The Education University of Hong Kong (EdUHK) is a publicly funded institution dedicated to the advancement of teaching and learning, through a diverse offering of undergraduate, postgraduate and professional development programs in teacher education, social sciences and humanities. To improve the quality of education, the university utilizes several new-age technologies including an LMS system, which can be used to upload and share materials, hold online discussions, arrange quizzes and surveys, employ peer-assessment and self-assessment, gather and review assignments and record grades.
While interacting with APAC CIO Outlook, John Hui, CIO of the Education University of Hong Kong, shares his insights on how educational technologies are transforming the modern education system.
1. In your opinion, how has the Education Tech landscape evolved over the years? How has technological evolution proved to be beneficial for Education Tech today?
Instead of starting with technology, I would like to start with the trend of education, which is pedagogy centric instead of technology driven. Over the last five years, three key trends in higher education have accelerated the adoption of education technology for teaching and learning:
1) Blended learning is a favored course delivery model defined by the proportions of face-to-face versus online coursework. Higher education values more and more on soft skills whereas traditional pedagogy focuses on hard skills. Soft skills such as interpersonal skills, emotional balance, and communication skills are quite personal. Media-rich learning platforms, personalized or adaptive courseware, and web conferencing tools capable of connecting students for synchronous distance activities are becoming common solutions for blended-learning designs. This was achieved mainly with basic ICT infrastructure, computing power, wireless connections, mobile/wearable devices, and of course the trend of cloud software, including, but not limited to, the SaaS Learning Management System (LMS). The advancement of ICT infrastructure not only facilitated the blended learning environment but also reduced latency so that real-time course in multiple locations can be achieved. For example, remote surgery, musical collaboration at different geographic locations, and many more are made possible.
2) Redesigning learning spaces for active learning refers to the transition to active learning classrooms and spaces. Designing and evaluating spaces that facilitate active learning and collaboration require investments and strategic planning. It involves renovating classrooms, libraries, and common spaces where efforts focus on wireless bandwidth, display screens, flexible furniture, varied writing surfaces, and abundant power to facilitate team-based learning and synchronous meeting spaces, and emerging learning spaces programmed in extended reality (XR). XR could create more engaging and personal experiences for learners than any current developments in online course design. Technology-enhanced spaces include instructional labs, collaborative spaces, active learning classrooms, team-based classes, among others. On top of the basic ICT infrastructure, these spaces are possible because of the extended reality and modern AV systems in classroom (example, Throwable mic, interactive multi-touch panel, robots and programming software being used in STEM education).
3) Focus on measuring learning (data-centered approach) is the capturing and measuring of academic readiness, learning progress, effectiveness of technologies, and other indicators of student success that have matured as courseware products and platforms, and are widely used. For example, some institutions make use of wearable devices to measure real-time health conditions of students so as to tailor the personalized learning pace of students in PE courses. Others make use of visual analytics to measure student engagement in class or make use of activity data in LMS to conduct early prediction on students’ final results, so assistance can be given to student in need at an earlier stage. These are possible because of various types of analytics technologies such as text mining, visual analytics, pattern analytics, and various machine learning algorithms.
2. What according to you are some of the challenges plaguing Education Tech today and how can they be effectively mitigated?
Procuring technical devices/systems is easy but having lecturers change the instructional design and gain the advantages of those technologies by fully utilizing them is the most challenging part. As an administrator for blended learning design, it is a challenge to train and educate faculty, which takes both time and resources. Even if blended learning is done right, there are still so many faculties who believe ‘chalk and talk’ is the best and continue to only lecture, despite having a lots of tools that could enhance the learning process. Students report a preference for blended learning, citing flexibility, ease of access, and the integration of sophisticated multimedia as the reasons behind. Although blended learning is becoming a common course design, the challenges of scaling this modality persist in some institutions. Supporting faculty to design learning experiences that take full advantage of digital platforms and to expand their pedagogical repertoire to include collaboration and student-centered learning design will support the growth of blended learning.
Media-rich learning platforms, personalized or adaptive courseware, and web conferencing tools capable of connecting students for synchronous distance activities are becoming common solutions for blended-learning designs
To facilitate learning space redesign, we need stakeholders to buy-in and transform their pedagogical approaches. Faculty, students, instructional designers, IT staff, and facility personnel are some of the key stakeholders in the redesigning of academic spaces. The challenge is to genuinely understand that a physical learning space is considered a short-term design and a commensurate focus on virtual learning spaces should be further out on the horizon. Faculty development and retraining faculty to adopt pedagogy for active learning classrooms (ALCs) is another concern.
Understanding how to use learning analytics to inform student progress may be elusive for campus leaders and faculty alike because the need to distinguish between different types of learner data is a relatively new skill. Preparing for a data-centered approach to teaching, learning, and advising will require a strategy to upskill key institutional roles and develop a clear understanding of what is measured across multiple platforms. Data definition such as completion status of individual activities must be considered from the very beginning. Besides, data privacy is another area to be addressed when tracking activities of learners and instructors.
3. Which are a few technological trends influencing Education Tech today? What are some of the best practices businesses catering to the Education Tech could probably adopt today?
Over the recent decade, there have been quite a number of technological developments and the more influential ones include Analytics Technologies, Mobile Learning, Artificial Intelligence, Mixed Reality, Virtual Assistants, and Blockchain.
From Gartner Hype Cycle, new concepts and technologies are initially at a point in which someone dreams about but they little know or discuss, and it is called Innovation Trigger. As people become familiar with new innovations, they are “hyped” until they reach the so-called Peak of Inflated Expectations. Interest wanes as experiments and implementations fail to deliver and this drives an idea into Slope of Enlightenment. Only after generations of improvement, such new concepts, ideas or technologies may appear from products to enter Plateau of Productivity for mainstream adoption to take off. Along the cycle, most new concepts disappear while only a few last.
