TY - JOUR
T1 - Emotions, Motivation, Cognitive–Metacognitive Strategies, and Behavior as Predictors of Learning Performance in Blended Learning
AU - Ramirez-Arellano, Aldo
AU - Bory-Reyes, Juan
AU - Hernández-Simón, Luis Manuel
N1 - Publisher Copyright:
© The Author(s) 2018.
PY - 2019/4/1
Y1 - 2019/4/1
N2 - Several studies have focused on identifying the significant behavioral predictors of learning performances in web-based courses by examining the log data variables of learning management systems, including time spent on lectures, the number of assignments submitted, and so forth. However, such studies fail to quantify the impact of emotional, motivational, behavioral, and cognitive–metacognitive factors simultaneously. This research was an attempt to understand the relations between students’ motivation, cognitive–metacognitive strategies, behavior, and learning performance in the context of blended courses in higher education. Then, relevant predictors are used to obtain a model to classify the students’ performance and to identify those who are at risk of failing the course. The authors conducted an empirical study in a higher educational course with 137 Mexican students. Nineteen variables related to emotions, motivation, cognitive–metacognitive strategies, and behavior. Only six were found to be significant. These variables explain approximately 67% of the variance between each student’s overall grade. The model, based on those variables, correctly classifies 96% of the students.
AB - Several studies have focused on identifying the significant behavioral predictors of learning performances in web-based courses by examining the log data variables of learning management systems, including time spent on lectures, the number of assignments submitted, and so forth. However, such studies fail to quantify the impact of emotional, motivational, behavioral, and cognitive–metacognitive factors simultaneously. This research was an attempt to understand the relations between students’ motivation, cognitive–metacognitive strategies, behavior, and learning performance in the context of blended courses in higher education. Then, relevant predictors are used to obtain a model to classify the students’ performance and to identify those who are at risk of failing the course. The authors conducted an empirical study in a higher educational course with 137 Mexican students. Nineteen variables related to emotions, motivation, cognitive–metacognitive strategies, and behavior. Only six were found to be significant. These variables explain approximately 67% of the variance between each student’s overall grade. The model, based on those variables, correctly classifies 96% of the students.
KW - blended learning
KW - cognitive–metacognitive strategies
KW - emotions
KW - higher education
KW - learning performance
KW - motivation
UR - http://www.scopus.com/inward/record.url?scp=85063288496&partnerID=8YFLogxK
U2 - 10.1177/0735633117753935
DO - 10.1177/0735633117753935
M3 - Artículo
SN - 0735-6331
VL - 57
SP - 491
EP - 512
JO - Journal of Educational Computing Research
JF - Journal of Educational Computing Research
IS - 2
ER -