Understanding Student Learning Pathways in Traditional Online History Courses: Utilizing Process Mining Analysis on Clickstream Data
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| Title: | Understanding Student Learning Pathways in Traditional Online History Courses: Utilizing Process Mining Analysis on Clickstream Data |
|---|---|
| Language: | English |
| Authors: | Crosslin, Matt (ORCID |
| Source: | Journal of Research in Innovative Teaching & Learning. 2021 14(3):399-414. |
| Availability: | Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight |
| Peer Reviewed: | Y |
| Page Count: | 16 |
| Publication Date: | 2021 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Online Courses, History Instruction, Learning Processes, Student Centered Learning, Independent Study, Peer Relationship, Computer Mediated Communication, Decision Making, Interaction Process Analysis, Learning Strategies, Learning Analytics, State Universities, Integrated Learning Systems, Undergraduate Students |
| DOI: | 10.1108/JRIT-03-2021-0024 |
| ISSN: | 1947-1017 |
| Abstract: | 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. |
| Abstractor: | As Provided |
| Entry Date: | 2022 |
| Accession Number: | EJ1334536 |
| Database: | ERIC |
| Abstract: | 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. |
|---|---|
| ISSN: | 1947-1017 |
| DOI: | 10.1108/JRIT-03-2021-0024 |
