Microlearning helps Alzheimer’s Disease Patients





Microlearning, Alzheimer’s disease, Machine learning, Just-in-Time Learning, Learners, Bite-Sized Learning Units, Caregivers, Healthcare


Alzheimer's disease is one of the most common diseases in older adults, and as the disease progresses, the need for daily care increases. Caregivers of Alzheimer's Disease patients face a variety of stresses and work pressures. Receiving professional and continuous training is one of the effective ways to improve their skills and competencies. A new approach to education is microlearning, where microeducational content is provided to learners. Microlearning as a pedagogical technique focuses on designing learning modules through micro-steps in a digital media environment. These activities can be integrated into learners' daily lives and tasks. Unlike "traditional" e-learning methods, microlearning often favours technology delivered through push media, thus reducing the cognitive load on the learner. Microlearning educational methods have been shown to be effective and efficient in educating and delivering materials to caregivers of older adults with Alzheimer's disease. This paper begins with a brief introduction to microlearning. And it details the key features and benefits of microlearning. Microlearning offers potential benefits to Alzheimer's Disease patients and their caregivers with its concise and focused approach. Secondly, machine learning enhances the design and delivery of microlearning, helping to provide a more personalised and effective learning experience. Machine learning plays a role in the design of microlearning. To conclude, microlearning offers a promising avenue of support and care for Alzheimer's Disease patients. Microlearning also provides a valuable resource for carers and healthcare professionals to gain the knowledge and skills needed to provide effective care.


J. Zhang, "Practices and Innovative Technologies for Enhancing Microlearning," 2022.

L. Kohnke, Using Technology to Design ESL/EFL Microlearning Activities: Springer Nature, 2023.

I. Nikkhoo, Z. Ahmadi, M. Akbari, S. Imannezhad, S. Anvari Ardekani, and H. Lashgari, "Microlearning for Today’s Students: A Rapid Review of Essentials and Considerations," Medical Education Bulletin, vol. 4, pp. 673-685, 2023.

N. Sachdeva, "Designing Evidence-Informed Microlearning for Graduate-Level Online Courses," University of Toronto (Canada), 2023.

A.-d. Taylor and W. Hung, "The effects of microlearning: a scoping review," Educational technology research and development, vol. 70, pp. 363-395, 2022.

K. K. Fujii, "Learning in Short Bursts: A Content Analysis of Professional Development Microlearning Videos," University of Hawai'i at Manoa, 2023.

T. Krasnova, A. Kouznetsova, М. Ovsyannikova, and A. Loginova, "MICROLEARNING FOR GENERATION Z IN THE FOREIGN LANGUAGE CLASSROOM," in EDULEARN23 Proceedings, 2023, pp. 987-996.

Z. Ghafar, S. T. Abdulkarim, L. M. Mhamad, R. A. Kareem, P. A. Rasul, and T. I. Mahmud, "Microlearning As a Learning Tool for Teaching and Learning in Acquiring Language: Applications, Advantages, And Influences on the Language," Canadian Journal of Educational and Social Studies, vol. 3, pp. 45-62, 2023.

D. A. K. Kusmana, R. Dewanti, and S. D. Sulistyaningrum, "An English Reading Material Analysis Through Microlearning and Critical Thinking Skill Views," ELT-Lectura, vol. 10, pp. 42-50, 2023.

H. Robles, M. Jimeno, K. Villalba, I. Mardini, C. Viloria-Nuñez, and W. Florian, "Design of a micro-learning framework and mobile application using design-based research," PeerJ Computer Science, vol. 9, p. e1223, 2023.

Y.-M. Lee, "Mobile microlearning: a systematic literature review and its implications," Interactive Learning Environments, vol. 31, pp. 4636-4651, 2023.

M. Kurni, M. S. Mohammed, and K. Srinivasa, "AI for mobile learning," in A Beginner's Guide to Introduce Artificial Intelligence in Teaching and Learning, ed: Springer, 2023, pp. 83-103.

S. Arnab and L. Walaszczyk, "The potential of game-based micro-learning resources for engaging learners with intercultural competence development," Journal of Cognitive Sciences and Human Development, vol. 8, pp. 1-22, 2022.

T. N. Fitria, "Microlearning in teaching and learning process: A review," CENDEKIA: Jurnal Ilmu Sosial, Bahasa Dan Pendidikan, vol. 2, pp. 114-135, 2022.


Y. Yilmaz, D. Papanagnou, A. Fornari, and T. M. Chan, "The Learning Loop: Conceptualizing Just‐in‐Time Faculty Development," AEM Education and Training, vol. 6, p. e10722, 2022.

M. C. Criveanu, M. C. Florescu, P. A. P. Ines, P. P. A. B. Gouveia, G. Casalino, A. Angelastro, et al., "Microlearning-Needs and Expectations," Advances in Science and Technology, vol. 131, pp. 35-50, 2023.

H. K. Khong and M. K. Kabilan, "A theoretical model of micro-learning for second language instruction," Computer Assisted Language Learning, vol. 35, pp. 1483-1506, 2022.

