Self paced learning

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Self paced learning
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Self paced learning is a recently proposed learning regime inspired by the learning process of humans and animals that gradually incorporates easy to more complex samples into training [1].

The philosophy under this learning paradigm is to simulate the learning principle of humans/animals, which generally starts by learning easier aspects of a learning task, and then gradually takes more complex examples into training [2].

As stated in How to Master Online Learning self paced learning or independent study, involves no interaction with instructors or other students. In these types of courses, students are directed to the course materials and are then expected to learn independently by following their own schedule. Most self paced courses do not have a start and end date. Instead, students begin the course and progress through the course materials at their own pace. These courses usually require the greatest amount of self-discipline because you are the only one to set your schedule for completing assignments and finishing the course [3].


As stated in Effective Learning Environments self paced learning opportunities are independent learning situations in which a learner progresses through activities at his or her own pace. Examples are tutorials and text-based, and computer-based training. One of the advantages of self-paced learning opportunities is the flexibility of use that results when these opportunities are modularized, self-contained, and technology based. Learners can access them whenever and wherever they want without the need to schedule a classroom delivery event [4].


There are many advantages of self paced learning for an example [5]:

  • students learn more
  • prepares individuals to become more self-directed
  • individuals become more responsible in further work experiences.


There are also some limitations to self-paced learning [6]:

  • requires careful planning for the development of self-study materials
  • requires extra equipment, multiple copies of materials, and suitable facilities
  • may require new habits for study to be formed by some students to overcome lack of self-discipline or procrastination
  • may require qualified personnel available to assist students while studying
  • requires variety in activities and resources so the same routine is not repeatedly followed in a lengthy training program that could become monotonous.

The deep active self-paced learning strategy

As stated in Deep Learning in Healthcare The Deep Active Self-paced Learning (DASL) strategy is a combination of Active Learning (AL) and Self-Paced Learning (SPL) that alleviates the lack of fully-annotated samples and make use of unannotated samples. Active Learning Strategy attempts to overcome the annotation bottleneck by querying the most confusing unannotated instances for further annotation. We utilize a straightforward strategy to select confusing samples during model training, different from, which applied a set of fully convolutional networks (FCN) for sample selection. The calculation of this sample uncertainty is defined as:

  • Ud= 1 - max(Pd,1 - Pd),

where Ud denotes the uncertainty of the dth sample and Pd denotes the posterior probability of dth sample [7].



  1. Jiang L., Meng D., Yu S., Lan Z., Shan S., Hauptmann A. 2014 p. 1
  2. Menga D., Zhaoa Q., Lu Jiangb L. 2016 p. 3
  3. Peterson's 2012
  4. Sisakhti R. 1998 p. 30
  5. Kemp J., Cochern G. 1994 p. 42
  6. Kemp J., Cochern G. 1994 p. 42
  7. Chen Y. 2020 p. 98

Author: Paulina Wolnik