Dulwich Insights | Designing non-physical learning environments

Last week, we looked at the role of technology in breaking down data silos between stakeholders as well as life-worlds and academic worlds, and how we can use technology to facilitate more personalised learning experiences. This week, Crispian discusses the relevance of non-physical classroom design in enhancing student agency.

Agency and the design of learning environments

Returning to the OECD's Student Agency for 2030 concept note, they note that teachers play a central role in designing learning environments that can enhance (or presumably detract) from student agency:

"In the traditional teaching model, teachers are expected to deliver knowledge through instruction and evaluation. In a system that encourages student agency, learning involves not only instruction and evaluation but also co-construction. In such a system, teachers and students become co-creators in the teaching-and-learning process. Students acquire a sense of purpose in their education and take ownership of their learning."

If a traditional didactic-mimetic approach – that is, where teachers transmit knowledge to students by direct instruction and in turn students must memorise and imitate the imparted information – is over-emphasised, this leaves little room for student and educator co-construction. The result renders student agency for the most part absent from the picture when the teacher's role is to relay knowledge and the student's role is to memorise this ready for the next test.

Drawing on Cope and Kalantzis again, a better approach is one that affords "pedagogical weaving" of varied approaches. It is not so much that traditional didactic methods have no place in education, but that a variety of pedagogical approaches is needed if we are to take seriously the agentic needs of students and recognise the impact this has on student wellbeing. Didactic approaches risk the default state for students being one of silence. Having a wide range of pedagogical tools to draw on allows teachers to create space in the learning architecture for students to take ownership of their learning.

Turning to technology then, how do our choices here influence this outcome? Many edtech tools today reinforce traditional approaches. Think of the "video followed by a knowledge quiz" format that is predominant on LMS platforms and apps. There are, however, tools available that drive more social pedagogical approaches by design. These tools allow students the space to learn in ways that leave room for greater self-expression and agency in both synchronous and asynchronous formats. Tools like Gather.Town can be used to create more interactive and social experiences than a Zoom call often defaults to. This is achieved by facilitating student choice in how and when to interact with peers. Think of it like being in a classroom with different groups collaborating face-to-face, and students moving between them as desired.

Bots can also be used in collaboration with tools like Microsoft Teams to encourage student participation in shared knowledge construction. Students co-construct and improve the knowledge base the chatbot is drawing on by answering questions and improving the answers from previous student attempts. Work by Antares which developed QBot with Dr David Kellerman at the UNSW show just how impactful this technology can be in building an engaged community of learners. In this example, Dr Kellerman was able to increase student engagement metrics ten-fold. Students had become co-constructors of the class knowledge base and were actively invested in their learning as a result.

Using technology to enhance meta-cognition: "learning how to learn"

Cope and Kalantzis' own research led to the LMS platform, CGScholar, which aims to deliver an environment where co-construction of learning is the default. Students share their drafts, receive peer feedback and improve their work while at the same time providing feedback to peers. This places ownership of the learning in the hands of the students and supports another factor tied with agency: meta-cognitive development or "learning how to learn".

To illustrate the scale of the shift such a platform (and therefore learning architecture) can deliver, consider that a single 8-week course with using CGScholar, gathered 1.7 million data points and generated 11,000 pieces of actionable feedback. (Cope and Kalantzis, 2020). It is hard to imagine how a didactic pedagogy, digitally delivered or otherwise, could come close to these numbers as it is the social interactions captured by the technology architecture that makes this possible. This is what is possible when we as educators use technology to encourage an epistemic shift in learning.

As the above CGScholar example shows, peers can influence each other's agency in ways that technology can amplify. Referencing research from Grieg (2000), Salmela-Aro (2017) and Hogan, Nastasi and Pressley (2000) and Gafney and Varma-Nelson (2007) the OECD note that "when students play an active role in shaping their lessons, they are more likely to participate, ask questions, have open and candid discussions, express opposing opinions and make challenging statements". Such engagement with their learning leads to higher levels of skill in things ranging from analysis to communication, a stronger sense of autonomy, and confidence working in teams. Moreover, these things seem to benefit students in many ways, including "better student achievement outcomes, attitudes and persistence, [and] a greater sense of empowerment..."

Returning to technology again then, platforms like PeerScholar aim directly at peer assessment and feedback. The platform structures learning in such a way as to first offer micro learning on things like how to give meaningful feedback. It highlights issues like how different feedback styles influence students' affective states before a peer assessment task is set. Students then give, receive, and rate any feedback. They reflect on what they will take from it to iterate on their work.

The activity above could have been achieved without a platform like PeerScholar. However, the ease and ready-made environment mean that the efficiency of interactions, the multi-modality and the data captured can all be enhanced. The learning architecture that PeerScholar encourages then, drives active learning and a healthy dollop of meta-cognition with it. When taken together, the peer assessment scores have proven encouragingly reliable indicators of skill level as well.

The point is that while teachers can design learning in all sorts of wonderful and creative ways, the technology we choose to use can limit or enhance those designs in ways that impact student agency and so wellbeing. As educators and parents, we must repeatedly ask ourselves what role the students will have in each of these learning architectures. Is it a role that is likely to develop student agency or one that diminishes it?

Final thoughts

The above examples scratch the surface of what is possible today, let alone tomorrow, given the rate of change. Like most things in education these examples also need to be considered contextually. What works well in one case won't necessarily work well in another. Furthermore, technology deployment alone isn't of course enough to derive these advantages. Thought must be given to educator, student and parent readiness. To security, privacy and governance of data captured. To the values that underpin the aims in each example and of course the ethics of certain approaches and tools.

We often talk about how the technology of tomorrow will bring changes. In fact, many of those technologies are already here, all around us, having an impact now. What matters is that educators and parents engage with these tools and seize the new opportunities they offer to become true partners in the learning of the students in their care. If we get this right, we will surely have a profound impact on student agency and in turn wellbeing.

Bibliography：

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Hogan, K., B. Nastasi and M. Pressley (2000), “Discourse patterns and collaborative scientific reasoning in peer and teacher-guided discussions”, Cognition and Instruction, Vol. 17, pp. 379-432, http://dx.doi.org/10.1207/S1532690XCI1704_2. (Accessed November 2021)

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