N. F. Alias and R. Abdul Razak, "Exploring The Pedagogical Aspects of Microlearning in Educational Settings: A Systematic Literature Review," Malaysian Journal of Learning and Instruction (MJLI), vol. 20, pp. 267-294, 2023.

I. Hyvärinen, K. Kainulainen, N. Villaman, and T. Quynh, "Aalto University Microlearning playbook–Crafting captivating learning experiences," 2023.

R. Damaševičius and T. Sidekerskienė, "Designing Metaverse Escape Rooms for Microlearning in STEM Education," in Fostering Pedagogy Through Micro and Adaptive Learning in Higher Education: Trends, Tools, and Applications, ed: IGI Global, 2023, pp. 192-211.

L. Kohnke, D. Foung, and D. Zou, "Microlearning: A new normal for flexible teacher professional development in online and blended learning," Education and Information Technologies, pp. 1-24, 2023.

E. Y. Sozmen, "Perspective on pros and cons of microlearning in health education," Essays in Biochemistry, vol. 66, pp. 39-44, 2022.

H. Praherdhiono and Y. Prihatmoko, "Optimization of web-based physics learning technology through on-demand microlearning video download facility in an internet accessibility variation case," Momentum: Physics Education Journal, vol. 7, pp. 290-298, 2023.

L. McNeill and D. Fitch, "Microlearning through the lens of Gagne’s nine events of instruction: A qualitative study," TechTrends, vol. 67, pp. 521-533, 2023.

I. S. Isibika, C. Zhu, E. De Smet, and A. K. Musabila, "The influence of user-perceived benefits on the acceptance of microlearning for librarians’ training," Research in Learning Technology, vol. 31, 2023.

M. Belkaisse and B. Manel, "Investigating Students’ Use of Micro-Learning on TikTok Mobile Application to Improve Their English Pronunciation Case Study: Undergraduate English Language Students at Abdelhafid Boussouf University Center of Mila," University Center of Abdel Hafid Boussouf Mila, 2023.

K. Leong, A. Sung, R. Au, and C. Lee, "A study of learners’ interactive preference on multimedia microlearning," 2022.


J. I. F. Almario, R. L. G. Castro, C. J. S. Pabustan, C. J. P. David, A. J. Macabali, J. C. G. Tolentino, et al., "Fostering Pre-service Physical Educators’ Retention of Concepts in a Professional Education Course Using Moneypoly Game," International Journal of Multidisciplinary: Applied Business and Education Research, vol. 4, pp. 3366-3389, 2023.

J. Goldstein, J. M. Martindale, C. Albin, K. Xixis, R. Gottlieb-Smith, S. Otallah, et al., "Be in the Digital Room Where it Happens, Part II: Social Media for Neurology Educators," Child Neurology Open, vol. 10, p. 2329048X231169400, 2023.

T. Beste, "Knowledge transfer in a Project-Based organization through microlearning on cost-efficiency," The Journal of Applied Behavioral Science, vol. 59, pp. 288-313, 2023.

J. T. Karlsen, E. Balsvik, and M. Rønnevik, "A study of employees’ utilization of microlearning platforms in organizations," The Learning Organization, 2023.

E. Roth, M. Moencks, G. Beitinger, A. Freigang, and T. Bohné, "Microlearning in Human-centric Production Systems," in 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2022, pp. 0037-0041.

O. Gherman, C. E. Turcu, and C. O. Turcu, "An Approach to Adaptive Microlearning in Higher Education," arXiv preprint arXiv:2205.06337, 2022.

D. Chen, A. Ayoob, T. S. Desser, and A. Khurana, "Review of learning tools for effective radiology education during the COVID-19 era," Academic Radiology, vol. 29, pp. 129-136, 2022.

R. Campos, R. P. dos Santos, and J. Oliveira, "Providing recommendations for communities of learners in MOOCs ecosystems," Expert Systems with Applications, vol. 205, p. 117510, 2022.

P. Aithal and S. Aithal, "Stakeholders’ Analysis of the Effect of Ubiquitous Education Technologies on Higher Education," International Journal of Applied Engineering and Management Letters (IJAEML), vol. 7, pp. 102-133, 2023.

E. Balsvik and M. Rønnevik, "Employees as self-regulated learners: a case study of employees’ upskilling through internal microlearning platforms," Handelshøyskolen BI, 2022.

V. Gaur and A. Bhatt, "Alzheimer’s: A Psycho-Social Concern," resmilitaris, vol. 13, pp. 5818-5829, 2023.

M. X. Richardson, O. Aytar, K. Hess-Wiktor, and S. Wamala-Andersson, "Digital microlearning for training and competency development of elderly care personnel: a mixed-methods implementation study to assess needs, effectiveness, and areas of application," 2022.

H. Haghighat, M. Shiri, M. Esmaeili Abdar, S. S. Taher Harikandee, and Z. Tayebi, "The effect of micro-learning on trauma care knowledge and learning satisfaction in nursing students," BMC Medical Education, vol. 23, p. 622, 2023.

Y. Zhang, "Smart detection on abnormal breasts in digital mammography based on contrast-limited adaptive histogram equalization and chaotic adaptive real-coded biogeography-based optimization," Simulation, vol. 92, pp. 873-885, 2016.

