Building solid foundations in educational scaffolding

Introduction  

When we consider the idea of scaffolding we often are drawn to Vygotsky’s Zone of Proximal Development. In practice, we are aiming to guide students in their learning through instruction, by breaking concepts into smaller components or providing pieces of the puzzle to support students in completing a task or achieving a particular learning objective. Of course, we know that Vygotsky’s Zone of Proximal Development (ZPD) says something along the lines that a student can achieve at a higher level when they are working under the guidance of a more knowledgeable other. However, this is a common misconception and does not provide the whole picture of what Vygotsky was proposing or the context of his theory.  

In actual fact, Vygotsky’s ZPD is part of his broader theory in cognitive development which is founded on socio-cultural theory. That is, Vygotsky’s ZPD is actually a social learning theory rather than a theory around learning design. When we are considering scaffolding, we are likely to be more closely aligned to Bruner’s thinking on this topic.  

In this article we will tease out the theories presented by Bruner and Vygotsky, the similarities and differences. The article will finish by thinking about how the theories have been applied in recent practice using technology and how we might apply them in the future using emerging technology.  

Exploring these perspectives further  

Lev Vygotsky  

Lev Vygotsky’s work has become foundational in our understanding of cognitive development and socio-cultural theory. He made significant contributions in our understanding of social constructivism. Vygotsky’s main theory was his socio-cultural theory of cognitive development which highlights the importance of social interactions and cultural factors which influence an individual’s cognitive development.  

A key idea within this broader theory is the ZPD. Vygotsky defines the ZPD as:  

“The distance between the actual development level as determined by independent problem solving and the level of potential development as determined through problem solving under adult guidance or in collaboration with more capable peers.”  

( Vygotsky, 1978, pp. 86 )  

That is, a student will be able to achieve at a higher level when working with a more knowledgeable other than when working alone.  

Vygotsky defines two developmental levels that we must be aware of. He asserts that the first development level of a student, as measured by prior activities, is called the actual development level . This is as a result of already completed development cycles and what the student can already achieve. In simple terms, we would say this level is the level that a student can achieve at the present time on their own. The second level is the ZPD and is the ability of the student with the guidance of a more knowledgeable other. Here we are looking at the development level beyond what the student can achieve at the present time by themselves and exploring their potential development level. That is, we are stretching students beyond what they already know and can do towards new knowledge and skill development.  

As we explore this idea in more depth, we see that it is the social interactions between the student and the more knowledgeable other that increases the student’s development level. Vygotsky says:  

“learning awakens a variety of internal development processes that are able to operate only when the child is interacting with people in his environment and in the cooperation with his peers.”  

( Vygotsky, 1978, pp. 90 )  

These ideas have a number of educational implications including the active role the student plays in the learning process, the requirement that the more knowledgeable other knows the student’s current level and that the new learning is achievable for the student (ie. It falls in the ZPD for the individual). Finally, it also highlights the social nature of the ZPD and the interactions that take place between the student and the more knowledgeable other.  

To draw these ideas together and summarise, we might more accurately describe Vygotsky’s ZPD as social scaffolding where we are aiming to push students beyond their current cognitive level.  

  Jerome Bruner  

Jerome Bruner was the first to coin the word “scaffolding” in the educational context. Like Vygotsky, Bruner’s work focused on social constructivism. If we dive into Bruner’s definition of “scaffolding” we certainly see some similarities with Vygotsky’s ZPD, however, it offers a slightly different perspective which has some significant educational implications. In Bruner’s paper he says:  

“[the] “scaffolding” process enables a child or novice to solve a problem, carry out a task or achieve a goal which would be beyond his unassisted efforts… [Scaffolding] consists essentially of the adult “controlling” those elements of the task that are initially beyond the learner’s capacity, thus permitting him to concentrate upon and complete only those elements that are within his range of competence.”  

