In a recent assignment for LRNT 524, I was asked to research and evaluate an instructional or learning design innovation. I chose to focus on a learning design innovation known as adapted learning in which technology is used to provide customized learning experiences for learners based on the needs of the individual by creating unique pathways and progression of learning material and activities (Leaders, 2022). As part of this discussion, I shared how artificial intelligence (AI) has progressed adapted learning, introducing tools such as ones that can detect the learners cognitive state based on conversational elements which it uses to guide the learner through productive conversations to enhance learning (Capuano & Caball\u00e9, 2020). <\/p>\n\n\n\n
As a follow up blog post, I have been asked to explore a learning innovation and discuss it\u2019s impact. Upon further research in adapted learning, I discovered deep learning which is a AI-based technology that attempts to mimic the human brain through image or object detection using a multi-layererd approach to make intelligent decisions (Han & Xu, 2020; IBM, n.d.). Deep learning is a tool that can enhance adapted learning through a complex analysis of objects that goes beyond a linear process of adaptation, similar to neural connections and processing in the human brain. After an initial exploration of the literature, I found that there were many interpretations of what deep learning is and that the term is often used interchangeably with machine learning and deep neural networks. Kavlakoglu (2020) at IBM contends that deep learning is a subset of machine learning with deep neural networks making up its algorithms. The lack of common language and understanding in the literature of what deep learning is made my research on this topic more difficult.\u00a0<\/p>\n\n\n\n
Furthermore, there does not seem to be a lot of literature about the use of deep learning technology in the context of learning in formal education. Deep learning is most known for its use in other sectors and innovations such as driverless cars where a car must learn how to detect a stop sign (Venkateswaran et al., 2021), a true focus on machine learning rather than human learning. However, I do see that deep learning can have a large impact on human learning, but perhaps in more of an \u2018unlearning\u2019 way. As deep learning technology advances in an effort to simulate processes of the human brain, less effort is required from humans to learn and complete tasks. This exclusive reliance on technology to make decisions and problem solve could be problematic for two reasons. Firstly, AI technology, including deep learning is still far from matching human intelligence, making outputs not always accurate (McClelland & Botvinick, 2020). And secondly, (and this is my own pondering) I am left wondering if the long-term use of AI, including deep learning technology, will change the architecture and performance of the human brain over time. With the use of AI driven deep neural networks, are we losing the opportunity to be develop our own neural networks in our own brains through problem solving? <\/p>\n\n\n\n
I see some potential for deep learning technology in creating more meaningful learning experiences for culturally diverse learners. For example, this technology could adapt learning content and images to represent the culture and worldview of the learner while still meeting the learning outcomes. In that case, this could lead to greater inclusion and sense-making according to diverse worldviews. However, there could still be bias present as there is a wide range of diversity within a culture, which will have to be considered in the design and data collection for deep learning technology.\u00a0<\/p>\n\n\n\n
References <\/strong><\/p>\n\n\n\n Baker, C. (2022, June 3). What is adaptive learning and can It work for business? <\/em>Leaders. https:\/\/leaders.com\/articles\/innovation\/adaptive-learning\/<\/a> <\/p>\n\n\n\n Capuano, N., & Caball\u00e9, S. (2020). Adaptive learning technologies. AI Magazine, 41<\/em>(2), 96-98. https:\/\/doi.org\/10.1609\/aimag.v41i2.5317<\/a> <\/p>\n\n\n\n Han, Z., & Xu, A. (2020). Ecological evolution path of smart education platform based on deep learning and image detection. Microprocessors and Microsystems, 80<\/em>, 103343. https:\/\/doi.org\/10.1016\/j.micpro.2020.103343<\/a> <\/p>\n\n\n\n IBM (n.d.). What is deep learning?<\/em> https:\/\/www.ibm.com\/topics\/deep-learning<\/a> <\/p>\n\n\n\n Kavlakoglu, E. (2022, May 27). AI vs. machine learning vs. deep learning vs. neural networks: What\u2019s the difference?<\/em> IBM. https:\/\/www.ibm.com\/cloud\/blog\/ai-vs-machine-learning-vs-deep-learning-vs-neural-networks<\/a> <\/p>\n\n\n\n McClelland, J. L., & Botvinick, M. M. (2020). Deep learning: Implications for human learning and memory.<\/em> PsyArXiv. https:\/\/doi.org\/10.31234\/osf.io\/3m5sb<\/a> <\/p>\n\n\n\n Venkateswaran, C., Amudha, M., Ramachandran, M., Saravanan, V., Vennila, T. (2021). A study on artificial intelligence with machine learning and deep learning techniques. Data Analytics and Artificial Intelligence 1<\/em>(1). https:\/\/secureservercdn.net\/50.62.90.29\/d8a.8cf.myftpupload.com\/wp-content\/uploads\/2022\/01\/A-Study-on-Artificial-intelligence-with-Machine-learning-and-Deep-Learning-Techniques.pdf<\/a> <\/p>\n","protected":false},"excerpt":{"rendered":" In a recent assignment for LRNT 524, I was asked to research and evaluate an instructional or learning design innovation. I chose to focus on a learning design innovation known as adapted learning in which technology is used to provide customized learning experiences for learners based on the needs of the individual by creating unique… Continue reading Deep Learning Technology: Impact on Human Learning<\/span>