Conceptual Tutoring Software for Promoting Deep Learning: A Case Study

Abstract

The paper presents a case study of the use of conceptual tutoring software to promote deep learning of the scientific concept of density among 50 final year pre-service student teachers in a natural sciences course in a South African university. Individually-paced electronic tutoring is potentially an effective way of meeting the students’ varied learning needs within the limited time available for content teaching in the pedagogically focused course. Both qualitative and quantitative data were collected in the forms of engagement patterns, surveys, focus-group discussions, and pre- and post- test scores. These were used to formulate a rich description in answer to the questions “Is deep learning evident when student teachers engage with a module on density using conceptual tutoring software?,” and “What design features of this module are effective in promoting deep learning?.” The findings suggest that conceptual tutoring software can be effective in promoting deep learning among student teachers. The sub-step design, branched structure, and conceptual approaches used in the tutoring design, and the inclusion of a written task and a test, were found to be effective in promoting deep learning.