Skip to main content

Unpacking the Inherent Design Principles of Mobile Microlearning

Abstract

Mobile microlearning targets a new audience of learners: employees and workers outside of offices, using smartphones for flexible, anywhere, anytime training. The term ‘mobile’ emphasizes that the content is made for small screens of smartphones. According to literature and industry reports, micro-lessons are generally between 30 s and 5 min. While research shows that mobile microlearning is a promising approach, it remains unclear how the current systems have been ‘built’: What are the underlying principles of such platforms? The goal of this study was to explore mobile-microlearning platforms and to unpack their inherent design principles. We applied different methods: First, we reviewed literature in both academic publications and industry reports in two iterative rounds. Second, we conducted interviews with industry professionals, e.g., directors and entrepreneurs of mobile- and micro-learning systems. Results show a set of 15 principles regarding technical issues, pedagogical usability of micro-content interaction and sequenced instructional flow. They can be used to detect issues and challenges in existing mobile platforms and may inform meaningful design principles for future development. The results expose that a more critical eye on the learning design implied in the small-screen platforms is needed e.g., future systems may include learning designs for higher order thinking skills.

This is a preview of subscription content, access via your institution.

Fig. 1

References

  • Ahmad, N. (2018). Effects of gamification as a micro learning tool on instruction (pp. 1–9). E-Leader Bangkok 2018. Retrieved March 13, 2018, from https://www.g-casa.com/conferences/bangkok18/pdf_paper/Ahmad%20Effects%20Gamification.pdf.

  • Aitchanov, B., Zhaparov, M., & Ibragimov, M. (2018). The research and development of the information system on mobile devices for micro-learning in educational institutes. In 2018 14th international conference on electronics computer and computation (ICECCO) (pp. 1–4). IEEE.

  • AlTameemy, F. (2017). Mobile phones for teaching and learning: Implementation and students’ and teachers’ attitudes. Journal of Educational Technology Systems,45(3), 436–451. https://doi.org/10.1177/0047239516659754.

    Article  Google Scholar 

  • Andoniou, C. (2017). Technoliterati: Digital explorations of diverse micro-learning experiences, Vol. 7. Retrieved October 18, 2017, from https://dspace.adu.ac.ae/handle/1/1141.

  • Anshari, M., Almunawar, M. N., Shahrill, M., Wicaksono, D. K., & Huda, M. (2017). Smartphones usage in the classrooms: Learning aid or interference? Education and Information Technologies. https://doi.org/10.1007/s10639-017-9572-7.

    Article  Google Scholar 

  • Asiimwe, E. N., Grönlund, Å., & Hatakka, M. (2017). Practices and challenges in an emerging m-learning environment. International Journal of Education & Development Using Information & Communication Technology,13(1), 103–122.

    Google Scholar 

  • Baek, Y., & Touati, A. (2017). Exploring how individual traits influence enjoyment in a mobile learning game. Computers in Human Behavior,69, 347–357. https://doi.org/10.1016/j.chb.2016.12.053.

    Article  Google Scholar 

  • Biloš, A., Turkalj, D., & Kelić, I. (2017). Mobile learning usage and preferences of vocational secondary school students: The cases of Austria, the Czech Republic, and Germany. Naše Gospodarstvo/Our Economy,63(1), 59–69. https://doi.org/10.1515/ngoe-2017-0006.

    Article  Google Scholar 

  • Bursztyn, N., Shelton, B., Walker, A., & Pederson, J. (2017). Increasing undergraduate interest to learn geoscience with GPS-based augmented reality field trips on Student’s own smartphones. GSA Today,27(6), 4–10.

    Google Scholar 

  • Butgereit, L. (2016). Gamifying mobile micro-learning for continuing education in a corporate IT environment. In Paper presented at the IST-Africa week conference. https://doi.org/10.1109/istafrica.2016.7530597.

  • Cairnes, R. (2017). Beyond the hype of micro learning: 4 steps to holistic learning. Retrieved November 21, 2018, from https://www.insidehr.com.au/hype-micro-learning-4-steps-holistic-learning/.

  • Callisen, L. (2016). Why micro learning is the future of training in the workplace. Retrieved October 18, 2017, from https://elearningindustry.com/micro-learning-future-of-training-workplace.

  • Carter, J. (2017). Expanding access to learning with mobile digital devices. Journal of Research & Practice for Adult Literacy, Secondary & Basic Education,6(2), 49–54.

