Application of Soft Computing Technologies toward Assessment and Skills Development

Schools and universities face multiple challenges when they target initiating or expanding undergraduate programs. Education has traditionally utilized a teacher-centered educational and assessment approach. Only few attempts exist to involve objective feedback and non-traditional assessment methods and technologies to improve the processes of teaching, learning, and education in general.

[1]  Emilio Corchado,et al.  Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit , 2002, Data Mining and Knowledge Discovery.

[2]  Fanny Klett,et al.  The Design of a Sustainable Competency-Based Human Resources Management: A Holistic Approach , 2010 .

[3]  Simone G. O. Fiori.  Visualization of Riemannian-manifold-valued elements by multidimensional scaling , 2011, Neurocomputing.

[4]  Álvaro Herrero,et al.  Neural visualization of network traffic data for intrusion detection , 2011, Appl. Soft Comput..

[5]  Technical skills assessment as part of the selection process for a fellowship in minimally invasive surgery , 2009, Surgical Endoscopy.

[6]  Emilio Corchado,et al.  Optimizing the operating conditions in a high precision industrial process using soft computing techniques , 2012, Expert Syst. J. Knowl. Eng..

[7]  Emilio Corchado,et al.  Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit , 2002, ICANN.

[8]  David Radcliffe,et al.  Innate design abilities of first year engineering and industrial design students , 1990 .

[9]  D. Freedman,et al.  Asymptotics of Graphical Projection Pursuit , 1984 .

[10]  Teodor P Grantcharov,et al.  Can everyone achieve proficiency with the laparoscopic technique? Learning curve patterns in technical skills acquisition. , 2009, American journal of surgery.

[11]  John W. Tukey,et al.  A Projection Pursuit Algorithm for Exploratory Data Analysis , 1974, IEEE Transactions on Computers.

[12]  Emilio Corchado,et al.  A three-step unsupervised neural model for visualizing high complex dimensional spectroscopic data sets , 2011, Pattern Analysis and Applications.

[13]  Lluís A. Belanche Muñoz,et al.  Feature and model selection with discriminatory visualization for diagnostic classification of brain tumors , 2010, Neurocomputing.

[14]  L. Behar-Horenstein,et al.  A case study examining classroom instructional practices at a U.S. dental school. , 2005, Journal of dental education.

[15]  Emilio Corchado,et al.  A maximum likelihood Hebbian learning-based method to an agent-based architecture , 2009, Int. J. Comput. Math..

[16]  D. Chambers,et al.  Predictors of academic performance for applicants to an international dental studies program in the United States. , 2011, Journal of dental education.

[17]  I. Polyzois,et al.  Can evaluation of a dental procedure at the outset of learning predict later performance at the preclinical level? A pilot study. , 2011, European journal of dental education : official journal of the Association for Dental Education in Europe.

[18]  H. Hotelling.  Analysis of a complex of statistical variables into principal components. , 1933 .