TASK PROJECT ALLOCATION IN HIGHER EDUCATION, DURING THE COVID-19 PERIOD
1 Miguel Hernandez University (SPAIN)
2 Alicante General Hospital (SPAIN)
About this paper:
Conference name: 13th International Conference on Education and New Learning Technologies
Dates: 5-6 July, 2021
Location: Online Conference
Abstract:The pandemic situation of the wold population has forced to modify labour and educational routines. For instance, in higher education, classes and exams are nowadays online and teachers and students are using new tools such as google meet or zoom. As a result, the level of anxiety has increased among university students. Collaborative working can improve the level of anxiety since students need to interact with other classmates. However, this kind of work presents an important difficulty, the task allocation. This can be done either randomly or considering the student characteristics. The latest consideration can imply either to allocate tasks to students considering its characteristics in order to improve its most developed ones, or, on the contrary, to allocate tasks to students to improve its less developed characteristics. The latest allocation aims to work with the less developed student abilities. This work introduces the level of student’s anxiety (trait anxiety) to improve the allocation task. The treat anxiety (T/A) shows the latent willingness to show one kind of reaction. In class, we introduced a project in which students need to do collaborative work. Such project aimed to analyse the repercussions of Law 3/2020 for the recovery and protection of the Mar Menor and of the agreement that the Segura Hydrographic Confederation has adopted on the declaration of the underground water mass 070.052 Campo de Cartagena in risk of not reaching good quantitative and chemical status. For this purpose, the teachers in charge of the project were asked to define the tasks to allocate to the students. Using linguistics labels, five tasks were assessed according to its adaptation to the eight chosen characteristics. Next, students were asked to make a self-assessment according to the former eight characteristics. For this purpose, a six-point scale was used. For the characteristic anxiety, all tasks assumed that the ideal level was zero, whereas, for the self-assessment, the treat anxiety STAI questionnaire was used (only questions 21 to 40, because the questions 1 to 20 are devoted to state anxiety). The total score is obtained by adding the answers to each question, which is assessed from 0 to 3, except for the inverse questions that are assessed from 3 to 1. The total score was properly homogenized to make it comparable with the remaining characteristics. Since the ideal valuation of each task and each group of students is available, the last step was the task allocation, according to the distance from each group to each task, minimizing the global distance. For this purpose, the distance from each group to each task was calculated, obtaining a matrix of order 5. Next, all the combinations were used to find the one with lower distances. This final solution hadn’t been the one with lower individuals’ distances, but it had to be the one with lower global distance. Finally, we want to point out that fuzzy mathematics has been especially useful to get such allocation, combining the valuation of traditional characteristics with the level of treat anxiety.
Keywords: Project allocation, treat anxiety, STAI, COVID-19.