    Google Scholar 

  • Cates, S., Barron, D., & Ruddiman, P. (2017). MobiLearn go: Mobile microlearning as an active, location-aware game. In Paper presented at the Proceedings of the 19th international conference on human-computer interaction with mobile devices and services. https://doi.org/10.1145/3098279.3122146.

  • Cerratto-Pargman, T., & Jahnke, I. (2019). Emergent practices and material conditions in learning and teaching with technologies. New York: Springer.

    Google Scholar 

  • Chee, K. N., Yahaya, N., Ibrahim, N. H., & Hasan, M. N. (2017). Review of mobile learning trends 2010–2015: A meta-analysis. Journal of Educational Technology & Society,20(2), 113–126.

    Google Scholar 

  • Clark, H., Jassal, P. K., Van Noy, M., & Paek, P. L. (2018). A new work-and-learn framework. In D. Ifenthaler (Ed.), Digital workplace learning (pp. 23–41). New York: Springer. https://doi.org/10.1007/978-3-319-46215-8_3.

    Chapter  Google Scholar 

  • Creswell, J. (2009). Research design. Thousand Oaks: Sage.

    Google Scholar 

  • Cruz, S., Carvalho, A. A. A., & Araújo, I. (2017). A game for learning history on mobile devices. Education and Information Technologies,22(2), 515–531. https://doi.org/10.1007/s10639-016-9491-z.

    Article  Google Scholar 

  • Dai, H., Tao, Y., & Shi, T. W. (2018). Research on mobile learning and micro course in the big data environment. In Proceedings of the 2nd international conference on e-education, e-business and e-technology (pp. 48–51). ACM.

  • Dale, L. P., White, L., Mitchell, M., & Faulkner, G. (2018). Smartphone app uses loyalty point incentives and push notifications to encourage influenza vaccine uptake. Vaccine. https://doi.org/10.1016/j.vaccine.2018.04.018.

    Article  Google Scholar 

  • Decker, J., Hauschild, A., Meinecke, N., Redler, M., Schumann, M. (2017). Adoption of micro and mobile learning in german enterprises: A Quantitative Study. In: European conference on e-Learning (pp. 132–141). Retrieved February 23, 2018, from https://search.proquest.com/openview/5c22efcba40bc65029b37b6a9863cb70/1?pq-origsite=gscholar&cbl=1796419.

  • D’Errico, D. (2016). Mobile learning: What’s it good for? Absolutely everything (that needs to be done now). Workforce Solutions Review,7(3), 11–13.

    Google Scholar 

  • Ely, M. (1991). Doing qualitative research: Circles within circles. New York: Routledge.

    Google Scholar 

  • Emerson, L., & Berge, Z. (2018). Microlearning: Knowledge management applications and competency-based training in the workplace. Knowledge Management & E-Learning: An International Journal,10(2), 125–132.

    Google Scholar 

  • Fang, Q. (2018). A study of college english teaching mode in the context of micro-learning. In 2018 International conference on management and education, humanities and social sciences (MEHSS 2018). Atlantis Press.

  • Faulkner, L. (2003). Beyond the five-user assumption: Benefits of increased sample sizes in usability testing. Behavior Research Methods, Instruments, and Computers,35(3), 379–383.

    Google Scholar 

  • Gagne, R. (1987). Instructional technology foundations. Hillsdale, NJ: Lawrence Erlbaum Association.

    Google Scholar 

  • Gao, B., Wan, Q., Chang, T., & Huang, R. (2019). A framework of learning activity design for flow experience in smart learning environment. In M. Chang, E. Popescu, N.-S. C. Kinshuk, M. Jemni, R. Huang, & D. G. Sampson (Eds.), Foundations and trends in smart learning (pp. 5–14). Singapore: Springer.

    Google Scholar 

  • Gassler, G., Hug, T., & Glahn, C. (2004). Integrated micro learning—An outline of the basic method and first results. Interactive Computer Aided Learning,4, 1–7.

    Google Scholar 

  • Giurgiu, L. (2017). Microlearning an evolving elearning trend. Buletin Stiintific,22(1), 18–23. https://doi.org/10.1515/bsaft-2017-0003.

