Week 9: When machine behaviourism have educational value and when is it potentially counterproductive to learning
Machine behaviorism
Machinery behaviorism is a concept that draws from behaviorism and it applies to machines or artificial intelligence systems which is used in educational technology.
Machine behaviorism are forms of learning that are shaped and conditioned by a combination of complex machine learning technologies with (often radical) behaviourist psychology and behavioural economics.(Knox, Williamson,Bayne 2020)
It focuses on modelling and understanding intelligent behavior in machines based on observable behaviors.
Machine behaviorism have great educational value in some contexts but it can also be counterproductive to learning in other context.
I would like to discuss when it has value and when it is counterproductive to learning.
When machine behaviorism is valuable in education
1. In skill acquisition : Machine behaviorism is so useful in teaching skills that can be easily measured and reinforced through feedback. For example when a child is being thought language learning where feedback can be provided immediately based on the learner’s actions.The concept can be taught again and again until the child is able to get it, there is an app called the Nigeria Learning Passport, it’s also an edtech platform which is based on the Nigeria educational curriculum especially the basic education which is the nursery, primary and secondary, I really love the lower basic part, it gives a dedicated user the opportunity to acquire the knowledge it is meant to, it takes feedback and would not move to the next level until the assessments shows that the child already got it.
2. Reinforcement and feedback : This is like an extension of my first point, machine behaviorism provids consistent and immediate feedback, the importance of feedback can never be over emphasized, for instance if I give a test to my students I must mark it, point out where their mistakes are ,and they must do correction, often times while encouraging them to write my test or do my assignments, I tell them that I’m not so particular about them getting everything right( although deep down in me I would love them to) but I would tell them the test/ assignment is for me to know where they are having issues, correct them through my feedback and then be better, and really this has improved my students, so I learnt it’s not just about giving test, it entails marking it , returning the script, pointing out where the mistake is and the students taking to correction is equally important.
Interestingly machine behaviorism does all these and even more, it can help reinforce desired behaviors and correct mistakes efficiently. This can also be effective in drills, practices or simulations where repetitive practice is necessary for mastery.
3. Personalized learning : AI systems based on behaviorist principles can adapt to individual learning paces and styles, providing personalized learning experiences for each learner. This can help address individual learning problems,be it a fast or slow learner and keep students engaged, thereby resulting to a great learning or educational outcome.
When machine behaviorism is counterproductive to learning
1.Lack of creativity and critical thinking: Over-reliance on behaviorist approaches will rob students’ opportunities to think critically and solve problems creatively and they will not be able to engage in higher-order thinking skills. Learning experiences that focus solely on rote memorization and repetitive drills may hinder the development of these important skills in the life of a learner.
2. Inflexibility : Machine behaviorism may struggle to accommodate the complexity and variability of human learning experiences. Learning is a big multifaceted process which is influenced by various factors such as motivation, emotions, reinforcement and social interactions, all these are not or may not be easily addressed by behaviorist systems.
Even the in the area of assessment, I formerly didn’t give this Edtech assessment so much thought until my blog tutor ( Micheal) commented on my week 7 topic, on how the future of education will be shaped by AI, honestly assessment is actually a big deal, is Edtech assessment through machine behaviorism really thorough, authentic and encompassing ? ( that is assessing imagination and criticality simultaneously)(Gallagher 2024)
Assessment is a particularly complex intersection of discourse, policy, practice, and imaginaries (Williamson, B., & Komljenovic, J. (2023).
Thinking widely now, even the NLP (Nigeria Learning Passport) app I talked about, what if during the time of assessment an older or more knowledgeable person help the child to take the assessment and the child moves to the next stage, there’s no way the platform will detect this, all forms of Edtech assessment need to be assessed.
3. Limited transferability: Skills learned through machine behaviorism have limited transferability to real-world contexts that require adaptation, creativity, and critical thinking, taking a cue from our lesson on personalized learning, one of it’s pitfall is that, it deprive the child of learning to live together and doing things with other people .Rote learning and immediate feedback may not all the time prepare students for complex, unpredictable situations where multiple solutions are required
Conclusion
while machine behaviorism can be a very valuable tool in education for certain types of learning objectives and contexts, it is important to balance its use with other instructional approaches that helps creativity and imagination, critical thinking and problem solving, and holistic learning also using variety of teaching methods and technologies can help create a more balanced well- rounded educational experience for the learners.
