Are we currently moving from the age of mobolism to age of artificail intelligence, learning analytics and robotics? Yes were are! How to couple emerging technology with learning and teaching?
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The document discusses the transition from mobilism to an age dominated by artificial intelligence, learning analytics, and robotics, emphasizing the importance of preparing youth for future jobs through enhanced educational technologies. It highlights the need for 21st-century skills like information literacy and management, and explores the potential of smart learning environments and educational robots to adapt to individual learning needs. Additionally, it outlines various technological advancements and strategies aimed at improving education and addressing future challenges.
![Example of smart Learning Environment [metatutor]
Adaptive learning materials: early steps
Chew, S. W., Cheng, I. L., & Chen, N. S. (2018). Exploring challenges faced by different
stakeholders while implementing educational technology in classrooms through expert
interviews. Journal of Computers in Education, 5(2), 175-197.
Metatutor Environment (left side:) Azevedo, R., Harley, J., Trevors, G., Duffy, M., Feyzi-
Behnagh, R., Bouchet, F., & Landis, R. (2013). Using trace data to examine the complex roles of
cognitive, metacognitive, and emotional self-regulatory processes during learning with multi-agent
systems. In International handbook of metacognition and learning technologies, Springer New
York, p. 431
..towards developing ”smart learning environment”
• That monitors learners’ learning process and
their progress,
• adapting to their learning patterns and needs,
• suggesting and feeding learners with relevant
information what they need in different forms
that suits each learner’s learning preference
and style
Future: Automated real-time adaptive learning
environment?](https://image.slidesharecdn.com/inted2019laru-190311120530/85/Are-we-currently-moving-from-the-age-of-mobolism-to-age-of-artificail-intelligence-learning-analytics-and-robotics-Yes-were-are-How-to-couple-emerging-technology-with-learning-and-teaching-10-320.jpg)
Are we currently moving from the age of mobolism to age of artificail intelligence, learning analytics and robotics? Yes were are! How to couple emerging technology with learning and teaching?
- 1. ARE WE CURRENTLY MOVING FROM THE AGE OF MOBILISM TO AGE OF ARTIFICIAL INTELLIGENCE, LEARNING ANALYTICS AND ROBOTICS? YES, WE ARE HOW TO COUPLE EMERGENT TECHNOLOGY WITH LEARNING AND TEACHING? Jari Laru, Dr in Education. University Lectorer, Technology Enhanced Learning, Research Unit for Learning and Educational Technology (http://www.oulu.fi/let) Faculty of Education, University of Oulu, Finland The 13th annual International Technology, Education and Development Conference, INTED2019, IValencia (Spain). 11th-13th of March, 2019. Special Learning Technology Accelerator (Lea) Horizon 2020 project session: Innovation procurement to steer user-driven innovations for digital learning.
- 2. This presentation is based on ”prediting future of edtech 2030” slideset https://www.slideshare. net/larux/predicting- future-of-edtech-2030- v2
- 3. Future of work? 2070* * Children who start in primary school this year will be in working life until 2070
- 4. https://medium.com/@shivsoni377/the-difference-between-augmented-reality-virtual-reality-and-mixed-reality- a028bdd81f9d?fbclid=IwAR17d57MG4e9-ClKnGKEk8Sv9tSn87Uac2Gqx28pnw2NIM8gq_-zEwcYy_g Rich interfaces & Environments: virtual assistants and xReality
- 5. Pjotos: Pixabay & Wikipedia Artificial intelligence: threat or possibility?
- 6. Frey, C. B., & Osborne, M. A. (2013). The future of employment: How susceptible are jobs to computerisation? Oxford, UK: Oxford Martin School. Available at http://acikistihbarat.com/Dosyalar/effect-of-computerisation-on- Labour market and computerisation (AI)
- 7. Neelen & Kirchner (2017). A THREE STAGE PLAN TO PREPARE OUR YOUTH FOR JOBS THAT DON’T EXIST (YET).https://3starlearningexperiences.wordpress.com/2017/08/18/a-three-stage-plan-to-prepare-our-youth-for-jobs-that-dont-exist-yet/ However, what is truly ‘21st century’ is the enormous increase in information (and information resources) and the challenge around the question whether or not the information is reliable. Therefore, Kirschner argues, the only skills that are truly ‘21st century’ are: • Information literacy: also known as information problem-solving skills including searching for, identifying, evaluating (the quality and reliability of information sources), and effectively using the information that has been obtained; and • Information management: the ability to capture, curate, and share information. How to prepare our Youth for jobs that don’t exist yet?
- 8. Near term future (present) Not-so—distant future (research and R&D) Distant Future Technology Enhanced Learning Technology Enhanced & Augmented Learning Processes No idea Today ”Tomorrow” ”No ETA, surprise” Three ”futures” of educational technology: A- B-C
- 9. To adress 21st centyry challenges and opportunities, Woolf (2010) suggests.. ● User modeling ● Mobile and network tools ● Rich interfaces and environments, including gamification and intelligent systems ● Educational data mining ● Personalizing education ● Assessing student learning ● Diminishing boundaries ● Developing altenative teaching strategies ● Enhancing the role of stakeholders ● Adressing policy changes Technology should be used for:New designs that include: Woolf B.P., A roadmap for education technology, National Science Foundation, Washington, DC, 2010, https://hal. archives-ouvertes.fr/hal-00588291. Technology is not answer, unless it can be used for ?