    Article  Google Scholar 

  • Glahn, C. (2017). Micro learning in the workplace and how to avoid getting fooled by micro instructionists—Christian Glahn. Retrieved November 21, 2018, from https://lo-f.at/glahn/2017/06/micro-learning-in-the-workplace-and-how-to-avoid-getting-fooled-by-micro-instructionists.html.

  • Goggins, S. P., Jahnke, I., & Wulf, V. (2013). Computer-supported collaborative learning at the workplace. New York: Springer. https://doi.org/10.1007/978-1-4614-1740-8.

    Book  Google Scholar 

  • Göschlberger, B., & Bruck, P. A. (2017). Gamification in mobile and workplace integrated microLearning. In iiWAS’17: The 19th international conference on information integration and web-based applications & services, December 4–6, 2017, Salzburg, Austria. https://doi.org/10.1145/3151759.3151795.

  • Griol, D., Molina, J. M., & Callejas, Z. (2017). Incorporating android conversational agents in m-learning apps. Expert Systems,34, 4. https://doi.org/10.1111/exsy.12156.

    Article  Google Scholar 

  • Harris, C. W. (2018). Gnowbe—The latest guest to the platform party is distinctly mobile. Journal of Applied Learning and Teaching,1(2), 38–42.

    Google Scholar 

  • Howland, J., Jonassen, D., & Marra, R. (2012). Meaningful learning with technology (4th ed.). Boston, MA: Pearson.

    Google Scholar 

  • Hug, T., Lindner, M., & Bruck, P. (2005). Microlearning: Emerging concepts, practices and technologies after e-learning. Innsbruck University Press. https://www.researchgate.net/publication/246822097_Microlearning_Emerging_Concepts_Practices_and_Technologies_after_e-Learning.

  • Hui, B. (2014). Application of micro-learning in physiology teaching for adult nursing specialty students. Journal of Qiqihar University of Medicine, (21), 61. Retrieved October 16, 2017, from http://en.cnki.com.cn/Article_en/CJFDTOTAL-QQHB201421061.htm

  • Jacob, S. A., & Furgerson, S. P. (2012). Writing interview protocols and conducting interviews: Tips for students new to the field of qualitative research. The Qualitative Report,17(42), 1–10.

    Google Scholar 

  • Jahnke, I., Bergstrom, P., Marell-Olsson, E., Hall, L., & Kumar, S. (2017). Digital Didactical Designs as research framework: iPad integration in Nordic schools. Computers & Education, 113, 1–15.

    Google Scholar 

  • Javorcik, T., & Polasek, R. (2018). The basis for choosing microlearning within the terms of e-learning in the context of student preferences. In 2018 16th international conference on emerging elearning technologies and applications (ICETA) (pp. 237–244). https://doi.org/10.1109/iceta.2018.8572183.

  • Jiang, J., Hou, Y., & Zhen, X. (2018). The design of mobile learning resources based on WeChat. In 2018 13th international conference on computer science education (ICCSE) (pp. 1–3). https://doi.org/10.1109/iccse.2018.8468841.

  • Jin, J., & Bridges, S. M. (2014). Educational technologies in problem-based learning in health sciences education: A systematic review. Journal of Medical Internet Research. https://doi.org/10.2196/jmir.3240.

    Article  Google Scholar 

  • Jing-Wen, M. (2016). A design and teaching practice of micro mobile learning assisting college English teaching mode base on WeChat public platform. DEStech Transactions on Social Science Education and Human Science (mess). https://doi.org/10.12783/dtssehs/mess2016/9595.

    Article  Google Scholar 

  • Jonassen, D. (1996). Computers in the classroom: mindtools for critical thinking. New Jersey: Prentice-Hall.

    Google Scholar 

  • Kabir, F. S., & Kadage, A. T. (2017). ICTs and educational development: The utilization of mobile phones in distance education in Nigeria. Turkish Online Journal of Distance Education,18(1), 63–76.

    Google Scholar 

  • Kaliisa, R., & Picard, M. (2017). A systematic review on mobile learning in higher education: The African perspective. Turkish Online Journal of Educational Technology - TOJET,16(1), 1–18.

    Google Scholar 

  • Kamilali, D., & Sofianopoulou, C. (2015). Microlearning as innovative pedagogy for mobile learning in MOOCs. Madrid: International Association for Development of the Information Society.