(Wood, Bruner & Ross, 1976, pp. 90)  

Bruner’s concept of scaffolding is like Vygotsky’s ZPD in the sense that we are trying to help students achieve beyond their current ability. Similarities also extend to the social nature of learning and the active role the student plays in the learning process. However, scaffolding is not only through social interaction. In their paper (see: Wood, Bruner & Ross, 1976), they propose a framework for scaffolding which involves 6 functions. Within the framework, scaffolding includes the instructional method and design of the learning sequence. This has some clear but broad pedagogical implications for us in the educational context.  

A tangible visual image that this idea replicates is the idea of placing construction scaffolding around a building which is under construction (Phillips, 2023). Often scaffolding provides temporary but much needed support to the structure in question and the opportunity for construction workers to complete carefully orchestrated and small tasks on the building until the entire building is able to stand independently. Likewise with learners, scaffolding aims to provide support for students to navigate new concepts and skills through social interaction and instructional design until they are able achieve it on their own. Some examples include the instruction given to students by the teacher, breaking concepts into smaller components, providing students with pieces of the puzzle along the way or explicit teaching.  

To summarise Bruner’s idea, scaffolding in the educational context is the carefully planned social and instructional guidance provided by a more knowledgeable other within the ability level of the student to help them achieve beyond their current capabilities.  

Practical implications using technology now and into the future  

The practical implications of Vygotsky’s ZPD and Bruner’s framework of scaffolding are significant in teaching and learning. These ideas can be applied in the face-to-face classroom and online in many different ways.  

Generative AI is currently dominating many discussions in education and infiltrating our technology. Rightly so, it has huge potential across many domains of learning. One significant distinction of generative AI and previous technology is its ability to generate new content in an instant using a simple prompt. When we consider the ZPD or scaffolding, generative AI could be a transformative technological advancement in meeting an individual’s needs and progressing their cognitive development.  

Two examples of using traditional technologies will be presented below followed by an alternative using generative AI to highlight the significant advancement of generative AI in this space. The examples will provide some possible applications of generative AI that address the short comings of the examples using current technology. It is acknowledged that these examples do not necessarily provide a better strategy as there are some clear disadvantages, but they provide an application of generative AI that overcomes some issues.  

ZPD through social interactions  

Implementing Vygotsky’s ZPD through technology has traditionally been achieved by using social learning platforms such as discussion boards, online synchronous sessions (such as Zoom, MS Teams or Blackboard Collaborate) and social media (e.g. Facebook). The use of these platforms align with the concept of flexible learning and allow students to engage in discussions, collaborate and learn from one another from any location.  

In theory, when we apply a pedagogical approach that is consistent with Vygotsky’s ZPD, we see that these platforms offer the opportunity for social interactions and the transformative role of the more knowledgeable other should be apparent. However, many of us know from lived experience that these approaches are not always effective; students don’t necessarily contribute, the approach doesn’t fit well with our subject matter or do not align well with our learning objectives.  

The emergence of generative AI in the form of a chatbot, such as ChatGPT, has seen researchers identify 1-on-1 tutoring as an application and benefit of the technology in education (See for example: Baidoo-Anu, 2023; Ding et al., 2023; Lo, 2022). In this application students can have meaningful conversations with the chatbot including asking questions, clarifying concepts, receiving explanations and asking for suggestions, all of which are tailored to the student’s ability and adapting to their level of understanding (Baidoo-Anu, 2023; Lo, 2022). This level of interaction has previously been unachievable without human-to-human interaction.  

As we reflect on Vygotsky’s ZPD we may begin to consider that a chatbot could be the knowledgeable other. We could set up discussions with the chatbot in a similar fashion to the way students might interact on the discussion board or in a breakout room. Here we might see that the interactions with the chatbot are conversational and could be considered as social interactions where the responses from the chatbot could be mistaken for a human providing the conversation. When we consider the drawbacks of our traditional social learning through online platforms, we can see that generative AI acting as the knowledgeable other can overcome some of these issues. A chatbot is on-demand and instant, it always participates, and the responses are tailored specifically to the student’s prompt.  

