Huang, David Junsong

Preferred name
Huang, David Junsong
Email
junsong.huang@nie.edu.sg
Department
Office of Education Research (OER)
Personal Site(s)
ORCID
Now showing 1 - 10 of 22
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    Open Access
    Analogical transfer in mathematics
    (National Institute of Education (Singapore), 2018)
    Lawrence, Sasha Raj
    ;
    Huang, David Junsong 
      59  69
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    Open Access
    Leadership in times of pandemics: Reflections from Singapore
    (Commonwealth Council for Educational Administration & Management, 2020)
    Hung, David 
    ;
    Huang, David Junsong 
    ;
    Tan, Chloe
    The COVID-19 pandemic is compressing the timeline for Singapore’s digital transformation in education. Reflecting on the implementation of Home-Based Learning (HBL) during the pandemic, we examine three barriers that inhibit digital transformation and technological implementation in education with leadership considerations: the first order barrier is infrastructural and can be mitigated by leadership foresight; the second order barrier concerns design capabilities of teachers which can be mitigated by tight-but-loose calibration; and the third order barrier deals with sustainability which can be mitigated by ecological leadership. The tight-but-loose calibration optimises the ‘tight’ system-led innovations such as Student Learning Space (SLS) for efficient deployment and for equitable access of high quality online resources for students; and ‘loose’ opportunities for teacher-led innovations on learning designs within and beyond system-led innovations to nurture teacher agency and professionalism. We posit that ecological leadership is key to sustaining deep change together with the ‘tight-but-loose’ system calibration.
      997  1200
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    Open Access
    School leaders’ learning of diffusion of innovation through agent based modeling: Coupling modeling and simulation process with learners’ interaction with diffusion system
    (2008-10)
    Huang, David Junsong 
    ;
    Chai, Ching Sing
    ;
    Chen, Der-Thanq
    If school diffusion of innovation is viewed as complex adaptive process, how shall we prepare school leaders to be effective diffusion decision makers? Coming from the epistemological belief that knowledge is subjective and embodied, this paper proposes to use Agent Based Modeling (ABM) for learning by focus on learning to “do” diffusion of innovation rather than learning about diffusion of innovation. We therefore recommend to engage school leaders in iterative agent based model development process and to couple it with their interaction in real world diffusion system. With feedback from real world system used for iterative model calibration and validation, the affordances of the agent based model allow school leaders to participate, experience, appropriate, perform and therefore to learn to make effective diffusion decisions in their schools.
      122  113
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    Restricted
    Cultivating laterality in learning communities in Singapore education system: Scaling of innovation through networked learning community
    (Office of Education Research, National Institute of Education, Singapore, 2020)
    Huang, David Junsong 
    ;
    Hung, David 
    ;
    Kwan, Yew Meng
    ;
    Lim, Fei Victor 
    ;
    Imran Shaari
    ;
    Cheah, Yin Hong
    Cultivating teachers to be active and agentic learners is crucial for contemporary teacher education (Lipponen & Kumpulainen, 2011). Those teachers’ qualities are essential in preparing students’ future readiness in an increasingly complex world (P21 Framework Definitions, 2015). In fact, both learning principles and evidence from practice inform us that purposeful collaboration in networked learning communities (NLCs) encourage teacher agency to learn (Lieberman & Wood, 2003; Muijs, West & Ainscow, 2010). As a complement to the literature, we are interested in the development of social relationships among teachers, which enables and facilitates their learning. We propose “laterality” – the relations and networks among peers (e.g., teachers) as an important concept to characterize NLCs.
    Studies on laterality, which have shown to support teacher learning, are usually found in the decentralized systems where individuals are the best entities to form these networks to support each other’s growth (Hargreaves & Goodman, 2006; Muijs et al., 2010). Thus, developing laterality from the bottom-up becomes natural in the decentralized contexts (Granovetter, 1973). Despite considerable theoretical promise of laterality and its increasing prevalence in practice, we wonder whether teacher laterality matters in the centralized education systems, and if it does, how it grows.
      366  19
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    Open Access
    Investigating analogical problem posing as the generative task in the productive failure design
    (2016-06)
    Huang, David Junsong 
    ;
    Lam, Rachel Jane
    ;
    Kapur, Manu
    Research on Productive Failure and preparatory mechanisms has consistently demonstrated a positive learning effect when students generate problem solutions before receiving formal instruction. However, it has been less examined whether the effect still holds when the generative task does not involve problem solving. Using a 2x2 experimental design, this study investigated the effects of generative tasks that involve analogical problem posing (without solving) on learning and transfer. Pedagogical sequence (i.e., generation-first or instruction-first) and type of analogical reasoning task (i.e., generating one’s own analogical problems or generating analogical mappings between given analogical problems) were the two factors manipulated. Preliminary analysis revealed no multivariate effects of the factors. Thus, we discuss the learning mechanisms enacted by analogical reasoning, reliability of the instruments, and the participants’ prior condition as possible reasons and to inform future studies.
      409  208
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    Open Access
    Cultivating laterality in learning communities – Scaling of innovation through a networked learning community
    (National Institute of Education (Singapore), 2018)
    Huang, David Junsong 
    ;
    Hung, David 
    ;
    Kwan, Yew Meng
    ;
    Lim, Fei Victor 
    ;
    Imran Shaari
    ;
    Cheah, Yin Hong
      377  171
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    Open Access
    Building the science of research management: What can research management learn from education research?
    (Society of Research Administrators International, 2018)
    Huang, David Junsong 
    ;
    Hung, David 
    Research management is an emerging field of study and its development is significant to the advancement of research enterprise. Developing the science of research management requires investigating social mechanisms involved in research management. Yet, studies on social mechanisms of research management is lacking in the literature. To address this gap, this paper proposes importing methodologies and theories from other social science disciplines to study the social mechanisms of research management and to build the science of research management. The paper first articulates what constitutes the science of research management, then proposes to appropriate Design-Based Research (DBR), a methodology in education research, for building the science of research management while at the same time strengthening the theory-practice nexus. A study of education research is then presented to illustrate how DBR is used to enact the theory of homophily which is imported from sociology. It reveals an opportunity to use social designs to develop social relationships among teachers from different schools for networked learning. Such a research endeavour also has potential to advance theories of relationship-building in sociology. Inferring from the example as an analogue to what is suggested for research management, the paper advocates a way to reciprocally connect research management as an emerging research field with more established social science disciplines at large and to advance both the theory and practice of research management.
      284  200
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    Unveiling the dynamics of learning behaviors in learning K-12 math: An exploration of an assistments dataset
    (IEEE, 2024)
    Huang, David Junsong 
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    Radhakrishnan, Arya
    ;
    Lee, Timothy
    ;
    Lee, Min
    ;
    Lum, Janice
    ;
    Liu, Guimei
    ;
    Kim, Jung Jae
    This study delves into the dynamics between diverse learning behaviors among K-12 students and their learning gains using a dataset of 508 students learning three math skills in ASSISTments. Employing K-means clustering based on students’ initial and final skill mastery alongside their engagement level, three distinct clusters emerged for each skill, revealing varying degrees of learning from ASSISTments. By analyzing decision tree classification models for each skill using affective labels such as boredom and frustration, we hypothesize that students within the same cluster of a skill may exhibit heterogeneous learning patterns that affect their subsequent learning of new skills. Further exploration demonstrates that students who transit between clusters when learning new skills differ significantly in their initial and final mastery of previously learned skills and their affective labels associated with those skills. Regression analysis underscores that students’ initial and final mastery of antecedent skills have some influence on their subsequent mastery of new skills. Unraveling the intricate relationship between student learning behaviors and the effectiveness of ASSISTments offers valuable insights into tailoring AI-enhanced educational tools, not only for learning the current skill but also for preparing for the future learning of new skills.
      7
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    Open Access
    Integrating artificial intelligence into science lessons: Teachers’ experiences and views
    (Springer, 2023)
    Park, Joonhyeong 
    ;
    Teo, Tang Wee 
    ;
    Teo, Arnold
    ;
    Huang, David Junsong 
    ;
    Koo, Sengmeng
    ;
    Chang, Jina

