email:
mlhow @ zukunft [dot] ai
(‘zukunft’ = ‘future’ in the German language)
EDUCATION:
Ph.D. (Multidisciplinary Research: Education Technology + Positive Psychology + Complexity Theory)
Monash University, Australia (graduated and conferred with PhD in 2015)
M.Sc. in Bioinformatics
University of Maryland, United States of America (graduated with M.Sc in 2006)
Received formal training in these skills:
(1) Strategies in Algorithmic Trading using Python Programming
University of Oxford (United Kingdom)
(2) Artificial Intelligence in Computational Finance & Algorithmic Trading using Python Programming
Hochschule für Technik und Wirtschaft des Saarlandes, Deutschland (Germany)
(3) Quantum Machine Learning in Finance using Python Programming
City, University of London (United Kingdom)
Teaching Experience in Institutes of Higher Learning
2023 – present
FlexiMasters Lecturer, Big Data in the Information Age
Nanyang Technological University, Singapore
2008 – present
Associate Lecturer, Software Technologies
Singapore University of Social Sciences, Singapore
2008 – 2017
Associate Lecturer, Software Technologies
University of Newcastle, Australia
2004 – 2007
Associate Lecturer, Software Technologies
Wee Kim Wee School of Communications and Information
Nanyang Technological University, Singapore
RESEARCH OUTPUT (full): Click here to view at Google Scholar
Peer-reviewed Journal Papers (selected)
- How, M.-L. & Cheah, S.M. (2024). Forging the Future: Strategic Approaches to Quantum AI Integration for Industry Transformation. AI 2024, 5(1), 290-323.
- How, M.-L. & Cheah, S.M. (2023). Business Renaissance: Opportunities and Challenges at the Dawn of the Quantum Computing Era. Businesses, 3(4), 585-605
- How, M.-L. (2022). Advancing Multidisciplinary STEM Education with Mathematics for Future-Ready Quantum Algorithmic Literacy. Mathematics, 10(7), 1146
Impact Factor: 2.592 - How, M.-L., Chan, Y.J., & Cheah, S.M. (2020). Predictive Insights for Improving The Resilience of Global Food Security using Artificial Intelligence. Sustainability, 12(15), 6272
5-year Impact Factor of the Journal: 3.889
[Indexed by Social Sciences Citation Index (SSCI), SCOPUS, Elsevier’s Inspec IET (Institute of Engineering & Technology), and Web of Science] - How, M.-L., Cheah, S.M., Khor, A.C., & Chan, Y.J. (2020). Artificial Intelligence-Enhanced Predictive Insights for Advancing Financial Inclusion: A Human-Centric AI-Thinking Approach. Big Data and Cognitive Computing, 4 (2), 8
[Indexed by SCOPUS, Elsevier’s Inspec IET (Institute of Engineering & Technology), and by Norwegian Register for Scientific Journals, Series and Publishers (NSD)] - How, M.-L., Cheah, S.M., Chan, Y.J., Khor, A.C., & Say, E.M.P. (2020). Artificial Intelligence-Enhanced Decision Support for Informing Global Sustainable Development: A Human-Centric AI-Thinking Approach. Information, 11(1), 39. [Indexed by SCOPUS, by Ei Compendex, and by Elsevier’s Inspec IET (Institute of Engineering & Technology)]
(This Open Access journal paper can be downloaded from: https://doi.org/10.3390/info11010039) - How M.-L., & Chan, Y.J. (2020). Artificial Intelligence-Enabled Predictive Insights for Ameliorating Global Malnutrition: A Human-Centric AI-Thinking Approach. AI, 1(1), 68-91.
