About this paper

Appears in:
Pages: 7279-7285
Publication year: 2014
ISBN: 978-84-617-0557-3
ISSN: 2340-1117

Conference name: 6th International Conference on Education and New Learning Technologies
Dates: 7-9 July, 2014
Location: Barcelona, Spain

AN INTERDISCIPLINARY PROPOSAL: THE USE OF QUANTITATIVE TECHNIQUES FOR STAFF SELECTION

J. Villagrasa, O. Blasco, V. Liern

University of Valencia (SPAIN)
The teaching proposal that we present is addressed to first-year Business Administration undergraduates. Through an interdisciplinary proposal we attempt to evaluate the acquired skills in the subjects with quantitative nature used in the business management context (Human Resources).

The crisis has developed an increasing interest regarding whether or not there will be an opportunity to get a job after finishing the university studies. Being aware of the importance of acquiring certain capabilities during the high education period which will have as a consequence, the creation of specific competences in the student, we create a teaching proposal whereby we will show our students the different types of competencies that a human resources manager can look for. We will focus on a list of more than 25 competences selected by two recognized and accepted books in the literature such as Ansorena, A. (1996) and Alles, M. (2006).

The process that we propose will be divided into four steps:
1. We will select a company and we will have a look at all the competences that a candidate could have to apply for a job at this company. Moreover, we will discuss and select which competences could be matched in a better way with each job position highlighting the fact that each job may need different competences (e.g. there can’t be the same required competences in a job as a cashier as in another job as an enterprise consultant).
2. We will focus on each job position. Here, we will define for all of them, the ideal interval that we would like to have in each competence (included in a range from 0 to 1). Through this process, we will describe our ideal candidate for this job position.
3. We will evaluate and will get the intervals of each candidate. As it was said before, for each job position we will use only the competences that we have already selected.
4. We will assess the difference from each candidate to the ideal one and we will eventually select the candidates who have less distance to that idealized candidate. Therefore, the job applicant who has less distance in their intervals to the ideal one adding all the competences selected for a specific job position would be probably the selected candidate.

The activity we propose consists of determining the solution of an actual problem in staff selection. Doing this task, the students must use quantitative nature knowledge and basic business management concepts that they should have acquired previously. Therefore, with this teaching proposal we expect to evaluate these issues as well as the team work and synthesis capabilities in order to determine whether the learning performance proposed in the activity has been obtained.
@InProceedings{VILLAGRASA2014ANI,
author = {Villagrasa, J. and Blasco, O. and Liern, V.},
title = {AN INTERDISCIPLINARY PROPOSAL: THE USE OF QUANTITATIVE TECHNIQUES FOR STAFF SELECTION},
series = {6th International Conference on Education and New Learning Technologies},
booktitle = {EDULEARN14 Proceedings},
isbn = {978-84-617-0557-3},
issn = {2340-1117},
publisher = {IATED},
location = {Barcelona, Spain},
month = {7-9 July, 2014},
year = {2014},
pages = {7279-7285}}
TY - CONF
AU - J. Villagrasa AU - O. Blasco AU - V. Liern
TI - AN INTERDISCIPLINARY PROPOSAL: THE USE OF QUANTITATIVE TECHNIQUES FOR STAFF SELECTION
SN - 978-84-617-0557-3/2340-1117
PY - 2014
Y1 - 7-9 July, 2014
CI - Barcelona, Spain
JO - 6th International Conference on Education and New Learning Technologies
JA - EDULEARN14 Proceedings
SP - 7279
EP - 7285
ER -
J. Villagrasa, O. Blasco, V. Liern (2014) AN INTERDISCIPLINARY PROPOSAL: THE USE OF QUANTITATIVE TECHNIQUES FOR STAFF SELECTION, EDULEARN14 Proceedings, pp. 7279-7285.
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