Statistical Validation of E-learning Assessment

Jesús Ortiz; Antonio Aznar; José I. Hernando; Adriana Ortiz; Jaime Cervera

doi:doi:10.11648/j.tecs.20160101.13

| Peer-Reviewed

Statistical Validation of E-learning Assessment

Jesús Ortiz, Antonio Aznar, José I. Hernando, Adriana Ortiz, Jaime Cervera

Published in Teacher Education and Curriculum Studies (Volume 1, Issue 1)

Received: 5 September 2016 Accepted: 14 September 2016 Published: 10 October 2016

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

This paper focuses on how to fulfill the objectivity and reliability goals, as well as the efficiency of the e-learning evaluation tools, and their integration in a blended evaluation system. In order to contribute to these goals, a new branch of statistics, i.e. “Statistical Learning”, has been chosen to support this study. The proposed techniques can be very simply implemented with little knowledge of arithmetic and with the help of a standard spreadsheet. These techniques can allow us to get the whole picture of the evaluation procedure output, in order to systematically sort the main categories of the different students, and to easily identify the outliers for further assessment.

Published in	Teacher Education and Curriculum Studies (Volume 1, Issue 1)
DOI	10.11648/j.tecs.20160101.13
Page(s)	20-27
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Computer-Based Assessment, On-Line Learning, Questionnaire, Computer-Assisted Learning

References

[1]	Jung, I., Choi, S., Lim, C. & Leem, J. (2002). Effects of Different Types of Interaction on Learning Achievement, Satisfaction and Participation in Web-Based Instruction. Innovations in Education and Teaching International. Vol. 39. No 2. pp. 153-162.
[2]	Jones, N. & Sze Lau A. M. (2010). Blending learning: widening participation in higher education. Innovations in Education and Teaching International. Vol. 47, No 4. pp. 405-416.
[3]	Aznar, A. & Hernando, J. I. (2011). Herramienta informática de auto-corrección mediante MOODLE. EvalTrends Proceeding book. Pp. 24-34.
[4]	Aznar, A., Hernando, J. I., Cervera, J. & Ortiz, J. (2012). Educational self-correcting application towards continuous assessment for e-learning in analysis of building structures. Educación y Futuro. Vol. 2: pp. 2-15.
[5]	Aznar, A. & Hernando, J. I. (2014). A New Automatic On-Line Evaluation for Graphics Applied to Building Structures. EDULEARN14-Proceedings 1. IATED. pp. 3061–3068.
[6]	Aznar, A., Hernando, J. I., Ortiz, H. & Cervera, J. (2014). Toward the Possibility of Automatic Evaluation of On-Line Graphics. ICEILT Proceeding book. pp. 388-395.
[7]	Aznar, A. & Hernando, J.I. (2014). Novel Educational Assessment for Bulding Structures: Automatic Evaluation of On-Line Graphics. IETC Proceedings book. Pp. 814-821.
[8]	Aznar, A. & Hernando, J. I. (2015). Novel educational assessment for building structures: Automatic evaluation of on-line graphics. Social and Behavioral Sciences. Elsevier. Vol 176. pp. 602-609.
[9]	Hastie, T., Tibshirani, R. & Friedman, J. (2001). The Elements of Statistical Learning Springer. Vol. 1. New York: Springer.
[10]	Hahn, G. H. & Shapiro, S. S. (1967). Statistical models in engineering. 130-134.
[11]	Fan, J. & Yao Q. (2005). Non-linear Time Series: Nonparametric and Parametric Methods. Springer.
[12]	Kessler, J. (2012). Brave new world without teachers, or learning, or thinkers. Letters, Financial Times, August, 18.

Cite This Article

Plain Text BibTeX RIS

APA Style

Jesús Ortiz, Antonio Aznar, José I. Hernando, Adriana Ortiz, Jaime Cervera. (2016). Statistical Validation of E-learning Assessment. Teacher Education and Curriculum Studies, 1(1), 20-27. https://doi.org/10.11648/j.tecs.20160101.13

Copy | Download

ACS Style

Jesús Ortiz; Antonio Aznar; José I. Hernando; Adriana Ortiz; Jaime Cervera. Statistical Validation of E-learning Assessment. Teach. Educ. Curric. Stud. 2016, 1(1), 20-27. doi: 10.11648/j.tecs.20160101.13

Copy | Download

AMA Style

Jesús Ortiz, Antonio Aznar, José I. Hernando, Adriana Ortiz, Jaime Cervera. Statistical Validation of E-learning Assessment. Teach Educ Curric Stud. 2016;1(1):20-27. doi: 10.11648/j.tecs.20160101.13