(This Open Access journal paper can be downloaded from: https://doi.org/10.3390/ai1010004) - How, M.-L. (2019). Future-Ready Strategic Oversight of Multiple Artificial Superintelligence-Enabled Adaptive Learning Systems via Human-Centric Explainable AI-Empowered Predictive Optimizations of Educational Outcomes, Big Data and Cognitive Computing, Special Issue: Artificial Superintelligence: Coordination & Strategy, 3(3), 46 [Indexed by SCOPUS, by Elsevier’s Inspec IET (Institute of Engineering & Technology), and by Norwegian Register for Scientific Journals, Series and Publishers (NSD)]
(This Open Access journal paper can be downloaded from: https://doi.org/10.3390/bdcc3030046) - How, M.-L., and Hung, W.L.D. (2019). Educing AI-Thinking in Science, Technology, Engineering, Arts, and Mathematics (STEAM) Education, Education Sciences, Special Issue: Trends in STEM Education, 9(3), 184. [Indexed by SCOPUS, and by Emerging Sources Citation Index (ESCI)]
(This Open Access journal paper has been indexed in the ERIC database and can be downloaded from: https://eric.ed.gov/?id=EJ1230968 ) - How, M.-L., and Hung, W.L.D. (2019). Harnessing Entropy via Predictive Analytics to Optimize Outcomes in the Pedagogical System: An Artificial Intelligence-Based Bayesian Networks Approach. Education Sciences, Special Issue: Emerging Technologies in Education, 9(2), 158. [Indexed by SCOPUS, and by Emerging Sources Citation Index (ESCI)]
(This Open Access journal paper has been indexed in the ERIC database and can be downloaded from https://eric.ed.gov/?id=EJ1222926 ) - How, M.-L., and Hung, W.L.D. (2019). Educational Stakeholders’ Independent Evaluation of an Artificial Intelligence-Enabled Adaptive Learning System using Bayesian Network Predictive Simulations. Education Sciences, Special Issue: Artificial Intelligence and Education, 9(2), 110. [Indexed by SCOPUS, and by Emerging Sources Citation Index (ESCI)]
(This Open Access journal paper has been indexed in the ERIC database and can be downloaded from: https://eric.ed.gov/?id=EJ1220412) - How, M.-L., and Looi, C.-K. (2018). Using Grey-based Mathematical Equations of Decision-making as Teaching Scaffolds: from an Unplugged Computational Thinking Activity to Computer Programming. International Journal of Computer Science Education in Schools, 2(2), 8359–1. https://doi.org/10.21585/ijcses.v2i2.24
(this Open Access journal paper has been indexed in the ERIC database and can be downloaded at: https://eric.ed.gov/?id=EJ1207403) - Chee-Kit Looi, Meng-Leong How, Wu Longkai, Peter Seow and Liu Liu (2018). Analysis of linkages between an unplugged activity and the development of computational thinking, Computer Science Education, 28(3), 255-279. [Indexed by SCOPUS, and by Emerging Sources Citation Index (ESCI)]
This journal paper can be accessed at DOI: 10.1080/08993408.2018.153329
[I worked on all the drafts of this paper for the research team, including the Qualitative Comparative Analysis (QCA) used in this paper]
My multidisciplinary Ph.D. dissertation included:
(1) positive psychology: Flow Experiences +
(2) pedagogy: how the traditional methods of the Japanese Zen shakuhachi flute transformed online teaching +
(3) education technology: how telepresence videoconferencing software was used by the Zen shakuhachi flute teachers
How, M.-L. (2015). Flow Experiences of Shakuhachi Teaching via Skype.
https://figshare.com/articles/Flow_experiences_in_Shakuhachi_teaching_via_Skype/4711723
PhD was conferred by Monash University, Australia
PhD supervisors (main): Dr. Jane Southcott and Dr. Peter de Vries
(I used concepts from Complexity Theory to expand / deepen Flow Theory)
Peer-reviewed Conference Papers
How, M.-L., & Hung, W.L.D. (April, 2020). Artificial Intelligence-enhanced Analytical Collaborations between Researchers and Educational Stakeholders for Oversight of Multiple Pedagogical Systems, 2020 American Educational Research Association Annual Meeting. San Francisco, United States of America.
How, M.-L, & Looi, C. (2018). Cross Comparison of Multiple Computational Thinking Activities : a Grey-based approach. In S. C. Kong, D. Andone, G. Biswas, T. Crick, H. U. Hoppe, T. C. Hsu, … J. Vahrenhold (Eds.), Proceedings of the International Conference on Computational Thinking Education 2018 (pp. 125–128). The Education University of Hong Kong.
The conference paper proceedings can be downloaded from https://www.eduhk.hk/cte2018/doc/CTE2018%20Proceeding_Full_20180604.pdf
Wu, L. , Looi, C.-K. , How, M.-L. & He, S. (2018)
Student Questioning Tendencies and Learning Performances in a Classroom Inquiry Curriculum: An SEM Analysis.
accepted by (ICCE) International Conference for Computer Education 2018
[Nominated for Best Conference Paper award by ICCE2018]
This conference paper can be downloaded from http://icce2018.ateneo.edu/wp-content/uploads/2018/12/C4-04.pdf
(The Structural Equation Modeling analysis was written by me)
Wu, L., Looi, C.-K., Liu, L. & How, M.-L. (2018)
Understanding and Developing In-Service Teachers’ Perceptions towards Teaching in Computational Thinking: Two Studies.