Therefore, after a decade, it seems that only six technologies are foreseen to last and still be important to teaching, learning, and creative inquiry:
1) Mobile learning is now focused on connectivity and convenience, with the expectation that learning experiences include mobile-friendly content, multi-device syncing, and anywhere/anytime access. The increased use of augmented reality (AR), virtual reality (VR), mixed reality (MR) and Internet of Things (IoT) devices has made mobile learning more active and collaborative. Early exploration of mobile learning began with the use of devices to enhance learning experience through asynchronous activities, content creation, and being a flexible in-class tool for reference and exploration. The asynchronous experience centers on formative learning, such as polls, clickers, and informal feedback. The use of mobile devices has made content creation easier because smartphones and tablets have built-in cameras to take photos and videos and a microphone to capture audio. The hardware, paired with powerful and intuitive mobile apps and increasingly available internet access, has created a revolution of content creation and sharing. With capabilities including Bluetooth, GPS, and NFC, mobile devices can create new interactive and personal experiences. Even the most basic smartphones can be paired with an inexpensive Google Cardboard to create an immersive experience. Powerful apps allow students to quickly reference or explore in a new way. For example, a student can visualize the layers and composition of different human organs or systems, or view a 3D model of chemical elements with the touch of a finger.
2) Analytics technologies: In recent CIO survey, this turn out to be the top higher education IT priority over the next 18 months. Analytics technologies are key elements of student success initiatives across institutions and a driving force behind the collaborative, targeted strategic planning and decision-making of higher education leaders. Analytics technologies and capabilities will be an essential component of institutional thriving in the years ahead. Beyond static, descriptive analyses of student learning, grades, and behaviors, analytics capabilities comprise dynamic, connected, predictive, and personalized systems and data. If it’s executed and maintained successfully, it can transform institutions and deeply enrich the educational experiences and success of the students and faculty.
3) Mixed Reality (MR) is an emerging environment in the intersection of the online and offline worlds .It is where digital and physical objects coexist. Virtual reality immerses the user in a simulation, such as the experience of flying or being on Mars. Augmented reality layers information over physical spaces and objects, such as labels and other supplementary data over museum displays. Holographic devices are also used to create mixed environments, as video displays 3D images in a physical space: A hologram of Teresa Teng who died in 1995, will “go on tour” with Jacky Chan in 2019. A key characteristic of MR is its interactivity, which is well suited for experiential learning as adopted by Kolb’s experiential learning model (ELM) for children with Autism Spectrum Disorder. Besides, through simulations and 360° videos, VR can enable users to visit places they might otherwise not be able to access, such as hospitals, art museums, archaeology sites, a refugee camp, or even Mount Everest or Mars.
4) Artificial Intelligence uses computer systems to accomplish tasks and activities that have historically relied on human cognition. Harnessing big data, AI uses foundations of algorithmic machine learning to make predictions and decisions. As the programming, data, and networks driving AI mature, so does the potential that industries such as education see in its application. Despite ethical concerns, AI applications for teaching and learning grow significantly. More educational AI applications are in practice. Watson Tutor, for example, embedded into student readings and the beta testing of the Canvas LMS smart reminders to nudge students toward more successful behaviors in online courses. AI’s ability to personalize learning experiences, reduce teaching workloads, and assist with learning analytics recommends it to educational applications to best meet student needs.
5) Blockchain: Its potential to disrupt and replace centralized systems has captured attention across sectors, including higher education. Universities are investigating how it could be used in areas including transcripts, records of achievement, and identity management. It creates a permanent, detailed record of formal and informal learning that allows individual users to control what is included in their learning record and who may access that information. A blockchain-based transcript could include information on courses and degrees, certifications, badges and other micro credentials, co-curricular activities, internships and employment, as well as other competencies and credentials. Such a record could follow students from one institution to another, serving as verifiable evidence of learning and enabling simpler transfer of credits across institutions. Higher education might also use blockchain to track intellectual property or as a tool to support identity management. Universities are developing uses of blockchain that can serve the administrative and educational functions such as offering self-paced MOOC certificates.
6) Virtual Assistants (VA): Automatic speech recognition (ASR) and natural language processing (NLP) of such “always listening” VA are becoming commonly supported by AI-augmented machine learning for accuracy and adding “skills” to go beyond a simple search tool. VA is becoming a familiar alternative for users to conversationally interact with their devices via any web-browser and is becoming more reliable through deep neural learning, resulting in an increase in the accuracy of NLP and ASR. VA is already capable of meeting basic student needs related to campus information and support services. Chatbot, which is a text-based VA to handle enquiry, provides students and teachers with 24-hour support, from IT Help Desk, academic advisory services to financial aid, for instance. With recent AI research and development by some local startup companies, the capability of understanding Chinese, including Cantonese and Mandarin, multiplies the educational uses for learners from Mainland China, either onsite or remotely. Besides, VA is expected to be used for research, tutoring, writing, and editing. Similarly, virtual tutors and virtual facilitators will soon be able to generate customizable and conversational learning experiences currently found in a variety of adaptive learning platforms.
4. Do you have any suggestions for our reader segment which comprises of industry veterans and young entrepreneurs from the Education Tech space?
As you may have noted from the beginning of our conversation, it was the key trends in higher education that have triggered and accelerated education technology adoption. So I would like to emphasize that Technology doesn’t need to be Hi-Tech nor expensive, but it needs to be pedagogical-driven, experience centric, and data-oriented.