    Background
    In the midst of digital transformation, schools are transforming their classrooms as they prepare students for a world increasingly automated by new technologies, including artificial intelligence (AI). During curricular implementation, it has not made sense to teachers to teach AI as a stand-alone subject as it is not a traditional discipline in schools. As such, subject matter teachers may need to take on the responsibility of integrating AI content into discipline-based lessons to help students make connections and see its relevance rather than present AI as separate content. This paper reports on a study that piloted a new lesson package in science classrooms to introduce students to the idea of AI. Specifically, the AI-integrated science lesson package, designed by the research team, provided an extended activity that used the same context as an existing lesson activity. Three science teachers from different schools piloted the lesson package with small groups of students and provided feedback on the materials and implementation.

    Findings
    The findings revealed the teachers’ perceptions of integrating AI into science lessons in terms of the connection between AI and science, challenges when implementing the AI lesson package and recommendations on improvements. First, the teachers perceived that AI and science have similarities in developing accurate models with quality data and using simplified reasoning, while they thought that AI and science play complementary roles when solving scientific problems. Second, the teachers thought that the biggest challenge in implementing the lesson package was a lack of confidence in content mastery, while the package would be challenging to get buy-in from teachers regarding curriculum adaptation and targeting the appropriate audience. Considering these challenges, they recommended that comprehensive AI resources be provided to teachers, while this package can be employed for science enrichment programs after-school.

    Conclusions
    The study has implications for curriculum writers who design lesson packages that introduce AI in science classrooms and for science teachers who wish to contribute to the development of AI literacy for teachers and the extension of the range of school science and STEM to students.

    WOS© Citations 1  60  48Scopus© Citations 12
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    Open Access
    Multi-level ICT integration for diffusing complex technology-mediated pedagogical innovations
    (National Institute of Education (Singapore), 2017)
    Toh, Yancy
    ;
    Chai, Ching Sing
    ;
    Huang, David Junsong 
    ;
    Wong, Lung Hsiang 
    ;
    Cheah, Yin Hong
      183  179