Teaching Innovations in Economics

Luis F. Rivera-Galicia holds a Ph.D. in Economics from the University of Alcalá and a B.Sc. in Mathematics and Computer Science from the Complutense University of Madrid. He is currently an associate professor of Quantitative Methods at the University of Alcalá, where he teaches statistical techniques for economics and business at both undergraduate and postgraduate levels. He is also a research associate at the Institute for Economic and Social Analysis. His scholarly work focuses on the application of mathematical and statistical models to social sciences, business, and education. He has authored or co-authored over 70 scientific publications, including journal articles, books, and conference papers. In addition to his academic work, he regularly contributes to research projects funded by Spanish and European agencies. His areas of interest include educational innovation, econometrics, and applied statistics.José-María Montero is a professor of Applied Economics and Statistics at the University of Castilla-La Mancha. He currently serves as the president of International Association of Applied Economics (ASEPELT) and director of the International Academic Council of Exponential Education. He has participated in numerous international academic committees and scientific councils, including the Social Sciences and Humanities Research Council of Canada and the Athenian Policy Forum. His academic trajectory includes 32 authored books, over 50 book chapters, and more than 100 articles in journals indexed in Scopus and Clarivate. He has led over 40 competitive research projects and has served as editor-in-chief or editorial board member of over 20 academic journals. He has been a keynote speaker alongside Nobel Laureates in both Economics and Medicine and is a recognized thought leader in applied economics and education policy.Carmelo García Pérez is a full professor of Quantitative Methods at the University of Alcalá, where he also earned his Ph.D. in Economics. His academic leadership includes serving as a vice-rector at the university and as deputy director-general for Economic Forecasting and Short-Term Analysis at the Spanish Ministry of Economy and Competitiveness. In that capacity, he represented Spain at the OECD’s New Approaches to Economic Challenges (NAEC) program. His research focuses on the measurement and analysis of poverty, inequality, and income distribution, with publications in high-impact journals and leading academic publishers. He has coordinated numerous national and international research projects and has played a key role in integrating quantitative research into public policy analysis. He is also active in teaching innovation and methodological development in social sciences.Eva Senra Díaz is a full professor of Quantitative Methods for Economics and Business at the University of Alcalá. She earned her Ph.D. in Economics from the University Carlos III of Madrid and a degree in Mathematics from the Complutense University of Madrid. She currently serves as a vice-rector for Economics, Entrepreneurship and Employment at the University of Alcalá and is a member of the Academic Committee of the Doctoral Program in Economics and Business Management. Her professional experience includes senior roles at the Economic Office of the Spanish Prime Minister, where she was responsible for macroeconomic analysis and forecasting. She has published extensively in the fields of applied economics, statistics, and economic forecasting and has supervised several doctoral theses.

• Part 1: Theoretical frameworks and critical reflections on AI and teaching.- A critical framework for pedagogical evaluation in generative environments: Integrating heuristic serendipity and assisted materiality in higher education.- Reinventing the human in the age of AI.- From enigma to a generative AI teaching-learning paradigm.- Part 2: Artificial intelligence as a cross-cutting tool in economics education.- Artificial intelligence applied to teaching and research in welfare economics, inequality, and poverty.- Using artificial intelligence (AI) in the teaching of economics and business at university level: Resources and examples.- Integrating AI and data analysis strategies in macroeconomics pedagogy: The case of the Phillips curve.- Personalized learning paths in microeconomics.- Teaching innovation in the teaching of economic history in the bachelor's degree in tourism.- Part 3: Technological innovations and AI applications in the classroom.- Personalizing the teaching of programming and social statistics through AI.- Python tools for teaching econometrics through interactive learning.- Integrating AI and visual tools in economics education: Enhancing pedagogy through mermaid and large language models.- Code generation through generative artificial intelligence: Solving various relevant mathematical and applied economics problems.- Part 4: Active learning, simulations, and hybrid environments.- Enhancing strategic thinking, resilience and conflict resolution skills through artificial-intelligence driven simulations.- Market simulations and custom GPTS as tools for active learning in “Introduction to Economics”.- Designing effective hybrid learning environments in higher education: A case study of successful implementation and evaluation.- When AI takes a seat at the desk: Innovating business education.- Part 5: Institutional, social, and motivational perspectives.- Data, educational technology, and teaching innovation: Establishing an observatory to enhance student motivation and academic performance in business administration.- Perception of student engagement in higher education: A comparative analysis.- Innovative teaching in business intelligence: Adapting to advanced tools and market demands.- Humor, corporate diplomacy and SCM in the classroom.- Artificial intelligence applied to mathematics in economics.