Smart Learning Environments
Enabling adaptive, personalised and context-aware interaction in a smart learning environment
keywords: smart learning environments, intelligent tutoring systems, context awareness, adaptive learning, personalised learning, learning analytics
Last year, a special issue from the Australasian Journal of Educational Technology (AJET) had my attention (well, Paula de Barba, my work colleague put me into this and I really loved it):
"Enabled by technological innovation, brand new learning environments can be created to support a wide range of teaching and learning activities, wherein learning experience can be enriched and learning effectiveness can be enhanced. A Smart Learning Environment (SLE) is conceptualized as a learning environment that emphasizes learning flexibility, effectiveness, efficiency, engagement, adaptivity, and reflectiveness (Spector, 2014), where both formal learning and informal learning are integrated (Gros, 2016). It is basically an adaptive system that improves learning experience based on learning traits, preferences and progress, features increased degrees of engagement, knowledge access, feedback and guidance, and uses rich-media with a seamless access to pertinent information, real-life and on-the-go mentoring with use of technologies to continuously enhance the learning environment (UNESCO, 2017). In recent years, researchers in the field have been actively investigating the design and implementation of a smart learning environment". The intent of this special issue from the Australasian Journal of Educational Technology (AJET) was to disseminate the latest research findings and share good practices on smart learning environments from different perspectives, including pedagogy, content development, instructional design, and technology.
I truly believe this is an important/interesting topic and together with Paula and Linda, jumped on the bandwagon to try to help AJET to disseminate interesting findings in this field.
SLE provide students with opportunities to interact with learning resources and activities in ways that are customised to their particular learning goals and approaches. A challenge in developing SLEs is providing resources and tasks within a single system that can seamlessly tailor learning experience in terms of time, place, platform, and form.
These challenges are huge! Technically and conceptually speaking. Part of them were investigated, addressed and/or discussed in our previous studies, which are now published as part of AJET special call.
In our latest publication, we introduced the iCollab platform, an adaptive environment where learning activities are moderated through conversation with an intelligent agent who can operate across multiple web-based platforms, integrating formal and informal learning opportunities.
Our intelligent tutoring system has a conversational interface and can be accessed from different social media platforms. That is, learning can be supported wherever the student is (anytime, anywhere learning). Personalisation is based on students personality and their use of social media and, is adapted/updated over time based on sentiment analysis and overall interaction with students.
One of the interesting features of iCollab is that it is also able to initiate interaction with students, reaching out to students rather than just waiting for them to access the system. This was also done in a personalised manner.
Results showed that once given the option, students preferred to interact with the smart learning environment out of the LMS, while they were learning informally in social media platforms. Students also had a high level of interaction with the smart learning environment for social purposes, suggesting this combination of CITS and social media platforms, using personalisation based on personality factors, may be a good option to foster a sense of belonging. Moreover, the findings suggest that personalisation on the basis of personality may impact students’ acceptance and usage of a smart learning environment, but not necessarily impact their learning outcomes.
Details about our data collection, analysis, findings and discussions can be found here: https://ajet.org.au/index.php/AJET/article/view/6792
Our study has implications for practice or policy:
iCollab illustrates features that can be implemented in smart learning environments to enable adaptive, context-based, and personalised learning.
Smart learning environments can combine formal and informal learning contexts to promote student engagement through the provision of flexibility of the platforms in which learning occurs.
Conversational intelligent tutoring systems can adapt the form of learning resources/activities so students can interact using natural language as they would with a teacher in the classroom.
I hope you enjoy reading our latest study. I'm really proud of this work (and of our contributions to AJET special call)!
If you have that extra time, I'd love to hear your thoughts. :)