Research line: Interaction and e learning
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This document summarizes presentations from a Doctoral Consortium on Interaction and eLearning. It includes summaries of 8 projects presented: 1) Designing a model to estimate the impact and cost effectiveness of online learning platforms. 2) Using personal social networks as a facilitating tool for collaborative knowledge construction. 3) Evaluating the quality and usability of educational websites in Portugal. 4) Proposing an IT governance framework for public universities in Ecuador. 5) Learning from complementary ways of developing experimental competences. 6) Analyzing the integration of software solutions to develop learning ecosystems. 7) Developing artificial neural network applications for computer-aided diagnosis and their use as an educational tool. 8) Rafael Molina Carmona moderated
Research line: Interaction and e learning
- 2. • Doris Meza-Bolaños, Patricia Compañ-Rosique and Rosana Satorre-Cuerda. Designing a model to es,mate the impact and cost effec,veness of online learning plaRorms • Dunia Inés Jara-Roa, María-Soledad Ramírez-Montoya and Marcos Cabezas González. Personal social network as a facilita,ng tool for collabora,ve knowledge construc,on. • José Antonio Cordón-García, Raquel Gómez Díaz and Ana M. Santos. Websites of learning support in Primary and High School in Portugal: a performance and usability study (Engineering and Educa-on) • Faraón Llorens-Largo and Francisco Xavier Valverde Alulema. Proposal of a Framework of IT Governance for Public Universi,es in Ecuador • Natércia Lima, Clara Viegas and Francisco J. García-Peñalvo. Learning from complementary ways of developing experimental competences • Alicia García-Holgado and Francisco J. García-Peñalvo. Learning ecosystems for knowledge management in educa,onal ins,tu,ons (Medicine and educa-on) • Jorge Hernández Rodríguez, María José Rodríguez Conde and Francisco Javier Cabrero Fraile. Ar,ficial Neural Networks applica,ons in Computer Aided Diagnosis. System design and use as an educa,onal tool TEEM16 - Doctoral Consor,um
- 3. Interac,on and eLearning Designing a model to es,mate the impact and cost effec,veness of online learning plaRorms Doris Meza-Bolaños, Ecuador, Universidad Central del Ecuador, dmeza@uce.edu.ec. Patricia Compañ-Rosique, Universidad de Alicante, patricia.company@ua.es, Rosana Satorre- Cuerda, Universidad de Alicante, There are different methodologies that have adempted to measure profitability and impact of using online learning plaRorms, all of which focus on a set of quan,fiable and non-quan,fiable aspects. These methods consider different items from various perspec,ves. The purpose of this work is to assess each one and determine the suitable indicators applicable to the reality of higher educa-on in Ecuador. A hybrid model with characteris,cs from different perspec,ves could be designed with these indicators. TEEM16 - Doctoral Consor,um
- 6. Engineering and Educa,on Proposal of a Framework of IT Governance for Public Universi-es in Ecuador Francisco Valverde-Alulema, Ecuador, Universidad Central del Ecuador, fvalverde@uce.edu.ec Faraón Llorens-Largo,, Universidad de Alicante, faraon.llorens@ua.es This paper describes the u,lity of a framework of corpora,ve IT (Informa,on Technology) Governance and how a specific, simpler and scalable model can be a reference and used in the Ecuadorian public universi,es. The IT department objec-ves must be aligned with the ins-tu-onal objec-ves. Ini,al data are collected trough instruments, using a generic framework as reference and applying the model to the university. The results will jus,fy and validate the contribu,on of this research. It is finally concluded that, the IT not only serve to automate the processes, but they must also get involved in the core business and strategy. TEEM16 - Doctoral Consor,um
- 9. Medicine and Educa,on Ar,ficial Neural Networks applica,ons in Computer Aided Diagnosis. System design and use as an educa,onal tool Jorge Hernández Rodríguez, Spain, Programa de Doctorado de Formación en la Sociedad del Conocimiento, Universidad de Salamanca, jorgeh@usal.es María José Rodríguez Conde, Ins,tuto Universitario de Ciencias de la Educación (IUCE), Universidad de Salamanca, mjrconde@usal.es Francisco Javier Cabrero Fraile, Departamento de Ciencias Biomédicas y del Diagnós,co (Facultad de Medicina), Universidad de Salamanca, cabrero@usal.es Computer Aided Diagnosis and Detec,on (CAD), is an automated tool for specialists who interpret medical images, that provides informa,on which can be used as a “second opinion”, or supplementary data in their decision making process. The main objec,ve of the first phase of this disserta,on is the development of CAD schemes, based in the machine learning models called Ar-ficial Neural Networks, which could be applied to different image modali-es. The valida,on of the system in clinical prac,ce and the inves,ga,on of their possible uses as an educa,onal tool for trainees during medical residency programs is the second phase. TEEM16 - Doctoral Consor,um