53
Exploring scientific models from the inside
Challenges, barriers, limitations
Despite the potential of XR and AI to revolutionise embodied model learning there are ongoing challenges to address. First, high-quality XR and AI technologies require significant financial investment and technical expertise, which can be a barrier for many schools. Second, teachers must devote substantial time to understand the complementary elements of pedagogy and data representations of learning activity; the use of AI in analysis may also lead to a ‘black box’ effect where data-insight are either regarded with suspicion or too unquestionably relied upon. Third, collecting and analysing multimodal data raises concerns about student privacy and data security, necessitating careful protocols and ethical guidelines. Finally, questions of equity, both in terms of which students have access to these advanced technologies and in what ways they feel empowered to engage with them, are important to address in ensuring that the benefits of novel pedagogies are distributed fairly.
Conclusions
The integration of XR and AI technologies to support students in learning about models from the inside, represents a powerful approach to enhancing student learning by providing rich, embodied experiences and reflective opportunities. This approach can help students better understand complex scientific models by allowing them both to experience these models firsthand and become the designers of them. Teachers, supported by AI-driven data visualisations, can gain deeper insights into student learning processes and facilitate more effective reflective discussions to advance learning. Despite the challenges and barriers, the potential benefits of these technologies in making abstract concepts more accessible and engaging make them a valuable addition to modern educational practices.. 

Scene 1

53
Exploring scientific models from the inside
Challenges, barriers, limitations
Despite the potential of XR and AI to 
revolutionise embodied model learning 
there are ongoing challenges to address. 
First, high-quality XR and AI technologies 
require significant financial investment and 
technical expertise, which can be a barrier 
for many schools. Second, teachers must 
devote substantial time to understand the 
complementary elements of pedagogy and 
data representations of learning activity; 
the use of AI in analysis may also lead to 
a ‘black box’ effect where data-insight 
are either regarded with suspicion or too 
unquestionably relied upon. Third, collecting 
and analysing multimodal data raises 
concerns about student privacy and data 
security, necessitating careful protocols and 
ethical guidelines. Finally, questions of equity, 
both in terms of which students have access 
to these advanced technologies and in what 
ways they feel empowered to engage with 
them, are important to address in ensuring 
that the benefits of novel pedagogies are 
distributed fairly.
Conclusions
The integration of XR and AI technologies to 
support students in learning about models 
from the inside, represents a powerful 
approach to enhancing student learning by 
providing rich, embodied experiences and 
reflective opportunities. This approach can 
help students better understand complex 
scientific models by allowing them both 
to experience these models firsthand and 
become the designers of them. Teachers, 
supported by AI-driven data visualisations, 
can gain deeper insights into student 
learning processes and facilitate more 
effective reflective discussions to advance 
learning. Despite the challenges and 
barriers, the potential benefits of these 
technologies in making abstract concepts 
more accessible and engaging make them 
a valuable addition to modern educational 
practices.

54
Innovating Pedagogy 2024
References
1. Short conference paper from the STEP project:
Danish, J., Enyedy, N., Humburg, M., Saleh, A., Dahn, M., Lee, C., and Georgen, C. (2018) ‘STEP-Bees and the role of collective embodiment in supporting learning within a system’, in J. Kay and R. Luckin (Eds.) ICLS 2018 Proceedings: International conference of the learning sciences, pp. 1249–
1250. Available at: https://repository.isls.org/
bitstream/1/600/1/272.pdf (Accessed 4 July 2024). 2. A conference paper describing several projects:
Moher, T., Slotta, J. D., Acosta, A., Cober, R., Dasgupta, C., Fong, C., ... and Peppler, K. (2015). Knowledge construction in the instrumented classroom: Supporting student investigations of their physical learning environment. pp. 631–638. CSCL 2015 Proceedings. International Society of the Learning Sciences, Inc. Available at: https://repository.isls.org/handle/1/449 (Accessed 3 July 2024). 3. A conference paper from the STEP project:
Enyedy, N., Danish, J., DeLiema, D., Saleh, A., Lee, C., Morris, N., and Illum, R. (2017) ‘Social affordances of mixed reality learning environments: a case from the Science through Technology Enhanced Play project (STEP)’, Papers from Hawaii International Conference on System Sciences 2017. Available at: https://scholarspace.manoa.hawaii.edu/
items/28ac995d-1cfe-4f03-b9e9-7915522896fa (Accessed 4 July 2024). 4. Journal article:
Lindgren, R., and Johnson-Glenberg, M. (2013) ‘Emboldened by embodiment: Six precepts for research on embodied learning and mixed reality’, Educational Researcher, 42(8), pp. 445–452.
5. Journal article:
Enyedy, N., Danish, J. A., Delacruz, G., and Kumar, M. (2012) ‘Learning physics through play in an augmented reality environment’, International Journal of Computer-Supported Collaborative Learning, 7, pp. 347–378.
6. A conceptual piece in a book chapter describing the value of students’ ability to see things from different perspectives in creating deep understanding:
Ackermann, E. (2012) ‘Perspective-taking and object construction: Two keys to learning’, in Y=. B. Kafai and M. Resnick (eds.) Constructionism in Practice, pp. 25–35. New York: Routledge.
7. Book chapter:
Hall, R., and Stevens, R. (2015) ‘Interaction analysis approaches to knowledge in use’, in A. A. diSessa, M. Levin and N. J. S. Brown (eds.) Knowledge and Interaction, pp. 88–124. Routledge.
Resources • STEP project website:
Science through Technology Enhanced Play (STEP). GEM-STEP Example Models. Available at: https://embodiedplay.org/gem-step_examples/ (Accessed 4 July 2024). • Short article on GenAI and XR, discussing the application of the AI approach to XR learning: Levine, E. (2024) ‘The Next Frontier in Education: How generative AI and XR will evolve the world of learning in the next decade’, Qualcomm blog post, 15 May. Available at: https://www.qualcomm.
com/news/onq/2024/05/the-next-frontier-in-
education-how-generative-ai-and-xr-evolve-
learning (Accessed 4 July 2024). • Feature article on several different applications of GenAI and XR (e.g., ‘Imagine learning about the history of ancient Rome, not from a textbook but standing in the Curia of Pompey next to Julius Caesar surrounded by angry senators, moments before the knives come out’):
J. Hutson (2023) ‘Reinventing education through generative AI and XR’, Research Features. Available at: https://researchfeatures.com/
reinventing-education-generative-ai-xr/ (Accessed 4 July 2024).. 

