Abstract
Emotions are a core factor of learning. Studies have shown that multiple emotions are co-experienced during learning and have a significant impact on learning outcomes. The present study investigated the importance of multiple, co-occurring emotions during learning about human biology with MetaTutor, a hypermedia-based tutoring system. Person-centered as well as variable-centered approaches of cluster analyses were used to identify emotion clusters. The person-centered clustering analyses indicated three emotion profiles: a positive, negative and neutral profile. Students with a negative profile learned less than those with other profiles and also reported less usage of emotion regulation strategies. Emotion patterns identified through spectral co-clustering confirmed these results. Throughout the learning activity, emotions built a stable correlational structure of a positive, a negative, a neutral and a boredom emotion pattern. Positive emotion pattern scores before the learning activity and negative emotion pattern scores during the learning activity predicted learning, but not consistently. These results reveal the importance of negative emotions during learning with MetaTutor. Potential moderating factors and implications for the design and development of educational interventions that target emotions and emotion regulation with digital learning environments are discussed.
Highlights
Learning is a complex multi-faceted process that requires students to deploy, monitor, and regulate their cognitive, metacognitive, affective and motivational processes based on the learning environment and the learning task and goal (Azevedo et al, 2018)
A few studies have investigated the complexity of students’ emotional experiences during learning using person-centered approaches (Ganotice et al, 2016; Jarrell et al, 2016, 2017; Robinson et al, 2017; Sinclair et al, 2018). These studies have found that groups of students who differ in their emotional experiences during learning in regard to multiple emotions meaningfully differ in their learning outcomes and academic achievement
We extended upon previous research by considering a broader range of emotion measures than previous studies, incorporating emotion regulation and temporal dynamics of emotions, and by substantiating personcentered analyses with a novel variable-centered approach
Summary
Learning is a complex multi-faceted process that requires students to deploy, monitor, and regulate their cognitive, metacognitive, affective and motivational processes based on the learning environment and the learning task and goal (Azevedo et al, 2018). Even though initial investigations on emotions and learning has almost exclusively focused on the importance of anxiety in learning and test situations (Pekrun et al, 2002), research on emotions and learning has diverged into investigations of a broad variety of affective states and emotions in differing learning contexts (e.g., classroom settings, research with advanced learning technologies or informal learning settings; Azevedo et al, 2019) These studies have demonstrated that many different emotions are commonly experienced in learning settings (e.g., boredom, confusion, or frustration; D’Mello, 2013) and they have a significant impact on students’ performance (e.g., Pekrun et al, 2002; D’Mello et al, 2014). We extended upon previous research by considering a broader range of emotion measures than previous studies (i.e., academic achievement emotions and learningcentered emotions), incorporating emotion regulation and temporal dynamics of emotions, and by substantiating personcentered analyses with a novel variable-centered approach
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