Knowledge-worker self-regulated learning with technology project (KW-SRL)
This project investigates knowledge-workers’ learning with technology.
Factual aims. This project aims to extend scientific knowledge regarding the form and content of psychological processes, activities, attitudes, habits and affect that determine, enable and influence cognitive productivity in knowledge workers, particularly with respect to their knowledge acquisition and self-regulated learning.
Some of our empirical questions include the following. How are knowledge workers regulating their learning with various types of knowledge resources (e.g., PDF files, web pages, videos, ebooks and ebook readers, paper books, paper documents, meetings with other people, etc.)? How do they view and overcome the potentially stultifying limitations of software (e.g., web browsers)? How are they coping with the abundance of information available to them? How are they coping with the sometimes excessive demands of work, family, etc., and their needs to learn? How are they leveraging cognitive productivity applications for learning? How are they prioritizing their readings and regulating their speed , depth and strategies of reading and knowledge acquisition? How do those knowledge workers who are thriving (learning-wise) distinguishing themselves from those who are struggling with modern learning demands?
Whereas almost all previous research on “self-regulated learning” examined learning of students (often freshmen, struggling students and K-12 students) this project is about knowledge workers including expert knowledge workers, with a particular emphasis on their advanced use of technology for learning. We are interested in their cognition itself as well as their affect that pertains to their learning.
Practical Aims. This project aims through the application of its results to extend benevolent human influence over knowledge worker cognitive productivity. We ask:
- How can practitioners help the best knowledge workers become even more productive learners?
- How can practitioners improve any knowledge worker’s learning with technology?
- How can knowledge workers help themselves learn better?
These are all critical questions for Canada’s knowledge economy as the abundance of information and the limitations of web browsers and related software present significant learning challenges to knowledge workers.
Luc P. Beaudoin is open to co-supervising Ph.D. students interested in the foregoing questions. While most of our questions are empirical, there are also significant theoretical SRL questions that can only be answered from the designer stance (i.e., AI cognitive science ). See for example : What is the design-based approach (“designer-stance”) and Architecture-Based Conceptions of Mind . The designer questions are particularly suitable to cognitive science students.