“Knowledge and skill are different. Vocabulary acquisition tools help learners improve their knowledge, which may in turn have a positive impact on skill, but it’s important to be cognisant of the differences.” [https://eltjam.com/machine-learning-summer-school-day-4/]
“We need to be careful though not to oversell the technology and be clear about what it can and can’t do. There is no silver bullet. This is especially the case when it comes to skills vs knowledge; a lot of the applications that could come from this sort of technology will help improve knowledge of English, and may contribute to accuracy” [https://eltjam.com/machine-learning-summer-school-day-5/]
The above two quotes are from a nice series of posts by ELTJam on a machine learning workshop. The first point from the first quote is indeed important to recognize. Bill VanPatten (2010) has argued that knowledge and skill are different. However what is meant by knowledge and what is meant by skill? For a nice video summary of the VanPatten paper see the video linked below.
Knowledge is mental representation which in turn is the abstract, implicit and underlying linguistic system in a speaker’s head. Abstract does not mean the rules in a pedagogical grammar rather it refers to a collection of abstract properties which can result in rule-like behaviors. Implicit means that the content of mental representation is not accessible to the learner consciously or with awareness. Underlying refers to the view that a linguistic system underlies all surface forms of language.
The actual content of mental representations include all formal features of syntax, phonology, lexicon-morphology, semantics. And a mental representation grows due to input being acted on by systems from the learners mind/brain.
Skill is the speed and accuracy with which people can do certain behaviours. For language skill this refers to reading, listening, writing, speaking, conversational interaction, turn taking. To be sure being skilled means that the person has a developed mental representation of the language. However having a developed mental representation does not entail being skilled. How skill develops depends on the tasks that people are doing. A person learns to swim by swimming. A person learns to write essays by writing essays.
It follows that the Write&Improve (W&I) tool (as the flagship example of machine learning based tool for language learning) can be seen as targeting how to be skillful in writing Cambridge English Exam texts. The claim that machine learning, and by implication the feedback by W&I, is changing the knowledge of the learner’s English does not accord with VanPatten’s description of knowledge as mental representation. His description implies that no explicit information, in the form of feedback in the case of the writing tool, can lead to changes in the mental representation of the language of writing. He states that research into writing is unclear as to whether feedback impacts writing development.
My point in this post is to briefly clarify the distinction between knowledge and skills (do read the VanPatten paper) and to suggest that the best machine learning based tools can offer are opportunities for students to practice certain skills.
W&I has never claimed that its tool has impact on language knowledge. See Diane Nicholls comment below.
Van Patten, B. (2010). The two faces of SLA: Mental representation and skill. International Journal of English Studies, 10(1), 1-18. PDF available [https://www.researchgate.net/publication/267793221_The_Two_Faces_of_SLA_Mental_Representation_and_Skill]
BlackBox Videocast 2: Mental Representation and Skill