Remote practical activities have been demonstrated to be efficient when learners come to acquire inquiry skills. In computer science education, virtualization technologies are gaining popularity as this technological advance enables instructors to implement realistic practical learning activities, and learners to engage in authentic and problem-based learning. However, virtualization solutions have not been designed especially for education and do not address any pedagogical concern. Since several large-scale studies showed that instructional supports during practical activities are almost as important as technical features, this article investigates the following research question: how the scaffolding around the lab increases students' engagement in remote practical learning of computer science? To answer this question, we introduce the Lab4CE environment, a remote laboratory for computer education which adopts a distributed, modular and flexible architecture to integrate a set of scaffolding tools and services intended for instructors and learners. An exploratory study conducted with 139 undergraduate students enrolled in the first year of a computer science degree suggests a positive effect of the framework on learners' engagement when they come to practice system administration, and reveals a significant positive correlation between students' activity within the system and students' learning achievement.
The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.
The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.
This study analyzes students' behaviors in a remote laboratory environment in order to identify new factors of prediction of academic success. It investigates relations between learners' activities during practical sessions, and their performance at the final assessment test. Based on learning analytics applied to data collected from an experimentation conducted with our remote lab dedicated to computer education, we discover recurrent sequential patterns of actions that lead us to the definition of learning strategies as indicators of higher level of abstraction. Results show that some of the strategies are correlated to learners' performance. For instance, the construction of a complex action step by step, or the reflection before submitting an action, are two strategies applied more often by learners of a higher level of performance than by other students. While our proposals are domain-independent and can thus apply to other learning contexts, the results of this study led us to instrument for both students and instructors new visualization and guiding tools in our remote lab environment.
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