Blending Fundamentals with Emerging Technologies in Education
•Download as PPTX, PDF•
0 likes•97 views
The document discusses how education can blend fundamentals with emerging technologies to personalize learning for each student. It examines the foundations of prior knowledge, scaffolding, reflection, and practice. It proposes personalizing learning through assessment for learning rather than testing, questions tailored to each student's understanding, hints and feedback, and engaging instructional units. However, it notes that technology alone is impersonal without these personalized elements.
Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Viewers also liked
Viewers also liked (9)
Similar to Blending Fundamentals with Emerging Technologies in Education
Similar to Blending Fundamentals with Emerging Technologies in Education (20)
More from Eduexcellence
More from Eduexcellence (20)
Recently uploaded
Recently uploaded (20)
Blending Fundamentals with Emerging Technologies in Education
- 1. 1 Education: Blending Fundamentals with Emerging Technologies Anil Mammen 25-04-2016
- 2. 2
- 4. 4 Collaborative Competitive School Learning
- 5. 5 Real Networks Virtual Networks Peer to Peer Learning
- 7. 7 Examining Foundations: Prior Knowledge This is not just about prior knowledge required to learn what we teach. What does each child know? How do we understand each child’s theory about what she is about to learn?
- 12. 12
- 13. 13
- 14. 14
- 15. 15 Then why can’t we personalize learning?
- 16. 16
- 17. 17 Personalization: How it works Assessment for learning, not testing (Practice – Learning by Doing) Questions that vary according to students’ level of understanding (allowing each child to reflect on her understanding) Hints and feedback (scaffolding) Recommended learning objectives that the student has to master before moving to the next lesson (required prior learning) Engaging instructional units (videos, games, simulations)
- 18. 18
- 19. 19 But… Technology is impersonal
- 20. 20
Editor's Notes
- This is Gautham. About to turn three. He can string small sentences. Uses subject and verb in the correct sequence. Also uses a few adjectives and adverbs. In essence, he can communicate reasonably well and get things done. Within a year he would have more or less managed to communicate somewhat fluently in a language that was totally alien to him at birth. And all this without schooling or technology. Regardless of what different schools of language acquisition say, we know that a child from day one is immersed in language, without fear of making errors. All conversations that others have with him also serve as a kind of feedback although it doesn’t sound like feedback. So, you have experiential learning, responsive adults, real-time feedback, freedom to make errors and lots of support. So, before we discuss any emerging trends, we must not lose sight of these fundamentals of learning.
- We learn in groups as well as by ourselves. In student life, this division translates into school and outside school.
- Each child is unique, and therefore you cannot design instruction for a mythical average learner that does not exist. Research has shown that even the use of vocabulary and contexts has an impact on the way children respond to learning. For a child who seldom watches or plays cricket, a mathematical problem involving a cricket field remains a purely academic puzzle. On the other hand, for a child who is passionate about cricket, it becomes an “authentic” problem. Also, each child processes information differently, depending on what they are familiar with and the unique ways in which they imagine things. They express their understanding in various ways too. Differing levels of understanding is another critical issue. A child who has not mastered pre-algebra will find algebra a difficult topic to tackle. If the teacher attempts remedial teaching for struggling students in a classroom, it could demotivate students who have learned to solve more complex problems. You may argue that these are outliers and that the majority of students are in the middle. But what exactly is this middle? How sure are we that the understanding of this “middle” is uniform?
- Scaffolding is the help given to a learner that is tailored to that learner’s needs in achieving his or her goals of the moment. The best scaffolding provides this help in a way that contributes to learning. For example, telling someone how to do something, or doing it for them, may help them accomplish their immediate goal; but it is not good scaffolding because the child does not actively participate in constructing that knowledge. In contrast, effective scaffolding provides prompts and hints that help learners to figure it out on their own. Example: A story builder to help students develop a story. You give them a story beginning, some hints, maybe the conflict and then allow them to work out the story. Effective learning environments scaffold students’ active construction of knowledge in ways similar to the way that scaffolding supports the construction of a building. When construction workers need to reach higher, additional scaffolding is added, and when the building is complete, the scaffolding can be removed. In effective learning environments, scaffolding is gradually added, modified, and removed according to the needs of the learner, and eventually the scaffolding fades away entirely.
