This is the first of the blog posts where I am going to summarize, explain and share my thoughts on some of the influential scientific papers that are related to learning, a subject that I am very passionate about. I am very passionate about. My aim in these blog posts is to present the thought process, the idea and the technicalities of these papers in a comprehensive and simple way.
In this blog post, the main subject will be the role of emotions in learning. The papers I have chosen to include are: Damasio (1996), Immordino-Yang & Damasio (2017) and Pekrun, Goetz, Titz, Perry (2002).
Damasio et al. (1996) – The Somatic Marker Hypothesis and the Possible Functions of the Prefrontal Cortex [and Discussion]
- Damasio introduced somatic markers in 1994 and further discussed them in this paper.
- It is a theory on how emotions influence decision-making.
- The term somatic marker can be simplified as bodily sensors.
- It is an important paper because it suggests that emotions are not simply irrational impulses, using biological and neurological evidence to supports the integration of emotion in decision-making.
The theory suggests that emotions, signaled through bodily markers, are key elements in decision-making, in risky and uncertain situations in particular. The ventromedial prefrontal cortex (vmPFC) plays a crucial role in integrating those signals into decision-making processes whether conscious or unconscious.
These somatic markers are particularly helpful in quickly and efficiently navigating complex decisions by using the emotional memory of past experiences.
His initial insights came from studying patients with damage to the vmPFC. These patients had no change in intellectual and cognitive abilities, but they struggled with real-life decision-making.
Short Thoughts: It is really interesting to me that the role of emotions in decision-making was acknowledged this late, near the 21st century. The role of emotions in decision-making seemed pretty intuitive to me while I was growing up. It was particularly obvious in situations where I needed to make fast decisions, similar to what Damasio points out, which I am guessing is the case for everybody else.
The first time someone trades stocks or cryptocurrencies is a perfect example of this because first timers seriously lack discipline and a plan, the decisions are almost solely guided by emotions. Even the ones who have discipline and a plan can be guided by their emotions, fear or greed. That’s what gives birth to the indicator called «market sentiment».
Immordino-Yang & Damasio (2017) – We Feel, Therefore We Learn: The Relevance of Affective and Social Neuroscience to Education
- It examines the link between social emotions and brain functions in the context of learning and culture.
- The key argument is that emotions are central to social cognition and play a fundamental role in decision-making, moral reasoning and learning.
- Yang points out the moral differences of kids and adult-onset patients with damaged vmPFC. The consequences are more severe in kids with damaged vmPFC and therefore, highlights the importance of integrating social-emotional learning in education to support moral development and critical thinking.
The difference between adult-onset patients and kids with damaged vmPFC is that while these adults are aware of moral and societal rules—having learned them—they have difficulty applying this knowledge in the real world. In contrast, kids with damaged vmPFC do not even know these rules, are unable to learn them, and therefore develop psychopathic and antisocial tendencies later in life.
Yang uses the term emotional rudder to talk about the role of emotions and emotional thought in real-world decision-making, stating that early damage on vmPFC results in loss of emotional rudder which takes away the ability to navigate in social contexts and differentiate positive and negative situations and actions. Later, Yang points out the importance of this emotional rudder in learning.
Yang also highlights the importance of social feedback in learning by stating that damaged vmPFC doesn’t only hinder the formation of emotions such as embarrassment, compassion and envy but also compromises the decision-making, rational thought and learning from mistakes or success.
Short Thoughts: The overall idea is that separating emotion from teaching can cause students to fail to use their knowledge in real world. This is interesting because ability to generalize and apply knowledge in real world is a serious separator of human intelligence and artificial intelligence. AI systems are really good at performing as domain experts, but they lack the generalization ability that human intelligence has.
Just a thought, the further research on vmPFC seems promising for AI generalization challenge that we have today. Maybe it’s the emotions, which AI systems obviously lack, that is a bridge between knowledge and generalization of knowledge – a question I would like to further explore.
Pekrun, Goetz, Titz, Perry (2002) – Academic Emotions in Students’ Self-Regulated Learning and Achievement: A Program of Qualitative and Quantitative Research
The paper is a continuation and expansion of past studies. Therefore, references to past studies will occasionally occur while reading the paper. There was not much research that investigated emotions other than anxiety, which makes this paper more important.
Paper explores:
- What emotions students feel in school (both good and bad).
