Understanding student learning pathways in traditional online history courses: utilizing process mining analysis on clickstream data

Purpose This study explores ongoing research into self-mapped learning pathways that students utilize to move through a course when given two modalities to choose from: one that is instructor-led and one that is student-directed. Design/methodology/approach Process mining analysis was utilized to examine and cluster clickstream data from an online college-level History course designed with dual modality choices. This paper examines some of the results from different approaches to clustering the available data. Findings By examining how often students interacted with others, whether they were more internal or external facing with their pathway choices, and whether or not they completed a learning pathway, this study identified five general tactics from the data: Individualistic Internal; Non-completing Internal; Completing, Interactive Internal; Completing, Interactive, and Reflective and Completing External. Further analysis of when students used each tactic led to the identification of four different strategies that learners utilized during class sessions. Practical implications The results of this analysis could potentially lead to the creation of customizable design models that can assist learners as they navigate modality choices in learner-centered or less-structured learning design methodologies. Originality/value Few courses are designed to give the learners the options to follow the instructor or create their own learning pathway. Knowing how to identify what choices a learner might take in these scenarios is even less explored. Preliminary data for this paper was originally presented as a poster session at the Learning Analytics and Knowledge conference in 2019

Discovering the Dynamics of Terms ’ Semantic Relatedness through Twitter

Abstract. Determining the semantic relatedness (SR) of two terms has been an appealing topic in information retrieval for many years as such information is useful for various tasks ranging from tag recommendation, over search query refinement to suggesting new web resources for the user to discover. Most approaches consider the SR of terms as static over time, and disregard the eventual temporal changes as imperfections. However, detecting and tracing changes in SR of terms over time may help in understanding the nature of changes in public opinion, as well as the change in the usage of terms in common language and jargon. In this paper, we propose an approach that makes use of microposts data in order to establish a dynamic measure of SR of terms, i.e., a measure that accounts for the changes in SR over time. We propose different scenarios of use (in online advertising and organizational knowledge management) which demonstrate the applicability of our approach in real life situations. We also provide a demo application for visualizing the change in micropost-based SR of terms

Using Online Presence to Improve Online Collaborative Learning

Social software tools have become an integral part of students’ personal lives and their primary communication medium. Likewise, these tools are increasingly entering the enterprise world (within the recent trend known as Enterprise 2.0) and becoming a part of everyday work routines. Aiming to keep the pace with the job requirements and also to position learning as an integral part of students’ life, the field of education is challenged to embrace social software. Personal Learning Environments (PLEs) emerged as a concept that makes use of social software to facilitate collaboration, knowledge sharing, group formation around common interests, active participation and reflective thinking in online learning settings. Furthermore, social software allows for establishing and maintaining one’s presence in the online world. By being aware of a student's online presence, a PLE is better able to personalize the learning settings, e.g., through recommendation of content to use or people to collaborate with. Aiming to explore the potentials of online presence for the provision of recommendations in PLEs, in the scope of the OP4L project, we have develop a software solution that is based on a synergy of Semantic Web technologies, online presence and socially-oriented learning theories. In this paper we present the current results of this research work