Trabajo colaborativo y la ecología del aprendizaje

Abstract

The purpose of this study is to develop behavioral profiles, by considering elements of learning ecology, of first-year higher education students that participate in collaborative discussion forums on a digital environment. To determine student profiles, student inputs are analyzed according to two dimensions: 1) message type (content and depth) and 2) context variables that include day of the week, time of the day, and input topic. A descriptive-quantitative analysis is applied. The sample is composed by 43 students enrolled in a computer science course. The results aim to identifying the times of the day and the days of the week that most affect deep learning. Student inputs with the greatest level of depth were attained after 7:00 p.m. In conclusion, this research study identifies learning ecology behavioral profiles that improve deep learning in students