Copy | Download

@article{10.11648/j.tecs.20160101.13,
  author = {Jesús Ortiz and Antonio Aznar and José I. Hernando and Adriana Ortiz and Jaime Cervera},
  title = {Statistical Validation of E-learning Assessment},
  journal = {Teacher Education and Curriculum Studies},
  volume = {1},
  number = {1},
  pages = {20-27},
  doi = {10.11648/j.tecs.20160101.13},
  url = {https://doi.org/10.11648/j.tecs.20160101.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.tecs.20160101.13},
  abstract = {This paper focuses on how to fulfill the objectivity and reliability goals, as well as the efficiency of the e-learning evaluation tools, and their integration in a blended evaluation system. In order to contribute to these goals, a new branch of statistics, i.e. “Statistical Learning”, has been chosen to support this study. The proposed techniques can be very simply implemented with little knowledge of arithmetic and with the help of a standard spreadsheet. These techniques can allow us to get the whole picture of the evaluation procedure output, in order to systematically sort the main categories of the different students, and to easily identify the outliers for further assessment.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Statistical Validation of E-learning Assessment
AU  - Jesús Ortiz
AU  - Antonio Aznar
AU  - José I. Hernando
AU  - Adriana Ortiz
AU  - Jaime Cervera
Y1  - 2016/10/10
PY  - 2016
N1  - https://doi.org/10.11648/j.tecs.20160101.13
DO  - 10.11648/j.tecs.20160101.13
T2  - Teacher Education and Curriculum Studies
JF  - Teacher Education and Curriculum Studies
JO  - Teacher Education and Curriculum Studies
SP  - 20
EP  - 27
PB  - Science Publishing Group
SN  - 2575-4971
UR  - https://doi.org/10.11648/j.tecs.20160101.13
AB  - This paper focuses on how to fulfill the objectivity and reliability goals, as well as the efficiency of the e-learning evaluation tools, and their integration in a blended evaluation system. In order to contribute to these goals, a new branch of statistics, i.e. “Statistical Learning”, has been chosen to support this study. The proposed techniques can be very simply implemented with little knowledge of arithmetic and with the help of a standard spreadsheet. These techniques can allow us to get the whole picture of the evaluation procedure output, in order to systematically sort the main categories of the different students, and to easily identify the outliers for further assessment.
VL  - 1
IS  - 1
ER  -

Copy | Download

Author Information

Jesús Ortiz

Department of Building Structures, Architecture School, Technical University, Madrid, Spain
Antonio Aznar

Department of Building Structures, Architecture School, Technical University, Madrid, Spain
José I. Hernando

Department of Building Structures, Architecture School, Technical University, Madrid, Spain
Adriana Ortiz

Department of Nuclear Services, IDOM (Ingenieria y Direccion de Obrasy Montaje) International, Madrid, Spain
Jaime Cervera

Department of Building Structures, Architecture School, Technical University, Madrid, Spain

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Jesús Ortiz, Antonio Aznar, José I. Hernando, Adriana Ortiz, Jaime Cervera. (2016). Statistical Validation of E-learning Assessment. Teacher Education and Curriculum Studies, 1(1), 20-27. https://doi.org/10.11648/j.tecs.20160101.13

Copy | Download

ACS Style

Jesús Ortiz; Antonio Aznar; José I. Hernando; Adriana Ortiz; Jaime Cervera. Statistical Validation of E-learning Assessment. Teach. Educ. Curric. Stud. 2016, 1(1), 20-27. doi: 10.11648/j.tecs.20160101.13

Copy | Download

AMA Style

Jesús Ortiz, Antonio Aznar, José I. Hernando, Adriana Ortiz, Jaime Cervera. Statistical Validation of E-learning Assessment. Teach Educ Curric Stud. 2016;1(1):20-27. doi: 10.11648/j.tecs.20160101.13

Copy | Download

@article{10.11648/j.tecs.20160101.13,
  author = {Jesús Ortiz and Antonio Aznar and José I. Hernando and Adriana Ortiz and Jaime Cervera},
  title = {Statistical Validation of E-learning Assessment},
  journal = {Teacher Education and Curriculum Studies},
  volume = {1},
  number = {1},
  pages = {20-27},
  doi = {10.11648/j.tecs.20160101.13},
  url = {https://doi.org/10.11648/j.tecs.20160101.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.tecs.20160101.13},
  abstract = {This paper focuses on how to fulfill the objectivity and reliability goals, as well as the efficiency of the e-learning evaluation tools, and their integration in a blended evaluation system. In order to contribute to these goals, a new branch of statistics, i.e. “Statistical Learning”, has been chosen to support this study. The proposed techniques can be very simply implemented with little knowledge of arithmetic and with the help of a standard spreadsheet. These techniques can allow us to get the whole picture of the evaluation procedure output, in order to systematically sort the main categories of the different students, and to easily identify the outliers for further assessment.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Statistical Validation of E-learning Assessment
AU  - Jesús Ortiz
AU  - Antonio Aznar
AU  - José I. Hernando
AU  - Adriana Ortiz
AU  - Jaime Cervera
Y1  - 2016/10/10
PY  - 2016
N1  - https://doi.org/10.11648/j.tecs.20160101.13
DO  - 10.11648/j.tecs.20160101.13
T2  - Teacher Education and Curriculum Studies
JF  - Teacher Education and Curriculum Studies
JO  - Teacher Education and Curriculum Studies
SP  - 20
EP  - 27
PB  - Science Publishing Group
SN  - 2575-4971
UR  - https://doi.org/10.11648/j.tecs.20160101.13
AB  - This paper focuses on how to fulfill the objectivity and reliability goals, as well as the efficiency of the e-learning evaluation tools, and their integration in a blended evaluation system. In order to contribute to these goals, a new branch of statistics, i.e. “Statistical Learning”, has been chosen to support this study. The proposed techniques can be very simply implemented with little knowledge of arithmetic and with the help of a standard spreadsheet. These techniques can allow us to get the whole picture of the evaluation procedure output, in order to systematically sort the main categories of the different students, and to easily identify the outliers for further assessment.
VL  - 1
IS  - 1
ER  -

Copy | Download