J. Azmi, M. Arif, M. T. Nafis, M. A. Alam, S. Tanweer, and G. Wang, "A systematic review on machine learning approaches for cardiovascular disease prediction using medical big data," Medical Engineering & Physics, vol. 105, p. 103825, 2022.

S. Wang, "Pathological Brain Detection by a Novel Image Feature—Fractional Fourier Entropy," Entropy, vol. 17, pp. 8278-8296, 2015.

A. Rajesh, Y. Kihara, C. S. Lee, and A. Y. Lee, "Semi-Supervised Learning Improves Model Performance for Retinal Vessel Segmentation on Infrared Reflectance Imaging," Investigative Ophthalmology & Visual Science, vol. 64, Article ID: 1112, 2023.

E. E. Seghers, L. A. Briceno-Mena, and J. A. Romagnoli, "Unsupervised learning: Local and global structure preservation in industrial data," Computers & Chemical Engineering, vol. 178, Article ID: 108378, 2023.

E. F. Morales and H. J. Escalante, "A brief introduction to supervised, unsupervised, and reinforcement learning," in Biosignal processing and classification using computational learning and intelligence, ed: Elsevier, 2022, pp. 111-129.

Y. Zhang, "Feature Extraction of Brain MRI by Stationary Wavelet Transform and its Applications," Journal of Biological Systems, vol. 18, pp. 115-132, 2010.

A. Gill, D. Irwin, D. Towey, and Y. Zhang, "Using digital pedagogy to redefine design education," in Multilingual Education Yearbook 2023: Teaching with Technology in English-Medium Instruction Universities in Multilingual China, ed: Springer, 2023, pp. 171-190.

Y. D. Zhang and S. Satapathy, "A seven-layer convolutional neural network for chest CT-based COVID-19 diagnosis using stochastic pooling," IEEE Sensors Journal, vol. 22, pp. 17573 - 17582, 2022.

K. M. Sudar, P. Nagaraj, M. Ganesh, D. A. Yadav, K. M. Kumar, and V. Muneeswaran, "Analysis of Seminary Learner Campus Network Behaviour using Machine Learning Techniques," in 2022 7th International Conference on Communication and Electronics Systems (ICCES), 2022, pp. 1117-1122.

S. Wang, "Detection of Dendritic Spines using Wavelet Packet Entropy and Fuzzy Support Vector Machine," CNS & Neurological Disorders - Drug Targets, vol. 16, pp. 116-121, 2017.

T. Javorcik, "Content Management System for Creating Microlearning Courses," in International Symposium on Educational Technology (ISET), Nihon Fukushi Univ, ELECTR NETWORK, 2021, pp. 223-227.

A. Alam, "A digital game based learning approach for effective curriculum transaction for teaching-learning of artificial intelligence and machine learning," in 2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS), 2022, pp. 69-74.

P. Rohini, S. Tripathi, C. Preeti, A. Renuka, J. L. A. Gonzales, and D. Gangodkar, "A study on the adoption of Wireless Communication in Big Data Analytics Using Neural Networks and Deep Learning," in 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2022, pp. 1071-1076.

S. Wang, "Magnetic resonance brain classification by a novel binary particle swarm optimization with mutation and time-varying acceleration coefficients," Biomedical Engineering-Biomedizinische Technik, vol. 61, pp. 431-441, 2016.

S.-H. Wang, "Diagnosis of COVID-19 by Wavelet Renyi Entropy and Three-Segment Biogeography-Based Optimization," International Journal of Computational Intelligence Systems, vol. 13, pp. 1332-1344, 2020.

N. A. Memon and D. Chown, "Being responsive to Muslim learners: Australian educator perspectives," Teaching and Teacher Education, vol. 133, Article ID: 104279, 2023.

L. N. Wu, "Improved image filter based on SPCNN," Science In China Series F-Information Sciences, vol. 51, pp. 2115-2125, 2008.

S.-H. Wang and S. Fernandes, "AVNC: Attention-based VGG-style network for COVID-19 diagnosis by CBAM," IEEE Sensors Journal, vol. 22, pp. 17431 - 17438, 2022.

B. Zhang, "An Exploration of the Reform of English Informatisation Teaching in Colleges and Universities Based on Deep Learning Model and Microteaching Mode," Applied Mathematics and Nonlinear Sciences, 2023.

A. Malik, E. M. Onyema, S. Dalal, U. K. Lilhore, D. Anand, A. Sharma, et al., "Forecasting students' adaptability in online entrepreneurship education using modified ensemble machine learning model," Array, vol. 19, p. 100303, 2023.

K. Ponniah, F. T. Jose, G. K. Kassymova, A. R. Saravanakumar, and P. Sasireha, "The impact of hybrid learning in educating Tamil educator and learner relationship," International Journal of Advanced and Applied Sciences, vol. 10, pp. 102-107, 2023.




How to Cite

J. Hu, “Microlearning helps Alzheimer’s Disease Patients”, EAI Endorsed Trans e-Learn, vol. 9, Nov. 2023.