What Is Surface Learning?

What Is Surface Learning?

In surface learning,

What is surface and deep learning?

Surface learners were defined as those only focused on grasping the main points and memorizing them. Conversely, deep learners explored the meaning behind the topic, and attempted to relate it to other knowledge to aid their understanding.

What are examples of surface learning?

Surface learning is retention of information without critical thinking. For example, have you ever memorized facts just to do well on a test without even thinking through what they meant or why they are important to you?

What is the difference between surface learning deep learning and strategic learning?

Deep learning is valued and fostered by educators. In this approach learners organise their learning with the objective of achieving a high or positive outcome. Strategic learning can involve a combination of both deep and surface learning strategies depending on the tasks at hand.

What is superficial memorization?

Superficial knowledge is short lived. It is memorizing something for a test and forgetting it a few days later. … Profound knowledge is having a deep understanding of something and as a result being able to retain this knowledge over time, refine and add to this knowledge, and apply it to new situations.

What is the importance of surface learning?

Surface learning is the more factual information or surface knowledge that is often a prerequisite for deep learning. Deep learning involves things like extending ideas, detecting patterns, applying knowledge and skills in new contexts or in creative ways, and being critical of arguments and evidence.” (Merrilyn Goos).

What are the 5 approaches to learning?

Approaches to Learning (5 elements)
  • Thinking skills. critical thinking. creativity and innovation. transfer.
  • Communication skills.
  • Social skills.
  • Self-management skills. organisation. affective. reflection.
  • Research skills. information literacy. media literacy.

What are the best strategies for surface to deep learning?

When teachers work with students on acquiring surface level learning, they are teaching students to use strategies like highlighting, note taking, mnemonics, underlining, and imagery.Aug 21, 2016

What is an example of deep learning?

Deep learning is a sub-branch of AI and ML that follow the workings of the human brain for processing the datasets and making efficient decision making. … Practical examples of deep learning are Virtual assistants, vision for driverless cars, money laundering, face recognition and many more.Sep 20, 2019

What are the characteristics of deep learning?

Characteristics of Deep Learning
  • Supervised, Semi-Supervised or Unsupervised. When the category labels are present while you train the data then it is Supervised learning. …
  • Huge Amount of Resources. …
  • Large Amount of Layers in Model. …
  • Optimizing Hyper-parameters. …
  • Cost Function.

What are examples of learning strategies?

  • Spaced Practice. Space out your studying over time. …
  • Retrieval Practice. Practice bringing information to mind without the help of materials. …
  • Elaboration. Explain and describe ideas with many details. …
  • Interleaving. Switch between ideas while you study. …
  • Concrete Examples. …
  • Dual Coding.

What is surface level?

a the uppermost level of the land or sea. b (as modifier) surface transportation.

What is deep learning used for?

Deep learning applications are used in industries from automated driving to medical devices. Automated Driving: Automotive researchers are using deep learning to automatically detect objects such as stop signs and traffic lights. In addition, deep learning is used to detect pedestrians, which helps decrease accidents.

Why is deep learning better than surface learning?

Goal. – Deep learners seek to construct their own knowledge by making connections between existing and new knowledge and they are intrinsically motivated and very curious about the subject, as opposed to surface learners who are not interested in the subject and who see learning tasks as forced work.

What is shallow knowledge?

Shallow knowledge is when you have information plus some understanding, meaning and sense‐making. To understand is to make some level of meaning, with meaning typically relating to an individual or organization and implying some level of action. To make meaning requires context.

Why is deep learning essential in the classroom?

Deep learning instruction provides students with the advanced skills necessary to deal with a world in which good jobs are becoming more cognitively demanding. It prepares them to be curious, continuous, independent learners as well as thoughtful, productive, active citizens in a democratic society.

What are the three domains of educational objectives?

Bloom’s Taxonomy comprises three learning domains: the cognitive, affective, and psychomotor, and assigns to each of these domains a hierarchy that corresponds to different levels of learning.

What is deep approach?

Definition. A deep approach to learning concentrates on the meaning of what is learned. That concentration may involve testing the material against general knowledge, everyday experience, and knowledge from other fields or courses. A student taking a deep approach seeks principles to organize information.

What is transfer strategies Hattie?

Hattie was speaking about transfer as part of his unveiling of what he believes are the top 10 learning strategies. … He defines learning as: “The process of developing sufficient surface knowledge to then move to deeper understanding such that one can appropriately transfer this learning to new tasks and situations.”

What are the 4 types of learning?

What are the four learning styles? The four core learning styles include visual, auditory, reading and writing, and kinesthetic. Here’s an overview of all four leaning style types.

What are ATL skills in PYP?

ATL skills are deliberate strategies, skills and attitudes that permeate the IB teaching and learning environment. ATL skills supports the IB belief that a large influence on a student’s education is not only what you learn but also how you learn.

What is IB ATL?

Approaches to learning (ATL) are skills designed to enable students in the IB Middle Years Programme (MYP) to “learn how to learn.” They are intended to apply across curriculum requirements and provide a common language for teachers and students to use when reflecting and building on the process of learning.

Why should deep learning be applied to the modern teaching environment?

Deep learning allows a student to take principles from one situation and apply it to another. Preparing students for the future can be incredibly challenging for teachers. … So, learning transferable, real-world skills is even more important for today’s pupils than yesterday’s.

How can we ensure students are learning and not simply recalling surface level facts?

Engage students in regular review

Regular practice, including consistent review of learned material, is the best way to fix new knowledge in long-term memory. This means students can put their full brain power towards analysis and not towards simply recalling information.

How can we promote positive transfer of learning?

10 ways to improve transfer of learning
  1. Focus on the relevance of what you’re learning. …
  2. Take time to reflect and self-explain. …
  3. Use a variety of learning media. …
  4. Change things up as often as possible. …
  5. Identify any gaps in your knowledge. …
  6. Establish clear learning goals. …
  7. Practice generalizing. …
  8. Make your learning social.

What is difference between machine learning and deep learning?

To recap the differences between the two: Machine learning uses algorithms to parse data, learn from that data, and make informed decisions based on what it has learned. Deep learning structures algorithms in layers to create an “artificial neural network” that can learn and make intelligent decisions on its own.Jan 23, 2020

What is the difference between ML and DL?

Machine Learning (ML) is commonly used along with AI but it is a subset of AI. ML refers to an AI system that can self-learn based on the algorithm. … Deep Learning (DL) is a machine learning (ML) applied to large data sets. Most AI work involves ML because intelligent behaviour requires considerable knowledge.Dec 4, 2020

What are examples of artificial intelligence?

Artificial Intelligence Examples
  • Manufacturing robots.
  • Self-driving cars.
  • Smart assistants.
  • Proactive healthcare management.
  • Disease mapping.
  • Automated financial investing.
  • Virtual travel booking agent.
  • Social media monitoring.

What are the benefits of machine learning?

Advantages of Machine Learning
  • Automation of Everything. Machine Learning is responsible for cutting the workload and time. …
  • Wide Range of Applications. …
  • Scope of Improvement. …
  • Efficient Handling of Data. …
  • Best for Education and Online Shopping. …
  • Possibility of High Error. …
  • Algorithm Selection. …
  • Data Acquisition.

What is AI analysis?

AI analytics refers to a subset of business intelligence (BI) in which software exhibits behaviors typically attributed to humans, such as learning and reasoning, in the process of data analysis. In practice, this means AI automates the steps that humans would take to complete analysis in an exhaustive fashion.

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