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Engineering Commons

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Educational Assessment, Evaluation, and Research

Iowa State University Articles and Manuscripts

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Articles 1 - 3 of 3

Full-Text Articles in Engineering

Data, Data Everywhere: Implications And Considerations, Matthew D. Pistilli Aug 2018

Data, Data Everywhere: Implications And Considerations, Matthew D. Pistilli

Iowa State University Articles and Manuscripts

Learning Analytics in Higher Education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical, theoretical, and practical perspectives on the current use and future potential of learning analytics for student learning and data-driven decision-making, ways to effectively evaluate and research learning analytics, integration of learning analytics into practice, organizational barriers and opportunities for harnessing Big Data to create and support use of these tools, and ethical considerations related to privacy and ...


Guiding Early And Often: Using Curricular And Learning Analytics To Shape Teaching, Learning, And Student Success In Gateway Courses, Matthew D. Pistilli, Gregory L. Heileman Dec 2017

Guiding Early And Often: Using Curricular And Learning Analytics To Shape Teaching, Learning, And Student Success In Gateway Courses, Matthew D. Pistilli, Gregory L. Heileman

Iowa State University Articles and Manuscripts

This chapter provides information on how the promise of analytics can be realized in gateway courses through a combination of good data science and the thoughtful application of outcomes to teaching and learning improvement efforts—especially with and among instructors.


Learner Analytics And Student Success Interventions, Matthew D. Pistilli Sep 2017

Learner Analytics And Student Success Interventions, Matthew D. Pistilli

Iowa State University Articles and Manuscripts

The implementation of analytics in support of student success requires effective use of feedback and interventions, as well as a system by which the use of feedback and institutional supports can be tracked and evaluated.