Scaffolding through Adaptive Learning  

Adaptive learning is commonly implemented using a web-based platform and accessed through a web browser. It provides a learner with a personalised learning experience where the course material, resources and questions are targeted for a specific individual (Kurt, 2021). Furthermore, the system offers immediate assistance and feedback specific to the learner needs (Kurt, 2021). If we examine this type of adaptive learning system, the scaffolding provided by the system aligns with Bruner’s scaffolding rather than Vygotsky’s ZPD. The support is provided by the learning design rather than social interactions.  

However, there are some challenges in using adaptive learning including the significant upfront financial costs, time required to develop them and the limited nature of the personalisation (i.e. The personalisation follows pre-defined pathways and algorithms) (Cavanagh et al., 2020). Research also suggests that adaptive learning is more suitable for some subject areas than others (Kok, 2020; Kurt, 2021).  

The application of generative AI in adaptive learning is very similar to 1-on-1 tutoring. However, in this case the subject and content at hand could live in a more traditional module of work where the content and subject matter is orchestrated by the instructor, in a similar way to an adaptive learning platform. Then, generative AI is incorporated to provide a tailored learning experience, offering up differentiated learning, a unique pathway and a learning assistant as the student works through the content and activities.  

This application of generative AI aligns more closely with Bruner’s idea of scaffolding. There are both social interactions and instructional design that supports the student in their learning process. If we compare this application of generative AI in adaptive learning to the traditional adaptive learning platforms, the generative AI application could provide far better personalisation and support.  

Conclusion  

As we look to the future and consider the emerging applications of Vygotsky’s ZPD and Bruner’s scaffolding using generative AI, we see there are endless possibilities which may be far more effective that pre-generative AI implementations.  

However, we must be critical of new technologies and approaches and consider the limitations, challenges and impacts. Generative AI in the public domain at this scale is only in its infancy. We expect it will improve and be more effective as time goes on. However, at present there are many issues that impact its viability and effectiveness in the educational context. This includes generative AI’s inability to understand concepts in the way that humans can understand them. This is because generative AI works on statistical patterns from the data it is trained on rather than a conceptual understanding of knowledge (Baidoo-Anu, 2023). Building on from this, generative AI exhibits bias due to the biases that exist in its training data (Baidoo-Anu, 2023). The list goes on, it lacks contextual understanding, the data set is limited so its knowledge is limited, it can hallucinate and make things up, there are privacy concerns, issues around intellectual property and a reliance on chatbots could take away from real human interactions (Baidoo-Anu, 2023).  

There are huge opportunities for generative AI, and thus we can embrace them with caution. We can leverage the strengths to support and improve student learning. Therefore, as we consider the ZPD and scaffolding in this context, we should be selective with how we ask our students to use and interact with generative AI. We should provide structure and guidelines to our students and teach students critical thinking skills which will enable them to evaluate the responses that generative AI provides.   

References  

Wood, D., Bruner, J.S. & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17 (2), 89-100. https://doi.org/10.1111/j.1469-7610.1976.tb00381.x  

Cavanagh, T., Chen, B., Lahcen, R., & Paradiso, J. R. (2020). Constructing a design framework and pedagogical approach for adaptive learning in higher education: A practitioner’s perspective. International Review of Research in Open and Distributed Learning, 21 (1), 173-197. https://doi.org/10.19173/irrodl.v21i1.4557  

Cicconi, M. (2014). Vygotsky meets technology: A reinvention of collaboration in the early childhood mathematics classroom. Early Childhood Education Journal, 42 , 57-65.  

Kok, M. (2020). Strengths And Weaknesses Of Adaptive Learning: A Case Study. eLearning Industry . https://elearningindustry.com/strenghts-weaknesses-adaptive-learning-paths-case-study  

Kurt, S. (2021). Adaptive learning: What is It, what are its benefits and how does it work? Educational Technology . https://educationaltechnology.net/adaptive-learning-what-is-it-what-are-its-benefits-and-how-does-it-work/  

Phillips, M. (2021) EDF5770 Designing for interaction and collaboration. Instructional courseware. Monash University.  

Vygotsky, L. (1978). Interaction between learning and development. In Cole, M., John-Steiner, V., Scribner, S., & Souberman, E. (Eds.) Mind and society: The development of higher psychological processes (pp. 79-91). Cambridge, MA: Harvard University Press.