- 10. Example of smart Learning Environment [metatutor] Adaptive learning materials: early steps Chew, S. W., Cheng, I. L., & Chen, N. S. (2018). Exploring challenges faced by different stakeholders while implementing educational technology in classrooms through expert interviews. Journal of Computers in Education, 5(2), 175-197. Metatutor Environment (left side:) Azevedo, R., Harley, J., Trevors, G., Duffy, M., Feyzi- Behnagh, R., Bouchet, F., & Landis, R. (2013). Using trace data to examine the complex roles of cognitive, metacognitive, and emotional self-regulatory processes during learning with multi-agent systems. In International handbook of metacognition and learning technologies, Springer New York, p. 431 ..towards developing ”smart learning environment” • That monitors learners’ learning process and their progress, • adapting to their learning patterns and needs, • suggesting and feeding learners with relevant information what they need in different forms that suits each learner’s learning preference and style Future: Automated real-time adaptive learning environment?
- 12. https://www.slamproject.org/uploads/5/7/5/1/57512023/j%C3%A4rvel%C3%A4 -keynote_lak_2017-final_optimized.pdf 101 hours of video, 266 216 000 data points of physiological data, 236 000 EdX log events… Collaboration with LA, data-mining and signal processing experts => Methodological development (LA) => Data vizualisation SLAM PROJECT https://www.slamproject.org/ Järvelä, S. , Kirschner, P. A., Hadwin, A., Järvenoja, H., Malmberg, J. Miller, M. & Laru, J. (2016, in press). Socially shared regulation of learning in CSCL: Understanding and prompting individual- and group-level shared regulatory activities. International Journal of Computer Supported Collaborative Learning. Järvelä, S., Malmberg, J. & Koivuniemi, M. (2016). Recognizing socially shared regulation by using the temporal sequences of online chat and logs in CSCL. Learning and Instruction, 42, 1-11. DOI: 10.1016/j.learninstruc.2015.10.006 Järvelä, S., Järvenoja, H., Malmberg, J., Isohätälä, J. & Sobocinski, M. (2016). How do types of interaction and phases of self-regulated learning set a stage for collaborative engagement? Learning and Instruction 43, 39-51. DOI:10.1016/j.learninstruc.2016.01.005 Järvelä, S., Malmberg, J., Sobocinski, M., Haataja, E., & Kirschner, P. (2016). What multimodal data can tell us about the self-regulated learning process? Submitted. Malmberg, J., Järvelä, S., Holappa, J., Haataja, E., & Siipo, A. (2016). Going beyond what is visible –What physiological measures can reveal about regulated learning in the context of collaborative learning. Submitted. Malmberg, J., Järvelä, S., & Järvenoja, H. (2016). Capturing temporal and sequential patterns of self-, co-, and socially shared regulation in the context of collaborative learning. Submitted. Pijeira-Díaz, H. J., Drachsler, H., Järvelä, S., & Kirschner, P. A. (2016). Investigating collaborative learning success with physiological coupling indices based on electrodermal activity. Proceedings of the Sixth International Conference on Learning Analytics and Knowledge. ACM. DOI:10.1145/2883851.2883897 Pijeira-Díaz, H. J., Drachsler, H., Kirschner, P. A., & Järvelä, S. (2018). Profiling sympathetic arousal in a physics course: How active are students? Journal of Computer Assisted Learning, (April), 1–12. DOI:10.1111/jcal.12271 Sedrakyan, G., Malmberg, J., Verbert, K., Järvelä, S., & Kirschner, P. A. (2018). Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation. Computers in Human Behavior. DOI:10.1016/j.chb.2018.05.004 Sobocinski, M., Malmberg, J. & Järvelä, S. (2016). Exploring temporal sequences of regulatory phases and associated interaction types in collaborative learning tasks. Submitted.
- 13. Educational robots Educational robot is not just a tool used in the class, but more general learning companion • Ability to have fully context aware whereby it would be to feed learner’s preference (Mishra, 2015) • Ability to understand and attain learning patterns and characteristics of the learners • Would be able to react to the learner’s input • Robot would grow together with child, learning the child’s living style and learning habits
- 14. D. Hood, S. Lemaignan and P. Dillenbourg. The CoWriter Project: Teaching a Robot how to Write. 2015 Human-Robot Interaction Conference, Portand, USA, 2015. Educational robots: example robot which can teach children to write See the project: https://chili.epfl.ch/page-92073-en-html/robotics/cowriter/
- 15. https://medium.com/@shivsoni377/the-difference-between-augmented-reality-virtual-reality-and-mixed-reality- a028bdd81f9d?fbclid=IwAR17d57MG4e9-ClKnGKEk8Sv9tSn87Uac2Gqx28pnw2NIM8gq_-zEwcYy_g Rich interfaces & Environments: virtual assistants and xReality
- 16. To adress 21st centyry challenges and opportunities, Woolf (2010) suggests.. ● User modeling ● Mobile and network tools ● Rich interfaces and environments, including gamification and intelligent systems ● Educational data mining ● Personalizing education ● Assessing student learning ● Diminishing boundaries ● Developing altenative teaching strategies ● Enhancing the role of stakeholders ● Adressing policy changes Technology should be used for:New designs that include: Woolf B.P., A roadmap for education technology, National Science Foundation, Washington, DC, 2010, https://hal. archives-ouvertes.fr/hal-00588291. Technology is not answer, unless it can be used for ?
- 17. DISTANT FUTURE (No ETA, surprise) We have no idea about it.
- 18. Next generation hardware and software: tool for living (so easy, intuitive and supportive)
- 19. NOW: Technology enhanced learning SOON: (future) Technology enhanced/augmented learning processes www.oulu.fi/let https://twitter.com/LET_Oulu