Scene 2

54
Innovating Pedagogy 2024
References
1. Short conference paper from the STEP project:
Danish, J., Enyedy, N., Humburg, M., Saleh, A., Dahn, 
M., Lee, C., and Georgen, C. (2018) ‘STEP-Bees and 
the role of collective embodiment in supporting 
learning within a system’, in J. Kay and R. Luckin 
(Eds.) ICLS 2018 Proceedings: International 
conference of the learning sciences, pp. 1249–
1250. Available at: https://repository.isls.org/
bitstream/1/600/1/272.pdf (Accessed 4 July 2024). 
2. A conference paper describing several projects:
Moher, T., Slotta, J. D., Acosta, A., Cober, R., 
Dasgupta, C., Fong, C., ... and Peppler, K. (2015). 
Knowledge construction in the instrumented 
classroom: Supporting student investigations of 
their physical learning environment. pp. 631–638. 
CSCL 2015 Proceedings. International Society of 
the Learning Sciences, Inc. Available at:  
https://repository.isls.org/handle/1/449  
(Accessed 3 July 2024). 
3. A conference paper from the STEP project:
Enyedy, N., Danish, J., DeLiema, D., Saleh, A., Lee, C., 
Morris, N., and Illum, R. (2017) ‘Social affordances of 
mixed reality learning environments: a case from 
the Science through Technology Enhanced Play 
project (STEP)’, Papers from Hawaii International 
Conference on System Sciences 2017. Available 
at: https://scholarspace.manoa.hawaii.edu/
items/28ac995d-1cfe-4f03-b9e9-7915522896fa 
(Accessed 4 July 2024). 
4. Journal article:
Lindgren, R., and Johnson-Glenberg, M. (2013) 
‘Emboldened by embodiment: Six precepts for 
research on embodied learning and mixed reality’, 
Educational Researcher, 42(8), pp. 445–452.
5. Journal article:
Enyedy, N., Danish, J. A., Delacruz, G., and Kumar, 
M. (2012) ‘Learning physics through play in an 
augmented reality environment’, International 
Journal of Computer-Supported Collaborative 
Learning, 7, pp. 347–378.
6. A conceptual piece in a book chapter describing 
the value of students’ ability to see things 
from different perspectives in creating deep 
understanding:
Ackermann, E. (2012) ‘Perspective-taking and 
object construction: Two keys to learning’, in Y=. 
B. Kafai and M. Resnick (eds.) Constructionism in 
Practice, pp. 25–35. New York: Routledge.
7. Book chapter:
Hall, R., and Stevens, R. (2015) ‘Interaction analysis 
approaches to knowledge in use’, in A. A. diSessa, 
M. Levin and N. J. S. Brown (eds.) Knowledge and 
Interaction, pp. 88–124. Routledge.
Resources 
• 
STEP project website:
Science through Technology Enhanced Play 
(STEP). GEM-STEP Example Models. Available at: 
https://embodiedplay.org/gem-step_examples/ 
(Accessed 4 July 2024). 
• 
Short article on GenAI and XR, discussing the 
application of the AI approach to XR learning: 
Levine, E. (2024) ‘The Next Frontier in Education: 
How generative AI and XR will evolve the world 
of learning in the next decade’, Qualcomm blog 
post, 15 May. Available at: https://www.qualcomm.
com/news/onq/2024/05/the-next-frontier-in-
education-how-generative-ai-and-xr-evolve-
learning (Accessed 4 July 2024). 
• 
Feature article on several different applications 
of GenAI and XR (e.g., ‘Imagine learning about 
the history of ancient Rome, not from a textbook 
but standing in the Curia of Pompey next to Julius 
Caesar surrounded by angry senators, moments 
before the knives come out’):
J. Hutson (2023) ‘Reinventing education through 
generative AI and XR’, Research Features. 
Available at: https://researchfeatures.com/
reinventing-education-generative-ai-xr/ 
(Accessed 4 July 2024).

Innovating Pedagogy 2024
Exploring new forms of teaching, learning and assessment, to guide educators and policy makers
Open University Innovation Report 12. 

Scene 3

Innovating Pedagogy 2024
Exploring new forms of teaching, learning and assessment,  
to guide educators and policy makers
Open University Innovation Report 12

Innovating Pedagogy 2024 part 5