I’m deeply suspicious, not of the claim that emotions are important in learning, but of the assumption made on the back of this, that emotion is quite simply a good thing in learning. It leads to all sorts of wrong assumptions about fun, gaming and no end of odd theorising about happiness.
Like the shallow side of social constructivists, who simply conclude that all learning should be ‘social’, whatever that means, there is a tendency to see ‘emotion’ as a good thing, no matter what. This problem has been exacerbated in recent times by the therapeutic assumption that emotions are somehow intrinsically virtuous.
New study
So this study caught my eye (thanks Carl Hwenrdrick) as it digs into something I had always thought may be true, that positive emotions don’t work the way you think.
https://www.sciencedirect.com/science/article/pii/S1041608024001900
While feeling good (like being happy or motivated) definitely helps with learning, it doesn’t seem to do so by lowering the mental effort (via cognitive load) needed to process new information. This challenges earlier ideas that positive emotions expand your mental resources.
Emotions aren’t set in stone and shift while you learn. For example, frustration at the start of a tough task can turn into satisfaction as students figure things out. So, frustration isn’t always a bad thing—it can be part of the process. Emotions also shape cognitive load. We usually think of cognitive load as tied to how complex the information is, but this study points out that emotions directly influence how much mental effort a task feels like it takes. Finally, not all positive emotions are equal. While being in a good mood generally helps, too much excitement or overconfidence can backfire. Students might rush through material, miss details, or oversimplify because they are ‘feeling too good’. This last point is important.
Emotions and learning
Affective learning deals with the emotional side of learners, their emotions and feelings. These feelings cover a wide range of positive and negative attitudes, interests, beliefs and motivations before, during and after learning.
Teachers, lecturers and trainers are professional learners and often understate the role that emotions play in learning. Yet speak to any learner and many learners will report not what they achieved in learning but how they felt. Few get through school without feeling bored or indifferent to lessons and subjects that seem dull, remote and irrelevant. Fewer still get through a degree without feeling numbed in boring lectures. On the other hand, successful learners report excitement, engagement and feelings of pride and achievement. The point is that this can go both ways.
This complex world of feelings and emotions is often sidelined by the dominance of the purely rational, academic cognitive side of learning theory. This is partly down to the dominance of Bloom’s silly taxonomy, the cognitive domain being only one of three, the other two the psychomotor and affective are often completely ignored.
Kahneman
Kahneman posits the idea that we have two brains, in Thinking Fast and Slow; System 1 - fast, emotional and instinctive, also System 2 - slower and rational. I am no longer convinced that the distinction is as clear as we think it is (sometimes expressed as elephant and rider). Our brain has substantial weaknesses, due to its long and messy evolutionary history. We know that it stubbornly procrastinates, fails to remain attentive (attention being a necessary condition for most learning) and easily distracted. It is also subject to emotional pulls and mood swings, even depression. This is both a blessing and a curse. The emotive dimension of learning is often underestimated but it can also distract and over-stimulate.
Krathwohl
Everyone knows Bloom, but we hear little about the man who completed Bloom’s work in the affective domain, the less known David Krathwohl. Although Bloom's original taxonomy consisted of six categories, when Krathwohl revised it in 2001, he put emphasis on the interaction between the cognitive and affective. With Lori Anderson he also helped reduce Bloom’s cognitive taxonomy down to four categories or knowledge dimensions:
Factual knowledge
Conceptual knowledge
Procedural knowledge
Metacognitive knowledge
For each of these four, smaller dimensions were identified. He also changed the cognitive processes to verbs and renamed Evaluation and Synthesis as Creation.
Krathwahl then proposed six levels of affective learning:
Characterization
Organization
Valuing
Responding
Receiving
My own view is that this Affective Taxonomy suffers from the same hierarchical rigidity as Bloom’s taxonomy in the Cognitive domain. It is far too rigid and hierarchical. Some even argue that there is no real taxonomy of affective learning as it emerges from or is part of the cognitive domain. Affective factors are also difficult to identify and assess as they involve feelings, attitudes, and beliefs, so ignored as something difficult to measure, vague and unimportant. While there is recognition that feelings and emotions play a strong role in motivation and learning, it is rarely be seen as being on a par with its cognitive counterpart.
There is certainly the tendency for schools and academia to focus on text-based, pure reason, as their primary skillset, at the expense of other aspects of learning. This has led to a paucity of research in the area.