References
Knox, J, Williamson, B & Bayne, S 2020, ‘Machine behaviourism: Future visions of ‘learnification’ and
‘datafication’ across humans and digital technologies’, Learning, Media and Technology, vol. 45, no. 1, pp.
31-45. https://doi.org/10.1080/17439884.2019.1623251
Williamson, B., & Komljenovic, J. (2023). Investing in imagined digital futures: the techno-financial ‘futuring’of edtech investors in higher education. Critical Studies in Education, 64(3), 234-249).
https://nigeria.learningpassport.org/
Hello there Olubukola,
Good work and I can appreciate the progress you are making here, building on the feedback each week. A few points in response:
First of all, I like what you did at the beginning. A brief introduction, you presented a thesis statement, you defined the term machine behaviourism (very important to always define terms), and then you presented a preview of what was to come. Good work and a good model to follow for everything going forward. I think important to remember that the reader might not always fully appreciate the term you are using and how you are using it. Defining it at the onset alleviates that problem and brings your reader in.
‘Even the in the area of assessment, I formerly didn’t give this Edtech assessment so much thought until my blog tutor ( Micheal) commented on my week 7 topic, on how the future of education will be shaped by AI, honestly assessment is actually a big deal, is Edtech assessment through machine behaviorism really thorough, authentic and encompassing ? ( that is assessing imagination and criticality simultaneously)(Gallagher 2024)’
Thanks for quoting me (I won’t discourage you from citing everything that isn’t yours!), but I might suggest that while machine behaviourism is encompassing and possibly thorough, it isn’t always authentic. It is based on data from other datasets, behaviours from other students, and only measures what can be quantified. So the level of personalisation that occurs there is largely categorical: taking the behaviour of one student and categorising according to behaviours from a much larger dataset. So what is being personalised is largely someone else’s behaviour (even it is similar to the student receiving the personalisation).
‘Thinking widely now, even the NLP (Nigeria Learning Passport) app I talked about, what if during the time of assessment an older or more knowledgeable person help the child to take the assessment and the child moves to the next stage, there’s no way the platform will detect this, all forms of Edtech assessment need to be assessed.’
Very interesting, the NLP and actually something I want to chat to you about in Accra in May. So what you are concerned about here is more about how do we know the student did the work themselves? Agreed that is an issue as is all assessment, really. There is always a degree of trust involved. I find myself most interested in assessments that move away from datafied outputs into something that is more discrete to the individual student (a portfolio, an interview, a recorded presentation, a discussion about their learning). Granted these are resource intensive but avoid many of the more problematic uses of edtech in these contexts. Either way, let’s chat in Accra about NLP.
‘Limited transferability: Skills learned through machine behaviorism have limited transferability to real-world contexts that require adaptation, creativity, and critical thinking, taking a cue from our lesson on personalized learning, one of it’s pitfall is that, it deprive the child of learning to live together and doing things with other people .Rote learning and immediate feedback may not all the time prepare students for complex, unpredictable situations where multiple solutions are required’
Excellent and this is what we are looking for: critically synthesising concepts into an applied context. The only thing that would make this better would be to find supporting evidence in the literature but your critical voice is coming through here loud and clear. Keep going with that. The point you raise is important as well: what is the transferability of what we are teaching with behaviourism? One might argue that behaviourism doesn’t work at all beyond a certain order of thinking (ie works best with lower order thinking like basic foundational learning). You note this by showing how behaviourism can strip away Biesta’s socialisation (children playing and learning together socially). That is a good point. What behaviour are we supporting here as such? Does behaviourism correlate to any sort of higher order thinking (abstract thinking, complex problem solving, navigating the ambiguities of community life)?
Good work Olubukola!
Thanks for always Michael,I always appreciate your objective comment, I will surely improve, looking forward to seeing you in Accra