Learnability

Learnability refers broadly to the ease with which a system, concept, or skill can be acquired, whether by humans or machines. While there is no direct definition of learnability, Merriam-Webster dictionary has defined the definition of a similar concept of ‘learnable’ as “the degree to which knowledge or skill (in something) can be acquired through study or experience”^[1]. In software development and product design field, learnability can also be described as a quality of products and interfaces that allows users to quickly become familiar with them and able to make good use of all their features and capabilities. While the term spans multiple disciplines, the focus vary across fields.

In human–computer interaction (HCI), learnability refers to how quickly and easily a person can acquire the skills to perform tasks, and interact with a product. The ability to quickly understand how to operate a product ties deeply with user experience, which aims to design an experience that is intuitive, easy to use, and has a low learning curve for the user^[2]. It is considered one dimension of usability, which ISO 9241-11:2018^[3] defines as “the extent to which a system, product or service can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use.” Within this framework, learnability focuses on “the ease with which a user can learn to operate, prepare inputs for, and interpret outputs of a system or component”^[2].

In education and cognitive science, learnability refers to the capability of individuals to acquire new knowledge, skills, or behaviors effectively and efficiently^[4]. This could be an acquisition of a new language, new subject areas, or desired social behaviors. In addition, learnability can also be described as the capacity to be a self-driven, life-long learner, and the willingness to evolve along with the changing world^[4][5]. This skill of learnability is becoming increasingly important in the workplace as one of the desired attributes in employees^[6].

In Machine learning, learnability describes the extent to which an algorithm can improve its performance, typically measured by its ability to generalize from training data to unseen data to perform tasks. Unlike human learning, it is based on statistical pattern recognition and is driven by large-scale data processing and parameter optimization rather than lived experience, socioeconomic status, or environmental influences, etc ^[7]. In software testing learnability, according to ISO/IEC 9126, is the capability of a software product to enable the user to learn how to use it. Learnability may be considered as an aspect of usability, and is of major concern in the design of complex software applications.

Computational Learning Theory

In computational learning theory, learnability is the mathematical analysis of machine learning. It is also employed in language acquisition in arguments within linguistics.

Frameworks include:

• Language identification in the limit proposed in 1967 by E. Mark Gold.^[8] Subsequently known as Algorithmic learning theory.
• Probably approximately correct learning (PAC learning) proposed in 1984 by Leslie Valiant^[9]