Computer Applications in Engineering Education · 2024 · 20 citations · 27 references
EducationComputer ScienceEducational TechnologyComputer-assisted InstructionInstructional DesignOnline TeachingAdaptive LearningOnline FeedbackOnline InstructionOnline LearningPersonalized Learning EnvironmentsVirtual Learning EnvironmentsComputer Science CurriculumComputer Science PedagogyDigital Logic CircuitsInteractive Learning ModulesLarge Language ModelsOnline Learning EnvironmentsOnline Learning ModulesPersonalized Learning Interfaces
Abstract This work provides online learning modules and instructions on how educators can leverage these technologies to help students learn in a personalized online environment. In particular, we focus on Google Colab, and the features provided by the Gradio Python library to provide interactivity within these modules. The contributions of this work include: (1) Development of a teaching framework using Gradio/Colab that offers automated grading and feedback for both educators and students; (2) Design of a versatile proposal, accommodating beginners with a straightforward interface while addressing the needs of advanced learners; (3) Creation of a comprehensive set of examples tailored for teaching digital logic subjects, with adaptability for application in various computer science areas. (4) A classification of these example learning modules in terms of their learning level for the students; (5) A novel client‐server approach based on Colab/Gradio, allowing teachers to manage the main notebook efficiently while providing a lightweight and reliable interface for students. The goal of this work is to further expose educators to the remarkable capabilities that cloud computing brings to online supplemental education, noting that large language models such as ChatGPT complement this work, in that chatbots will be able to guide students in these dynamic simulations.
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