    Google Scholar 

  • Khaddage, F., Müller, W., & Flintoff, K. (2016). Advancing mobile learning in formal and informal settings via mobile app technology: Where to from here, and how? Journal of Educational Technology & Society,19(3), 16–26. https://doi.org/10.2307/jeductechsoci.19.3.16.

    Article  Google Scholar 

  • Khurgin, A. (2015). Will the real microlearning please stand up? Association for Talent Development. Retrieved January 25, 2017 from https://www.td.org/insights/will-the-real-microlearning-please-stand-up.

  • Kim, S.-J., Shin, H., Lee, J., Kang, S., & Bartlett, R. (2017). A smartphone application to educate undergraduate nursing students about providing care for infant airway obstruction. Nurse Education Today,48, 145–152. https://doi.org/10.1016/j.nedt.2016.10.006.

    Article  Google Scholar 

  • Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. New Jersey: Prentice-Hall.

    Google Scholar 

  • Kovacs, G. (2015). FeedLearn: Using Facebook feeds for microlearning. Proceedings of the 33rd annual ACM Conference extended abstracts on human factors in computing systems. https://doi.org/10.1145/2702613.2732775.

  • Lau, K. P., Chiu, D. K. W., Ho, K. K. W., Lo, P., & See-To, E. W. K. (2017). Educational usage of mobile devices: Differences between postgraduate and undergraduate students. The Journal of Academic Librarianship,43(3), 201–208. https://doi.org/10.1016/j.acalib.2017.03.004.

    Article  Google Scholar 

  • Lee, W.-P., Chen, C.-T., Huang, J.-Y., & Liang, J.-Y. (2017). A smartphone-based activity-aware system for music streaming recommendation. Knowledge-Based Systems,131, 70–82. https://doi.org/10.1016/j.knosys.2017.06.002.

    Article  Google Scholar 

  • Liao, K. (2015). PressToPronounce: An output-oriented approach to mobile language learning. Massachusetts Institute of Technology. http://hdl.handle.net/1721.1/100628.

  • Lin, H.-H., Wang, Y.-S., Li, C.-R., Shih, Y.-W., & Lin, S.-J. (2017). The measurement and dimensionality of mobile learning systems success: Two-stage development and validation. Journal of Educational Computing Research,55(4), 449–470. https://doi.org/10.1177/0735633116671324.

    Article  Google Scholar 

  • Major, A., & Calandrino, T. (2018). Beyond chunking: micro-learning secrets for effective online design. FDLA Journal, 3(1). Retrieved from https://nsuworks.nova.edu/fdla-journal/vol3/iss1/13.

  • Mamba, T., & Kohda, Y. (2017). Smartphone applications improve high school students’ learning achievements. In Proceedings of the multidisciplinary academic conference (pp. 499–506).

  • Merriam, S. B., & Tisdell, E. J. (2015). Qualitative research: A guide to design and Implementation. San Francisco: Wiley.

    Google Scholar 

  • Mohammed, G. S., Wakil, K., & Nawroly, S. S. (2018). The effectiveness of microlearning to improve students’ learning ability. International Journal of Educational Research Review,3(3), 32–38. https://doi.org/10.24331/ijere.415824.

    Article  Google Scholar 

  • Moore, J., Dickson-Deane, C., & Liu, M. (2014). Designing CMC Courses From a Pedagogical Usability Perspective. In A. Benson (Ed.), Perspective in Instructional Technology and Distance Education (chap. 7, pp. 154–169). Information Age Publishing.

  • Nickerson, C., Rapanta, C., & Goby, V. P. (2017). Mobile or not? Assessing the instructional value of mobile learning. Business and Professional Communication Quarterly,80(2), 137–153. https://doi.org/10.1177/2329490616663707.

    Article  Google Scholar 

  • Nielsen, J. (1999). Designing Web Usability: The Practice of Simplicity. Indianapolis: New Riders Publishing.

    Google Scholar 

  • Nielsen, J. (2012). How many test users in a usability study? Retrieved from http://www.nngroup.com.

  • Nikou, S. A., & Economides, A. (2017). Mobile-based assessment: Investigating the factors that influence behavioral intention to use. Computers & Education,109, 56–73. https://doi.org/10.1016/j.compedu.2017.02.005.

    Article  Google Scholar 

  • Nikou, S. A., & Economides, A. A. (2018a). Mobile-based assessment: A literature review of publications in major referred journals from 2009 to 2018. Computers & Education,125, 101–119. https://doi.org/10.1016/j.compedu.2018.06.006.

