Work

Facilitating Student's Learning Transfer in a Database Programming Class

Year: 2025

Type: conference-paper

Abstract: Transferring programming skills learned in the classroom to diverse real-world scenarios is both essential and challenging in computing education. This experience report describes an approach to facilitate learning transfer by fostering adaptive expertise. Students were engaged in co-creating contextualized worked-out examples, including step-by-step solutions. Through three homework assignments in a Spring 2023 database programming course, we observed substantial improvements, where students generated detailed and accurate solutions and enriched their problem-solving contexts from simple phrases to detailed stories, drawn from 17 real-life scenarios. Our results also suggest that the peer assessment process cultivated a supportive learning environment and fostered adaptive expertise. We discuss the lessons learned and draw pedagogical implications for integrating student-generated contextualized materials in other programming courses.

Source: ACM Technical Symposium on Computer Science Education (SIGCSE)

DOI: 10.1145/3641554.3701828

Authors: Yuzhe Zhou, Alejandra J. Magana, Tianyi Li

Institution: Purdue University West Lafayette

Language: English

Topic: Teaching and Learning Programming

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Funder: Universitas Brawijaya