Speak to workplace trainers or sports coaches and you will hear far more about affective learning, as it really does matter. These are ever present in learning and can also be internalised, either to hinder learning or harnessed and used positively by the learner to move forward. So feelings play a strong role in both demotivation and motivation. Understanding their role is essential if you are a learning professional, yet few could name a single theorist in this area.
Panksepp
Jaak Panksepp introduces the evolutionary origins of emotions and warns us that although emotions are vital in learning, they can also hinder learning. Panksepp saw life as being empty without emotions, emotions being survival features, as part of our evolutionary heritage. We do not teach or learn these seven PRIMARY affective systems, as they are innate:
SEEKING (expectancy)
FEAR (anxiety)
RAGE (anger)
LUST (sexual excitement)
CARE (nurturance)
PANIC/GRIEF (sadness)
PLAY (social joy)
We can learn from these emotions, but we do not learn them, only learn to modulate them, He did think that they formed the basis of our personality, different emphases producing different personality types. SECONDARY emotional processes are learnt through classical and operant conditioning and TERTIARY emotions are sensory (taste, pleasure, pain) and homeostatic affects (hunger and thirst).
We, unlike animals, are cognitive creatures, but he regrets the common disregard of emotions and our evolutionary heritage in understanding the foundations of learning and higher cognitive processes. Much of what is presented in traditional learning theory, whether rewards, punishments or reinforcements actually rely on the emotional responses of the brain. Yet emotions are a double-edged sword.
Some emotions, such as RAGE, FEAR and PANIC are not conducive to learning and may inhibit or hinder learning. On the other hand, learning may benefit from the SEEKING emotion, with its feeling of enthusiasm, as it is instinctive for survival, it promotes learning through purpose, anticipation and curiosity. Its absence diminished a disposition towards learning.
Damasio & Immordino‐Yang
Damasio & Immordino‐Yang see emotions and reason as entwined or enmeshed. They not only not only regulate our lives, they regulate learning. Emotion is therefore critical to learning and memories well as playing a powerful role in learning as motivators.
Conclusion
A complex area but we must be careful of being too shallow on our consideration of emotions. It may be that acts of learning or thinking induce emotions, not that emotions are always the well spring for learning. It is also clear that they may limit, cap or damage learning. We must keep a close eye of the detailed research in this area, rather than trite statements about the important and efficacy of learning.
There are many surprising things we can learn from research into video and learning. I have given many talks on the subject showing research on video and memory (the transience effect), does learning at x1.5 or x2 affect learning? Do segmentation, length, perspective, picture quality, audio and so on affect learning? Here are 15 THINGS that may shock you from the research… some will surprise you!
But is AI generated video as good as real video in learning?
Leiker et al (2023) in Generative AI for learning looked at this hypothesis.
The study took 83 adult learnersn randomly assigning them into 2 groups:
1. Traditionally produced instructor video
2. Video with realistic AI generated character
Pre and post learning assessment and survey data were used to determine what was learnt and how learners perceived the two types of video.
NO SIGNIFICANT DIFFERENCES
No significant differences were found in either learning or how the videos were perceived. They suggest that AI-generated synthetic, talking head learning videos (limited) are a viable substitute for videos.
This doesn't surprise me. I’ve been creating avatars of myself at increasing levels of fidelity in appearance, movement, lip-synch & voice, speaking many languages from Chinese to Zulu. This involved going into a studio for video capture and separate audio studio for voice capture. A range of services are available from Synthesia to Heygen. These avatars can be used as employees in management training, patients in healthcare training and customers in retail training.
SIGNIFICANT DIFFERENCES
Any form of human interaction can use this technique for training; in instructional videos, trigger videos, branched scenario videos and videos with additional AI generated learning experiences and assessment. In fact, the use of AI can lead to significant UPLIFTS in learning outcomes. In one trial with a client, before GenAI appeared, in 2020, AI enhanced learning resulted in a 61% increase in assessed learning.
INTERACTIVE CHARACTERS
We now have avatars that one can converse with using AI chatbot technology taking it to another level through scenarios and simulations, using real dialogue. We can expect tons of these to appear in computer games (OpenAI have dealings with GTA). But it is in training that they have huge potential. It has been impossible to create high fidelity simulations for soft skills in the past. I created a lot using fixed video clips in interviewing skills, conflict, language training and so on. They took a lot of time to design write and produce. These are about to get a lot quicker and cheaper.
CONCLUSION
The use of AI generated video is already here and will continue to evolve. We are not yet at the level of full drama but the direction of travel is clear.