    Article  Google Scholar 

  • Nikou, S., & Economides, A. (2018b). Mobile-based micro-learning and assessment: Impact on learning performance and motivation of high school students. Journal of Computer Assisted learning,15, 12. https://doi.org/10.1111/jcal.12240.

    Article  Google Scholar 

  • Norsanto, D., & Rosmansyah, Y. (2018). Gamified mobile micro-learning framework: A case study of civil service management learning. International Conference on Information and Communications Technology (ICOIACT),2018, 146–151. https://doi.org/10.1109/ICOIACT.2018.8350765.

    Article  Google Scholar 

  • Oyelere, S. S., Suhonen, J., Wajiga, G. M., & Sutinen, E. (2017). Design, development, and evaluation of a mobile learning application for computing education. Education and Information Technologies. https://doi.org/10.1007/s10639-017-9613-2.

    Article  Google Scholar 

  • Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research,42(5), 533–544. https://doi.org/10.1007/s10488-013-0528-y.

    Article  Google Scholar 

  • Park, Y., & Kim, Y. (2018). A design and development of micro-learning content in e-learning system. International Journal on Advanced Science, Engineering and Information Technology,8(1), 56–61. https://doi.org/10.18517/ijaseit.8.1.2698.

    Article  Google Scholar 

  • Paul, A. M. (2016). Microlearning 101. HR Magazine,61(4), 36.

    Google Scholar 

  • Rajala, L. (2016). Making training mobile (cover story). New Hampshire Business Review,38(3), 1.

    Google Scholar 

  • Rao, M. (2014). Microlearning from the KM perspective (cover story). KM World,23(2), 1–20.

    Google Scholar 

  • Reinhardt, K. S., & Elwood, S. (2019). Promising practices in online training and support: Microlearning and personal learning environments to promote a growth mindset in learners. In Handbook of research on virtual training and mentoring of online instructors (pp. 298–310). https://doi.org/10.4018/978-1-5225-6322-8.ch013.

  • Sauro, J., & Lewis, J. R. (2012). Quantifying the user experience: Practical statistics for user research. Waltham, MA: Morgan Kaufmann.

    Google Scholar 

  • Schneegass, C., Terzimehić, N., Nettah, M., & Schneegass, S. (2018). Informing the design of user-adaptive mobile language learning applications. In: Proceedings of the 17th international conference on mobile and ubiquitous multimedia (pp. 233–238). https://doi.org/10.1145/3282894.3282926.

  • Shank, P. (2018). Microlearning, macrolearning. What does research tell us? Retrieved November 21, 2018, from https://elearningindustry.com/microlearning-macrolearning-research-tell-us.

  • Shen, C. W., Kuo, C. J., & Ly, P. T. M. (2017). Analysis of social media influencers and trends on online and mobile learning. The International Review of Research in Open and Distributed Learning,18(1), 208–224.

    Google Scholar 

  • Shooriabi, M., & Gilavand, A. (2017). Investigating the use of smartphones for learning purposes by Iranian dental students. Middle East Journal of Family Medicine,15(7), 108–113.

    Google Scholar 

  • Simons, L. P., Foerster, F., Bruck, P. A., Motiwalla, L., & Jonker, C. M. (2015). Microlearning mApp raises health competence: Hybrid service design. Health and Technology,5(1), 35–43. https://doi.org/10.1007/s12553-015-0095-1.

    Article  Google Scholar 

  • Skalka, J., & Drlík, M. (2019). Educational model for improving programming skills based on conceptual microlearning framework. In M. E. Auer & T. Tsiatsos (Eds.), The challenges of the digital transformation in education (pp. 923–934). Cham: Springer International Publishing.

    Google Scholar 

  • Sun, G., Cui, T., Beydoun, G., Chen, S., Dong, F., Xu, D., et al. (2017). Towards massive data and sparse data in adaptive micro open educational resource recommendation: A study on semantic knowledge base construction and cold start problem. Sustainability,9(6), 898. https://doi.org/10.3390/su9060898.

    Article  Google Scholar 

  • Sun, G., Cui, T., Chen, S., Guo, W., & Shen, J. (2015). MLaaS: A cloud system for mobile micro learning in MOOC. Mobile Services (MS), 2015 IEEE International Conference. https://doi.org/10.1109/mobserv.2015.26.

