EARLY IDENTIFICATION OF UNDER-PERFORMING STUDENTS FOR PROACTIVE ASSISTANCE THROUGH FORMATIVE EVALUATION
Universitat Politècnica de València (SPAIN)
About this paper:
Appears in: EDULEARN14 Proceedings
Publication year: 2014
Conference name: 6th International Conference on Education and New Learning Technologies
Dates: 7-9 July, 2014
Location: Barcelona, Spain
Abstract:Unsatisfactory academic progress of university students is an important issue in educational systems. Student under-performance is the outcome of poor acquisition of professional competences and results in inefficient use of valuable resources (instructor’s time, student’s time, teaching facilities, laboratories, availability of places for students who actively engage with their studies…).
Therefore, to optimize resources for both the student and the institution, it is interesting to identify as soon as possible the students who more likely will underperform in a given subject. Although not easy to implement, early identification tools would allow the proactive initiation of an intervention program to help the identified students. This would enhance the learning process and would improve the efficiency and throughput of the degree.
This interdisciplinary work studies the correlation between student performance in practical lessons and their academic progress in a particular subject at the end of the semester. To cover different student profiles, the analysis has been done over three different degrees of the Universitat Politècnica de València in Spain (two different ICT related engineering degrees and a communication and journalism degree). The hypothesis is that student performance in different formative evaluations carried out in the practical lessons can be used as an early indicator of the students with higher risk of achieving academic performance below requirements. This indicator could be used for triggering a proactive intervention program. The findings suggest that there is considerably variability in the results but there is a certain correlation between both variables. Thus, it is possible to identify some of the students with higher likelihood of underperforming in a given subject.