Daniel S. Brogan

Insights Gained from Tracking Users’ Movements Through a Cyberlearning System’s Mediation Interface

Cyberlearning has the ability to connect learners from diverse settings to learning resources regardless of the learners’ proximity to traditional classroom environments. Tracking users’ movements through a cyberlearning interface provides data that can be used both to interpret students’ level of engagement in the learning process and to improve the cyberlearning system’s user mediation interface. The Online Watershed Learning System (OWLS), which serves as the end user interface of the Learning Enhanced Watershed Assessment System (LEWAS), is an open-ended guided cyberlearning system that delivers integrated live and/or historical environmental monitoring data and imagery. Anonymous user tracking in the OWLS helped to identify students from various courses as ‘groups of users’ across the world and assisted in providing information about the importance of various components of the mediation interface. A pilot test of this tracking capability was conducted in two first-year engineering courses at Virginia Western Community College during the fall 2015 semester. During this pilot test, tracking data was collected from a total of roughly 80 students from a total of four course sections. The data collected included the amount of time that each student spent using each component of the OWLS, the paths that he or she used to navigate through these components and how frequently each student returned to the OWLS. Suggestions for system modifications based on comparison of the time students spent using various system components with students’ post-test evaluation of the educational value of these components are included. To address the limitation of the data collected during the pilot study, which could not identify a user across different devices, a user login system is being developed for investigating individualized learning. The current system will address the need to understand in real-time the learner-specific pathways of content and progression, and these learners’ levels of engagement within the system.

A Virtual Learning System in Environmental Monitoring

This paper provides an overview of a Learning Enhanced Watershed Assessment System (LEWAS) and its public interface called the Online Watershed Learning System (OWLS). These systems provide access to environmental monitoring case studies that are developed based on high frequency water and weather data from a small urban watershed on the campus of Virginia Tech (VT) and represent applications of the innovation cycle of engineering education research and practice. The development of LEWAS was motivated by a programming learning unit in a first-year engineering class in 2008, and since then it has grown into a unique research and education lab on the VT campus. Several examples of learning activities based on the LEWAS/OWLS are provided and applications of these systems within and outside VT are discussed. Results of a pilot study to track the OWLS’ users are provided and this work is expected to provide guidelines to develop personalized learning systems in environmental monitoring. Interdisciplinary collaboration facilitated by the LEWAS/OWLS work has resulted in a several new NSF awards, and examples are provided.

Towards an understanding of ECE students' Use of online homework help forums

Online discussion forums have emerged as a popular Web application to build and support online communities for numerous engineering interest areas and practice. However, a review of engineering education literature reveals scant research on the use of online discussion forums for engineering learning beyond the classroom. This study addresses this gap in knowledge through a study of the “Homework Help” section on AllAboutCircuits.com to examine what students sought help for and for what purpose. We downloaded over 6,000 discussion messages spanning over 8 years and extracted the textual data with a Python program. Instead of analyzing the data through manual means, we utilized the Natural Language Toolkit (NLTK) to capture textual patterns and leverage a topic modeling approach, Latent Dirichlet Allocation, to identify connected clusters of words. Linguistic Inquiry and Word Count (LIWC) analysis was also used to determine how often students use words associated with cognitive processes. We found that the homework help section of informal online discussion forums cater to students seeking help on fundamental ECE topics. Our findings also suggest that online discussion forums are supportive learning environments, as students freely engage in meaningful inquiries and social interactions with other learners.