  • Sweller, J. (2008). Cognitive load theory and the use of educational technology. Educational Technology,48(1), 32–35.

    Google Scholar 

  • Tipton, S. (2017). Maximizing Microlearning. Training,54(3), 58.

    Google Scholar 

  • Tongdee, P., Srisawat, S., Loyd, R. A., Temnitithikul, B., Phumwiriya, T., & Nimkuntod, P. (2017). Leopold’s Maneuver mobile learning technology for facilitating knowledge application and self-reported confidence of preclinical medical students. Suranaree Journal of Science & Technology,24(1), 99–103.

    Google Scholar 

  • Twum, R. (2017). Utilization of smartphones in science teaching and learning in selected universities in Ghana. Journal of Education and Practice,8(7), 216–228.

    Google Scholar 

  • Vrana, R., Gaščić, D., & Podkonjak, M. (2017). Supporting mobile learning: usability of digital collections in Croatia for use on mobile devices. In 40th jubilee International convention MIPRO 2017. Croatian Society for Information and Communication Technology, Electronics and Microelectronics-MIPRO.

  • Wang, Y.-H. (2017). Integrating self-paced mobile learning into language instruction: Impact on reading comprehension and learner satisfaction. Interactive Learning Environments,25(3), 397–411. https://doi.org/10.1080/10494820.2015.1131170.

    Article  Google Scholar 

  • Wang, N., Chen, X., Song, G., Lan, Q., & Parsaei, H. R. (2017). Design of a new mobile-optimized remote laboratory application architecture for m-learning. IEEE Transactions on Industrial Electronics,64(3), 2382–2391. https://doi.org/10.1109/TIE.2016.2620102.

    Article  Google Scholar 

  • Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. Retrieved October 16, 2017, from http://www.jstor.org/stable/pdf/4132319.pdf?refreqid=excelsior%3Acbf922481eba11f61fc85f6df40d5573.

  • Yamamoto, N., & Uchida, N. (2017). Improvement of the interface of smartphone for an active learning with high learning concentration. In 2017 31st international conference on advanced information networking and applications workshops (WAINA) (pp. 531–534). https://doi.org/10.1109/waina.2017.89.

  • Yang, L., Zheng, R., Zhu, J., Zhang, M., Liu, R., & Wu, Q. (2018). Green city: An efficient task joint execution strategy for mobile micro-learning. International Journal of Distributed Sensor Networks,14(6), 1550147718780933. https://doi.org/10.1177/1550147718780933.

    Article  Google Scholar 

  • Yun, M., & Zhengqiu, L. (2018). Characteristic personnel training and teaching reform via advanced centralized practice courses under the new format of internet. In 2018 13th international conference on computer science education (ICCSE) (pp. 1–5). https://doi.org/10.1109/iccse.2018.8468757.

  • Zhao, Y., Robal, T., Lofi, C., & Hauff, C. (2018). Stationary vs. non-stationary mobile learning in MOOCs. In Adjunct publication of the 26th conference on user modeling, adaptation and personalization (pp. 299–303). https://doi.org/10.1145/3213586.3225241.

  • Zheng, W. (2015). Design of mobile micro-english vocabulary system based on the ebbinghaus forgetting theory. In Internet computing for science and engineering (ICICSE), 2015 Eighth International Conference. https://doi.org/10.1109/icicse.2015.51.

  • Zheng, R., Zhu, J., Zhang, M., Liu, R., Wu, Q., & Yang, L. (2019). A novel resource deployment approach to mobile microlearning: From energy-saving perspective [Research article]. https://doi.org/10.1155/2019/7430860.

  • Zhou, Y. (2018). The construction and application of micro learning environment under the background of new media. In: Presented at the 2018 3rd international conference on education, sports, arts and management engineering (ICESAME 2018). https://doi.org/10.2991/icesame-18.2018.46.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Isa Jahnke.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix 1: Industry Reports (n = 30)

Appendix 1: Industry Reports (n = 30)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Jahnke, I., Lee, YM., Pham, M. et al. Unpacking the Inherent Design Principles of Mobile Microlearning. Tech Know Learn 25, 585–619 (2020). https://doi.org/10.1007/s10758-019-09413-w

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10758-019-09413-w

Keywords

  • Microlearning
  • Mobile-microlearning systems
  • Learning outdoors
  • Workplace learning
  • Smartphones
  • Mobile devices
  • Design principles