series, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 26

Published: Dec. 20, 2024

Focusing on the identification of important themes, new trends, and essential elements that define subject, this report offers a thorough bibliometric analysis research terrain surrounding Smart Learning Environments (SLEs). Three main clusters were found by means investigation keyword co-occurrence network visualization: learner-centric technologies methods, artificial intelligence adaptive learning systems, assessment results. Driven developments in mobile learning, virtual reality, intelligence, analytics, study exposes growing focus tailored, immersive, data-driven educational experiences. The also looks at affecting SLE adoption: technology infrastructure, instructional efficacy, personal attitudes, organizational support. results underline dynamic changing character provide understanding how these settings may be efficiently used into teaching strategies to improve outcomes for learning.

Language: Английский

Citations

0