By Professor Chong Beng Keok
COVID-19 has ushered in an education revolution. Because of the pandemic’s disruption, faculty members must rapidly translate their teaching expertise for online delivery.
From a student’s perspective, this enormous disruption was initially met with some trepidation. However, the pandemic has accelerated their willing adoption of online delivery. Given the likely extended duration of the pandemic, it is conceivable that education institutions will adopt technology-enabled delivery as a central aspect of a new educational norm, rather than as an ‘add-on’ to campus-based delivery.
These shifts in mindset may well set the stage for the advent of more advanced initiatives. It is worthwhile to invest more into artificial intelligence (AI).
But be that as it may, experience has shown that educational institutions are slow to embrace change. Conventional face-to-face interactions remain the prevalent mode of instruction. There has been a gradual shift in approaches over the last decade, with school teachers and university faculty experimenting with new pedagogies such as active-learning methods. Active learning, though, has its limitations.
In conventional classrooms, it is challenging to personalize active learning for students. This is where AI is poised to enter the mainstream of educational delivery. AI’s ability to leverage on big data – identifying common features or patterns and transforming them into a structural knowledge base — can play an important role.
The analytics and predictive capabilities of machine-learning, particularly deep learning, can be used to analyse learning styles of students. AI can then suggest teaching methods with customised materials to assist students to achieve better learning outcomes. Its content analytics power can select learning resources for each student, organise textbooks and lecture materials and optimise active learning and experimental designs.
IBM Research recently partnered with Rensselaer Polytechnic Institute, in Troy, New York, to use AI-based teaching to assist students learning Mandarin. Taught in an immersive classroom environment by an AI-powered assistant, students feel as though they are learning to speak Mandarin in a restaurant in China.
With AI-based education, the role of academic faculties changes significantly from one that disseminates knowledge to one that mentors students. This transition was seen when Georgia Institute of Technology in the United States used chatbots to answer common academic enquiries of students.
It was amusing to see that many students in a master’s level AI class were unaware that one of the teaching assistants, Jill Watson, was not human but was rather a virtual assistant. It was even more amusing that Jill Watson was appraised as the most effective and efficient teaching assistant of them all.
It is time for all institutions, especially those with large student populations, to create AI systems that can deconstruct the context of queries and respond to repetitive academic queries like Jill Watson. This frees the teaching staff to perform work that requires the human touch.
There will never come a time when the human touch is not important. AI-based teaching will require faculty members to be experts and effectively identify and support students who need extra mental and moral support.AI can take charge of repetitive and routine tasks while faculty members perform roles that require creative, cognitive, and emotionally intelligent skillsets.
Chatbots like Woebot can play a role in reducing student stress and improving their motivation to study. While students wait for academic mentoring, Woebot can provide immediate relief by helping students to manage their mental well-being through ‘intelligent mood tracking’. Faculty members will subsequently benefit from gaining the AI’s feedback on students’ mental health.
AI can teach rule-based or theoretical principles and guide students with repetitive exercises. Faculty members then guide, support, and mentor students, helping them with critical thinking.
To achieve quality outcomes for AI-teaching, institutions must be equipped with state-of-the-art AI technology. However, most institutions in Malaysia, except for a few large ones, are ill-equipped with the required hardware and software. Most are still at the infancy stage.
Higher institutions need to first build momentum in artificial intelligence research to gain a greater understanding of the technology before integrating AI into online delivery models.
At UOW Malaysia KDU, both undergraduate and postgraduate students work with the faculty to build machine learning models for facial recognition, converting text-to-speech and speech-to-text (speech recognition) for Internet-of-Things devices and building models capable of forecasting various trends.
The emphasis is on interdisciplinary collaboration. For example, between computing and engineering students for projects which require expertise in mechanics, electronics and programming.
The time to change has come, and perhaps educators can find the epiphany needed for that by watching the rapid embrace of technology among petty traders. When Malaysia went into lockdown to flatten its Covid-19 curve, petty traders were forced to go online and accept e-wallet transactions. The rate of adoption was phenomenal.
Time for educators to change too.
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