accepted by International Conference for Computer Education 2018
Book Chapters
Meng-Leong How, Sin-Mei Cheah, Yong Jiet Chan, Aik Cheow Khor, Eunice Mei Ping Say (2023)
Artificial Intelligence for Advancing Sustainable Development Goals (SDGs): An Inclusive Democratized Low-Code Approach
(free with institutional access at https://doi.org/10.1007/978-3-031-21147-8_9)
Seow, P., Looi, C.-K., How, M.-L., Wadhwa, B., & Wu, L. (2019)
Educational Policy and Implementation of Computational Thinking and Programming: Case Study of Singapore. In: Kong SC., Abelson H. (eds) Computational Thinking Education. Springer, Singapore
(This open access book chapter can be downloaded from https://doi.org/10.1007/978-981-13-6528-7_19)
Looi, C.-K., Mulstisilta, J., Wu, L., How, M.-L., & Toumi, P.
Teachers’ Perceptions and Readiness to Teach Coding Skills: A Comparative Study between China, Finland, Singapore, Taiwan, and South Korea
(In Singapore, I continued the work started by Toumi in Finland to perform the quantitative statistical analyses for the research team to compare the data from China, Finland, Singapore, Taiwan, and South Korea)
Invited keynote presentation
“Harnessing AI Thinking in Education Research” was presented on 26 Nov 2019 in Singapore at the International Workshop of Artificial Intelligence in Education (WAIE) Conference. Organized by the Education University of Hong Kong (EduU HK)
Workshops
‘AI for Policymaking in Education’, presented by Dr. How at the ‘Future-Ready Colloquium’ on 9 Apr 2021, organized by the Policy, Curriculum, and Learning (PCL) Academic Group, and Academic Quality (AQ) NIE Director’s Office, National Institute of Education, Nanyang Technological University Singapore.
free online SkillsFuture sharing session https://skillsfuture.ntu.edu.sg/speakers/
Date: Wednesday 29 July 2020
My software demo session: Low-code AI-enabled Predictive 3D Simulations for Manufacturing and Healthcare Industries
My session time-slot: 3:30pm-4:10pm (Singapore time GMT +8)
Human-Machine Teaming in Practice: Bayesian Networks as a Collaborative Approach to Artificial Intelligence
Date & Time: 28 March 2019, 1:00pm – 4:00pm
Venue: TCT-LT (Tan Chin Tuan Lecture Theatre) LT2, Nanyang Technological University
Webpage: https://www.nie.edu.sg/event-detail/human-machine-teaming-in-practice-bayesian-networks-as-a-collaborative-approach-to-artificial-intelligence
Data Analytics Workshop:
Structural Equation Modeling (SEM) for Non-statisticians using SmartPLS
conducted on Friday 24th Aug 2018
in Block 5 Level 3 Meeting Room 56A
National Institute of Education, Nayang Technological University
RESEARCH GRANTS:
Research Grant which I contributed to in Nanyang Technological University (2021)
My specific role in the NTU research team: I contribute by using Artificial Intelligence techniques to create predictive models about Metacognition in Human Learning Transfer.
Project Title: Paving the Way Towards Lifewide and Lifelong Learning: Exploring and Fostering Metacognition for Learning and Transfer (Approved Programmatic-level Research)
Grant number: OER 02/21 LNH
University: National Institute of Education, Nanyang Technological University, Singapore
Research Grant which I contributed to in Nanyang Technological University (2021)
My specific role that contributed to the NTU research team: I am pivotal in initiating the collaboration between the National University of Singapore (NUS) Keio-CUTE (Connective Ubiquitous Technology for Embodiments) Centre and the Artificial Intelligence in Education research team in the National Institute of Education Singapore. (NIE).
Project Title: AI-Strokes: An AI-powered Chinese handwriting teaching aid with instant diagnostic and predictive capabilities to address cognitive and motor-related learning difficulties via game-based engagements.
Grant number: ERFP 24th Grant – DEV 04/21 YCC
University: National Institute of Education, Nanyang Technological University, Singapore
Research Grant which I contributed to in Nanyang Technological University (2020)
It was a great honor that I was invited to join MOE’s Artificial Intelligence project team as a collaborator to build the Bayesian network predictive model. The team received a Senior Specialist Track Research Fund (SSTRF) grant which had been approved for 2020. This work is a continuation of the Artificial Intelligence Adaptive Learning project announced in the National AI Strategy of Singapore in 2019.
Team: Jean Phua (PI, MOE), Tay Siu Hua (Co-PI, MOE), Tan Liang Soon (Co-PI, MOE), & How Meng Leong (Collaborator, NIE/NTU)
Project Title: Modelling Students’ Learning Progression in Mathematics with Bayesian Networks as part of Assessment for Learning (AfL). Singapore: Ministry of Education, Education Technology Division.