Improving Learning by Imitation in Online Courses using Memorization, Learning by Doing and Lecture Architecture for Naive Programmers

摘要

Learning by Imitation (LBI) is the most natural way of learning natural languages. The designers of online courses focus on approaches like learning by doing, adaptive learning, and so on for designing online education systems like Massive Open Online Courses (MOOC) and Intelligent Tutoring System (ITS). They don’t consider LBI as an essential parameter while designing courses and MOOC/ITS for naive programmers. The purpose of this research is to arrive at a framework that helps in designing pedagogically effective MOOC/ITS for naive programmers which reflects LBI approach. We conducted an online survey where 130 students participated. Online lectures were designed using our reference framework. A desktop App was developed for naive programmers allowing them to code at different levels of abstractions. The Lectures plus App provides a learning environment reflecting LBI. We conducted pre and post-tests and found a remarkable increase in programming performance of these participants.