Need to exploit emerging technologies
Over the past few months, educational institutions have slowly emerged from an emergency distance learning (ERT) environment as the Covid-19 pandemic has subsided. There seems to be a refocused view on how to continue to use emerging technologies for a more impactful teaching and learning process.
During the pandemic, many educational institutions have transformed teaching and learning from a very face-to-face environment to a fully online environment.
While there hasn’t been enough time to plan and execute technology-enhanced learning using time-tested learning design principles, we should now go back to the drawing board and find out how our learners would like to continue their learning and how we can best meet each other. their requirements and expectations.
Going forward and planning for more intuitive teaching and learning practices, we should take the following trends as shown in the Horizon EDUCAUSE 2021 Report: Teaching and Learning Editionin consideration.
Artificial Intelligence (AI)
The role of AI in teaching and learning, as reiterated by the Beijing Consensus on Artificial Intelligence and Education (BCAIE), is to systematically innovate education and accelerate the building open and flexible education systems, thereby enabling equitable and quality lifelong learning opportunities for all. Its role in transforming teaching and learning is becoming increasingly critical, particularly with respect to learning management systems, assessment processes, student educational experiences and admissions. .
In some recent discussions about AI and higher education, two key points have emerged.
First, the question of whether AI can be used to address the challenges of teaching and learning, as well as a successful learner experience.
Second, the suggestion to carefully rethink the impact of the existing program and whether it will serve the new generation of digital learners.
The education sector can actively participate in these disruptions by taking an active initiative in capitalizing on AI to influence curricula and instructional designs.
Growing amounts of teaching and learning digital data have become available and harnessing this huge data resource will enable education researchers to better design AI-supported ecosystems. To do this, it is important to think about the challenges facing educators and how AI and emerging technologies can be harnessed to positively disrupt education to help educators and be a great help for learners.
Here are some innovative suggestions from different research studies, publications and white papers on using AI to transform teaching and learning:
> Use AI to recognize teaching and learning patterns to enable high-quality support for educators, especially freeing them from routines such as administrative responsibilities, teaching core content and activities rote learning;
> Use AI to create new forms of learning adapted to the needs of future learners. To this end, AI and emerging technologies must be designed and programmed to capture available technology-based teaching and learning algorithms; > Capitalize on AI to determine how different learning pathways (formal, informal and non-formal) can be mapped to core learning outcomes, and how this can then be analyzed to form new curricular needs ;
> Use AI to determine the impact of collaborative learning and how teachers can be supported in this highly cognitive activity, which consumes teachers’ teaching and planning time;
> Develop AI applications to empower teachers towards the adoption of more inclusive pedagogies, to help teachers detect learning gaps, diagnose the various learning challenges faced by learners and suggest solutions; and
> Develop collaborative human-machine AI tools to improve the quality of disciplinary and interdisciplinary learning, especially in courses related to science, technology, engineering, arts and mathematics (STEAM).
Learning Analytics (LA)
LA involves tracking, analyzing, and interpreting student data related to learning behaviors, especially those digitally related.
An institution’s learning management system (LMS) is the primary means of delivering LA because it is where data related to student-faculty interactions are stored or occur the most.
According to a review of UK and international practice on LA in higher education institutions, the following are some of the important contributions of LA:
> A quality assurance and improvement tool
LA can be used on an individual level by an academic to provide a more personalized and fulfilling learning experience for learners.
At the university level, it could be used to transform the curriculum. In the long term, LA data can help a university create better teaching and learning policies, instructional frameworks, and assessment methods and processes.
At the national level, LA could help improve compliance and quality assurance, especially with regard to the requirements of the Malaysian Qualifications Agency.
It could also provide analytical insights for future national education transformation.
> A tool to boost retention rates
Data from LA could help catch at-risk students earlier in the program than would otherwise be possible, because LA captures the digital traces of learning in the LMS.
Although most educators have incorporated Universal Design learning principles into their e-learning designs, as a method to boost retention, there is still great potential for improved learning design. based on LA data.
Retaining geographically displaced online students, using different learning modes (hybrid and blended) and managing different time zones can be quite demanding.
As a result, LA can be used powerfully to identify at-risk students and develop strategies to provide timely, effective, and meaningful support to these students.
> A tool to provide a more personalized learning experience
Personalized learning reframes learning experiences by incorporating the most appropriate approaches and content for an individual student.
The beauty of having access to LA data is that it allows adaptive learning experiences to be built into the system to allow learners with different learning challenges to have a better learning experience.
One of the keys to implementing a quality personalized learning approach – an approach more likely to improve student learning outcomes – is to focus on available analytics.
In other words, one must understand LA to personalize and adapt learning to ensure a more successful learning experience.
As personalized learning grows in the coming years, the demand for LA to improve the quality and efficiency of learning designs will also increase.
As the number of students with access to, and skills in, personal internet-connected devices grows and schools open their networks to support them, it is important that educators be aware of LA’s capabilities to support personalized learning.
In conclusion, it is both imperative and timely for education stakeholders to consider harnessing new technologies such as AI and LA to transform teaching and learning, enabling experiences impactful learning experiences that matter most to learners.
Dr. Abtar Kaur is Professor of Innovative Digital Learning, Director of the Digital Learning Hub and Unesco Chair – Using Innovative Technologies to Improve the Quality of Education – at Asia University of Technology and Innovation -Pacific (APU). She earned a Master of Science in Instructional Design, Development and Assessment from Syracuse University in the United States and a PhD in Web-Based Learning from Universiti Malaya. Abtar did his post-doctoral research (Fulbright) at Indiana University, USA.
The opinions expressed here are those of the author.