About this Research Topic
Digital platforms such as E-books, learning management systems, Massive online open course-ware (MOOC), etc. are aiding educators to teach classes. These platforms allow educators to develop, use, and reuse digital learning objects, generating a vast amount of teaching materials. These materials are diverse in nature which may include e-book, syllabus, lesson plan, presentation, learning module, assessment, etc. The digital nature of these objects mean that we can apply data analytic approaches to identify interesting trends that are otherwise latent. Analyses can be done to identify prevalent concepts, find topic distribution, investigate the quality of educational material, or detect potential links between different types of educational materials.
One of the useful aspects of digital technology is the ability to track usage. For example, when students utilize digital learning materials, large amount of data is generated during those sessions. Capturing and analyzing the usage data is critical for a number of reasons. Such data provide insight into students’ engagement with the teaching module. These data also can shed light on the impact of using digital learning material.
Aside from digital learning objects, there are digital platforms that assist in collaborative learning that can have more information on student engagement in and out of the class. These usage data can help us identify the impact of digital teaching platforms, for example, usage data can be used to identify whether there is a correlation between the increased usage of digital educational materials and better grade, if using collaborative learning platform leads to a positive impact on student learning, how digital materials effect student metacognition, etc. Usage data can also help educators understand how students are progressing through the course. Gaining these insights is critical for online courses where there is no direct interaction with the student and the faculty.
Many of the digital education platforms contain assessment components. There are also independent digital assessment systems. Educators use digital assessment systems to various extent to track student progress. Analyses of digital assessments data can help us gain insight into how students grasp new concepts at various stages of their learning. It would be useful to know the effectiveness of digital assessments compared to paper-based assessments.
Digital educational materials, their usage data, and data from the assessments and collaborative platforms give us a unique way to look into the learning of students from different perspectives. Analyzing these data can help educators identify the effectiveness of current teaching strategies, which in turn can help with the development of better pedagogical practices. Such analyses can also help educators to stay up-to- date about the capabilities of the learning audience. Lastly, developers of educational platforms can also gain insight about the effectiveness of the designed platforms.
The topics of interest include, but not limited to:
- Learning data – current state of capturing student data, standards, and protocols.
- Modeling student data.
- Identify learning trends.
- Relation between digital educational platform and student performance.
- Analyzing educational resources.
- Analyzing quality of educational resources.
- Personalized learning.
- Digital assessment.
- Student engagement and digital education.
- Impact of technology in pedagogical practices.
Keywords: learning analytics, personalized learning, educational data mining, student modeling, student profiling, student engagement pattern, student learning pattern, learning behavior, educational research, massive open online courses, digital learning objects, pedagogical research, educational data
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