Learning data analytics through a Problem Based Learning course

Miguel Núñez-Del-Prado, Zoila del Rosario Gómez Gamarra

Producción científica: Contribución a una conferencia

10 Citas (Scopus)

Resumen

Achieving significant meaningful in Engineering is always a challenge. Problem or Project Based Learning (PBL) is one of the different methodologies that tries to enhance a learning process based on student inquiries and innovative solutions to solve real problems. In the present effort, we present a new approach for assessing the impact of PBL applied to analytics courses for Information Engineering students. We describe the analysis, design, implementation, evaluation and visualization of a Web mining platform as well as of a Library Analysis System. These projects concern the Web Analytics and Data Mining courses, respectively. The former provides students the opportunity to develop a real project ranging from data acquisition, from a Web site, data storing, analytics and visualization. The latter course furnishes a framework to learn and to apply the Knowledge Data Discovery (KDD) methodology over a library dataset to profile customers and understand business dynamics. In both courses, students are confronted to handle big amounts of heterogeneous data.

Conferencia

ConferenciaEDUNINE 2017 - IEEE World Engineering Education Conference: Engineering Education - Balancing Generalist and Specialist Formation in Technological Carriers: A Current Challenge, Proceedings
Período2/05/17 → …

Palabras clave

  • Computer and Information
  • Data mining
  • Problem Based Learning
  • Science Education
  • Web analytics

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