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An empirical study of neural network-based audience response technology in a human anatomy course for pharmacy students.

Fern�ndez-Alem�n, Jos� Luis; L�pez-Gonz�lez, Laura; Gonz�lez-Sequeros, Ofelia; Jayne, Chrisina; L�pez-Jim�nez, Juan Jos�; Carrillo-de-Gea, Juan Manuel; Toval, Ambrosio


Jos� Luis Fern�ndez-Alem�n

Laura L�pez-Gonz�lez

Ofelia Gonz�lez-Sequeros

Chrisina Jayne

Juan Jos� L�pez-Jim�nez

Juan Manuel Carrillo-de-Gea

Ambrosio Toval


This paper presents an empirical study of a formative neural network-based assessment approach, by using mobile technology to provide pharmacy students with intelligent diagnostic feedback. An unsupervised learning algorithm was integrated with an audience response system called SIDRA, in order to generate states that collect some commonality in responses to questions and add diagnostic feedback for guided learning. A total of 89 pharmacy students enrolled on a Human Anatomy course were taught using two different teaching methods. Forty-four students employed intelligent SIDRA (i-SIDRA), whereas 45 students received the same training but without using i-SIDRA. A statistically significant difference was found between the experimental group (i-SIDRA) and the control group (traditional learning methodology), with T (87)=6.598, p < 0.001. In four MCQs tests, the difference between the number of correct answers in the first attempt and in the last attempt was also studied. A global effect size of 0.644 was achieved in the meta-analysis carried out. The students expressed satisfaction with the content provided by i-SIDRA and the methodology used during the process of learning anatomy (M=4.59). The new empirical contribution presented in this paper allows instructors to perform post hoc analyses of each particular student's progress to ensure appropriate training.


FERNANDEZ-ALEMAN, J.L., LOPEZ-GONZALEZ, L., GONZALEZ-SEQUEROS, O., JAYNE, C., LOPEZ-JIMENEZ, J.J., CARRILLO-DE-GEA, J.M. and TOVAL, A. 2016. An empirical study of neural network-based audience response technology in a human anatomy course for pharmacy students. Journal of medical systems [online], 40(4), article number 85. Available from:

Journal Article Type Article
Acceptance Date Jan 11, 2016
Online Publication Date Jan 27, 2016
Publication Date Apr 30, 2016
Deposit Date Apr 14, 2016
Publicly Available Date Jan 28, 2017
Journal Journal of medical systems
Print ISSN 0148-5598
Electronic ISSN 1573-689X
Publisher Springer
Peer Reviewed Peer Reviewed
Volume 40
Issue 4
Article Number 85
Keywords ELearning; Human anatomy; Neural network; Experiment
Public URL


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