Effects of different types of guidance on students’ motivation and learning in a remote laboratory in computer science

Abstract

ABSTRACT Background and Context During online learning, it is essential to provide instructional guidance to support learning. However, guidance can be given in different forms and quantities. Thus, one important challenge is to provide the right amount and type of instructional guidance. Objective The aim of the study is to investigate types of guidance which are effective for students with heterogenous programming knowledge and skills solving programming tasks in a remote laboratory. Method We carried out two studies with a single factor pre-post-design with guidance (basic/enhanced) as a between-subjects factor. Findings In study 1, we implemented enhanced guidance in the form of prompts in the introduction to the tasks. Whereas we found no differences in learning outcome or extraneous cognitive load, students in the enhanced guidance group reported less intrinsic motivation, and logfiles revealed a lower programming performance. In study 2, we implemented enhanced guidance in the form of adaptive just-in-time explanations for error streaks. Enhanced guidance led to a lower extraneous cognitive load, and this way increased learning outcome. Implications The type and timing of instructional guidance for students in computer science matters. More guidance is not better in each case. Instructional guidance should be tailored to students’ needs.