Human Computer Interaction (HCI) in Education
Human Computer Interaction (HCI) in Education
Shaping the Future of Learning
Tell us about yourself
I currently conduct human-computer interaction (HCI) research at the National University of Singapore. I’m interested in the design of technological tools and systems that support lifelong learning and health/wellbeing practice. My recent projects have involved the use of augmented reality (AR) headsets to support digital tasks in casual everyday settings. Some example projects are listed here.
I graduated from Yale-NUS College in Singapore, majoring in Psychology and minoring in Mathematical, Computational and Statistical Sciences. Subsequently, I worked in the tech entrepreneurial space, first at an early-stage venture capital and then with startups. The goals of commercialisation and academic research are vastly different, and for me at this point of my life, I find great meaning in research. As one professor explained, “research is seeking to explore a possible future by building early-stage prototypes and trying to figure out what’s important, what’s not, and where the interesting problems lie.” In doing so, somewhere down the line, I hope to guide the translation of academic insights into tangible, real-world applications in industry, policy and non-profit initiatives.
Could you explain your role in human-computer interaction to a 10-year-old?
It might help to break down the acronym “HCI”. Human. Computer. Interaction.
While a social scientist might be interested in studying the “Human” part, and a computer scientist in the “Computer” part, a HCI researcher focuses on the two-way communication between man and machine. You’d need to know quite a bit about humans (how humans think, feel, behave) and also about various technicalities (tech systems, devices, frameworks, interaction styles, etc.).
Now, imagine that you are asked to fly this plane.
It sure looks overwhelming. While pilots are trained to operate this, they too may be prone to errors, balancing several tasks all at once, confusing its knobs, faders and indicators. The HCI researcher might ask - how can we redesign/reengineer this to help a pilot do their job better? How do we also help humans communicate more effectively with this piece of machinery, and vice-versa? How do we enhance seamlessness, intuitiveness and most importantly, safety? It is also vital to balance human needs with technological possibilities. In other words, some ideas might be perfect but not technologically viable.
The above case and line of questioning is just a relatively simplistic example. It’s exciting to know that HCI research spans all topics possible — Privacy and security network for banks, textiles fabrication via 3D printing, autonomous driving vehicles, natural language processing (a branch of AI) to study social media content…you name it.
What factors make coding tools engaging for young learners?
I read somewhere that “Curiosity is for knowledge what hunger is for food”. The curious learner is self-motivated, creative, and resourceful. Curiosity actually arises from uncertainty (a rather uncomfortable feeling)! When we realise that we lack desired knowledge, we become curious and feel compelled to uncover missing information. In this vein, when educators present information in a way that makes 'information gaps' salient, we encourage learners to seek out more.
What design techniques make coding tools engaging for young learners?
1. Rousing Curiosity
One technique could be to reveal enough of a puzzle/topic, but also leaving salient information gaps that compels children to ask about it, or explore as a means of filling the knowledge gap. A teacher can also weave coding education with narratives or storytelling to rouse curiosity, or pose challenging questions that encourage students to seek answers in their own unique way.
2. Balancing Stimulation
There is a fine line between understimulation and overstimulation. When the content lacks sufficient novelty or complexity, children end up bored and would rather do something else. When overstimulated or overloaded with information, students may disengage (e.g. daydream) to reduce their level of arousal. They may be discouraged and give up. An observant teacher would be able to identify and cater to this, finding the sweet spot for each child’s optimal learning.
3. Personalising Delivery
In today’s highly digitalised world of education, I’m a fan of learning platforms with adaptive feedback systems. These coding platforms provide just-in-time feedback for learners just like a real teacher might. They may have dynamic features, such as automatically adapting the difficulty level according to students' behaviour and understanding level. These tech platforms can supplement educational journeys in very real ways, especially given the shortage of educators and lack of access some students face.
Latest Trends in HCI for Education
HCI pulls together methods and insights from many disciplines, to inform the design and development of technology. The intersection between HCI and education is a broad one, but here are some established areas of research that I personally find fascinating:
1. Productive Failure
This is an educational approach where learners are deliberately given challenging tasks or problems that may initially result in failure. Through this process, they gain deeper understanding, problem-solving skills, and resilience.
Example research paper: Oleson et al. 2020 “Computing Students’ Learning Difficulties in HCI Education”
2. Gamification
HCI researchers may explore how gamification enhances student motivation, skill development, and learning outcomes.
Example research paper: Borges et al. 2014 “A Systematic Mapping on Gamification Applied to Education”
3. Learning Analytics and Educational Data Science
HCI researchers analyse data from educational systems like learning management systems and online courses, using methods such as machine learning and statistical analysis. They visualise this data to understand student behaviour and improve teaching strategies.
Example research paper: Lemay et al. 2021 “Comparison of learning analytics and educational data mining: A topic modeling approach”
Where can we find you?
You can visit my website feliciatan.co or reach out to me via email felicia.tanfy@gmail.com.