Bbookx: An automatic book creation framework

ABSTRACT As more educational resources become available online, it is possible to acquire more up-to-date knowledge and information. We propose BBookX, a novel computer facilitated system that automatically and collaboratively builds free open online books using publicly available educational resources such as Wikipedia. BBookX has two separate components: one creates an open version of existing books by linking different book chapters to Wikipedia articles, while another with an interactive user interface supports interactive realtime book creation where users are allowed to modify a generated book from explicit feedback

Quantifying the mismatch between course content and students' dialogue in online learning environments

Due to the internet???s increasing global availability, online learning has become a new paradigm for distance learning in higher education. While student interactions and reactions are readily observable in a physical classroom environment, monitoring student interactions and quantifying divergence between lecture topics and the topics that interest students are challenging in online learning platforms. Understanding the effects of this divergence is important for monitoring student engagement and aiding instructors, who are focused on improving the quality of their online courses. The authors of this paper propose a topic modeling method, based on latent Dirichlet allocation (LDA), that quantifies the effects of divergence between course topics (mined from textual transcriptions) and student-discussed topics (mined from discussion forums). Correlations between the measured dissimilarities and (a) the number of posts and comments in discussion forums, (b) the number of submitted assignments, and (c) students??? average performance scores are presented. A case study involving video lecture transcripts and discussion forum posts/comments in a massive open online course (MOOC) platform demonstrates the proposed method???s potential success and informs course providers about the challenges of measuring the topics that interest students

Recovering Concept Prerequisite Relations from University Course Dependencies

Prerequisite relations among concepts play an important role in many educational applications such as intelligent tutoring system and curriculum planning. With the increasing amount of educational data available, automatic discovery of concept prerequisite relations has become both an emerging research opportunity and an open challenge. Here, we investigate how to recover concept prerequisite relations from course dependencies and propose an optimization based framework to address the problem. We create the first real dataset for empirically studying this problem, which consists of the listings of computer science courses from 11 U.S. universities and their concept pairs with prerequisite labels. Experiment results on a synthetic dataset and the real course dataset both show that our method outperforms existing baselines

Investigating Active Learning for Concept Prerequisite Learning

Concept prerequisite learning focuses on machine learning methods for measuring the prerequisite relation among concepts. With the importance of prerequisites for education, it has recently become a promising research direction. A major obstacle to extracting prerequisites at scale is the lack of large-scale labels which will enable effective data-driven solutions. We investigate the applicability of active learning to concept prerequisite learning.We propose a novel set of features tailored for prerequisite classification and compare the effectiveness of four widely used query strategies. Experimental results for domains including data mining, geometry, physics, and precalculus show that active learning can be used to reduce the amount of training data required. Given the proposed features, the query-by-committee strategy outperforms other compared query strategies

BBookX: Building Online Open Books for Personalized Learning

We demonstrate BBookX, a novel system that auto-matically builds in collaboration with a user online openbooks by searching open educational resources (OER).This system explores the use of retrieval technologies todynamically generate zero-cost materials such as text-books for personalized learning