The Invisible Breadcrumbs of Digital Learning

2020 ◽  
pp. 302-316
Author(s):  
Luc Paquette ◽  
Nigel Bosch
Keyword(s):  
Data Mining ◽  
Learning Environments ◽  
Test Scores ◽  
Learning Analytics ◽  
Educational Data Mining ◽  
Digital Learning ◽  
Fine Grained ◽  
Digital Learners ◽  
High Level ◽  
Digital Learning Environments

A main opportunity provided by digital learning environments is the ability to not only examine the final products of learning activities (e.g., essays, test scores, final answers to problems), but also the detailed logs of how learners interact with the environment itself. Those logs of the learners' actions serve as breadcrumbs marking the path they take as they engage with the environment, providing fine-grained information about when and how they interact with specific components of its user interface. The emerging fields of learning analytics and educational data mining have taken a particular interest in studying how we can make sense of those fine-grained interactions to better inform us of digital learners' experiences and how we can provide new opportunities to better support learners as they engage with digital learning environments. This chapter discusses how those fine-grained logs can be analyzed to identify high-level behaviors, investigate their relationships with learning, and provide us with insights about how to adapt learning environments to learners' needs.

Educational Data Mining and Learning Analytics for Improving Online Learning Environments

2020 ◽  
Vol 64 (1) ◽  
pp. 500-504
Author(s):  
Yancy Vance Paredes ◽  
Robert F. Siegle ◽  
I-Han Hsiao ◽  
Scotty D. Craig
Keyword(s):  
Data Mining ◽  
Educational Technology ◽  
Human Factors ◽  
Learning Environments ◽  
Learning Analytics ◽  
Educational Data Mining ◽  
Educational Systems ◽  
User Centered Design ◽  
High Quality ◽  
Online Learning Environments

The proliferation of educational technology systems has led to the advent of a large number of datasets related to learner interaction. New fields have emerged which aim to use this data to identify interventions that could help the learners become efficient and effective in their learning. However, these systems have to follow user-centered design principles to ensure that the system is usable and the data is of high quality. Human factors literature is limited on the topics regarding Educational Data Mining (EDM) and Learning Analytics (LA). To develop improved educational systems, it is important for human factors engineers to be exposed to these data-oriented fields. This paper aims to provide a brief introduction to the fields of EDM and LA, discuss data visualization and dashboards that are used to convey results to learners, and finally to identify where human factors can aid other fields.

scholarly journals Student Online Activity in Blended Learning: A Learning Analytics Perspective of Professional Teacher Education Studies in Finland

SAGE Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 215824402110566
Author(s):  
Arto O. Salonen ◽  
Annukka Tapani ◽  
Sami Suhonen
Keyword(s):  
Teacher Education ◽  
Distance Learning ◽  
Blended Learning ◽  
Learning Environments ◽  
Learning Analytics ◽  
Digital Learning ◽  
Online Activity ◽  
Professional Teacher ◽  
Digital Learning Environments ◽  
The Impact

Distance learning is rapidly gaining ground globally. In this case study, we focused on professional (vocational) teacher education (PTE) student online activity in a blended learning context. We applied learning analytics (LA) to identify students’ ( n = 19) online study patterns. Our key interest was in determining when and what kinds of online activity and behavior PTE students engage in during their studies. We applied quantitative content analysis to analyze the students’ behavior. Moodle’s event log enabled us to identify active hours and days, variation in use of learning materials, the impact of interventions, and stumbling blocks to student learning in the study unit. Based on our data, educator availability is an essential factor for good student engagement in digital learning environments. Interaction forums are important for PTE students effective learning. Monday and Tuesday afternoons are the most effective times for educators to be available for PTE students. There is a clear need for contact learning in professional teacher education, even when operating in digital learning environments. It plays an essential role in keeping students’ activity alive. It could be beneficial to plan a post-process for students who do not graduate as planned, including regular group meetings for supporting studies, receiving guidance, and meeting peers. PTE students’ behavior in a distance learning environment in the context of blended learning follows Zipf’s law, which models the occurrence of distinct objects in particular sorts of collections.

scholarly journals Multimodal Learning Analytics and Education Data Mining: using computational technologies to measure complex learning tasks

2016 ◽  
Vol 3 (2) ◽  
pp. 220-238 ◽  
Author(s):  
Paulo Blikstein ◽  
Marcelo Worsley
Keyword(s):  
Data Mining ◽  
Learning Analytics ◽  
Online Courses ◽  
Educational Data Mining ◽  
Multimodal Learning ◽  
Learning Tasks ◽  
Education Data ◽  
Multimodal Learning Analytics ◽  
High Degree ◽  
Learning Analysis

New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics and educational data mining has been focused on online courses and cognitive tutors, both of which provide a high degree of structure to the tasks, and are restricted to interactions that occur in front of a computer screen. In this paper, we argue that multimodal learning analytics can offer new insights into students’ learning trajectories in more complex and open-ended learning environments. We present several examples of this work and its educational application.

scholarly journals Notes on Corpoliteracy: Bodies in Post-digital Educational Contexts

2021 ◽  
pp. 167-182
Author(s):  
Gila Kolb
Keyword(s):  
Learning Environments ◽  
Teaching Practices ◽  
Power Relations ◽  
Teaching And Learning ◽  
Digital Art ◽  
Digital Learning ◽  
Conceptions Of Learning ◽  
Global Pandemic ◽  
Art Teaching ◽  
Digital Learning Environments

AbstractThis chapter demonstrates the potential to challenge power relations, and reconsider teaching practices and conceptions of learning bodies. How do bodies in a digital learning setting perform are read and observed? How they can be included in learning settings? Since teaching and learning increasingly take part in digital learning environments, especially since the outbreak of the COVID-19 global pandemic, digital art teaching needs rethinking toward the knowledge of learning bodies and of the perception of learning in the digital realm: a digital corpoliteracy.

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