About this Research Topic
The profound interconnections between cognition and emotions mean that the affective domain plays a key role in the process of learning. The learning process of facts, concepts, theories and skills and the rational thinking cannot be separated from the feelings, attitudes, emotions, etc., that arise because of that process since all of them interact intrinsically in the limbic system. (Damasio, 2005)
The consideration of affective parameters in the process of science learning is particularly important given the complex and, generally, abstract nature of STEM subjects. Besides, conceptual change is both cognitive and affective, so ignoring the affective domain in science learning can lead to limit the process of conceptual change and, so, hinder the acquisition of a meaningful and profound learning. (Duit, Treagust & Widodo, 2008).
Because of that, over the last years, the study of the role of affective factors in learning science and the development of STEM skills has risen in popularity. Up to date, most research on affective factors in science education has used observational or declarative methods. Although these approaches are solid and present key strengths, they may have limitations for deepening our understanding of the affective domain in the learning process that can be covered thanks to the emergence of new research methodologies based on instrumental techniques such as facial recognition, functional magnetic resonance image (fMRI), galvanic skin response (GSR), eye-tracking analysis or speech emotion recognition (SER).
Affective parameters influence processes such as memory, attention, conceptual change, problem-solving, self-regulation, study strategies, and academic results, among others (Barrett et al., 2019; Chevrier et al., 2019; Graesser, 2020). Taking properly into account the affective domain may have an important impact on the quality of teaching and learning. Its recognition may also help educators to better tailor their pedagogical approaches. Our focus in this Research Topic is to further explore the role of the affective domain in the process of learning science by gathering research evidence coming out from different current approaches.
This Research Topic aims at serving as a window to show what is the state-of-the-art of this field as well as to provide insights related to what we have learned so far in relation to the role of the affective domain in STEM learning. So we welcome all studies addressing the study of the affective domain of STEM learning, conceptual change and/or the development of STEM skill including, but no limited to:
- Design, validation, and implementation of declarative research instruments.
- Facial recognition studies.
- Magnetic resonance image studies.
- Galvanic skin response.
- Eye-tracking analysis.
- Speech emotion recognition.
- The combination of any of the above-mentioned techniques.
Important notice for spontaneous submissions: In order to evaluate the scope and relevance of your prospective manuscript, the editors require authors to submit a tentative abstract, up to 1000 words. This is not the abstract that will be published in the journal, but a brief overview of the contribution which the Topic Editors can provide feedback on.
The consideration of affective parameters in the process of science learning is particularly important given the complex and, generally, abstract nature of STEM subjects. Besides, conceptual change is both cognitive and affective, so ignoring the affective domain in science learning can lead to limit the process of conceptual change and, so, hinder the acquisition of a meaningful and profound learning. (Duit, Treagust & Widodo, 2008).
Because of that, over the last years, the study of the role of affective factors in learning science and the development of STEM skills has risen in popularity. Up to date, most research on affective factors in science education has used observational or declarative methods. Although these approaches are solid and present key strengths, they may have limitations for deepening our understanding of the affective domain in the learning process that can be covered thanks to the emergence of new research methodologies based on instrumental techniques such as facial recognition, functional magnetic resonance image (fMRI), galvanic skin response (GSR), eye-tracking analysis or speech emotion recognition (SER).
Affective parameters influence processes such as memory, attention, conceptual change, problem-solving, self-regulation, study strategies, and academic results, among others (Barrett et al., 2019; Chevrier et al., 2019; Graesser, 2020). Taking properly into account the affective domain may have an important impact on the quality of teaching and learning. Its recognition may also help educators to better tailor their pedagogical approaches. Our focus in this Research Topic is to further explore the role of the affective domain in the process of learning science by gathering research evidence coming out from different current approaches.
This Research Topic aims at serving as a window to show what is the state-of-the-art of this field as well as to provide insights related to what we have learned so far in relation to the role of the affective domain in STEM learning. So we welcome all studies addressing the study of the affective domain of STEM learning, conceptual change and/or the development of STEM skill including, but no limited to:
- Design, validation, and implementation of declarative research instruments.
- Facial recognition studies.
- Magnetic resonance image studies.
- Galvanic skin response.
- Eye-tracking analysis.
- Speech emotion recognition.
- The combination of any of the above-mentioned techniques.
Important notice for spontaneous submissions: In order to evaluate the scope and relevance of your prospective manuscript, the editors require authors to submit a tentative abstract, up to 1000 words. This is not the abstract that will be published in the journal, but a brief overview of the contribution which the Topic Editors can provide feedback on.
Keywords: Affective factors in STEM, Emotions, Deep learning, Conceptual change, Cognitive conflict, fMRI studies, Gesture analysis, Declarative methods.
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
