ERIC Number: EJ1027384
Record Type: Journal
Publication Date: 2013
Pages: 18
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-2165-3151
EISSN: N/A
Available Date: N/A
Deepening Learning through Learning-by-Inventing
Apiola, Mikko; Tedre, Matti
Journal of Information Technology Education: Innovations in Practice, v12 p185-202 2013
It has been shown that deep approaches to learning, intrinsic motivation, and self-regulated learning have strong positive effects on learning. How those pedagogical theories can be integrated in computing curricula is, however, still lacking empirically grounded analyses. In a more general level, it has been widely acknowledged that in tertiary-level computing education there is a desperate need for more creativity and innovation-friendly instructional approaches. While the use of, for example, problem-based instructional approaches into computing education is increasing, their penetration into computing pedagogy is still shallow. In many contexts of higher computing education, teaching still follows a fixed set of instructional lectures, a fixed set of short-term learning objectives, and a fixed set of predetermined take-home exercises, followed by a pen-and-paper exam. A typical way to teach software development in higher computing education is to utilize industry-standard project management principles in a project, which aims for efficient and risk-free production of software which meets the demands of a customer or a client. As an alternative to the typical conventions, this study investigated students' learning in a learning environment that explicitly focused on inventing and creativity. In other words, this study integrated, in a robotics-based programming class, a method of learning-by-inventing and studied its qualitative effects on students' learning through 144 interviews. Five findings were related with learning theories: changes in students' problem management cycle, problem-rich learning environment, conceptions of the nature of computing, extension of deep and surface approaches to problem solving and management, and the use of robotics to facilitate deep learning strategies. Our analysis suggests that a combination of an open learning environment, robotics as the learning tool, and learning-by-inventing provides a conducive environment for deep learning strategies, intrinsic motivation, and self-regulated learning, which are prerequisite conditions for creativity and inventing.
Descriptors: Computer Science Education, Creativity, Robotics, Problem Based Learning, Student Attitudes, Interviews, Learning Strategies, Motivation, Self Management, Learning Theories, College Students, Problem Solving, Foreign Countries
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Finland (Helsinki)
Grant or Contract Numbers: N/A
Author Affiliations: N/A