- When learners articulate their developing knowledge, they learn more effectively. This is more complex than it might sound, because it is not the case that learners first learn something, and then express it. Instead, the best learning takes place when learners articulate their unformed and still developing understanding, and continue to articulate it throughout the process of learning. Articulating and learning go hand in hand, in a mutually reinforcing feedback loop. In many cases, learners do not actually learn something until they start to articulate it – in other words, while thinking out loud, they learn more rapidly and deeply than studying quietly. One of the reasons that articulation is so helpful to learning is that it makes possible reflection or metacognition – thinking about the process of learning and thinking about knowledge. Learning scientists have repeatedly demonstrated the importance of reflection in learning for deeper understanding. Once students have articulated their increasing comprehension , learning environments should support them in reflecting on what they have just articulated. One of the most central topics in learning sciences research is how to support students in educationally beneficial reflection.
- The more practice and more opportunities students have to make errors and get feedback (without unhealthy comparisons and rankings), the better it is for learning. However, practice should ideally be grounded in real world tasks or engaging problems. Left to themselves why do many children spend hours on mobile games? They are not real world problems but engaging games that force them to get better at what they are doing. Unfortunately, many of these games have nothing much to teach.
- My personalised search results from Google
- You Tube recommendations based on the videos I watch
- Online bookstore recommendations based on what I browse or buy
- Big data is about measuring a large amount of small bits of data like searches, purchase history, browsing patterns, etc. Based on the analysis of large volumes of data, the system becomes strong enough to make sound recommendations to you. Tata ClassEdge has tied up with Knewton, the world’s most prominent adaptive learning company to offer personalized learning for students. Knewton’s big data is the data generated by the homework patterns of millions of students worldwide. Based on this data, Knewton can assess what a student knows, his learning patterns and needs, what he is struggling with and what next he can attempt. This helps them develop the next “perfect piece of content” for the student. This allows learning to become more adaptive. Adaptive learning allows lessons to be tailor made for students – they learn at their own pace, absorb the past learning and move to the next stage only when ready. Backgrounds, interests, attention spans and levels of understanding can distinguish one student’s pace of learning from another. Yet conventional teaching methods force learning speeds to be equated across all students. With standardized content and tests, if you are in a bottom half of the class, it’s too hard for you and if you are in the top half of the class, it’s too easy for you. In conventional learning, if there’s something you didn’t follow from two years ago, it won’t be in this year’s textbooks. But today you can pluck a concept you haven’t followed from as many years ago and learn and clear it today. The use of big data allows Knewton to sift which concepts are clear to the students and which aren’t. The system can inform the teacher that the class has failed to understand 3 of 10 concepts taught to them so she can reinforce what students have failed to follow. Unlike traditional teaching, if there is something a student is unable to understand in science because of a concept he may have failed to understand in math, he can access the content on math to help him understand his science better. You can move across disciplines with ease. Otherwise, to learn a concept that may have been covered a year ago in another subject, you’d have to try and schedule an extra class with someone.
- Adaptive learning allows lessons to be tailor made for students – they learn at their own pace, absorb the past learning and move to the next stage only when ready. Backgrounds, interests, attention spans and IQ levels can distinguish one student’s pace of learning from another. Yet conventional teaching methods force learning speeds to be equated across all students. If you are in a bottom half of the class, standardized tests and practice are hard for you and you quit. If you are in the top half of the class, it’s too easy for you, you’re bored and you quit. In conventional learning, if there’s something you didn’t follow from two years ago, it won’t be in this year’s textbooks. But today you can pluck a concept you haven’t followed from as many years ago and learn and clear it today. The use of big data allows Knewton to sift which concepts are clear to the students and which aren’t. “A teacher can be told that the class has failed to understand 3 of the 22 concepts taught to them so he or she can repeat what students have failed to follow”. Unlike traditional teaching, if there is something a student is unable to understand in science because of a concept he may have failed to understand in math, he can access the content on math to help him understand his science better. You can move across disciplines with ease. Otherwise, to learn a concept that may have been covered a year ago in another subject, you’d have to try and schedule an extra class with someone.
- However, it is absolutely essential to bring teacher interaction and peer collaboration into this autonomous learning process. A computer is an impersonal object that can help identify certain gaps in understanding through intelligent algorithms, but real personalisation happens when teachers provide adequate support, feedback and encouragement, with a deeper understanding of each student. And we need to be mindful of the age at which we introduce technology.