- How to measure these emotions using a tool called the Academic Emotions Questionnaire (AEQ).
- How emotions impact learning—helping or hurting motivation, memory, and study habits.
- Where these emotions come from (for example, feeling in control of learning and valuing schoolwork influences emotions).
- How to support students emotionally to improve their learning experience.
I am going to explain how it does these shortly:
1. Emotions students feel in school: The paper emphasizes that students experience a wide range of emotions in academic settings. These emotions include both positive emotions such as enjoyment of learning, hope, pride, and relief, as well as negative emotions such as anger, boredom, shame, anxiety and hopelessness. The frequency with which students experience certain emotions can depend on the specific academic situation.
2. Measuring emotions (Academic Emotions Questionnaire – AEQ): The researchers developed the Academic Emotions Questionnaire (AEQ) to quantitatively measure academic emotions. The AEQ measures nine academic emotions: enjoyment, hope, pride, relief, anger, anxiety, shame, hopelessness, and boredom. The questionnaire has versions to measure emotions related to class, learning, and tests. The scales can also be adapted to measure emotions as traits, states, or course-related feelings.
3. Impact of emotions on learning: Emotions influence motivation, learning strategies, cognitive resources, and self-regulation.
- Positive emotions like enjoyment can boost academic motivation and encourage flexible learning strategies.
- Negative emotions such as boredom and hopelessness can reduce motivation and lead to superficial processing of information.
- Activating negative emotions like anxiety can hurt intrinsic motivation but strengthen extrinsic motivation under certain conditions.
- Task-related enjoyment can direct attention toward the task, using cognitive resources effectively.
4. Sources of emotions: The control-value theory suggests that academic emotions stem from appraisals of control and value.
- Control-related appraisals include self-efficacy, control of achievement, and causal expectancies.
- Value-related appraisals involve intrinsic and extrinsic values and goals related to academic learning and outcomes.
- The quality of classroom instruction, autonomy support, achievement expectancies, feedback, and social relatedness also play a role.
5. Supporting students emotionally: The paper suggests several strategies to foster positive academic emotions and help students cope with negative ones. These include:
- Improving the quality of academic instruction.
- Providing autonomy while ensuring students can self-regulate their learning.
- Conveying the value of academic mastery while adjusting social expectations.
- Increasing opportunities for success and fostering a culture of learning from errors.
- Creating flexible interaction structures that promote affiliation, cooperation, and support.
Key Takeaways:
- Emotions in learning matter: Students feel emotions like enjoyment, pride, anxiety, and boredom, which affect their performance.
- Measuring emotions: The AEQ helps track different emotions in school settings.
- Good and bad emotions: Positive emotions (like enjoyment) usually help learning, but negative ones (like anxiety) can sometimes be useful (e.g., motivating students to study harder).
- Why emotions happen: They depend on how much control students feel over their work and how much they value what they’re learning.
- It’s a cycle: Emotions influence learning, and learning outcomes also affect emotions in return.
Short Thoughts: I think this paper is a deep dive into something we all experience but rarely think about critically: emotions in learning. I always knew that my mood affected how well I studied, but I never realized how diverse and complex these emotions could be. The idea that positive emotions are not always good and negative emotions not always bad is awakening. Also, the point that anxiety can be helpful for some students, pushing them to study harder, while crippling others strongly resonates with my experiences and observations of the people around me.
For me, the biggest and most critical takeaway is that educators need to acknowledge this emotional diversity and create environments that foster well-being and help students develop a healthy relationship with their emotions. Keeping the same routine and pace throughout the year, while ignoring mood shifts due to different seasons, weekdays, or nationwide and worldwide events, negatively affects student performance. In addition, crowded classrooms obstruct the idea of creating classrooms that act according to the emotional diversity in class. Therefore, traditional educational systems in most countries are unable to create classrooms that implement the findings of this research – and this is by design.
📌 Sources & Further Reading
- Damasio, A., Tranel, D., & Damasio, H. (1996). The somatic marker hypothesis and the possible functions of the prefrontal cortex [and discussion]. Philosophical Transactions of the Royal Society B: Biological Sciences.
- Immordino-Yang, M. H., & Damasio, A. (2017). We feel, therefore we learn: The relevance of affective and social neuroscience to education. Mind, Brain, and Education.
- Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational Psychologist.
- Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist.
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