Advanced search
1 file | 1.22 MB Add to list

Curricular design analysis : a data-driven perspective

Author
Organization
Abstract
Learning analytics has been as used a tool to improve the learning process mainly at the micro-level (courses and activities). However, another of the key promises of Learning Analytics research is to create tools that could help educational institutions at the meso- and macro-level to gain a better insight of the inner workings of their programs, in order to tune or correct them. This work presents a set of simple techniques that applied to readily available historical academic data could provide such insights. The techniques described are real course difficulty estimation, course impact on the overall academic performance of students, curriculum coherence, dropout paths and load/performance graph. The usefulness of these techniques is validated through their application to real academic data from a Computer Science program. The results of the analysis are used to obtain recommendations for curriculum re-design.

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 1.22 MB

Citation

Please use this url to cite or link to this publication:

MLA
Mendez, Gonzalo et al. “Curricular Design Analysis : a Data-driven Perspective.” JOURNAL OF LEARNING ANALYTICS 1.3 (2014): 84–119. Print.
APA
Mendez, G., Ochoa, X., Chiluiza, K., & De Wever, B. (2014). Curricular design analysis : a data-driven perspective. JOURNAL OF LEARNING ANALYTICS, 1(3), 84–119.
Chicago author-date
Mendez, Gonzalo, Xavier Ochoa, Katherine Chiluiza, and Bram De Wever. 2014. “Curricular Design Analysis : a Data-driven Perspective.” Journal of Learning Analytics 1 (3): 84–119.
Chicago author-date (all authors)
Mendez, Gonzalo, Xavier Ochoa, Katherine Chiluiza, and Bram De Wever. 2014. “Curricular Design Analysis : a Data-driven Perspective.” Journal of Learning Analytics 1 (3): 84–119.
Vancouver
1.
Mendez G, Ochoa X, Chiluiza K, De Wever B. Curricular design analysis : a data-driven perspective. JOURNAL OF LEARNING ANALYTICS. Society for Learning Analytics Research; 2014;1(3):84–119.
IEEE
[1]
G. Mendez, X. Ochoa, K. Chiluiza, and B. De Wever, “Curricular design analysis : a data-driven perspective,” JOURNAL OF LEARNING ANALYTICS, vol. 1, no. 3, pp. 84–119, 2014.
@article{8617799,
  abstract     = {Learning analytics has been as used a tool to improve the learning process mainly at the micro-level (courses and activities).  However, another of the key promises of Learning Analytics research is to create tools that could help educational institutions at the meso- and macro-level to gain a better insight of the inner workings of their programs, in order to tune or correct them. This work presents a set of simple techniques that applied to readily available historical academic data could provide such insights. The techniques described are real course difficulty estimation, course impact on the overall academic performance of students, curriculum coherence, dropout paths and load/performance graph. The usefulness of these techniques is validated through their application to real academic data from a Computer Science program. The results of the analysis are used to obtain recommendations for curriculum re-design.},
  author       = {Mendez, Gonzalo and Ochoa, Xavier and Chiluiza, Katherine and De Wever, Bram},
  issn         = {1929-7750},
  journal      = {JOURNAL OF LEARNING ANALYTICS},
  language     = {eng},
  number       = {3},
  pages        = {84--119},
  publisher    = {Society for Learning Analytics Research},
  title        = {Curricular design analysis : a data-driven perspective},
  url          = {http://dx.doi.org/10.18608/jla.2014.13.6},
  volume       = {1},
  year         = {2014},
}

Altmetric
View in Altmetric