Banca de DEFESA: ITALO RODRIGO DA SILVA ARRUDA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : ITALO RODRIGO DA SILVA ARRUDA
DATE: 22/11/2023
TIME: 15:30
LOCAL: Online
TITLE:

Cognitive Load in Sending Feedback from Dashboards and Learning Analytics: a controlled experiment with teachers

KEY WORDS:

Massive Open Online Course. Sentiment Analysis. Educational Environments. Learning Analytics. Teachers' Perception. Technology Acceptance Model.

PAGES: 111
BIG AREA: Ciências Humanas
AREA: Educação
SUBÁREA: Ensino-Aprendizagem
SPECIALTY: Tecnologia Educacional
SUMMARY:

The use of Information Technologies is increasingly evident in educational environments. Online educational teaching platforms make it possible to help students and teachers in the formative mission of teaching and learning in various areas of knowledge. Among the educational platforms focused on e-learning, we have the Massive Open Online Course - MOOC, which allow an adaptive educational environment for users with the support of automated resources for recommendations, carried out by artificial intelligence techniques, with the objective of learning of students according to their usage profiles. In this sense, researchers have been increasingly interested in providing teachers with strategies to accompany students more efficiently in sending feedback in the context of MOOCs in order to use the inherently human capacities of teachers to adjust the feedbacks according to the needs of students, taking into account the Sentiment analysis in posts. However, this work focuses on investigating the perception of teachers in relation to their cognitive effort and time spent in creating and adapting feedback recommendations in a simulated educational platform. This study will compare three groups of teachers, using one of the scenarios (manual, automated and semi-automated) of monitoring a simulated educational platform. The scenarios set will be used in a random experiment, where the participating teachers will evaluate through a form what is their perception of cognitive effort and time dedicated to the creation and adequacy of feedback recommendations and monitoring of students on the platform. In addition to evaluating the Technology Acceptance Model (TAM) of the proposed scenarios as a Leaning Analitics module for MOOCs environments. The results are expected to validate the hypotheses raised: that the use of artificial intelligence in the automated scenario influences the perception of teachers, leading them to present a lower workload than the manual scenario. When evaluating teachers according to the level of feelings of students in the posts, we look for indications that the perception of mental demand in the automated scenario does better when analyzing the manual scenario. Being important contributions to understand the perception of teachers when using educational platforms in their classes.

COMMITTEE MEMBERS:
Presidente - 2943096 - DIEGO DERMEVAL MEDEIROS DA CUNHA MATOS
Interno(a) - 1774996 - RAFAEL DE AMORIM SILVA
Interno(a) - 3221659 - RANILSON OSCAR ARAÚJO PAIVA
Externo(a) à Instituição - HELENA MACEDO REIS - UFPR